OCS Study 

BOEMRE 2010-041 

 

Study of Deepwater Currents 

in the Eastern Gulf of Mexico 

U.S. Department of the Interior 

Bureau of Ocean Energy Management, 

 Regulation and Enforcement 

Gulf of Mexico OCS Region 
OCS Study 

BOEMRE 2010-041 

Study of Deepwater Currents 

in the Eastern Gulf of Mexico 

Authors 

Jeff Cox 

Carol Coomes 

S. DiMarco 

Kathleen Donohue 

George Forristall 

Peter Hamilton 

Robert Leben 

D.R. Watts 

Prepared under BOEMRE Contract 

M04PC00008 (1435-01-04-CT-34239) 

by 

Evans-Hamilton, Inc. 

4608 Union Bay Place 

Seattle, WA 98105 

Published by 

U.S. Department of the Interior

Bureau of Ocean Energy Management, 

 Regulation and Enforcement 

Gulf of Mexico OCS Region 

New Orleans

December 2010 
 iii 

DISCLAIMER 

This report was prepared under contract between the Bureau of Ocean Energy Management, 

Regulation and Enforcement (BOEMRE) and Evans-Hamilton, Inc. (EHI). This report is 

undergoing review by the BOEMRE, and it has been approved for publication. Approval does 

not signify that the contents necessarily reflect the views and policies of the BOEMRE, nor does 

mention of trade names or commercial products constitute endorsement or recommendation for 

use. It is, however, exempt from review and compliance with the BOEMRE editorial standards. 

REPORT AVAILABILITY 

This report is available only in compact disc format from the Bureau of Ocean Energy 

Management, Regulation, and Enforcement, Gulf of Mexico OCS Region, at a charge of $15.00, 

by referencing OCS Study BOEMRE 2010-041. The report may be downloaded from the 

BOEMRE website through the Environmental Studies Program Information System (ESPIS). 

You will be able to obtain this report also from the National Technical Information Service in the 

near future. Here are the addresses. You may also inspect copies at selected Federal Depository 

Libraries. 

 U.S. Department of the Interior U.S. Department of Commerce 

 Bureau of Ocean Energy Management, National Technical Information Service 

 Regulation, and Enforcement 5285 Port Royal Road 

 Gulf of Mexico OCS Region Springfield, Virginia 22161 

 Public Information Office (MS 5034) Phone: (703) 605-6040 

 1201 Elmwood Park Boulevard Fax: (703) 605-6900 

 New Orleans, Louisiana 70123-2394 Email: bookstore@ntis.gov

Telephone requests may be placed at 

 (504) 736-2519, 1-800-200-GULF, or 

Rush Orders: 1-800-553-6847 

 Fax: (504) 736-2620 

CITATION 

Cox, J., C. Coomes, S. DiMarco, K. Donohue, G.Z. Forristall, P. Hamilton, R.R. Leben, and D.R. 

Watts. 2010. Study of deepwater currents in the Eastern Gulf of Mexico. U.S. Dept. of the 

Interior, Bureau of Ocean Energy Management, Regulation, and Enforcement, Gulf of 

Mexico OCS Region, New Orleans, LA. OCS Study BOEMRE 2010-041. 473 pp. 

ABOUT THE COVER 

The cover shows the location of the study area (rectangle) within the eastern Gulf of Mexico, and 

the locations of the four current measurement moorings (M1-M4) plus the locations of the seven 

PIES measurement moorings (P1-P7) overlaid on a sea surface temperature image of 22 April 

2005. On that date, warm (red) loop current waters extended well north into the Gulf of Mexico, 

and contained several frontal eddies, cyclones, and filaments around its periphery. Both a portion 

of the Loop Current, and filaments from it, can be seen impacting a portion of the study area. 
 v 

ACKNOWLEDGEMENT 

Many outstanding individuals contributed to the overall success of this program. While there are 

too many to identify all of them individually, the following deserve special recognition. Mr. 

Keith Kurrus and Mr. Kevin Redman of EHI planned and very successfully led the field 

operations. PIES field operations were ably performed by Mr. G. Chaplin from URI. Thanks also 

to the captains and crew of the R/V Pelican from which the field operations were conducted. 

Data reduction, QA/QC, final edited data files, and initial graphical displays of mooring, 

hydrographic, and ancillary data were conducted by Mrs. Kari Walker and her team at EHI. Mr. 

Paul Blankinship at SAIC, and Dr. Matt Howard and Ms. Kelly Cole at Texas A&M University 

provided extensive analysis assistance to the PIs in their organizations. 

Compilation, blending, and editing of all the PI inputs to the report, and adapting the inputs to 

the BOEMRE report format, was ably conducted by Mrs. Rachel Halfhill of EHI. 

Lastly, the support, encouragement, and patience of Dr. Alexis Lugo-Fernandez, the BOMRE 

COTR, was critical to the project’s success. 
TABLE OF CONTENTS 

Page 

LIST OF FIGURES ....................................................................................................................XI

LIST OF TABLES ................................................................................................................ XXXI

EXECUTIVE SUMMARY .................................................................................................XXXV

1.0 INTRODUCTION AND OBJECTIVES...................................................................... 1-1

1.1 Background..........................................................................................................1-1 

1.2 Study Area ...........................................................................................................1-3 

1.3 Study Approach ...................................................................................................1-5 

1.4 Study Objectives..................................................................................................1-6 

1.5 Study Team..........................................................................................................1-7 

1.6 Report Organization.............................................................................................1-8 

2.0 EXPERIMENT DESIGN AND METHODOLOGY .................................................. 2-1

2.1 Moorings..............................................................................................................2-1 

2.1.1 Instrumentation ........................................................................................2-1 

2.1.2 Instrumentation and Moorings Preparation .............................................2-1 

2.1.3 Moorings Deployment, Servicing, and Recovery....................................2-5 

2.1.4 Processing and QA/QC of Mooring Measurements ................................2-8 

2.1.5 Mooring Data Coverage.........................................................................2-12 

2.1.6 Mooring Data Graphical Products and Analyses...................................2-12 

2.2 Hydrography ......................................................................................................2-20 

2.2.1 Survey Pattern and Instrumentation.......................................................2-21 

2.2.2 Hydrography Data Processing and QAQC ............................................2-26 

2.2.3 CTD vs XBT Data .................................................................................2-30 

2.2.4 Comparison to Historical Data...............................................................2-31 

2.3 PIES ...................................................................................................................2-33 

2.3.1 Gravest Empirical Mode Method...........................................................2-34 

2.3.1.1 Determine τ Index...................................................................... 2-34 

2.3.1.2 Assemble Regional Hydrographic Data Set ..............................2-34 

2.3.1.3 Sort Hydrographic Data by τ Index ........................................... 2-39 

2.3.1.4 Seasonal Correction ................................................................... 2-39 

2.3.2 Conversion of Measured τ to τ(150-1000) ............................................2-39 

2.3.3 Upper-Ocean Maps................................................................................2-50 

2.3.4 Bottom Pressure.....................................................................................2-50 

2.3.5 Reference-Level Maps...........................................................................2-52 

2.3.6 Total Maps.............................................................................................2-54 

2.3.7 Mooring Comparisons ...........................................................................2-55 

2.4 Remote Sensing .................................................................................................2-57 

2.4.1 Altimetry................................................................................................2-60 

 vii 
2.4.1.1 Alongtrack Altimeter Data......................................................... 2-62 

2.4.1.2 Mesoscale Analysis.................................................................... 2-63 

2.4.1.3 Mean Reference Surface and Model Mean SSH .......................2-63 

2.4.1.4 Objective Mapping..................................................................... 2-64 

2.4.1.5 Objective Analysis Procedure.................................................... 2-64 

2.4.2 Ocean Color Imagery.............................................................................2-66 

2.4.3 SST Imagery ..........................................................................................2-67 

2.5 PIES/Altimeter Comparison ..............................................................................2-67 

2.5.1 Altimetric Sampling and Aliasing .........................................................2-67 

2.5.2 Signal-to-Noise ......................................................................................2-75 

2.5.3 Sea Surface Height Time Scales............................................................2-78 

2.5.4 Comparison of CCAR Mesoscale and PIES SSH..................................2-80 

2.6 Ancillary Data....................................................................................................2-83 

2.6.1 River Discharge .....................................................................................2-84 

2.6.2 Coastal and Offshore Winds..................................................................2-84 

2.6.3 Coastal Water Levels.............................................................................2-84 

2.6.4 Hurricanes and Tropical Storms ............................................................2-84 

2.6.5 Horizon Marine Eddy Watch and Drifting Buoys.................................2-90 

3.0 LOOP CURRENT EVENTS AND HISTORICAL PERSPECTIVE .......................3-1

3.1 Loop Current and Loop Current Eddies...............................................................3-1 

3.1.1 LC and LCEs During the Study Period....................................................3-1 

3.1.2 Loop Current Metrics and Statistics ........................................................3-9 

3.1.3 Loop Current Eddy Metrics and Statistics.............................................3-12 

3.1.4 Loop Current Frontal Eddies and Other Cyclonic Eddies.....................3-20 

3.2 Study Time Period in the Context of the Historical Record ..............................3-22 

3.2.1 Loop Current..........................................................................................3-22 

3.2.2 Loop Current Eddies..............................................................................3-23 

4.0 LC AND LCE DYNAMICS .......................................................................................... 4-1

4.1 Kinematic Analysis..............................................................................................4-1 

4.1.1 Drifting Buoy Data and Analysis Approach............................................4-1 

4.1.2 Eddy Vortex.............................................................................................4-2 

4.1.3 Cyclones...................................................................................................4-2 

4.1.4 Combined Kinematic and Altimetric Analysis........................................4-3 

4.2 Dynamic Analysis................................................................................................4-8 

4.2.1 Mapped Surface Circulation and Sea Surface Height from PIES............4-8 

4.2.2 Relative Vorticity Calculated from the PIES.........................................4-16 

4.2.3 Anticyclonic and Cyclonic Events in PIES Relative Vorticity Time 

Series......................................................................................................4-19 

5.0 MOORING AND HYDROGRAPHY RESULTS....................................................... 5-1

5.1 Mooring Measurements.......................................................................................5-1 

5.1.1 Velocity Time-Series...............................................................................5-1 

 viii 
5.1.2 Current Roses, Joint Probability Distributions of Speed by Direction ....5-6 

5.1.3 Current Speed Persistence Tables............................................................5-6 

5.1.4 Velocity Spectra.......................................................................................5-7 

5.1.4.1 Upper Ocean Spectra ................................................................... 5-7 

5.1.4.2 Deep Ocean Spectra................................................................... 5-11 

5.1.5 Coherency Spectra .................................................................................5-11 

5.1.5.1 Current – Wind Coherence ........................................................ 5-11 

5.1.5.2 Vertical Current – Current Coherence ....................................... 5-12 

5.1.5.3 Horizontal Current – Current Coherency Spectra......................5-16 

5.1.6 Mean, Minimum and Maximum Currents.............................................5-17 

5.1.7 Extreme Current Value Distributions ....................................................5-20 

5.1.8 Responses to Hurricanes........................................................................5-26 

5.1.8.1 Inertial Oscillations.................................................................... 5-26 

5.1.8.2 Wavelet Analysis of the Inertial Oscillations ............................5-42 

5.1.8.3 1-D Turbulence Closure Model ................................................. 5-47 

5.2 Hydrography Measurements..............................................................................5-52 

6.0 DEEP CIRCULATION................................................................................................. 6-1

6.1 Overview of Observations of Topographic Rossby Waves in the Deep Gulf.....6-1 

6.1.1 Background..............................................................................................6-1 

6.1.2 Data..........................................................................................................6-4 

6.1.2.1 Moorings...................................................................................... 6-4 

6.1.2.2 RAFOS Floats.............................................................................. 6-4 

6.1.3 Gulf-Wide Overview of Deep Currents...................................................6-6 

6.2 Basic Statistics from Moorings..........................................................................6-18 

6.2.1 Event Analysis.......................................................................................6-19 

6.3 Topographic Rossby Waves North of the Loop Current ...................................6-24 

6.3.1 Wavelet Analysis...................................................................................6-38 

7.0 VERTICAL COUPLING.............................................................................................. 7-1

7.1 CEOFs..................................................................................................................7-1 

7.1.1 Potential Vorticity.......................................................................................7-4 

7.2 Dynamic Modes...................................................................................................7-8 

7.2.1 Vertical Structure of Low-Frequency Variability....................................7-8 

7.2.1.1 Empirical Orthogonal Function (EOF) Analysis.........................7-8 

7.2.1.2 Dynamical Mode Analysis......................................................... 7-18 

7.2.1.3 Model Utility Test for Dynamic Modes..................................... 7-32 

7.2.1.3.1 Temporal Correlation of First Baroclinic Mode and 

Sea Surface Height Gradient ....................................... 7-32 

7.2.1.3.2 Spectra and Temporal Scales of Modes ...................... 7-45 

7.3 Upper/Lower-Layer Coupling Analysis Using PIES Data ................................7-45 

8.0 SUMMARY AND CONCLUSIONS ............................................................................ 8-1

8.1 Summary of the Results.......................................................................................8-1 

 ix 
 x 

8.2 Conclusions..........................................................................................................8-3 

8.3 Recommendations................................................................................................8-4 

9.0 LITERATURE CITED ................................................................................................. 9-1

APPENDIX A Hurricanes and Tropical Storm Events........................................................ A-1 

APPENDIX B Color Vector Plots of Current Magnitude and Direction............................ B-1 

APPENDIX C Basic Statistics for Current Measurements.................................................. C-1 

APPENDIX D Barotropic Tides.............................................................................................. D-1 

APPENDIX E Elliptical Fit Parameters................................................................................. E-1 

APPENDIX F Ocean Response to Hurricane Katrina in Presence of a Cyclone. .............. F-1
LIST OF FIGURES 

Page 

Figure 1.1-1. Locations of the BOEMRE Gulf of Mexico regions and other major 

features of the Gulf of Mexico.............................................................................1-2 

Figure 1.2-1. Map of the study area (outlined in red) including locations of moorings 

M1, M2, M3 and M4 in black, and PIES in purple. ............................................1-4 

Figure 2.1-1. Design of the tall (M1, M2, and M3) and short (M4) moorings..........................2-2 

Figure 2.1-2. Example current rose diagram: Mooring M1, deployment 1.............................2-18 

Figure 2.1-3. Example persistence table: Mooring M1, deployment 1. ..................................2-19 

Figure 2.1-4. Kinetic energy spectra of unfiltered (blue) and detided (red) versions of 

ADCP data during deployment 1 at mooring 1. ................................................2-19 

Figure 2.2-1. Grid pattern proposed for hydrography cruises. ................................................2-23 

Figure 2.2-2. Grid pattern of Hydrography Cruise 1...............................................................2-24 

Figure 2.2-3. Grid pattern of Hydrography Cruise 2...............................................................2-25 

Figure 2.2-4. Pinwheel station grid for intensive Hydrography Cruise 3................................2-27 

Figure 2.2-5. Station pattern for Hydrography Cruise 3..........................................................2-28 

Figure 2.2-6. CTD vs. XBT profile information for Hydrographic Cruise 3 January 

2006....................................................................................................................2-31 

Figure 2.2-7. Profiles from all three hydrographic cruises plotted as potential 

temperature vs salinity superimposed on the historical data boundaries...........2-32 

Figure 2.3-1. Time series of τ (tau) anomaly in seconds plotted according to 

approximate geographic location.......................................................................2-35 

Figure 2.3-2. Time series of bottom pressure anomaly in dbar plotted according to 

approximate geographic location.......................................................................2-36 

Figure 2.3-3. Two views of the temperature structure in the region for August 5, 2005 

provided by the PIES. ........................................................................................2-37 

Figure 2.3-4. Several views of the current structure in the region for August 5, 2005 

provided by the PIES and current meter measurements. ...................................2-38 

Figure 2.3-5. Spatial and temporal distribution of hydrocasts used to construct the 

Gravest Empirical Mode....................................................................................2-41 

 xi 
Figure 2.3-6. Temperature profiles interpolated every 10 dbar and sorted by τ(150-

1000). .................................................................................................................2-42 

Figure 2.3-7. Scatter plots of temperature versus τ(150-1000) for six representative 

pressure levels....................................................................................................2-43 

Figure 2.3-8. Contour plot of the cubic smoothing spline fits for the temperature GEM 

field. ...................................................................................................................2-44 

Figure 2.3-9. The GEM-determined temperature and salinity profiles agree well with 

measured profiles...............................................................................................2-45 

Figure 2.3-10. Upper panels: Scatter plots of temperature versus τ(150-1000) for surface 

(left), 50 dbar (middle) and 100 dbar (right) with the cubic spline fit 

shown as a solid dark line. .................................................................................2-46 

Figure 2.3-11. Seasonal temperature correction/amplitude contoured as function of 

yearday and pressure..........................................................................................2-47 

Figure 2.3-12. τ(150-1000) for each time series........................................................................2-48 

Figure 2.3-13. Upper panel: Scatter plots of τ(0-150) versus τ(150-1000)...............................2-49 

Figure 2.3-14. Correlation coefficient between pairs of τ records longer than one year...........2-51 

Figure 2.3-15. Top Panel: Common mode subtracted from bottom pressure records 

before mapping deepwater dynamical properties. .............................................2-53 

Figure 2.3-16. Time series of bottom pressure anomaly with the common mode removed 

in dbar plotted according to approximate geographic location..........................2-54 

Figure 2.3-17. Correlation coefficient between pairs of pressure records.................................2-55 

Figure 2.3-18. Comparison between the moorings (red) and PIES-derived (blue) 

temperatures near 400 m depth..........................................................................2-58 

Figure 2.3-19. Comparison between the M2 mooring (red) and PIES-derived (blue) zonal 

(top) and meridional (middle) velocities at 415 m depth...................................2-59 

Figure 2.4-1. Satellite altimeter groundtrack coverage in study region. .................................2-61 

Figure 2.5-1. Maps of PIES barotropic unaliased variance for 10-day, 17-day, and 35-

day sampling. .....................................................................................................2-71 

Figure 2.5-2. Maps of PIES baroclinic unaliased variance for 10-day, 17-day, and 35-

day sampling. .....................................................................................................2-72 

 xii 
Figure 2.5-3. Maps of PIES SSH unaliased variance for 10-day, 17-day, and 35-day 

sampling.............................................................................................................2-73 

Figure 2.5-4. Maps of PIES SSH signal-to-noise ratio (SNR) for 10-day, 17-day, and 

35-day sampling.................................................................................................2-77 

Figure 2.5-5. Spatial maps of the half-power period, T, computed from the PIES 

barotropic, baroclinic, and combined SSH anomaly time series. ......................2-79 

Figure 2.5-6. Spatial map of the CCAR/PIES SSH temporal correlation. ..............................2-81 

Figure 2.5-7. Scatterplot and correlation values of PIES time series points located on 

altimeter groundtracks with the coincident points from the along-track 

detrended altimeter data.....................................................................................2-82 

Figure 2.6-1. River discharge in m3 s-1 during the first deployment (Rivers 1-7). Note 

Mississippi River is at larger scale.....................................................................2-85 

Figure 2.6-2. River discharge in m3

 s

-1 during the first deployment (Rivers 8-15).................2-85 

Figure 2.6-3. River discharge in m3 s-1 during the second deployment (Rivers 1-7). 

Note Mississippi River is at larger scale............................................................2-86 

Figure 2.6-4. River discharge in m3 s

-1 during the second deployment (Rivers 8-15). ...........2-86 

Figure 2.6-5. Vector plots of wind speed (mph) and direction (degrees from) for the first 

deployment (Winds 1-5). ...................................................................................2-87 

Figure 2.6-6. Vector plots of wind speed (mph) and direction (degrees from) for the first 

deployment (Winds 6-10). .................................................................................2-87 

Figure 2.6-7. Vector plots of wind speed (mph) and direction (degrees from) for the 

second deployment (Winds 1-5). .......................................................................2-88 

Figure 2.6-8. Vector plots of wind speed (mph) and direction (degrees from) for the 

second deployment (Winds 6-10). .....................................................................2-88 

Figure 2.6-9. Predicted and measured tide height (m) from gauges located on the coast 

from Louisiana to Florida for deployment 1......................................................2-89 

Figure 2.6-10. Predicted and measured tide height (m) from gauges located on the coast 

from Louisiana to Florida for deployment 2......................................................2-89 

Figure 2.6-11. Timing and paths of all six storm events that passed near the study area 

during the study period. .....................................................................................2-91 

Figure 3.1-1. Eight-day composite image of chlorophyll concentration overlaid with the 

SSH contour map from 15 September 2005 showing the recent separation 

of LCE Vortex from the LC.................................................................................3-3 

 xiii 
Figure 3.1-2. Three-day composite SST images overlaid with SSH contour maps 

showing the detachment of LCE Vortex from the LC in late February 

2005......................................................................................................................3-4 

Figure 3.1-3. Three-day composite SST images overlaid with SSH contour maps 

showing the reattachment of LCE Vortex to the LC in early April 2005............3-5 

Figure 3.1-4. Three-day composite SST images overlaid with SSH contours showing 

LCE Vortex detachment (upper panels) and reattachment (lower panels) 

for events #1 and #2.............................................................................................3-7 

Figure 3.1-5. Eight-day composite chlorophyll concentration images overlaid with SSH 

contours showing LCE Vortex detachment (upper panels) and 

reattachment (lower panels) for events #3 and #4. ..............................................3-8 

Figure 3.1-6. SST and chlorophyll concentration images overlaid with SSH showing the 

four LCE detachment events identified in the altimeter record.........................3-10 

Figure 3.1-7. Loop Current maximum northern/western extension and length time series 

with percent occurrence histograms...................................................................3-13 

Figure 3.1-8. Loop Current area, volume, and circulation time series with percent 

occurrence histograms. ......................................................................................3-14 

Figure 3.1-9. Loop Current maximum northern/western extensions and length time 

series with percent occurrence histograms during the EGOM study.................3-15 

Figure 3.1-10. Loop Current area, volume, and circulation time series with percent 

occurrence histograms during the EGOM study................................................3-16 

Figure 3.1-11. Histograms of Loop Current metrics during the EGOM study (red bars) 

versus the historical time period (blue bars)......................................................3-17 

Figure 3.1-12. LCE separation events identified in the altimeter record...................................3-19 

Figure 3.1-13. Nighttime composite SST image from 22 April 2005 showing the LC and 

its associated cyclonic features. .........................................................................3-21 

Figure 3.2-1. Histograms of yearlong running averages of Loop Current metrics from 

the historical altimetry record. ...........................................................................3-24 

Figure 3.2-2. Histogram of the LCE separation period using data from Table 3.2-2 are 

shown for selected time intervals.......................................................................3-27 

Figure 3.2-3a. Zoomed SSH maps of LCEs 1 through 8 at the time of separation from the 

LC. .....................................................................................................................3-28 

 xiv 
Figure 3.2-3b. Zoomed SSH maps of LCEs 9 through 16 at the time of separation from 

the LC.................................................................................................................3-29 

Figure 3.2-3c. Zoomed SSH maps of LCEs 17 through 20 at the time of separation from 

the LC.................................................................................................................3-30 

Figure 3.2-4. The 17-cm tracking contour at the time of separation for all 20 LCEs 

observed from1 January 1993 through 30 June 2006. .......................................3-31 

Figure 3.2-5. Composite of LCE Vortex detachment and reattachment events. .....................3-32 

Figure 4.1-1. Ocean color images overlaid with SSH at 3-day intervals from July 9-18, 

2005......................................................................................................................4-4 

Figure 4.1-2. Ocean color images overlaid with SSH at 3-day intervals from July 21-30, 

2005......................................................................................................................4-5 

Figure 4.1-3. Ocean color images overlaid with SSH at 3-day intervals from August 2-

11, 2005................................................................................................................4-6 

Figure 4.1-4. Ocean color images overlaid with SSH at 3-day intervals from August 14-

23, 2005................................................................................................................4-7 

Figure 4.2-1. Top Panel: Time-average mean sea surface height (contours) and currents 

(black vectors) at the surface. ............................................................................4-10 

Figure 4.2-2. Upper panel: Mean surface eddy kinetic energy averaged between 27 

January to 19 January 2006 contoured every 200 cm2

s

-2...................................4-11 

Figure 4.2-3. 16 February 2005 to 28 February 2005..............................................................4-12 

Figure 4.2-4. 19 May 2005 to 31 May 2005............................................................................4-13 

Figure 4.2-5. 15 June 2005 to 27 June 2005............................................................................4-14 

Figure 4.2-6. 12 December 2005 to 24 December 2005..........................................................4-15 

Figure 4.2-7. Diagrams #1 and #2 show schematics used to compute relative vorticity 

from the Eastern Gulf PIES stations. .................................................................4-18 

Figure 4.2-8. Altimeter-derived SSH overlaid on 8-day composite chlorophyllconcentration image from 16 Feb 2005. ............................................................4-20 

Figure 4.2-9. Altimeter-derived SSH overlaid on 8-day composite chlorophyllconcentration image for 15 June 2005...............................................................4-21 

Figure 4.2-10. Altimeter-derived SSH overlaid on 8-day composite chlorophyllconcentration images for selected dates before Eddy Vortex separation. .........4-22 

 xv 
Figure 4.2-11. Altimeter-derived SSH overlaid on 8-day composite chlorophyllconcentration images for selected dates after Eddy Vortex separation. ............4-23 

Figure 5.1-1. Color contour of speed (top) and direction (bottom) for M1 during 

deployment 1 showing the effects of mooring draw down due to high 

currents.................................................................................................................5-2 

Figure 5.1-2. Color contour of temperature for M3 during deployment 1. ...............................5-3 

Figure 5.1-3. Color contour of speed (top) and direction (bottom) for M3 during 

deployment 2 showing inertial oscillations on the mooring due to 

hurricanes.............................................................................................................5-4 

Figure 5.1-4a. Gap-filled, gridded current speed from five moored ADCP depths and 

moored current meters M1 for deployments 1 (left) and 2 (right).......................5-5 

Figure 5.1-4b. Gap-filled, gridded current speed from five moored ADCP depths and 

moored current meters M2 for deployments 1 (left) and 2 (right).......................5-5 

Figure 5.1-4c. Gap-filled, gridded current speed from five moored ADCP depths and 

moored current meters M3 for deployments 1 (left) and 2 (right).......................5-6 

Figure 5.1-5. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M1 from 

deployment 1........................................................................................................5-8 

Figure 5.1-6. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M2 from 

deployment 1........................................................................................................5-9 

Figure 5.1-7. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M3 from 

deployment 1......................................................................................................5-10 

Figure 5.1-8. Detided, gap-filled, gridded u velocity time-series at mooring 1 during 

deployment 1 at 100 m and 428 m.....................................................................5-13 

Figure 5.1-9. (Clockwise from top left) Coherence, admittance, power, and phase 

spectra between u velocity components at 100 m and 428 m at mooring 1 

during deployment 1. .........................................................................................5-14 

Figure 5.1-10. (Clockwise from top left) Coherence, admittance, power, and phase 

spectra of north-south (v) velocity components at 70 m and 494 m at 

mooring M2 during deployment 2. ....................................................................5-15 

Figure 5.1-11. (Clockwise from top left) Coherence, admittance, power, and phase 

spectra between v velocity components at 749 m at mooring M1 and 

mooring M2 during deployment 1. ....................................................................5-17 

 xvi 
Figure 5.1-12. Detided, gap-filled, gridded east-west velocity time-series at mooring M2 

and mooring M3 during deployment 1 at 1995 m and 2699 m respectively. ....5-18 

Figure 5.1-13. (Clockwise from top left) Coherence, admittance, power, and phase 

spectra between u velocity components at mooring 2 and mooring 3 

during deployment 1 at 1995 m and 2699 m respectively.................................5-19 

Figure 5.1-14. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M1 (left: east-west 

component; right: north-south component). ......................................................5-21 

Figure 5.1-15. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M2 (left: east-west 

component; right: north-south component). ......................................................5-22 

Figure 5.1-16. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M3 (left: east-west 

component; right: north-south component). ......................................................5-23 

Figure 5.1-17. Extreme value fits for current speeds at Mooring 1, Depths 749 – 1492 m. .....5-27 

Figure 5.1-18. Extreme value fits for current speeds at Mooring 1, depth 2499 m and 

Mooring 2, depths 749 – 1244 m.......................................................................5-28 

Figure 5.1-19. Extreme value fits for current speeds at Mooring 2, depths 1492 – 1995 m 

and Mooring 3, Depths 750 – 997 m. ................................................................5-29 

Figure 5.1-20. Extreme value fits for current speeds at Mooring 3, depths 1245 – 2499 m. ....5-30 

Figure 5.1-21. Extreme value fits for current speeds at Mooring 3, depth 2699 m, and 

Mooring 4, depths 2530 – 2630 m.....................................................................5-31 

Figure 5.1-22. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 1. ..................................................................................5-32 

Figure 5.1-23. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 2. ..................................................................................5-32 

Figure 5.1-24. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 3. ..................................................................................5-33 

Figure 5.1-25. Total current speed and diurnal bandpass current speed for the second 

deployment at mooring 1. ..................................................................................5-33 

Figure 5.1-26. Total current speed and diurnal bandpass current speed for the second 

deployment at mooring 2. ..................................................................................5-34 

 xvii 
Figure 5.1-27. Total current speed and diurnal bandpass current speed for the second 

deployment at mooring 3. ..................................................................................5-34 

Figure 5.1-28. Total current speed and diurnal bandpass current speed during Hurricane 

Katrina at mooring 1. .........................................................................................5-35 

Figure 5.1-29. Total current speed and diurnal bandpass current speed during Hurricane 

Katrina at mooring 2. .........................................................................................5-36 

Figure 5.1-30. Total current speed and diurnal bandpass current speed during Hurricane 

Katrina at mooring 3. .........................................................................................5-36 

Figure 5.1-31. Total current speed and diurnal bandpass current speed during Hurricane 

Rita at mooring 1. ..............................................................................................5-37 

Figure 5.1-32. Total current speed and diurnal bandpass current speed during Hurricane 

Rita at mooring 2. ..............................................................................................5-38 

Figure 5.1-33. Total current speed and diurnal bandpass current speed during Hurricane 

Rita at mooring 3. ..............................................................................................5-38 

Figure 5.1-34. Scatter plot of band passed current speed vs. total current speed at 100 m 

depth...................................................................................................................5-39 

Figure 5.1-35. Scatter plot of band passed current speed vs. total current speed at 200 m 

depth...................................................................................................................5-39 

Figure 5.1-36. Scatter plot of band passed current speed vs. total current speed at 300 m 

depth...................................................................................................................5-40 

Figure 5.1-37. Scatter plot of band passed current speed vs. total current speed at 400 m 

depth...................................................................................................................5-40 

Figure 5.1-38. Ratio of band passed speed to total current speed. ............................................5-41 

Figure 5.1-39. (Top left) Wavelet power spectrum of the hourly east-west current timeseries at ~ 80 m depth at mooring 3 during deployment 2.................................5-43 

Figure 5.1-40. Contours of the frequency-averaged wavelet power in the inertial band 

(0.5 – 2 day period) during the weeks after Hurricanes Katrina and Rita in 

the upper 500 m of the water column at moorings M1 (top), M2 (middle), 

and M3 (bottom). ...............................................................................................5-44 

Figure 5.1-41. Principal component time-series for the leading modes from the combined 

three-mooring, full water column vertical EOF analysis of the frequencyaveraged wavelet power in the inertial band (0.5 – 2 day period) during 

deployment 2......................................................................................................5-45 

 xviii 
Figure 5.1-42. Amplitudes of leading modes for moorings M1 (left), M2 (center), M3 

(right), for combined three-mooring full water-column vertical EOF 

analysis of the frequency-averaged wavelet power in the inertial band (0.5 

– 2 day period) during deployment 2.................................................................5-46 

Figure 5.1-43. Eddy Vortex just before Hurricane Katrina.......................................................5-48 

Figure 5.1-44. Measurements at Mooring 3 compared to a one dimensional turbulence 

model. 5-49 

Figure 5.1-45. Diurnal bandpass currents at Mooring 3............................................................5-50 

Figure 5.1-46. Diurnal bandpass currents at Mooring 1............................................................5-51 

Figure 5.1-47. Lowpass current speed at Mooring 3 compared to the diurnal bandpass 

speed. .................................................................................................................5-52 

Figure 5.2-1. Color contour of the depth of the 20° isotherm during Hydrographic 

Cruise 1 in January 2005....................................................................................5-53 

Figure 5.2-2. Color contour of the depth of the 20° isotherm during Hydrographic 

Cruise 2 in August 2005. ...................................................................................5-54 

Figure 5.2-3. Color contour of the depth of the 20° isotherm during Hydrographic 

Cruise 3 in January 2006....................................................................................5-55 

Figure 5.2-4. Hydrocruise 3 Transect 1 temperature from XBT and CTD casts.....................5-56 

Figure 5.2-5. Hydrocruise 3 Transect 2 temperature from XBT and CTD casts.....................5-57 

Figure 5.2-6. Hydrocruise 3 Transect 3 temperature from XBT and CTD casts.....................5-58 

Figure 6.1-1. Locations of the principal full-depth moorings used in the analyses...................6-3 

Figure 6.1-2. Spaghetti plot of all 36 RAFOS float smoothed trajectories at all depths 

(1000 to 2500 m) in the Exploratory Study. ........................................................6-6 

Figure 6.1-3. Depth-integrated EKE for the CEOF mode 1 lower-layer currents at the 

locations identified in Table 6.1-2 (thick vertical bars).....................................6-11 

Figure 6.1-4. CEOF mode 1 normalized amplitudes for lower-layer currents........................6-12 

Figure 6.1-5. Spectra, in variance preserving form, for the normalized CEOF mode 1 

amplitudes of the lower-layer currents. .............................................................6-13 

Figure 6.1-6. a) Depth-integrated EKE as a function of frequency band................................6-14 

Figure 6.1-7. Lower-layer mean currents from RAFOS floats (red) and lower-layer 

current meters (purple).......................................................................................6-16 

 xix 
Figure 6.2-1. Mean (LH panel) and standard deviation ellipses (RH panel) for currents 

100 to 500 m above bottom (red) and ~ 1200 m depth (blue) except for 

42375 where the upper level is at 1560 m. ........................................................6-19 

Figure 6.2-2. Stick plots of the 40-HLP currents for the indicated moorings and depths.......6-21 

Figure 6.2-3. Tracks of the center low pressures of tropical storms and hurricanes that 

passed over the Gulf of Mexico in 2005............................................................6-22 

Figure 6.2-4. Upper panel: Mean lower-layer (2500 m) eddy kinetic energy averaged 

between 27 January to 19 January 2006 contoured every 20 cm2

s

-2. ................6-25 

Figure 6.2-5a. The LH panel shows the 3-day composite SST overlaid with CCAR 

altimeter-derived SSH for April 25, 2005..........................................................6-26 

Figure 6.2-5b. The LH panel shows the 3-day composite SST overlaid with CCAR 

altimeter-derived SSH for May 22, 2005...........................................................6-27 

Figure 6.2-5c. The LH panel shows the 3-day composite chlorophyll concentration 

overlaid with CCAR altimeter-derived SSH for August 1, 2005. .....................6-28 

Figure 6.2-5d. The LH panel shows the 3-day composite SST overlaid with CCAR 

altimeter-derived SSH for December 6, 2005....................................................6-29 

Figure 6.2-5e. The LH panel shows the 3-day composite SST overlaid with CCAR 

altimeter-derived SSH for December 26, 2005..................................................6-30 

Figure 6.2-5f. The LH panel shows the 3-day composite SST overlaid with CCAR 

altimeter-derived SSH for January 16, 2006......................................................6-31 

Figure 6.2-6. Snapshot of upper and lower layer circulation on May 23 (bottom panel) 

with surface geopotential referenced to 2500 m denoted by colored lines 

and bottom streamfunction indicated by filled colored contours.......................6-32 

Figure 6.2-7. Upper layer 40-HLP currents, temperatures (solid contours) and salinities 

from mooring M3...............................................................................................6-33 

Figure 6.3-1. Variance preserving kinetic energy spectra for selected lower-layer 

velocity observations at......................................................................................6-35 

Figure 6.3-2. Variance preserving kinetic energy spectra for near-bottom velocity 

observations on the indicated moorings.............................................................6-36 

Figure 6.3-3. West of 89°W, the near-bottom (100 to 500 MAB) EKE is contoured for 

the 335-33 day EOF mode 1 velocities from the Exploratory Program. ...........6-39 

Figure 6.3-4. West of 89°W, the near-bottom (100 to 500 MAB) EKE is contoured for 

the 33-17 day EOF mode 1 velocities from the Exploratory Program. .............6-40 

 xx 
Figure 6.3-5. RH panels show the local wavelet power spectrum of the velocity 

components from M3 at 2490 m for the indicated time interval using the 

Morlet wavelet normalized by the variances of the respective series................6-42 

Figure 6.3-6. RH panels show the local wavelet power spectrum of the velocity 

components from L3 at 2500 m for the indicated time interval using the 

Morlet wavelet normalized by the variances of the respective series................6-43 

Figure 7.1-1. Depth profiles of CEOF amplitudes (cm/s) from a) separate analyses of 

upper and lower layer currents at M3, and b) full water column analysis of 

normalized currents at M3. ..................................................................................7-2 

Figure 7.1-2. Mode 1 amplitude vector time series (top panel: upper-layer; bottom 

panel: lower-layer) from the M3 CEOF layer analysis........................................7-3 

Figure 7.1-3. Relative vorticity (as a fraction of f) contoured for the upper layer, and as 

time series for the lower layer (1500 and 2300 m) calculated for the M1, 

M2 and M3 moorings...........................................................................................7-7 

Figure 7.1-4. Coherence squared and phase differences between upper and lower layer 

averaged ζ (red lines), and ζ at 300 and 2300 m (blue lines)...............................7-8 

Figure 7.1-5. Potential vorticity anomalies and their component relative vorticity and 

stretching terms for the upper and lower layers with interface defined by 

the 8 °C isotherm (lower panel)...........................................................................7-9 

Figure 7.2-1. Vertical EOFs of east-west and north-south current velocity at mooring 

M1 during deployment 1....................................................................................7-12 

Figure 7.2-2. Vertical EOFs of east-west and north-south current velocity at mooring 

M1 during deployment 2....................................................................................7-13 

Figure 7.2-3. Vertical EOFs of east-west and north-south current velocity at mooring 

M2 during deployment 1....................................................................................7-14 

Figure 7.2-4. Vertical EOFs of east-west and north-south current velocity at mooring 

M2 during deployment 2....................................................................................7-15 

Figure 7.2-5. Vertical EOFs of east-west and north-south current velocity at mooring 

M3 during deployment 1....................................................................................7-16 

Figure 7.2-6. Vertical EOFs of east-west and north-south current velocity at mooring 

M3 during deployment 2....................................................................................7-17 

Figure 7.2-7. Location of BOEMRE Eastern Gulf of Mexico Circulation Study (EGOM) 

moorings and MMS Deepwater Physical Oceanography Reanalysis and 

Synthesis of Historical Data stations in the eastern Gulf of Mexico (east of 

89° W) that were used to estimate dynamic modes. ..........................................7-19 

 xxi 
Figure 7.2-8. T-S plot of CTD, XBT, and Nansen/Niskin bottle data collected between 

1915 and 2000 and analyzed in the MMS-funded Physical Oceanography 

Reanalysis and Synthesis of Historical Data Report (Nowlin et al. 2001) 

and CTD cast data from three EGOM cruises taken near each of the three 

EGOM mooring sites. ........................................................................................7-20 

Figure 7.2-9. Vertical profiles of Brunt-Vaisala frequency at or nearest to each mooring 

site based on three EGOM hydrographic cruises in January 2005, August 

2005, and January 2006. ....................................................................................7-21 

Figure 7.2-10. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at mooring M1 from cruises in January and August of 

2005....................................................................................................................7-22 

Figure 7.2-11. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at mooring M1 from cruises in August 2005 and January 

2006....................................................................................................................7-22 

Figure 7.2-12. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at mooring M2 from cruises in January and August of 

2005....................................................................................................................7-23 

Figure 7.2-13. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at mooring M2 from cruises in August 2005 and January 

2006....................................................................................................................7-23 

Figure 7.2-14. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at M3 from cruises in January and August of 2005...................7-24 

Figure 7.2-15. Normalized barotropic and first two baroclinic modes calculated with 

averaged casts at M3 from cruises in August 2005 and January 2006. .............7-24 

Figure 7.2-16. (Top) Spatial correlation between observed u velocity at mooring M1 from 

deployment 1 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-26 

Figure 7.2-17. (Top) Spatial correlation between observed v velocity at mooring M1 from 

deployment 1 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-26 

Figure 7.2-18. (Top) Spatial correlation between observed u velocity at mooring M1 from 

deployment 2 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-27 

Figure 7.2-19. (Top) Spatial correlation between observed v velocity at mooring M1 from 

deployment 2 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-27 

 xxii 
Figure 7.2-20. (Top) Spatial correlation between observed u velocity at mooring M2 from 

deployment 1 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-28 

Figure 7.2-21. (Top) Spatial correlation between observed v velocity at mooring M2 from 

deployment 1 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-28 

Figure 7.2-22. (Top) Spatial correlation between observed u velocity at mooring M2 from 

deployment 2 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-29 

Figure 7.2-23. (Top) Spatial correlation between observed v velocity at mooring M2 from 

deployment 2 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-29 

Figure 7.2-24. (Top) Spatial correlation between observed u velocity at mooring M3 from 

deployment 1 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-30 

Figure 7.2-25. (Top) Spatial correlation between observed v velocity at mooring M3 from 

deployment 1 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-30 

Figure 7.2-26. (Top) Spatial correlation between observed u velocity at mooring M3 from 

deployment 2 and the modeled u velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-31 

Figure 7.2-27. (Top) Spatial correlation between observed v velocity at mooring M3 from 

deployment 2 and the modeled v velocity from CTD cast data on the 

EGOM hydrographic cruises. ............................................................................7-31 

Figure 7.2-28. Temporal amplitudes of first baroclinic (bc) mode of the east-west 

velocity at M1 during deployment 1 (blue) and the SSH gradient in the 

north-south direction (green). ............................................................................7-33 

Figure 7.2-29. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the east-west velocity at M1 during 

deployment 1 and the SSH gradient in the north-south direction......................7-33 

Figure 7.2-30. Temporal amplitudes of first baroclinic mode of the north-south velocity 

at mooring M1 during deployment 1 (blue) and the SSH gradient in the 

east-west direction (green).................................................................................7-34 

Figure 7.2-31. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the north-south velocity component at 

mooring M1 during deployment 1 and the SSH gradient in the east-west 

direction. ............................................................................................................7-34 

 xxiii 
Figure 7.2-32. Temporal amplitudes of first baroclinic mode of the east-west velocity at 

mooring M1 during deployment 2 (blue) and the SSH gradient in the 

north-south direction (green). ............................................................................7-35 

Figure 7.2-33. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the east-west velocity component at mooring 

M1 during deployment 2 and the SSH gradient in the north-south 

direction. ............................................................................................................7-35 

Figure 7.2-34. Temporal amplitudes of first baroclinic mode of the north-south velocity 

at mooring M1 during deployment 2 (blue) and the SSH gradient in the 

east-west direction (green).................................................................................7-36 

Figure 7.2-35. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the north-south velocity first baroclinic mode at M1 during deployment 2 

and the SSH gradient in the east-west direction. ...............................................7-36 

Figure 7.2-36. Temporal amplitudes of first baroclinic for the east-west velocity mode at 

mooring M2 during deployment 1 (blue) and the SSH gradient in the 

north-south direction (green). ............................................................................7-37 

Figure 7.2-37. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode of the east-west velocity component at mooring 

M2 during deployment 1 and the SSH gradient in the north-south 

direction. ............................................................................................................7-37 

Figure 7.2-38. Temporal amplitudes of first baroclinic mode of the north-south velocity 

at mooring M2 during deployment 1 (blue) and the SSH gradient in the 

east-west direction (green).................................................................................7-38 

Figure 7.2-39. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the north-south velocity component at 

mooring M2 during deployment 1 and the SSH gradient in the east-west 

direction. ............................................................................................................7-38 

Figure 7.2-40. Temporal amplitudes of first baroclinic mode for the east-west velocity at 

mooring M2 during deployment 2 (blue) and the SSH gradient in the 

north-south direction (green). ............................................................................7-39 

Figure 7.2-41. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the east-west velocity component at mooring 

M2 during deployment 2 and the SSH gradient in the north-south 

direction. ............................................................................................................7-39 

Figure 7.2-42. Temporal amplitudes of first baroclinic mode for the north-south velocity 

at mooring M2 during deployment 2 (blue) and the SSH gradient in the 

east-west direction (green).................................................................................7-40 

 xxiv 
Figure 7.2-43. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the north-south velocity component at 

mooring M2 during deployment 2 and the SSH gradient in the east-west 

direction. ............................................................................................................7-40 

Figure 7.2-44. Temporal amplitudes of first baroclinic mode for the east-west velocity at 

mooring M3 during deployment 1 (blue) and the SSH gradient in the 

north-south direction (green). ............................................................................7-41 

Figure 7.2-45. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the east-west velocity component at mooring 

M3 during deployment 1 and the SSH gradient in the north-south 

direction. ............................................................................................................7-41 

Figure 7.2-46. Temporal amplitudes of first baroclinic mode for the north-south velocity 

at M3 during deployment 1 (blue) and the SSH gradient in the east-west 

direction (green).................................................................................................7-42 

Figure 7.2-47. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the north-south velocity at M3 during 

deployment 1 and the SSH gradient in the east-west direction. ........................7-42 

Figure 7.2-48. Temporal amplitudes of first baroclinic mode for the east-west velocity at 

M3 during deployment 2 (blue) and the SSH gradient in the north-south 

direction (green).................................................................................................7-43 

Figure 7.2-49. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic mode for the east-west velocity at M3 during 

deployment 2 and the SSH gradient in the north-south direction......................7-43 

Figure 7.2-50. Temporal amplitudes of first baroclinic (bc) mode for the north-south 

velocity at M3 during deployment 2 (blue) and the SSH gradient in the 

east-west direction (green).................................................................................7-44 

Figure 7.2-51. Coherency (top) and phase (bottom) spectra of the temporal amplitudes of 

the first baroclinic (bc) mode for the north-south velocity at M3 during 

deployment 2 and time series of the SSH gradient in the east-west 

direction. ............................................................................................................7-44 

Figure 7.2-52. Power spectra of the time-series amplitudes of the first three theoretical 

modes (top: barotropic mode; middle: first baroclinic mode; bottom: 

second baroclinic mode) time-series for fits to the east-west (left) and 

north-south (right) velocity data at mooring M3 during deployment 1.............7-46 

Figure 7.2-53. Normalized autocovariance function (NACF) of mode amplitudes from 

the fit to east-west and north-south velocity component data at mooring 

M3 during deployment 1....................................................................................7-47 

 xxv 
Figure 7.3-1. Measurement array mean eddy kinetic energy (EKE) at the surface (blue) 

and at 2500 m (red)............................................................................................7-48 

Figure 7.3-2. Top (bottom) panel: Mean (standard deviation) lower-layer potential 

vorticity..............................................................................................................7-51 

Figure 7.3-3. Top (middle) panel: Mean (standard deviation) of lower-layer thickness.........7-52 

Figure 7.3-4. Top (middle) panel: Mean (standard deviation) of lower-layer relative 

vorticity divided by the local Coriolis parameter (f). ........................................7-53 

Figure 7.3-5. Top panel: Snapshot of upper and deep circulation on August 3, 2005. 

PIES derived SSH (thick lines) and 2500 m streamfunction (solid color; 

blue shades cyclonic, pink shades anticyclonic)................................................7-54 

Figure 7.3-6. Top panel: Snapshot of upper and deep circulation on August 3, 2005. 

PIES derived SSH (thick lines) and 2500 m streamfunction (solid color; 

blue shades cyclonic, pink shades anticyclonic)................................................7-55 

Figure 7.3-7. Properties of event c cyclone. ............................................................................7-56 

Figure A-1. Storm track and wind extent of tropical storm Arlene............................................ 3 

Figure A-2. Storm track and wind extent of hurricane Cindy.................................................... 4 

Figure A-3. Storm track and wind extent of hurricane Dennis. ................................................. 5 

Figure A-4. Storm track and wind extent of hurricane Katrina.................................................. 6 

Figure A-5. Storm track and wind extent of hurricane Rita. ...................................................... 7 

Figure A-6. Storm track and wind extent of hurricane Wilma................................................... 8 

Figure B-1. Mooring 1 current vectors for Deployment 1. ........................................................ 3 

Figure B-2. Mooring 1 current vectors for Deployment 2. ........................................................ 4 

Figure B-3. Mooring 2 current vectors for Deployment 1. ........................................................ 5 

Figure B-4. Mooring 2 current vectors for Deployment 2. ........................................................ 6 

Figure B-5. Mooring 3 current vectors for Deployment 1. ........................................................ 7 

Figure B-6. Mooring 3 current vectors for Deployment 2. ........................................................ 8 

Figure B-7. Mooring 4 current vectors for Deployment 1. ........................................................ 9 

Figure B-8. Mooring 4 current vectors for Deployment 2. ...................................................... 10 

 xxvi 
Figure D-1. Amplitude (left column) and phase (right column) of the O1, K1, Q1, and 

P1 constituents determined with the tidal response method (Munk and 

Cartwright, 1966) from the six bottom pressure records........................................ 3 

Figure D-2. Amplitude (left panels) and phase (right panels) of the M2, K2, N2, and 

S2 constituents determined with the tidal response method (Munk and 

Cartwright, 1966) from the six bottom pressure records. ....................................... 4 

Figure E-1. Latitude of the center of Eddy Ulysses................................................................... 5 

Figure E-2. Longitude of the center of Eddy Ulysses................................................................ 5 

Figure E-3. Orbital period in Eddy Ulysses............................................................................... 6 

Figure E-4. Eccentricity of Eddy Ulysses.................................................................................. 6 

Figure E-5. Orientation of the major axis of Eddy Ulysses. ...................................................... 7 

Figure E-6. Latitude of the center of Eddy Vortex early in 2005. ............................................. 8 

Figure E-7. Longitude of the center of Eddy Vortex early in 2005. .......................................... 8 

Figure E-8. Orbital period of Eddy Vortex early in 2005.......................................................... 9 

Figure E-9. Eccentricity of Eddy Vortex early in 2005. ............................................................ 9 

Figure E-10. Orientation of the major axis of Eddy Vortex early in 2005. ............................... 10 

Figure E-11. Latitude of the center of Eddy Vortex late in 2005. ............................................. 11 

Figure E-12. Longitude of the center of Eddy Vortex late in 2005. .......................................... 11 

Figure E-13. Orbital period of Eddy Vortex late in 2005. ......................................................... 12 

Figure E-14. Eccentricity of Eddy Vortex late in 2005. ............................................................ 12 

Figure E-15. Orientation of the major axis of Eddy Vortex late in 2005................................... 13 

Figure E-16. Latitude of the center of Eddy Walker.................................................................. 14 

Figure E-17. Longitude of the center of Eddy Walker............................................................... 14 

Figure E-18. Orbital period of Eddy Walker. ............................................................................ 15 

Figure E-19. Eccentricity of Eddy Walker................................................................................. 15 

Figure E-20. Orientation of the major axis of Eddy Walker...................................................... 16 

Figure E-21. Latitude of the center of Cold Eddy 1................................................................... 17 

 xxvii 
Figure E-22. Longitude of the center of Cold Eddy 1................................................................ 17 

Figure E-23. Orbital period of Cold Eddy 1. ............................................................................. 18 

Figure E-24. Eccentricity of Cold Eddy 1.................................................................................. 18 

Figure E-25. Orientation of the major axis of Cold Eddy 1....................................................... 19 

Figure E-26. Latitude of the center of Cold Eddy 2................................................................... 20 

Figure E-27. Longitude of the center of Cold Eddy 2................................................................ 20 

Figure E-28. Orbital period of Cold Eddy 2. ............................................................................. 21 

Figure E-29. Eccentricity of Cold Eddy 2.................................................................................. 21 

Figure E-30. Orientation of the major axis of Cold Eddy 2....................................................... 22 

Figure E-31. Latitude of the center of Cold Eddy 3................................................................... 23 

Figure E-32. Longitude of the center of Cold Eddy 3................................................................ 23 

Figure E-33. Orbital period of Cold Eddy 3. ............................................................................. 24 

Figure E-34. Eccentricity of Cold Eddy 3.................................................................................. 24 

Figure E-35. Orientation of the major axis of Cold Eddy 3....................................................... 25 

Figure E-36. Latitude of the center of Cold Eddy 4................................................................... 26 

Figure E-37. Longitude of the center of Cold Eddy 4................................................................ 26 

Figure E-38. Orbital period of Cold Eddy 4. ............................................................................. 27 

Figure E-39. Eccentricity of Cold Eddy 4.................................................................................. 27 

Figure E-40. Orientation of the major axis of Cold Eddy 4....................................................... 28 

Figure E-41. Latitude of the center of the Loop Current. .......................................................... 29 

Figure E-42. Longitude of the center of the Loop Current. ....................................................... 29 

Figure E-43. Orbital period in the Loop Current. ...................................................................... 30 

Figure E-44. Eccentricity of the Loop Current. ......................................................................... 30 

Figure E-45. Orientation of the major axis of the Loop Current. .............................................. 31 

Figure F-1. Mooring map for the Eastern GOM observational program................................. 10 

 xxviii 
 xxix 

Figure F-2. Locations of tall moorings M1-M3 (shown with read stars) overlaid on the 

real-time analysis of surface fronts for August 29, 2005 (provided by 

Horizon Marine Inc.) ............................................................................................ 11 

Figure F-3. Near-inertial response to hurricane Katrina at Mooring 1 (Forristall, 2007)........ 12 

Figure F-4. Near-inertial response to hurricane Katrina at Mooring 3 (Forristall, 2007)........ 13 

Figure F-5. Surface frontal analysis provided by Horizon Marine Inc. for August 20, 

2005....................................................................................................................... 14 

Figure F-6. Surface frontal analysis provided by Horizon Marine Inc. for August 27, 

2005....................................................................................................................... 15 

Figure F-7. Surface currents simulated during the “spinup” initialization on August 24, 

2005....................................................................................................................... 16 

Figure F-8. Surface currents simulated during the “spinup” initialization on August 25, 

2005....................................................................................................................... 17 

Figure F-9. Surface currents simulated during the “spinup” initialization on August 26, 

2005....................................................................................................................... 18 

Figure F-10. Surface currents simulated during the “spinup” initialization on August 27, 

2005....................................................................................................................... 19 

Figure F-11. Observed (upper panel) and simulated (lower panel) current speed at the 

northern mooring. ................................................................................................. 20 

Figure F-12. Observed (upper panel) and simulated (lower panel) current speed at the 

middle mooring..................................................................................................... 21 

Figure F-13. Observed (upper panel) and simulated (lower panel) current speed at the 

southern mooring. ................................................................................................. 22 
LIST OF TABLES 

Page 

Table 2.1-1. Deployment locations of the moorings for Deployment 1...................................2-3 

Table 2.1-2. Deployment locations of the moorings for Deployment 2...................................2-4 

Table 2.1-3. Deployment information of the tall (M1, M2, and M3) and short (M4) 

moorings for each instrument deployed...............................................................2-7 

Table 2.1-4. Summary of data coverage by each instrument and their sensors for 

Mooring 1 during January 2005 to January 2006. .............................................2-13 

Table 2.1-5. Summary of data coverage by each instrument and their sensors for 

Mooring 2 during January 2005 to January 2006. .............................................2-14 

Table 2.1-6. Summary of data coverage by each instrument and their sensors for 

Mooring 3 during January 2005 to January 2006. .............................................2-15 

Table 2.1-7. Summary of data coverage by each instrument and their sensors for 

Mooring 4 during January 2005 to January 2006. .............................................2-16 

Table 2.1-8. Data return statistics for each mooring and each instrument type during 

both deployments...............................................................................................2-16 

Table 2.3-1. Temperature Differences. ..................................................................................2-56 

Table 2.3-2. Velocity Differences. .........................................................................................2-57

Table 2.4-1. Satellite Altimeter Missions during the Eastern Gulf Program. ........................2-60 

Table 2.5-1. Satellite Periods. ................................................................................................2-70 

Table 2.5-2. Variance Statistics..............................................................................................2-74 

Table 2.5-3. PIES Statistics....................................................................................................2-75 

Table 2.5-4. SNR Statistics. ...................................................................................................2-76 

Table 2.5-5. Half-power Period of PIES Barotropic, Baroclinic, and Total SSH Signals.....2-80 

Table 2.5-6. Satellite Altimeter and PIES SSH Correlation...................................................2-83 

Table 2.6-1. Storm Events......................................................................................................2-90 

Table 3.1-1. LCE Vortex Detachment and Reattachment Events............................................3-6 

Table 3.1-2. Altimeter-derived Summary Statistics...............................................................3-12 

 xxxi 
Table 3.1-3. Ring Separation Events from the Altimetric Record: 1 January 1993 

through 30 June 2006.........................................................................................3-18 

Table 3.2-1. Intrusion Events. ................................................................................................3-23 

Table 3.2-2. LCE Separation Periods.....................................................................................3-25 

Table 5.1-1. Extreme current speed distributions at Mooring 1.............................................5-24 

Table 5.1-2. Extreme current speed distributions at Mooring 2.............................................5-24 

Table 5.1-3. Extreme current speed distributions at Mooring 3.............................................5-25 

Table 5.1-4. Extreme current speed distributions at Mooring 4.............................................5-25 

Table 6.1-1. Moorings Deployed by Observational Studies in the Deep GOM. .....................6-5 

Table 6.1-2. Lower-Layer EOF Analysis of Currents by Mooring..........................................6-9 

Table 6.1-3. Time Scales and Degrees of Freedom for Lagrangian and Eulerian 

Velocity Statistics ..............................................................................................6-17 

Table 6.3-1. EOF and Wavenumber Analysis of Eastern GOM Deep Currents....................6-34 

Table 7.1-1. Potential Vorticity Parameters .............................................................................7-6 

Table 7.2-1. EOF Mode Variance ..........................................................................................7-11 

Table C-1. Statistics from Mooring 1 Deployment 1 ADCP for the u and v 

components of the currents measured................................................................. C-3 

Table C-2. Statistics from Mooring 1 Deployment 1 single point current meters for 

the u and v components of the currents measured. ............................................. C-5 

Table C-3. Statistics from Mooring 2 Deployment 1 ADCP for the u and v 

components of the currents measured................................................................. C-6 

Table C-4. Statistics from Mooring 2 Deployment 1 single point current meters for 

the u and v components of the currents measured. ............................................. C-8 

Table C-5. Statistics from Mooring 3 Deployment 1 ADCP for the u and v 

components of the currents measured................................................................. C-9 

Table C-6. Statistics from Mooring 3 Deployment 1 single point current meters for 

the u and v components of the currents measured. ........................................... C-11 

Table C-7. Statistics from Mooring 4 Deployment 1 single point current meters for 

the u and v components of the currents measured. ........................................... C-11 

 xxxii 
 xxxiii 

Table C-8. Statistics from Mooring 1 Deployment 2 ADCP for the u and v 

components of the currents measured............................................................... C-12 

Table C-9. Statistics from Mooring 1 Deployment 2 single point current meters for 

the u and v components of the currents measured. ........................................... C-14 

Table C-10. Statistics from Mooring 2 Deployment 2 ADCP for the u and v 

components of the currents measured............................................................... C-15 

Table C-11. Statistics from Mooring 2 Deployment 2 single point current meters for 

the u and v components of the currents measured. ........................................... C-17 

Table C-12. Statistics from Mooring 3 Deployment 2 ADCP for the u and v 

components of the currents measured............................................................... C-18 

Table C-13. Statistics from Mooring 3 Deployment 2 single point current meters for 

the u and v components of the currents measured. ........................................... C-20 

Table C-14. Statistics from Mooring 4 Deployment 2 single point current meters for 

the u and v components of the currents measured. ........................................... C-20 

Table D-1. Amplitude in cm and phase in degrees for the eight major tidal 

constituents (O1, K1, Q1, P1, M2, K2, N2, S2) constituents determined 

with the tidal response method (Munk and Cartwright, 1966). .......................... D-5 
EXECUTIVE SUMMARY 

Project Background 

The major source of energy forcing currents in the surface waters of the Gulf of Mexico (GOM) 

is the Loop Current (LC) which flows northward through the Yucatan Channel into the GOM, 

and then turns eastward and exits through the Straits of Florida to join the Gulf Stream. The LC 

varies in its penetration into the GOM, sometimes constraining itself to the southern Gulf, and 

sometimes penetrating far northward into the northern Gulf. During most periods when the LC 

has penetrated northward, cold core eddies and warm water filaments can be found migrating 

around its periphery. Often when extended far northward, the LC pinches off, forming a Loop 

Current Eddy (LCE) that migrates through the northern Gulf, eventually moving westward to die 

within its western regions. LCEs detach from the LC at periods ranging from 3 to 17 months, 

with a mean frequency of separation near 10 months (Sturges and Leben 2000). Very energetic 

LCEs interact with one another, the LC, and bathymetry, forming cyclonic eddies with which 

they also interact. There are times, however, that the LC retreats southward without shedding an 

eddy. 

All this activity by the LC, LCE’s, and associated features, imparts significant energy to the 

surface waters of the GOM. While the overall net circulation of the surface waters in the GOM 

based on drifter records is generally understood to be a clockwise circulation pattern around the 

basin (DiMarco et al. 2005), the magnitude of the velocity and variance of the surface currents 

are known to be greatest in the vicinity of the LC, where speeds often exceed 1.5 m s-1. 

In deeper waters of the GOM, previous studies (Hamilton 1990; Donohue et al. 2006) have 

identified energetic, deep, barotropic (below about 1000 m) motions with some indications of 

bottom intensification at various locations on the slope and rise of the North-central Gulf, 

particularly along the Sigsbee Escarpment. With time scales of 10 d or more and amplitudes up 

to 1 m s-1, the phenomena responsible for these motions are generally attributed to topographic 

Rossby waves (TRWs). In general, little coupling of upper and lower layer circulation in the 

GOM appears to occur. However, some instances of coupling have been observed in other 

observation programs. Also, modeling studies output suggest that deep cyclonic (anti-clockwise) 

and anti-cyclonic (clockwise) eddies form in the Eastern and Central Gulf and propagate into the 

Western Gulf guided by topography. Some modeling results (Welsh and Inoue 2000) suggest 

that an anticyclone/cyclone pair form in the lower level in response to an anti-cyclonic LCE in 

the upper layer. 

Recent agency studies have investigated the circulation features and their characteristics and 

vertical variations over the coastal shelf off Texas and Louisiana (Nowlin et al. 1998a, Nowlin et 

al. 1998b), and in the deeper waters of the central (Donohue et al. 2006) and western Gulf of 

Mexico (Dononhue et al. 2008). A lack of current measurements and understanding of the 

circulation in the deep northeastern Gulf of Mexico prompted the BOEMRE to develop and fund 

a study titled: Survey of Deepwater Currents in the Eastern Gulf of Mexico. In July 2004 a 

contract was awarded to Evans-Hamilton, Inc. (EHI) and its science team to perform this study. 

This study is part of a larger research effort by the BOEMRE to gain a better understanding of 

the surface and deep dynamic processes in the GOM. 

 xxxv 
Study Area 

The study area is located within the Eastern GOM. This area consists of the area of the Eastern 

Gulf Lease Sale 181. The study area is located south of Mobile Bay in water depths ranging from 

2000 to 2800 m, and is bounded approximately by the following coordinates: 

NW Corner: 28.848 oN, 87.918 oW NE Corner: 28.850 oN, 87.523 oW 

SW Corner: 27.453 oN, 87.907 oW SE Corner: 27.455 oN, 87.516 oW 

Bathymetrically, the area is bounded as follows. 

To the north: by the ~2000 m isobath, & by a slope incised by hills & valleys 

To the east: the northern half by the steep slope of the West Florida Escarpment 

To the east: the southern half by a flat plain at 2500-2800 m depth 

To the south: by a relatively flat featureless plain 

To the west: by a slope with isobaths directed NNE to SSW 

Key bathymetric features of the study area include that the: 

1. Area lies to NE of the Sigsbee Escarpment, and SW of the DeSoto Canyon. 

2. Area contains primarily NNE to SSW oriented isobaths, rather than E-W isobaths 

3. Area contains the farthest northward extent of the 2000 m isobath in the Gulf of Mexico, 

plus NNE of the study area is located the farthest northward extent of the 200 m isobath. 

As a result, the area provides the best opportunity for the most northerly penetration of 

the LC or a LCE within the Gulf of Mexico. 

4. Area surrounding the study area has the largest separation between the 2000 and 3000 m 

isobaths within the Gulf of Mexico. This area is a large, relatively flat area. 

5. The West Florida Escarpment intersects the eastern boundary of the study area at ~ 28.4o 

N, or approximately one-third the distance from the NE to the SE corners of the study 

area. 

Study Objectives 

The goal of this study was to investigate and document the deepwater circulation in the Eastern 

GOM. This is an area of sparse previous deepwater current measurements. Specific study 

objectives were to: 

• Conduct measurements of currents using moorings to increase the regional 

database of ocean currents in the Eastern GOM. 

• Improve the scientific community’s overall knowledge and understanding 

of circulation features in this deepwater area. 

• Collect hydrographic, remote sensing, and other relevant measurements 

useful to understanding what controls the region’s circulation. 

• Assess the key processes energizing the circulation. 

• Add to the database of LC and LCE characteristics, and how these features 

affect the study area. 

 xxxvi 
• Establish an improved base of knowledge to help design future circulation 

studies in this part of the GOM. 

• Provide measurements and knowledge which could assist with future 

calculations of horizontal and vertical trajectories of released oil and its 

dispersion. 

The objectives of the study were met by conducting a one-year measurement program to collect 

an integrated set of current, hydrography, remote sensing, and ancillary measurements that could 

provide an excellent understanding of the circulation processes in the area. These measurements 

were collected from January 2005 to January 2006 and included current measurements and water 

properties collected from four moorings in water depths from ranging from 2500 to 2800 m. The 

mooring measurements were supplemented with measurements from bottom-moored PIES, three 

hydrography (profiling CTD and XBT) cruises, and satellite imagery and altimetry. Satellitetracked drifting buoy data along with Eddy Watch maps were obtained from Horizon Marine, 

Inc. for the period of the study’s measurements, and utilized under a limited license for 

additional analyses of the characteristics of the LC and LCE’s. Publicly available river discharge 

data, coastal and offshore wind data, and coastal water level data during the measurement period 

were also obtained. 

Study Team 

The Science Team Principal Investigators (PIs) for the study all have conducted research and 

analysis of the circulation of the Gulf of Mexico for several years. Drs. Peter Hamilton, Robert 

Leben, Kathleen Donohue, and Randolph Watts have participated in recent MMS studies of the 

deep central and western GOM, and were selected to provide continuity of their past work to the 

planning and analyses performed for this study. Dr. Steven DiMarco led the compilation and 

analysis of all available current measurements in the GOM for MMS (Nowlin et al. 2001), and 

was selected for his overall understanding of the circulation features within the GOM. Dr. 

George Forristall was a Senior Oceanographer at Shell Oil Company who studied extreme and 

operational oceanographic conditions within the GOM, and was selected to provide his 

knowledge and an oil industry perspective to the science team. 

All PIs contributed to the design of the study, analyses of the measurements and remote sensing 

data, and participated in the writing of this report. Extensive collaboration occurred between PIs, 

both during planning of the study and during analysis of the measurements resulting from this 

study. In addition to the Science Team PI’s, the following personnel led the organization and 

conduct of the project: 

Mr. Jeffrey Cox, EHI – Program Manager 

Mrs. Carol Coomes – Assistant Program Manager, Data Manager 

Mr. Keith Kurrus and Mr. Kevin Redman, EHI – Cruise Chief Scientists 

Mrs. Kari Walker, EHI – Data Processing & QA/QC Team Leader 

Many additional personnel in all team member organizations contributed significantly to the 

performance of work conducted for this study. 

 xxxvii 
Study Design 

The current measurement moorings consisted of three tall moorings and one short mooring. The 

tall moorings reached from ~70 m depth to bottom in water depths between 2600 to 2800 m. The 

one short mooring reaching 250 m above the bottom to the bottom at 2750 m depth. The design 

of the moorings was to provide measurement of current velocity and temperature over the full 

water column, but at higher vertical resolution over the top 500 m where the LC and LCE’s most 

strenuously influence the currents. Horizontally the moorings were spaced close enough to 

examine correlations between them and assess regional vorticity, but far enough apart to provide 

regional coverage of the study area. 

The three tall moorings contained upward-looking 75 kHz ADCPs at 500 m depth, with single 

point current meters spaced at intervals from 750 m to near bottom. The short mooring contained 

two single point current meters in the lower 100 m of the water column. Overall, excellent data 

coverage was achieved from the moorings. 

An array of seven inverted echo sounders with pressure gauges (PIES) was deployed in order to 

increase the spatial extent of the moored current meter array. Also, two PIES instruments were 

deployed at two of the seven PIES deployment sites for a portion of the study. Data return from 

the PIES was excellent. Full deployment records are available from all PIES with two 

exceptions: first, the initial instrument at PIES site 6 did not have valid τ records and therefore 

only the second deployment’s data from this site were used; and second, the PIES at site 7 was 

not recovered, although the full daily average data set was received by acoustic transmission. 

Three hydrography cruises were conducted during the 12-month measurement period. The 

hydrography cruises used a combination of CTD casts and XBT profiles designed to ensure 

sufficient data density, efficiency of operations during the cruise, and coverage of the study area. 

The first hydrography cruise was conducted January 17-23, 2005 and followed a grid pattern as 

no LC features were located near the study area at the time. The second hydrography cruise was 

conducted August 18-25, 2005 and again followed the grid pattern and the general station type. 

Additional XBT profiles were collected every 10 km as the ship crossed the loop eddy on the 

way back to shore. Hydrographic Cruise 2 finished one day ahead of Hurricane Katrina entering 

the GOM. 

The third hydrography cruise was conducted January 20-28, 2006 and did not use the grid 

design. As the time was approaching for retrieval of all the moorings and PIES and the third 

hydrography cruise, satellite imagery showed the LC was moving northeastward toward the 

study area, and two cold core eddies appeared to be located in the southern half of the study area 

along with some other frontal features. A cruise plan was devised to intensively sample the edge 

of the LC and the cold core eddies. 

All data from the moorings and hydrographic cruises were processed, QA/QC’d, and converted 

to standard format files. Graphical displays and tabular summaries of these data were then 

created. These were then distributed along with the processed data files to all PI’s for their 

specific analyses of the measurements. 

 xxxviii 
Remote sensing (satellite) data collected for the study included sea surface height (SSH) data, 

high-resolution sea surface temperature (SST), and ocean color imagery. These data were 

collected, processed, and the results distributed to team members by the Colorado Center for 

Astrodynamics Research (CCAR). 

Five hurricanes and one tropical storm passed through the GOM during the measurement 

program in 2005. Information on the tracks of the storms was obtained from the National 

Hurricane Center (NHC) website http://www.nhc.noaa.gov. 

Results 

Loop Current Events 

From the remote sensing data, statistics of LC intrusion as well as LCE detachment, 

reattachment, and final separation events that occurred during the program time period were 

developed based on an objective method (Leben 2005) for tracking the LC and detecting LCE 

separation events that gives separation periods comparable to those determined by subjective 

tracking methods. Continuous altimeter mapping of the sea surface height in the GOM since 

1993 provided the ability to place the LC and LCE events during the study period into 

perspective with this historical period. Additional historical perspective back to July 1973 is also 

provided based on previous LCE identifications using SST imagery (Vukovich 1988). Herein LC 

and LCE statistics are presented both for the study period and for these historical periods. 

During the study period, the LC penetrated and remained far north in the central and eastern 

portions of the GOM, often influencing the study area. Only a single large anticyclonic eddy, 

which was given the name “Vortex”, separated from the LC during the study period. However, 

Eddy Vortex detached and re-attached from the LC four times prior to its final separation from 

the LC on 13 September 2005. For historical perspective, although eddies may detach from and 

reattach to the LC, ultimate LCE separation occurs most frequently at intervals of about 6, 9 and 

11.5 months based on the available historical measurements (Leben 2005). 

The extended intrusion of the LC into the northern GOM associated with Eddy Vortex was one 

of the most northerly intrusions of the LC on record, only exceeded by the intrusion that 

generated Eddy Sargassum during the Exploratory Study. This far northerly intrusion of the LC 

and Eddy Vortex during late summer 2005 contributed to the intensification of Hurricanes 

Katrina and Rita (Walker et al. 2005). After the separation of Eddy Vortex, the LC did not retreat 

substantially to the south. As a result the LC remained intruded into the eastern-central GOM 

close to the study area during the remainder of the study’s measurement period. 

The extended LC intrusion associated with the repeated detachment and reattachment of LCE 

Vortex before ultimate separation in September 2005 significantly impacted the study region 

upper ocean circulation during the first half of the EGOM program. Once Eddy Vortex 

separated, fewer LC or LC frontal feature impacts to the circulation in the study area occurred, 

and the character of the circulation returned to conditions more typical of this northern location 

in the eastern deepwater GOM basin. 

 xxxix 
The 13.5 year historical altimetry record (1993-June 2006) showed that LC or LCE intrusions 

into the study area averaged about 22 days per year, whereas during the study, the LC or Eddy 

Vortex intruded into the study area 52 days total in 2005, over twice the historical average. Only 

one other calendar year had a greater occurrence of intrusion, which was 91 days in 2003 

associated with Eddy Sargassum. 

Mooring Measurements 

During the mooring measurements the study area experienced the influence of either the LC, 

Eddy Vortex, or frontal features multiple times. In addition, several hurricanes and a tropical 

storm passed through the GOM during 2005, some of them close enough to the study area to 

result in distinguishable impacts to the current measurements. The end result is that the moorings 

captured a robust set of measurements showing the impacts to the eastern GOM circulation by 

the LC, an LCE, frontal features, and hurricanes. The measurements were collected during two 

deployments, with the servicing of the moorings occurring just prior to the arrival of Hurricane 

Katrina. 

During the first deployment all three tall moorings experienced significant periods of stronger 

currents primarily but not entirely generated by the LC, Eddy Vortex, or LC or LCE frontal 

features. At M3, nearly the entire first deployment contained stronger currents. Currents at M2 

were quite similar to those at M3, whereas the strength and duration of stronger currents at M1 

were reduced as compared to those at M2 and M3. During the second deployment, periods of 

stronger currents were normally shorter, and current strengths reduced as compared to the first 

deployment, although Mooring M3 continued to show influences on the currents due to both 

hurricanes and the LC/LCE/frontal features. 

Currents during both deployments at all three tall moorings showed a high degree of coherency 

at water depths above 500 m, with weak coherence extending down to 750 m, and with only 

occasional coherence at deeper depths. However, during those occasional events, the 

observations indicated a strong barotropic component to the flow structure. For example, in midAugust 2005, at mooring M3, there was a barotropic event associated with the detachment and 

reattachment of an LCE. The feature was coherent throughout the water column and peaked in 

the upper ocean with only gradual diminishment with depth. In October through mid-December 

2005, there was a second barotropic current event that was seen in the velocity data collected at 

M2 and M3. During this second event, the increase in current speed was associated with a LC 

meander into the study area. 

Large-amplitude inertial oscillations in the study area were excited immediately after the 

passages of Hurricanes Katrina in late August 2005 and Rita on 21 September 2005. These 

oscillations persisted for at least two weeks after the passage of the storms. The inertial motions 

were strongest at M3 and penetrated down to 500 m. Hurricane Dennis, which entered the Gulf 

on July 9th and later passed very close to the study area, also generated less intense inertial 

oscillations at M1. 

 xl 
During the first deployment, the moorings each had similar inertial energy amplitudes. During 

the second deployment, moorings M2 and M3 had significantly more energy in the inertial band 

than mooring M1, owing to the closer proximity of these mooring to the centers of Hurricanes 

Katrina and Rita. Hurricane Katrina came closest to all three moorings late on August 28. All the 

moorings were to the right of the storm track and roughly the same distance from it. The 

resulting clockwise rotating wind stress vector had about the same potential for generating 

inertial oscillations at all the moorings. The inertial oscillations were much stronger at M3 than 

at the other moorings. This difference in strength cannot be explained by any large difference in 

the wind forcing at the moorings. The very strong inertial response at M3 is believed to have 

been caused by the coincidence of the hurricane and a cyclonic eddy. 

The inertial motions generated by Hurricanes Katrina and Rita were also investigated using the 

wavelet transform. This method estimates the temporal variability of energy in specified 

frequency bands. Looking at the wavelet power spectrum, it was clear that inertial motions were 

excited immediately following hurricanes Katrina and Rita and persisted for around 2 weeks at 

this depth. Not only did the storms amplify inertial motions; energy was elevated throughout the 

sub-inertial frequency domain. The average variance in the inertial band time-series was 

constructed by integration of the wavelet power spectrum in the period band 0.5 – 2 days. The 

significant peaks in the variance in early September further illustrate the effects of the passage of 

the two hurricanes. 

There were generally two subsurface maxima of energy present after the storms and two paths 

for inertial energy were revealed. There was a direct influence on the entire water column that 

occurred during or immediately after the storm due to the storm’s intensity. There was also the 

downward propagation of inertial energy, evidenced by the diagonal streak of high energy 

following the storm. 

Inertial waves after Katrina were present more than 2 weeks after the storm and penetrated 

quickly to the base of the upper layer. The amplitudes of the inertial oscillations after Hurricane 

Rita were not as large as the motions excited by Hurricane Katrina and didn’t penetrate as deep, 

but appeared to persist at the surface longer. The rate of downward inertial energy propagation 

was roughly 30 m day-1. 

A full water column vertical empirical orthogonal function (EOF) of the average variance in the 

inertial band was performed. Modes 1, 2, and 3 explain ~71%, ~8%, and ~4% respectively of the 

variance in the inertial band energy. 

Spectral energy from the currents was greatest in the shallow ocean (< 300 m depth). Surface 

records (~ 50 m) contained larger weather-band variance than deeper records as expected since 

the influence of winds on currents generally diminishes with depth. This was especially true at 

moorings M2 and M3, where the variance steadily increased between 0.9 cpd and 0.1 cpd. 

Near-surface spectral energy associated with periods of 20-60 days was typically associated with 

mesoscale processes such as the LC and LCEs. Low-frequency spectral estimates in the upper 

ocean at all tall moorings were roughly equal. There was slightly more sub-inertial energy 

present during deployment 1, especially at the 20 – 60 day period. This is likely attributable to 

the penetrations of the LC and Eddy Vortex into the study area multiple times. 

 xli 
Relative to the surface, spectral energy in deeper currents were less energetic. The overall shapes 

of the trends of the spectra energy of the deeper records closely resembled those of the upper 

ocean. Subinertial variability, particularly in the lowest bands shown, decreased from south to 

north. This may be attributed to the motions associated with the LC and LCE events at each 

mooring. There were some cases where low frequency variance (20 – 60 day period band) in the 

deepest record (usually 2500 m) was greater than the energy in the record at ~ 1000 m, which 

could be evidence of topographic Rossby waves. 

The vertical coherence of the currents at low frequencies between velocity time-series at 100 m 

and records to depths of ~500 m depth were mostly significant for every mooring deployment. 

Coherency was also observed at near-inertial frequencies. Coherency in the inertial band 

between near-surface velocity and records between 100 – 200 m diminished owing to the 

location of the pycnocline at these depths. Below this depth, inertial motions may be attributable 

to other forcing processes such as eddy features. Inertial oscillations at the surface and at depth 

therefore would not be expected to be coincident or phase locked. The exception to this is when a 

powerful hurricane is able to affect layers below the pycnocline. 

Estimates of the coherency spectra for horizontal separations were calculated between moorings 

for all velocity combinations at the same depth. East-west velocity at moorings M1 and M2 were 

coherent at the lowest frequency band (~90 days) and with zero phase lag. Near the inertial 

frequency in the upper water column, coherency was found at 750 m, 1244 m, and 1492 m. The 

phase of the correlation at the near inertial peak was variable with depth. The east-west velocity 

component at mooring M1 and north-south velocity component at mooring M2 were also 

coherent at low frequencies but with a phase difference of about 1 radian (~90°) at the lowest 

frequency, which indicated that the M1 velocity lead the M2 velocity. 

Coherency between mooring M1 v velocity and mooring M2 u velocity, as well as coherency 

between v velocity at both moorings indicated coherency at low frequency with a phase of ~-1.0 

radian, which meant that M2 lead M1. The phase relationship of the two components likely 

indicated the influence of the eddy fields. Deeper current meter records at M1 and M2, except for 

the records at 1995 m, were only significantly correlated between north-south velocity 

components at both moorings in the inertial band and at low frequencies (~ 80 - 90 days). This 

may be an indication of topographic steering along the bathymetry. 

Mooring M1 and mooring M3 east-west velocities were coherent at near-inertial frequencies at 

every depth in the upper layers. M1 u and M3 v were correlated at the fundamental frequency 

(~90 days) at a phase of ~2 radians (180°) throughout the water column and near inertial peaks 

were present down to 998 m. v velocity at M1 and M3 were correlated at low frequencies down 

to 998 m with zero phase difference. Only near-inertial correlation was present between M1 v

and M3 u. 

 xlii 
East-west velocity at moorings M2 and M3 illustrated very little significant coherency beyond 

some intermittent near-inertial correlations in the upper water column; however, the east-west 

velocity was coherent between moorings M2 and M3 in all current meter records in the deep 

ocean at periods of about 50 days. North-south velocity was correlated at low frequencies in the 

upper water column, and there was correlation at 20-day periods and above between the data 

from the deep current meters at 750, 998, and 1245 m. There were some near-inertial peaks in 

the upper water column between M2 east-west (north-south) velocity and M3 north-south (eastwest) velocity. 

The mean current velocity at mooring M3 was predominantly to the southeast during deployment 

1 and eastward during deployment 2. We attribute this to the relative location of the mooring 

near the northern edge of the LC and Eddy Vortex during the first deployment, while during 

deployment 2 portions of a frontal cyclonic eddy passed over this region producing mostly 

eastward-directed currents. Mooring M3 was also closest to Hurricanes Katrina and Rita; 

therefore, the minimum/maximum current velocity envelopes were greatest here than for any 

other moorings. The mean current velocity during the first deployment was primarily 

southeastward at mooring M2, and to the east at mooring M1. However, during the second 

deployment, currents were dominated by various cold core frontal eddies moving in and out of 

the study area resulting in relatively small mean current velocities at both moorings. 

For engineering applications, one often needs an estimate of the extreme value of the current 

speed over some return interval. Herein, we developed such estimates for the measurements 

made by the Aanderaa current meters on the moorings, but not for the ADCP measurements. The 

extremes were developed using weekly maximum current speed values for each Aanderaa 

current meter record. The weekly maxima were fit to the generalized extreme value (GEV) 

distribution. The GEV is the limit distribution of the maxima of a sequence of independent and 

identically distributed random variables. In general, the extreme values near 750 m depth and 

near the bottom were largest, with smaller values at intermediate depths. By far the largest were 

at 749 m depth on Mooring 1. The extrapolated near-bottom current speeds at Mooring 1 near 

the Florida Escarpment were no larger than those at Mooring 3 on the abyssal plane. 

Hydrography Measurements 

To gain additional perspective on the influence of the LC and LCE’s on the study area, 

hydrographic measurements were acquired during the mooring deployment, servicing, and 

recovery cruises. The hydrographic conditions during the cruises were as follows. During 

Hydrography Cruise 1 (17-23 January 2005) the southwest section of the study area was being 

impacted by the edge of the LC, which can be seen as deep warm water mesoscale feature in the 

hydrographic data. The LC was close to, but had not yet reached, the mooring locations. During 

Hydrographic Cruise 2 (18-25 August 2005) the LC and Eddy Vortex were not over the study 

area as evidenced by the 20° isotherm remaining fairly shallow throughout much of the study 

area during the cruise. A cold core eddy sitting atop Mooring 3 was quite clearly visible in the 

data. 

 xliii 
Hydrographic Cruise 3 (20-28 January 2006) saw the most dramatic and intensive influence from 

the LC. During this period, the edge of the Loop current lay just to the southwest of the study 

area, and was advancing toward it. In addition, a cold core eddy lay over the southern portion of 

the study area in the vicinity of Mooring 3. Intensive hydrographic sampling resulted in excellent 

data across the edge of the LC and within the cold core eddy. However, due to both the rapid 

advancement of the LC towards the moorings, and the resultant rapid evolution and movement of 

the cold core eddy during the nine-day period of the cruise, it was difficult to capture a 

representative static snapshot of these conditions over the entire area. Changes to the edge of the 

LC as it migrated toward the study area were captured in selected transects that were repeated 

during the cruise. 

Deep Circulation 

Previously Hamilton (1990) showed that much of the current variability under the LC in the 

north central and northwest Gulf of Mexico had the characteristics of topographic Rossby waves 

(TRWs). Such characteristics included high coherence through the lower water column, bottom 

intensification, and period and wavevector agreements with the dispersion relation as given by 

Rhines (1970). Hamilton (1990) speculated that pulsations of the LC were the primary source of 

the lower-layer TRWs, and evoked the Malanotte-Rizzoli et al. (1987) model of broad-band 

radiation from a pulsating meander in a channel over a sloping bottom as an explanation of the 

observations. Hamilton (1990) suggested that the TRW-trains propagate generally westward at 

higher group speeds than LCE’s, therefore motions in the lower layer are largely decoupled from 

the eddy currents in the upper layer. 

To assess the motions in the deep circulation, mean current and standard deviation ellipses were 

calculated of the deep current measurements from the study area, and from a mooring maintained 

by Louisiana State University (LSU) to the south of the study area (L7). The deep mean flows 

were north-northwestward at L7, which is similar to the 2003-2004 results for the same location. 

Near-bottom mean flows at M3 and M4 are westward towards the escarpment south of the delta. 

At M3, and to a lesser extent at M2, the mean currents at 1200 m are essentially negligible, 

which is a contrast to the more depth independent mean flows at L7. Where the slope is steeper 

(M1) the mean flows tend to follow the isobaths. 

The current fluctuations were more energetic at L7 than at moorings M1, M2, and M3 within the 

study area. Under the LC at L7, the fluctuations of the currents were predominantly northwards 

with few reversals, depth independent from 1200 to 3200 m, with relatively long periods (~ 30 

days or more), and with the maximum speeds (~ 30 cm s-1 in late December 2005) of all the deep 

measurements versus moorings M1, M2, and M3. The standard deviation ellipses at M2 and M3 

clearly show evidence of bottom intensification, with principal axes directed westward and 

southwestward, respectively, across the isobaths into shallower water, which is characteristic of 

TRW motions. The lower water column still contained considerably more eddy kinetic energy 

(EKE) because of the approximate doubling of the thickness of the lower water column between 

M3 and L7. 

 xliv 
For the M2, M3 and M4 moorings, the fluctuations were more variable in amplitude, had more 

frequent reversals, and had somewhat shorter periods than at L7. There was clearly a decrease in 

energy moving from south to north over the 45 km spacing from M3 to M4 and M2. Near the 

slope at M1 the fluctuations were much less energetic, with amplitudes mostly less than 5 cm s-1, 

and characteristic periods much shorter, generally less than ~ 20 days. 

As discussed earlier, during the study period the LC and Eddy Vortex impacted the study area 

multiple times, and several hurricanes passed close by. Evidence of some of these events was 

seen in the deep currents. For example, in the deep current records, there was evidence of lowfrequency pulses at some of the moorings when storms were intense and passed fairly close to 

the moorings. The center of Hurricane Katrina passed close to L7 on August 28, 2005 at which 

time it was classified as a category 4 hurricane. A short-lived northward pulse of ~ 20 cm s-1 was 

observed in the lower water column at L7 at this time, which stood out from the background 

flows. A month later, a similarly intense Hurricane Rita passed by L7 at a greater distance, but 

there was no obvious pulse from the hurricane at L7. 

In contrast, deep currents at moorings M2, M3 and M4 on the abyssal rise showed no discernable 

response to the passage of these major storms. However, the near-bottom currents at M1 did 

show consistent short period pulses at the times of the closest approaches of the major hurricanes 

Dennis, Katrina and Rita. 

Deep circulation was also punctuated by a number of energetic low-frequency events. The six 

largest EKE peaks were analyzed. Maps of SST overlaid with altimeter-derived SSH were used 

to analyze these six high EKE events in context of the LC and Eddy Vortex movements. High 

resolution lower-layer streamlines and geostrophic bottom currents overlaid with PIES derived 

SSH were used to show the relationship of the bottom flows to the upper-layer. 

One event occurred in late April 2005, where the deep circulation contained south or 

southwestward flows over the main part of the array and northwest flows at M1. During this 

period, the LC was extended well towards the delta and bordered moorings M2 and M3. The 

study region was dominated by a LC frontal eddy resulting upper layer southeastward flows at 

M2 and M3 along the LC front and reversed flows on the north side of the cyclone at M1. The 

lower layer streamlines were approximately normal to the upper-layer flows and the strong deep 

currents were caused by a deep cyclone in the southern part of the array; however the present 

view is that apparent deep cyclones and anticyclones are primarily the result of packets of 

dispersive TRWs. 

The LC remained in this configuration for most of April, May and June, though the cyclonic LC 

fontal eddy propagated along the front towards the southeast and possibly merged with another 

cyclone during this interval. The upper-layer flows at M3 persisted through this interval as the 

LC front moved further over the mooring in May. In the lower-layer, the deep anticyclone in the 

northeast part of the study area strengthened and moved southeastward. The cyclone decayed in 

early May or possibly moved out of the study area towards the southeast, which was 

approximately in the direction of the surface LC front. The deep cyclone either moved into the 

study area from the east at the beginning of the event or intensified in place. The apparent growth 

and decay of deep vortexes without any direct connection to upper-layer forcing could be 

considered evidence for the planetary wave-like nature of lower-layer circulations. 

 xlv 
The three following events in May, August and early December, respectively, at M3 had similar 

behavior to each other, which consisted of a northward pulse accompanied by a cyclonic rotation 

of the velocity vectors. In all three cases, cyclonically rotating velocity vectors were caused by 

an anticyclone-cyclone pair translating fairly rapidly southeastward through the array. This was 

again the general orientation of the surface LC front, and moorings M2 and M3 were on the 

northeast edge of this front. In all these three cases the cyclone – anticyclone pair appeared to 

propagate southeastward, intensify in the southeast corner of the mooring array and possibly 

decay in place. There was an intriguing consistency with the surface layer LC flows, because the 

deep cyclone tended to follow and remain locked to an upper-ocean high. 

An event at the end of December had very similar characteristics, for both upper and lower layer 

flows, to the event in April. The LC and an incipient LC eddy extended to the northwest, and a 

fairly stationary cyclonic frontal eddy dominated the upper-layer flows in the study area. This 

cyclone was larger and more vigorous than the one in April-May. The lower layer flows at M3 

and M4, and to a lesser extent at M2 were dominated by a cyclone, which, similar to the event in 

April, intensified in place and then decayed while moving out of the study area towards the 

southeast. At the same time, the deep anticyclone to the north began to strengthen. The deep 

strong northward flows at L7 that began in the middle of December appear to be unrelated to the 

deep circulations in the study area during this event. 

The final event occurred in the middle of January 2006. At the time a LC eddy was still attached 

but had moved westward, and the study area moorings were primarily on the northern side of a 

cyclonic frontal eddy. In the lower-layer however, a cyclone and anticyclone were in the 

reversed positions with the cyclone to the northeast of the anticyclone, which produced large 

northeast flows at M2. The deep cyclone may have moved in from the west and intensified. The 

deep eddy pair began to move southwards just before the end of the data records. 

The common characteristics of these events were the presence of deep high and low pressure 

centers with separation length scales of ~ 50 to 100 km that intensified and decayed while 

propagating south or southeastwards in the general direction of the overlying front along the 

east-side of the LC. Lower and upper layer streamlines invariably crossed at right angles during 

the more energetic lower-layer events. The significance of this is not clear at present. 

Kinetic energy spectra was computed for the lower-layer currents. The M1 spectra show very 

low energy and have very little in common with the spectra from the moorings located further 

south. M2, M3, and M4 have a prominent spectral peak at 20 days, while M3 and L7 also have 

energy at longer periods with peaks at 30 to 35 days. M2, M3 and L7 show bottom 

intensification at the depth levels deeper than 1000 m, whereas at M4 the fluctuations are 

essentially depth independent through the 100 m separation of the measurements. Therefore, 

except for M1, the lower layer signals have spectra characteristic of TRWs. Low frequency nearbottom EKE increases towards the west and south from M4. 

 xlvi 
TRW wavelengths were estimated by calculating the frequency domain EOF modes for the 

records at 100 to 500 m above the bottom for moorings M2, M3 and M4. Based on the spectra, 

two frequency bands were analyzed. In the M2, M3 and M4 moorings, the highest 60-day energy 

was at M3 reflected by mode 1. The wavelength calculated from the phase differences was 162 

km, which was within the range of previously derived estimates in the deep GOM (Hamilton 

1990; 2007). The direction of the major axes of the 1st mode ellipses indicated that phase 

propagation was south or southeastwards and thus corresponded to the propagation direction of 

the deep eddies described earlier. The second mode was barely significant and the derived 

wavelength was larger than expected, suggesting that this weak signal was not a propagating 

wave. 

TRW ray tracing from the full dispersion relation showed that a TRW could reach the upper 

escarpment in about 40 to 45 days, but the region of impact was an area of low energy as 

measured by the earlier study. However, if the ray is moved slightly southward so that it favors 

the larger fluctuations at M3, then it is apparent that the EGOM region could potentially supply 

some energy to the northern part of the high EKE region below the escarpment. Southward 

displacement of the ray could also be caused by the westward mean flow along the escarpment; 

this effect was not included in the ray tracing calculations conducted here. 

The EOF analyses of wavelengths were also conducted for 20 to 25 day periods. For the EGOM 

moorings, the first two modes were significant and the directions of the major axes of the ellipses 

at M3 and M4 implied that energy was propagating up-slope (mode 1) and down-slope (mode 2). 

With the estimated wavelengths from the phase analysis, the ray tracing produced two similar 

ray paths towards the escarpment because the down-slope ray was reversed by the topography. 

The backward ray paths were also similar and pointed to the M1 location, which had very low 

energy in this frequency band. This implied again that the generation zone was fairly local to the 

deeper parts of the study area. The 25-day forward ray paths implied that the EGOM moorings 

could be an upstream source for the relatively weak fluctuations at the shallower eastern end of 

the escarpment. Transit times would be in the range of ~ 12 to 15 days. 

The wavelet power spectra were calculated for the cross (u) and along (v) isobath components of 

the 2500 m currents at M3. The results indicated that there was significant variance at shorter 

periods in the u- than the v-component, and that the v-component dominated at longer periods. 

This was expected from the dispersion relation for TRWs, because the principal major axis of the 

fluctuations rotates from across to along isobaths as the wave period increases. This further 

confirms that the lower-layer motions in the study area are dominated by TRWs as such a pattern 

would not be expected from translating eddies. 

The analyses also showed that the fluctuations were intermittent but that times of significant 

power occurred throughout the summer (May through August, 2005) when the LC was extended 

to the northwest and Eddy Vortex was undergoing a sequence of detachments and reattachments. 

After the final separation and the rapid translation of Eddy Vortex to the west at the beginning of 

September, the power decreased below the 95% significance levels, particularly at shorter 

periods, suggesting that the presence of the LC or a LCE over the study area had a direct 

influence on the amplitudes of the lower-layer TRWs. 

 xlvii 
Vertical Coupling 

Establishing relationships between observations of upper and lower circulations in the deep 

GOM has proved to be difficult over the years. Generally, currents above 800 m and below 1200 

m have not been correlated at significant time scales. There have been occasional intriguing 

events where flows appear to be similar through the whole water column; however, they were 

not long lasting and generally quite rare. 

To further evaluate potential vertical coupling between the upper and lower layers, several 

analyses were undertaken. First, a complex empirical orthogonal function (CEOF) analysis was 

utilized similar to that employed on just the deeper currents. Time domain CEOFs were used 

rather that frequency domain EOFs because the 1-year time series of upper-layer currents does 

not resolve the ~ 6 to 18 month fluctuations of the LCE shedding cycle. Another approach using 

dynamical normal modes, which are a theoretical decomposition of current profiles based on the 

vertical profiles of the Brunt-Vaisala (buoyancy) frequency, was also used. This analysis has 

many similarities to the purely statistical CEOFs. A limitation of dynamic modes is that the 

bottom is assumed to be level, and this precludes any bottom intensification of the currents. 

Initially upper and lower layer CEOF were calculated for 6 levels of demeaned currents in each 

the upper and lower layer at M3, with the 987 m level being common to both. The first CEOF 

mode for each layer accounted for > 90% of the total variance of each set of 6 records. The 

upper-layer mode was strongly sheared, and approximately unidirectional with the principal axis 

directed approximately north – south. The 987 m level currents were only weakly coherent with 

the mode. The lower-layer currents were highly coherent with the lower-layer mode 1 from 1000 

m to the bottom. The mode CEOFs were unidirectional, with the principal axes being more along 

the isobaths trending southwest to northeast, and showed an increase in amplitude towards the 

bottom. 

The complex mode 1 amplitude time series (normalized to unit variance) of the upper and lower 

layers shows the observed 40-HLP currents at one upper and two lower layer measurement 

depths at M3. The upper and lower layer modes closely resembled the observed currents from 

the upper layer (179 m) and lower layer (987 and 1985 m), respectively. The two-layer CEOF 

analysis thus indicated that there was minimal connection between the modes that account for > 

90% of the variance in each layer. 

Currents at 983 m and below were highly coherent with mode 1. The correlations then decayed 

towards the surface. This mode did indicate that some of the signal above 1000 m was 

attributable to TRW motions. 

Mode 2 was primarily surface intensified and was clearly similar to the upper-layer mode 1. 

However, it also had a weak almost depth-independent expression, in the opposite direction 

below1000 m, that had small, barely significant correlation coefficients. The zero crossover point 

was at about 800 m, and this mode closely resembled the dynamical normal mode 1. The lower 

layer had a small contribution from upper-layer LC or eddy fluctuations through dynamical 

coupling, just as the upper layer had a small contribution from TRW flows decaying upwards 

through the water column. Therefore, the separate layer and full water column CEOF velocity 

modes were essentially equivalent and indicated only very weak interactions. 

 xlviii 
Analyses of the CEOF velocity modes for M1 and M2 generated similar results of the 

interactions of the upper and lower layers as occurred at M3. 

Potential vorticity (PV) of the upper and lower layers was calculated from the current 

measurements at M1, M2, and M3. Layer thicknesses were estimated by averaging isotherm 

depths, calculated by linear interpolation between temperature sensors at M1, M2 and M3. Only 

two layers were considered: between the surface and the 8 °C isotherm, and between the 8 °C 

isotherm and the bottom. The depth of the 8 °C isotherm was used to delineate the lower parts of 

the LC eddies. 

The relative vorticity was at a maximum near the surface and decreased with depth through the 

upper layer. It then showed a slight increase towards the bottom, similar to the vertical profile of 

velocity variances. There was some correspondence between the lower and upper layer peaks in 

relative vorticity, indicating a connection that was not apparent in the velocity fluctuations. 

For the most part the 8 °C isotherm lies between 400 and 750 m where relative vorticity has 

smaller magnitudes and showed the expected relations with deep and shallow excursions 

corresponding to anticyclonic and cyclonic flows, respectively. The mean relative vorticity in 

both the upper and lower layers was positive. In the upper layer the relatively large mean value 

was a consequence of the array being on the east and cyclonic side of the LC front for most of 

the study interval, as well as from the frequent passage of cyclonic frontal eddies. 

The upper and lower layer vertically averaged relative vorticities were significantly correlated 

though some of the correlation was caused by the upper layer relative vorticity leaking below the 

8 °C isotherm depth. There was significant coherence at TRW frequencies in the 20 to 35 day 

period band, with the upper layer lagging the lower layer by ~ 90°, that was suggestive of 

baroclinic instability mechanisms (McWilliams 2006). 

Time series of potential vorticity anomaly (PVA; potential vorticity with stretching effect, 

sometimes defined as the Sverdrup PVA) and its constituent terms (relative vorticity and 

stretching) were calculated for both layers. For many events the stretching term dominated (e.g., 

the warm and cold eddy events in May-June and October-November, respectively), and because 

the stretching terms were inversely correlated in the two layers, this contributed to the overall 

coherence of the total PVA of the layers. However, there were other events when the stretching 

was weak and relative vorticity dominated the total PVA (e.g., the events in March-April, and at 

the beginning of August and the middle of December). 

An analysis of potential upper and lower layer coupling was also performed using primarily the 

PIES data. The array-averaged EKE for the upper (surface) and deep (2500 m) layers did not 

indicate a direct one-to-one correspondence between the major surface and deep energetic 

current events. To help elucidate potential vertical coupling between the layers during any of the 

higher energy events, the lower-layer potential vorticity was analyzed. 

 xlix 
The resolution of the PIES and moorings array allowed investigation of both the advective and 

tendency terms in the deep potential vorticity budget. The mean and standard deviation of the 

lower layer potential vorticity, layer thickness, and relative vorticity were therefore computed. 

Lower-layer potential vorticity exhibited maximums along the northwestern edge of the array, 

whereas the largest fluctuations of potential vorticity occurred along the southwestern edge of 

the array which is coincident with the location of the largest fluctuations in lower-layer 

thickness. Lower layer relative vorticity exhibited the largest variability in the southern portion 

of the array where the Rossby number reached maximum values near 0.28 during strong cyclonic 

events and varied from -0.12 to 0.28. 

The contributions of lower layer stretching and relative vorticity were investigated. Both 

thickness and relative vorticity variability contributed to the local rate of change in the total 

potential vorticity. The potential vorticity associated with one of the energetic deep circulation 

events showed that cyclone’s potential vorticity was nearly constant, while its relative vorticity 

and thickness increased over time. Thus the production of relative vorticity was balanced by 

lower-layer stretching as the cyclone propagated southeastward into deeper water. The thickness 

increase was due almost entirely to the change in ocean depth as the feature propagated to the 

southeast. The depth of the thermocline showed no discernable increase over time. The cyclone 

spun up over time as a consequence of its propagation into deeper ocean depths. This result was 

similar to two other events. 

EOF analysis was also conducted on the current meter data in a manner consistent with previous 

studies (Nowlin et al. 2001). The results of the EOF analyses of the current measurements from 

this study affirm that the horizontal current structure in this region of the Gulf resembles a 2-

layer system. The eddy field causes intensification of the surface currents, which exponentially 

decay in magnitude with depth to ~ 800 meters. This structure is observed in the Mode 1 

amplitudes, which contains the largest percentage of variance (~ 80 - 95 %). This mode shows 

maximum amplitudes at the surface that decrease with depth to nearly zero below 1000 m. The 

dynamic effect of eddies are rarely seen below 800 m. 

Mode 2 explains the second largest percentage of variance. In general, the amplitude crosses zero 

near 200 meter depth and is nearly constant or gradually increasing with increasing depth. 

During deployment 1, the amplitude of Mode 2 at mooring M1 shows a mid-water maximum 

300 and 1000m. The structure of this mode, however, is more similar to the vertical structure 

found in Mode 3 at moorings M2 and M3. Further, the percentage of variance in the second and 

third modes increases from M1 to M3, indicating more variance in the higher order modes closer 

to the Loop Current. During the second deployment, Mode 2 at mooring M1 again resembles 

higher order modes at M2 and M3. However, the percentage of variance in modes 2 and greater 

is a maximum in the east-west velocity component of mooring M2 and generally greater during 

deployment 2 than deployment 1. 

The vertical structure of Mode 3 is more complex with two zero crossings typically in the upper 

1000 m and relatively constant in water depths below 1000 m. The amount of variance contained 

in this mode is a small fraction of the current variance (< 4 %). 

 l 
Stability profiles were derived from temperature and salinity (CTD) data from hydrographic data 

collected adjacent to mooring sites M1, M2, and M3. The CTD data were used to calculate 

vertical buoyancy modes that represent the mean horizontal current structure at the three 

mooring locations. Vertical profiles of Brunt-Vaisala frequency for the three EGOM 

hydrographic cruises were computed in which a maximum occurred between 100 - 200 m during 

the winter and near the surface (< 20 m depth) during the summer. 

Dynamic modes calculated from CTD casts at (or closest to) the mooring sites during the three 

cruises were used to create a normalized set of modes to fit to the velocity measurements. The 

barotropic mode was simply equal to one throughout the water column. First and second 

baroclinic modes had similar shapes at each mooring. The first mode crossed zero around 600 m; 

the second mode crossed zero twice, around 200 and 900 m. Below 1200 m all modes were 

barotropic, i.e., nearly constant with increasing depth. The general shape of these modes was the 

same for each deployment. The relative amplitudes were nearly identical; the principal difference 

between casts was the depth of zero-crossing of the modes. 

The temporal variation of the barotropic and first two baroclinic modes were estimated using a 

least squares minimization that fits the calculated set of vertical modes to synoptic vertical 

profiles of the moored ADCP and single-point current meter data. Three modes were used in the 

least squares fit. Generally, the barotropic time series amplitudes were significantly smaller than 

the baroclinic amplitudes at all moorings for both velocity components during both deployments. 

As found previously in the EOF analysis, most of the variance in the observed velocity data can 

be explained by a surface trapped mode that decays exponentially with depth. Therefore, we 

expect that the temporal amplitudes of the first baroclinic mode to be large and to indicate the 

presence of surface trapped, i.e., eddy related, motions. The amplitudes of the second dynamic 

mode were more variable, i.e., possessed higher frequency motions, than the first baroclinic 

mode and were small relative to the amplitudes of the first baroclinic mode. 

During the first deployment, the east-west velocity amplitudes were mostly positive, i.e., 

eastward, because of the location of the mooring relative to the location of the northeastern edge 

of the LC. In general, mode amplitudes were greater during the first deployment, as more surface 

intensified, high-speed current eddy events were encountered in the spring and summer of 2005 

than during the fall and winter of 2005–2006. The high correlation between mode 1 amplitudes 

and CTD pressure records, which fluctuated due to mooring draw down, were also validation of 

the first baroclinic mode amplitudes as indicators of eddy activity in the EGOM. 

Spatial correlation at every sample time between observed and modeled velocity from the least 

squared fit of dynamic modes showed that when the first baroclinic mode amplitudes were close 

to zero, the correlation was poor. The low correlation could possibly indicate times of relative 

quiescence in the wake of eddies. 

 li 
Two types of model utility tests were performed on the modal fit to the observed currents in the 

space domain. The first test utilized the F statistic to assess whether a useful relationship between 

the observed data and any of the modal predictors existed. The goodness of the fit test confirmed 

that the barotropic and at least one of the baroclinic modes are necessary to the regression 

approximately 80-90 % of the time. The second statistical test is an inference for a single mode 

coefficient, which determines if a certain mode needs to be included in the fit. This test indicated 

that the first baroclinic mode was the only mode necessary to explain the current structure at 

moorings M1, M2, and M3 during most of their deployment; however, the second baroclinic 

mode was necessary to the fit of velocity data during portions of the deployments, and 

particularly to the data collected at mooring M3 during periods within its second deployment. 

Power spectra and autocorrelation functions were generated for the dynamic mode time series 

using FFT methods. The results from these analyses were consistent between data from each 

mooring deployment. Spectra for mode fits to u and v velocity exemplified a typical energy and 

enstrophy-conserving velocity spectrum, with an energy cascade in the red direction, i.e., from 

high to low frequencies. The barotropic amplitudes exhibited less energy than the first baroclinic 

modes at low frequencies. The second baroclinic mode spectra are nearly white (constant) at 

frequencies less than 1 cpd. 

All of the above analyses and results provide an intriguing but limited view of the dynamics and 

coupling between the upper layer and deep circulation features. The results are highly suggestive 

of upper and deep layer coupling under certain conditions not yet well understood. 

Conclusions 

Prior to the study, the study team had a significant concern if the eastern GOM would experience 

any sizable current energetics. The primary conclusion from the study is that the eastern GOM is 

a very active region in terms of circulation, especially when the LC or an LCE is present. The 

circulation characteristics of the region are very similar to those in the north-central GOM when 

similar processes are at work, whether they be the presence of the LC, and LCE, frontal features, 

or major storms. Significant advancement in the understanding of the circulation in the eastern 

GOM was achieved including: 

• Extended LC intrusion significantly impacted the study area upper ocean 

circulation during the first half of the EGOM program. Once Eddy Vortex 

finally separated, fewer LC or frontal features impacted the circulation and 

the character of the circulation returned to conditions more typical for this 

region. 

• Cyclones are an important dynamical component of the general circulation 

of the GOM and significantly impacted the study region during the 

program. 

• Comparisons were drawn between the mean surface circulation over the 

first six months of measurements versus the last six months. The mean for 

the first six months revealed southeast flow from the presence of Eddy 

Vortex while the last six months had comparatively weak circulation. 

• The PIES array captured the mesoscale frontal meanders along the 

periphery of the LC and while well resolved provided a limited window. 

 lii 
• Cyclonic events occurred more frequently than anticyclonic events in the 

EGOM vorticity record. 

• Currents during both deployments at all three tall moorings showed a high 

degree of coherency at water depths above 500 m, with weaker coherence 

extending down to 750 m, and with only occasional coherence at deeper 

depths. 

• Large amplitude inertial oscillations are evident immediately after the 

passages of Hurricanes Katrina and Rita. These current oscillations 

persisted for at least two weeks after the passage of these storms. 

• The passage of Hurricane Katrina near the study’s moorings while a 

cyclonic (cold core) eddy was sitting over the southern portion of the 

study area, is believed to have generated stronger than normal currents. 

• In general, spectral energy was greatest in the shallow ocean depth (<300 

m). Surface records (~ 50 m) contained larger weather-band variance than 

deeper records. 

• The extrapolated near-bottom current speeds at M1 near the Florida 

Escarpment were no larger than those at M3 on the abyssal plane. This 

was an interesting contrast to near-bottom currents near the Sigsbee 

Escarpment farther west, where bottom currents were much stronger in 

proximity to the Escarpment. 

• The lower-layer motions in the study area are dominated by TRWs. The 

presence of the LC or LCE over the study area had a direct influence on 

the amplitudes of the lower-layer TRWs. 

• Deep circulation experiences TRW packets, though generation of TRWs 

that translate into the north-central GOM do not appear to be generated in 

this region. TRW generated currents are also not affected significantly by 

steep bathymetry in this region. 

• The lower layer had a small contribution from upper LC or eddy 

fluctuations through dynamical coupling, just as the upper layer had a 

small contribution from TRW flows decaying upwards through the water 

column. 

• The horizontal current structure in this region of the Gulf resembles a 2-

layer system. The eddy field causes intensification of the surface currents, 

which exponentially decay in magnitude with depth to ~ 800 m., while the 

lower layer was influenced primarily by TRWs propagating through the 

region. 

 liii 
 liv 

Recommendations 

The one year measurement program in the eastern GOM was judicious in timing in that it caught 

significant penetrations of the LC and an LCE into the region, as well as multiple large storms. 

The study region, however, was actually fairly small, and fairly limited in measurement 

locations, to extrapolate the study results to a much larger portion of the eastern GOM. The 

primary recommendations for future studies to further assess the larger eastern GOM circulation 

features, and to better explore the dynamics and interactions of the water column with the LC 

and its eddies, are as follows: 

• Conduct a larger-scale circulation study of the eastern GOM spanning 

more of this area to better assess the geographic extent of the circulation 

and processes found during this study. 

• Conduct in-situ measurements at both small (25km) and large (50-100km) 

scales so as to observe currents over a wider area, yet maintain the ability 

to calculate vorticity, coherence between measurement sites, and to assess 

the small scale interactions at the edges of the LC and LCEs which are 

imparting significant energy into the water column. 

• Add gliders so as to better map hydrography changes in critical areas, such 

as the LC and LCE edges, and so as to provide hydrography 

measurements over much longer time scales than can be achieved by 

hydrography cruises using CTDs and XBTs. 

• Concentrate a set of moorings in the path of, and at the boundaries of, the 

LC and LCEs, as best as they can be positioned, to improve understanding 

of the frontal features and how they affect and control LC movements and 

eddy shedding. 

• Continue to employ remote sensing (satellite measurements) in future 

studies, as these provide such a great basis of understanding of the features 

that affect specific in-situ measurement sites. 

• Conduct coordinated programs geographically to obtain measurements in 

the southern portion of the LC as well as the northern portion so as to 

better understand what drives and controls its northward intrusions and 

southward retractions. 

• Conduct coordinated programs with other institutions, in particular those 

institutions conducting oceanographic measurements of major storms, so 

as to make use of their fast response measurement capabilities in front of 

the storms. 

• Finally, keep funding quality research in the GOM. 
1.0 INTRODUCTION AND OBJECTIVES 

1.1 Background 

The major source of energy forcing currents in the surface waters of the Gulf of Mexico is the 

Loop Current (LC) which flows northward through the Yucatan Channel into the Gulf of 

Mexico, and then turns eastward and exits through the Straits of Florida to join the Gulf Stream. 

The LC varies in its penetration into the Gulf of Mexico, sometimes constraining itself to the 

southern Gulf, and sometimes penetrating far northward into the northern Gulf. During most 

periods when the LC has penetrated northward, cold core eddies and warm water filaments can 

be found migrating around its periphery. Often when extended far northward, the LC pinches off, 

forming a Loop Current Eddy (LCE) that migrates through the northern Gulf, eventually moving 

westward to die within its western regions. LCEs detach from the LC at periods ranging from 3 

to 17 months, with a mean frequency of separation near 10 months (Sturges and Leben 2000). 

Very energetic LCEs interact with one another, the LC, and bathymetry, forming cyclonic eddies 

with which they also interact. There are times, however, that the LC retreats southward without 

shedding an eddy. 

All this activity by the LC, LCE’s, and associated features, imparts significant energy to the 

surface waters of the Gulf of Mexico. While the overall net circulation of the surface waters in 

the Gulf of Mexico based on drifter records is generally understood to be a clockwise circulation 

pattern around the basin (DiMarco et al. 2005), the magnitude of the velocity and variance of the 

surface currents are known to be greatest in the vicinity of the Loop Current, where speeds often 

exceed 1.5 m s-1. 

The other main source of energy to surface waters are winds generated by strong storms and 

hurricanes. Tropical storms and hurricanes provide the greatest storm-related energy, and 

primarily occur during summer and fall months. 

In deeper waters of the Gulf of Mexico, previous studies (Hamilton 1990; Donohue et al. 2006) 

have identified energetic, deep, barotropic (below about 1000 m) motions with some indications 

of bottom intensification at various locations on the slope and rise of the North-central Gulf, 

particularly along the Sigsbee Escarpment. With pseudo-periods of 10 d or more and amplitudes 

up to 1 m·s-1, the phenomena responsible for these motions are generally attributed to 

topographic Rossby waves (TRWs). 

In general, little coupling of upper and lower layer circulation in the Gulf of Mexico appears to 

occur. However, some instances have been observed in other observation programs. Also, the 

modeling studies of Sturges et al. (1993), Inoue and Welsh (1997), and Welsh and Inoue (2000), 

and the CUPOM (University of Colorado Princeton Ocean Model) output suggest that deep 

cyclonic (anti-clockwise) and anti-cyclonic (clockwise) eddies form in the Eastern and Central 

Gulf and propagate into the Western Gulf guided by topography. Some modeling results (Welsh 

and Inoue 2000) suggest that an anticyclone/cyclone pair form in the lower level in response to 

an anti-cyclonic LCE in the upper layer. 

 1-1 
Recent Minerals Management Service (MMS) studies have investigated the circulation features 

and their characteristics and vertical variations over the coastal shelf off Texas and Louisiana 

(Nowlin et al. 1998a, Nowlin et al. 1998b), and in the deeper waters of the central (Donohue et 

al. 2006) and western Gulf of Mexico (Dononhue et al. 2008). These regions are shown in Figure 

1.1-1. A lack of current measurements and understanding of the circulation in the deep 

northeastern Gulf of Mexico prompted the BOEMRE to develop and fund a study titled: Survey 

of Deepwater Currents in the Eastern Gulf of Mexico. In July 2004 a contract was awarded to 

Evans-Hamilton, Inc. (EHI) and its science team to perform this study. This study is part of a 

larger research effort by the Minerals Management Service to gain a better understanding of the 

surface and deep dynamic processes in the Gulf of Mexico (GOM). 

Figure 1.1-1. Locations of the BOEMRE Gulf of Mexico regions and other major features of 

the Gulf of Mexico. 

 1-2 
1.2 Study Area 

The study area is located within the Eastern GOM (Figure 1.2-1). This area consists of the area 

of the Eastern Gulf Lease Sale 181. The study area is located south of Mobile Bay in water 

depths ranging from 2000 to 2800 m, and is bounded approximately by the following 

coordinates: 

NW Corner: 28.848 o

N, 87.918 oW NE Corner: 28.850 oN, 87.523 oW 

SW Corner: 27.453 oN, 87.907 oW SE Corner: 27.455 oN, 87.516 oW 

Bathymetrically, the area is bounded as follows. 

To the north: by the ~2000 m isobath, & by a slope incised by hills & valleys 

To the east: the northern half by the steep slope of the West Florida 

Escarpment 

To the east: the southern half by a flat plain at 2500-2800 m depth 

To the south: by a relatively flat featureless plain 

To the west: by a slope with isobaths directed NNE to SSW 

Key bathymetric features of the study area include that the: 

• Area lies to NE of Sigsbee Escarpment, and SW of the DeSoto Canyon. 

• Area contains primarily NNE to SSW oriented isobaths, rather than E-W 

isobaths 

• Area contains the farthest northward extent of the 2000 m isobath in the Gulf 

of Mexico, plus NNE of the study area is located the farthest northward extent 

of the 200 m isobath. As a result, the area provides the best opportunity for the 

most northerly penetration of the LC or a LCE within the Gulf of Mexico. 

• Area surrounding the study area has the largest separation between the 2000 

and 3000 m isobaths within the Gulf of Mexico. This area is a large, relatively 

flat area. 

• The West Florida Escarpement intersects the eastern boundary of the study 

area at ~ 28.4o N, or approximately one-third the distance from the NE to the 

SE corners of the study area. 

 1-3 
Figure 1.2-1. Map of the study area (outlined in red) including locations of moorings M1, M2, 

M3 and M4 in black, and PIES in purple. Ancillary data set locations are marked 

for wind gauges (red), river discharge and flow gauges (blue) and tide gauges 

(green). Major rivers that drain into the Northern Gulf are also marked. 

 1-4 
1.3 Study Approach 

The study called for a one-year measurement program to collect an integrated set of current, 

hydrography, remote sensing, and ancillary measurements that could provide an excellent 

understanding of the circulation processes in the area. The one-year measurement period allowed 

for observations across all seasons, as well as potentially capturing the effects of some tropical 

storms or hurricanes. As a result, from January 2005 to January 2006 one year of current 

measurements were collected from four moorings in water depths from ranging from 2500 to 

2800 m. The moorings also contained measurements of water temperature and conductivity in 

the upper 500 m. The mooring measurements were supplemented with measurements from 

bottom-moored PIES, three hydrography (profiling CTD and XBT) cruises, and satellite imagery 

and altimetry. Eddy Watch, a proprietary operational oceanographic product that tracks, maps, 

and forecasts the LC and its eddies, along with drifting buoy data used in the Eddy Watch 

analysis, were obtained from Horizon Marine, Inc. for the period of the study’s measurements, 

and utilized under a limited license for additional analyses of the characteristics of the LC and 

LCE’s. Publicly available river discharge data, coastal and offshore wind data, and coastal water 

level data during the measurement period were also obtained as ancillary data. 

The current measurement moorings consisted of three tall (M1, M2, & M3) and one short (M4) 

moorings (Figure 1.2-1). The tall moorings were full water column moorings designed to reach 

within 70 m of the surface. The short mooring was 250 m tall, and was designed to provide 

additional near-bottom current measurements. The current meter moorings were deployed from 

January 2005 to January 2006, with servicing of the moorings occurring in August 2005 just a 

few days prior to the arrival of hurricane Katrina. The tall moorings contained upward-looking 

75 kHz ADCPs at 500 m depth, with single point current meters spaced at intervals from 750 m 

to near bottom. 

PIES measurements were obtained from seven locations (Figure 1.2-1). The PIES were deployed 

in December 2004, interrogated in August 2005 plus additional PIES added to the array, and 

recovered in January 2006. 

In positioning the moorings and PIES, the approach was taken to place at least one tall mooring 

as far south as possible within the study area so as to maximize the potential for the LC, its 

frontal features, or an LCE to impact the mooring. Positions of the other two tall moorings were 

selected to maximize coverage of the study area while maintaining scales and a triangular 

configuration to conduct along and across isobath coherence and vorticity analyses. The northern 

tall mooring was also positioned to assess the potential intensification of the current along the 

Florida Escarpment. PIES were positioned surrounding and within the moorings to as to provide 

a more regional perspective on the conditions affecting the moorings. Positioning of the 

moorings and PIES, as well as the hydrography stations, was intended to provide an ability to 

conduct both regional (50-200 km) as well as smaller scale (10-25 km) analyses. 

 1-5 
Hydrographic measurements consisting of CTD casts and XBT profiles were collected in 

January and August 2005, and January 2006 during mooring deployment, servicing, and 

recovery cruises. The hydrographic measurements were targeted to capture interesting loop 

current, eddy, or other related features affecting the study area. The final hydrographic survey 

was targeted to capture small scale interactions between the edge of a Loop Current Eddy (LCE) 

and a Cold Core Eddy (CCE) that lay over a portion of the study area. 

To help place the study’s measurement data in perspective, ancillary coastal wind and runoff 

data were obtained from the National Climatic Data Center (NCDC), National Data Buoy Center 

(NDBC), and from the US Geological Survey for the sites shown in Figure 1.2-1. 

1.4 Study Objectives 

The goal of this study was to investigate and document the deepwater circulation in the Eastern 

GOM. This is an area of sparse previous deepwater current measurements. Specific study 

objectives were to: 

• Conduct measurements of currents using moorings to increase the regional 

database of ocean currents in the Eastern GOM. 

• Improve the scientific community’s overall knowledge and understanding 

of circulation features in this deepwater area. 

• Collect hydrographic, remote sensing, and other relevant measurements 

useful to understanding what controls the region’s circulation. 

• Assess the key processes energizing the circulation. 

• Add to the database of LC and LCE characteristics, and how these features 

affect the study area. 

• Establish an improved base of knowledge to help design future circulation 

studies in this part of the GOM. 

• Provide measurements and knowledge which could assist with future 

calculations of horizontal and vertical trajectories of released oil and its 

dispersion. 

Anticipated key circulation processes in this area included: 

• Loop Current (LC) intrusionsLoop Current Eddy (LCE) dynamicsLCE 

frontal features including cyclonic and anti-cyclonic eddies 

• Eddy-topography interactions 

• Potential TRW genesis and propagation 

• Potential deep cyclone and anti-cyclone pairs 

• Interactions between upper and lower layers 

• Response to hurricanes and storms 

The data acquired by this study was used to look for and better understand the key processes 

listed above as they occurred within or affected the circulation within the study area. 

 1-6 
1.5 Study Team 

The Science Team Principal Investigators (PIs) for the study, listed below along with their 

primary areas of responsibility for this project, all have conducted research and analysis of the 

circulation of the Gulf of Mexico for several years. Drs. Peter Hamilton, Robert Leben, Kathleen 

Donohue, and Randolph Watts have participated in recent MMS studies of the deep central and 

western GOM, and were selected to provide continuity of their past work to the planning and 

analyses performed for this study. Dr. Steven DiMarco led the compilation and analysis of all 

available current measurements in the GOM for MMS (Nowlin et al. 2001), and was selected for 

his overall understanding of the circulation features within the GOM. Dr. George Forristall was a 

Senior Oceanographer at Shell Oil Company who studied extreme and operational 

oceanographic conditions within the GOM, and was selected to provide his knowledge and an oil 

industry perspective to the science team. 

All PIs contributed to the design of the study, analyses of the measurements and remote sensing 

data, and participated in the writing of this report. Extensive collaboration occurred between PIs, 

both during planning of the study and during analysis of the measurements resulting from this 

study. The primary data sets they utilized and the focus of their analyses were as follows: 

Remote Sensing: 

Dr. Robert Leben, University of Colorado, Colorado Center for Astrodynamics Research 

(CCAR) – Dr. Leben acquired and provided the remote sensing products to the study team for 

this project. His focus was on the analysis of the movement and characteristics of the Loop 

Current, LCEs, and LC frontal features, and in placing the characteristics of these features during 

the study period into historical perspective. 

In-Situ Current and Hydrographic Measurements: 

Dr. Steven DiMarco, Texas A&M University – Dr. DiMarco’s focus was on the analysis of the 

upper Gulf of Mexico circulation features, and coupling of the upper and lower layers. 

Dr. Peter Hamilton, SAIC – Dr. Hamilton’s focus was on the analysis of deep Gulf of Mexico 

circulation features. 

Dr. George Forristall, Forristall Ocean Engineering – Dr. Forristall’s focus was on the kinematics 

of LCEs, the analysis of current extremes, and the analysis of storm-induced inertial oscillations. 

PIES: 

Dr. Kathleen Donohue and Dr. Randolph Watts, University of Rhode Island – Dr. Donohue and 

Dr. Watts’ team conducted the PIES measurements. The focus of their analysis was on the PIES 

data and geostrophic flow patterns. 

Program Management Team: 

In addition to the Science Team PI’s, the following personnel led the organization and conduct of 

the project: 

 1-7 
 1-8 

Mr. Jeffrey Cox, EHI – Program Manager 

Mrs. Carol Coomes – Assistant Program Manager, Data Manager 

Mr. Keith Kurrus and Mr. Kevin Redman, EHI – Cruise Chief Scientists 

Mrs. Kari Walker, EHI – Data Processing & QA/QC Team Leader 

Many additional personnel in all team member organizations contributed significantly to the 

performance of work conducted for this study. EHI was responsible for the preparation, 

deployment, servicing, and recovery of the current meter moorings for the study, along with the 

initial data processing, QA/QC, and preparation of final data sets for distribution to the Science 

Team PIs. EHI was also responsible for conducting the hydrographic cruises that were performed 

in conjunction with the mooring deployment, servicing, and recovery cruises. URI was 

responsible for the preparation, deployment, servicing, and recovery of the PIES, and all 

processing of the PIES data. 

1.6 Report Organization 

The report is organized to provide a background to the purpose and objectives of the study, the 

methods used and data acquired, and a description of the circulation processes identified in the 

upper and lower layers of Eastern Gulf of Mexico during the study period. Chapters contained 

within the report include: 

Executive Summary. 

Chapter 1: Introduction and objectives. 

Chapter 2: Experiment design and methodology. 

Chapter 3: Measurement results from the moorings. 

Chapter 4: Loop current events. 

Chapter 5: Upper layer circulation. 

Chapter 6: Deep circulation. 

Chapter 7: Vertical coupling. 

Chapter 8: Summary and conclusions. 

Chapter 9: Literature cited. 

Chapter 10: Appendices 
2.0 EXPERIMENT DESIGN AND METHODOLOGY 

2.1 Moorings 

Direct measurement of current velocity of the full water column was designed to provide 

estimates of subinertial (low-frequency), inertial (temporal periods of about 24 hours), and superinertial (periods less than one day) band motions and oscillations. Because anticyclones separate 

from the Loop Current in this area and cyclonic Loop Current frontal eddies frequently may 

develop or pass through this region, the moorings were designed to obtain high vertical 

resolutions (~8 m) in the upper 500 m of the water column. 

The current measurement moorings program consisted of the follow key components: 

• 3 tall moorings reaching from 70 m depth to bottom at between 2600 to 2800 m depths 

• 1 short mooring reaching from bottom at 2750 m depth to 2500 m depth 

2.1.1 Instrumentation 

Three tall (designated M1, M2, and M3) and one short (M4) moorings were deployed from 

January 2005 to January 2006, with servicing of the moorings occurring in August 2005 just a 

few days prior to the arrival of Hurricane Katrina (August 26, 2005). The tall moorings 

contained upward-looking 75 kHz ADCPs at 500 m depth, with single point current meters 

spaced at intervals from 750 m to near bottom Figure 2.1-1. The tall moorings also contained 

combinations of temperature, or temperature-conductivity-pressure sensors at various depths. 

The short mooring contained two single point current meters in the lower 100 m of the water 

column. The instrumentation contained on the moorings, the parameters measured, and the 

planned and actual depth of the instrumentation at the start of each deployment is provided in 

Tables 2.1-1 and 2.1-2. 

2.1.2 Instrumentation and Moorings Preparation 

Upon determining the final planned mooring locations and instrumentation, designs of the 

subsurface taut-wire moorings were initiated. The moorings were designed using a standard 

mooring design software package along with the same current profile representative of a LC 

event that was utilized by SAIC for design of the deepwater current moorings for the Exploratory 

Study in the North-central GOM (Donohue et al. 2006). The program permits using a variety of 

flotation, current meters, anchor configurations, mooring wire, and mooring hardware 

components to assess mooring performance under different current profile conditions. Moorings 

for this study were designed to: 

• Minimize bending 

• Minimize vertical displacement of instruments 

• Ensure the moorings have sufficient anchor weight to remain in place 

• Ensure if the mooring parted at any location, flotation is sufficient to bring 

all components to the surface once released from the anchor 

 2-1 
M1 M2 M3

M4

2500m

2000m

1500m

1250m

1000m

750m

500m-ADCP

2700m

Currents

75m – T/C/P

112m - T

150m – T/C/P

187m - T

225m – T/C/P

300m - T

400m - T

Temp/Cond/Press

750m - T

1000m - T

1250m - T

1500m - T

2000m - T

2500m - T

2700m – T

2500m

2400m

Figure 2.1-1. Design of the tall (M1, M2, and M3) and short (M4) moorings. The column 

labeled Currents indicates the depths of the meters for M1 – M3. The column 

Temp/Cond/Press indicates the depths of sensors measuring temperature, 

conductivity, and pressure on the tall moorings (T/C/P had all three sensors, T is 

only temperature). 

To maximize recovery of the moorings, each mooring also included dual acoustic releases that, 

upon triggering either release, would release the mooring from the anchor allowing the mooring 

to surface. The dual releases thus provided redundancy. The top flotation buoy containing the 

ADCP also contained an ARGOS satellite transmitting device that upon surfacing, began 

transmitting its position to aid mooring recovery, especially if the mooring surfaced prematurely. 

A flashing light that also activates upon surfacing and aids recovery of the mooring at night was 

also mounted on the ADCP flotation buoy. 

 2-2 
Table 2.1-1 

Deployment locations of the moorings for Deployment 1. 

Shaded instrument types had a pressure sensor. Abbreviations for measured parameters: c – 

conductivity, t – temperature, p – pressure, u,v – north and east current component. 

Type and Model Serial Number Other Sensors Planned Depth (m) 

Deployed 

Depth (m) 

D1M1 SeaBird SBE37 59 c,t,p 75 11 

 StarOddi Hugrun c919 t 112 47 

 SeaBird SBE37 2697 c,t,p 150 85 

 StarOddi Hugrun c926 t 187 122 

 SeaBird SBE37 2698 c,t,p 225 159 

 StarOddi Hugrun c932 t 300 233 

 StarOddi Hugrun c933 t 400 331 

 TRDI ADCP LR 4487 t,p,u,v 499 446 

 InterOcean S4 7801745 c,t,u,v 749 679 

 Aanderaa RCM7/8 7223 c,t,u,v 997 926 

 Aanderaa RCM7/8 7692 t,p,u,v 1244 1173 

 Aanderaa RCM7/8 9722 t,u,v 1492 1426 

 Aanderaa RCM7/8 10053 t,p,u,v 1995 1939 

 Aanderaa RCM7/8 12085 t,p,u,v 2499 2423 

D1M2 SeaBird SBE37 57 c,t,p 75 6 

 StarOddi Hugrun c937 t 112 42 

 SeaBird SBE37 2699 c,t,p 150 79 

 StarOddi Hugrun c939 t 187 116 

 SeaBird SBE37 2700 c,t,p 225 153 

 StarOddi Hugrun c940 t 300 226 

 StarOddi Hugrun c944 t 400 322 

 TRDI ADCP LR 5165 t,p,u,v 499 435 

 InterOcean S4 8161753 c,t,u,v 749 676 

 Aanderaa RCM7/8 7507 c,t,u,v 997 933 

 Aanderaa RCM7/8 7771 t,p,u,v 1244 1189 

 Aanderaa RCM7/8 12803 t,u,v 1492 1464 

 Aanderaa RCM7/8 9807 t,p,u,v 1995 2022 

 Aanderaa RCM7/8 12807 t,u,v 2499 2526 

D1M3 SeaBird SBE37 2701 c,t,p 76 49 

 StarOddi Hugrun c946 t 113 85 

 SeaBird SBE37 2702 c,t,p 151 122 

 StarOddi Hugrun c950 t 188 159 

 SeaBird SBE37 2703 c,t,p 226 196 

 StarOddi Hugrun c959 t 301 269 

 StarOddi Hugrun c960 t 401 366 

 TRDI ADCP LR 5699 t,p,u,v 500 479 

 InterOcean S4 2129 c,t,u,v 750 713 

 Aanderaa RCM7/8 12084 c,t,u,v 998 961 

 Aanderaa RCM7/8 10643 t,p,u,v 1245 1208 

 Aanderaa RCM7/8 9480 c,u,v 1292 1254 

 Aanderaa RCM7/8 9809 t,p,u,v 1996 1945 

 Aanderaa RCM7/8 12808 t,u,v 2499 2448 

 Aanderaa RCM7/8 12809 t,u,v 2699 2648 

D1M4 Aanderaa RCM7/8 10112 t,p,u,v 2530 2513 

 Aanderaa RCM7/8 12810 t,u,v 2630 2613 

 2-3 
Table 2.1-2 

Deployment locations of the moorings for Deployment 2. 

Shaded instrument type indicates it had a pressure sensor. Abbreviations for measured 

parameters: c – conductivity, t – temperature, p – pressure, u,v – north and east current 

component (current speed and direction). 

Type and Model Serial Number Other Sensors Planned Depth (m) 

Deployed 

Depth (m) 

D2M1 SeaBird SBE37 59 c,t,p 75 74 

 StarOddi Hugrun c919 t 112 110 

 SeaBird SBE37 2697 c,t,p 150 148 

 StarOddi Hugrun c926 t 187 185 

 SeaBird SBE37 2698 c,t,p 225 222 

 StarOddi Hugrun c932 t 300 296 

 StarOddi Hugrun c933 t 400 395 

 TRDI ADCP LR 4487 t,p,u,v 499 509 

 InterOcean S4 7801745 c,t,u,v 749 742 

 Aanderaa RCM7/8 12805 t,u,v 997 990 

 Aanderaa RCM7/8 7692 t,p,u,v 1244 1238 

 Aanderaa RCM7/8 9722 t,u,v 1492 1493 

 Aanderaa RCM7/8 10053 t,p,u,v 1995 2011 

 Aanderaa RCM7/8 12085 t,p,u,v 2499 2428 

D2M2 SeaBird SBE37 2693 c,t,p 75.2 80 

 StarOddi Hugrun c937 t 112.2 117 

 SeaBird SBE37 2699 c,t,p 150.2 155 

 StarOddi Hugrun c939 t 187.2 191 

 SeaBird SBE37 2700 c,t,p 225.2 229 

 StarOddi Hugrun c940 t 300.2 297 

 StarOddi Hugrun c944 t 400.2 389 

 TRDI ADCP LR 5165 t,p,u,v 527.3 520 

 InterOcean S4 8161753 c,t,u,v 749 741 

 Aanderaa RCM7/8 7507 c,t,u,v 997 1007 

 Aanderaa RCM7/8 7771 t,p,u,v 1244 1271 

 Aanderaa RCM7/8 12803 t,u,v 1492 1544 

 Aanderaa RCM7/8 9807 t,p,u,v 1995 2097 

 Aanderaa RCM7/8 12807 t,u,v 2499 2601 

D2M3 SeaBird SBE37 2701 c,t,p 75.7 56 

 StarOddi Hugrun c946 t 112.7 93 

 SeaBird SBE37 2702 c,t,p 150.7 130 

 StarOddi Hugrun c950 t 187.7 166 

 SeaBird SBE37 2703 c,t,p 225.7 204 

 StarOddi Hugrun c959 t 300.7 277 

 StarOddi Hugrun c960 t 400.7 374 

 TRDI ADCP LR 5699 t,p,u,v 499.85 487 

 InterOcean S4 8111780 c,t,u,v 750 720 

 Aanderaa RCM7/8 12084 c,t,u,v 997 967 

 Aanderaa RCM7/8 10643 t,p,u,v 1245 1214 

 Aanderaa RCM7/8 9480 c,u,v 1492 1452 

 Aanderaa RCM7/8 9809 t,p,u,v 1996 1939 

 Aanderaa RCM7/8 12808 t,u,v 2499 2442 

 Aanderaa RCM7/8 12809 t,u,v 2699 2642 

D2M4 Aanderaa RCM7/8 10112 t,p,u,v 2530 2513 

 Aanderaa RCM7/8 12810 t,u,v 2630 2613 

 2-4 
All instrumentation used on the moorings were inspected early in the program, and 

determinations made for whether instrumentation needed to be sent back to the manufacturers for 

checkout, refurbishment, and recalibration. Aanderaa single point current meters were sent to 

Aanderaa Instruments in Norway for factory checkout and recalibration. InterOcean S4 current 

meters were sent to InterOcean Systems for checkout and refurbishment. Seabird SBE37 CTDs 

that did not have recent factory calibrations were sent to Seabird Instruments for checkout and 

recalibration. All Hugren temperature only sensors were returned to Star-Oddi for factory 

checkout and new batteries. Four acoustic releases also were sent to Benthos for checkout and 

refurbishment prior to use. 

After return of the instruments, and prior to shipping to the vessel mobilization site, all 

instrumentation was inspected, prepared, and run through standard pre-deployment checkout 

procedures, including tests in water in EHI’s test tank. All instrumentation and mooring 

components were then packed up and transported to the Louisiana Universities Marine 

Consortium (LUMCON) facility at Cocodrie, Louisiana where they were loaded onto the R/V 

Pelican. 

Aboard the vessel and prior to deployment, all instrumentation was again run through predeployment checkouts. 

2.1.3 Moorings Deployment, Servicing, and Recovery 

After arrival at each mooring deployment location, a small bathymetric survey of the planned 

mooring location was performed to confirm the water depth, as the accuracy of water depth 

information for deployment sites often varies, and variations in water depth can affect the depths 

of instrument measurements and sometimes also affect instrument performance. Extra mooring 

wire and chain was carried aboard the R/V Pelican and used to adjust the mooring length as 

necessary so as to keep the sensors at their planned depths. 

Next, a ship drift test was performed to help assess the proper distance and direction from the 

deployment site to begin spooling out the mooring into the water as the ship steams towards the 

deployment site. Locations to begin deploying the mooring, and to release the anchor, were 

chosen based on the drift test, the length of the mooring, and the anticipated fall-back of the 

mooring due both to currents and drag on the mooring flotation as it descends through the water 

column. 

Upon confirmation of the water depth, conclusion of final mooring adjustments, and selection of 

the ship’s approach to the deployment site and the anchor drop location, the mooring deployment 

was initiated. The mooring was deployed using the top first, anchor last deployment method. 

Using this method, the top of the moorings was first put over the stern of the vessel, and then the 

mooring paid out as the vessel slowly steamed ahead. Payout of the mooring was halted and 

instruments attached at pre-designated and tagged points in the mooring which correspond to 

specific end pieces of mooring cables. Once the entire mooring was trailing astern of the vessel, 

the anchor was attached to the bottom of the mooring, and the anchor positioned at the very stern 

of the vessel and secured using a Quick-Release hook attached to the vessel with cables and 

safety taglines. Upon arriving at the planned anchor drop location, the Quick-Release was 

triggered and the mooring dropped anchor first. 

 2-5 
 2-6 

After the mooring’s anchor had reached the bottom, the mooring’s exact deployed location was 

checked by both ranging from three locations on the acoustic releases that are contained on the 

mooring just above the anchor so as to triangulate a fix, and by passing over the mooring and 

identifying the buoy on the ship’s fathometer. This also permitted confirming the depth of the top 

flotation buoy on the mooring against its planned depth. 

After each deployment, the final mooring locations were determined utilizing a series of acoustic 

ranges which were interrogated from the acoustic releases attached at the bottom of the mooring. 

Triangulation of these ranges, from cardinal locations around the mooring location, determined 

the final mooring positions. The final mooring positions for each deployment, along with the 

measurement dates and instrument setup details, are provided in Table 2.1-3. 

To release and recover the moorings for either servicing or their final recovery, several steps 

were undertaken. First, upon arriving at a mooring’s location and prior to its recovery, the 

position of the mooring was checked by ranging on the acoustic releases to obtain a new fix so as 

to insure the mooring had not moved. The vessel was then positioned a short distance away from 

the confirmed mooring location, and an acoustic signal was transmitted to trigger the acoustic 

releases on the mooring. 

Upon surfacing of the mooring, the ship was maneuvered to acquire the bottom end of the 

mooring first. This end was grabbed by means of a boat hook or rope and hook device, after 

which a snaphook, which is attached to the end of the main lifting cable of the deck winch, was 

attached to appropriate hardware on the mooring to lift the acoustic releases and other mooring 

hardware aboard. Once the bottom end of the mooring and the acoustic releases were onboard, 

the mooring was pulled aboard the ship by pulling the mooring wire with the deck winch. This 

wound the bottom end of the mooring on the deck winch first, resulting in the mooring cable 

being in the best position for re-deployment after servicing. As each instrument or flotation 

component reached the back end of the ship, the mooring line was secured with a safety line, the 

instrument or flotation components removed from the mooring, the mooring hardware 

reattached, and recovery of the mooring continued until all components were onboard. 

Once removed from the moorings, each instrument was carefully cleaned and visually checked 

for damage, and properly turned off to end data recording. Next, the instruments were serviced to 

download their data, install new batteries as needed, replace parts and anodes as needed, and 

restart the instruments. In addition, downloaded data from each instrument underwent an initial 

QA/QC inspection aboard the vessel to confirm proper functioning of the instrument. After 

servicing, all instruments were run through the standard pre-deployment checkout procedures 

prior to release for redeployment. 

All data recovered during the service trip in August 2005 and the final recovery trip in January 

2006 were downloaded initially to computer hard drives. Backup copies of the raw data files 

were also made to CDs. 
Table 2.1-3 

Deployment information of the tall (M1, M2, and M3) and short (M4) moorings for each instrument 

 = Instruments with 

Pressure Sensors Deployment 1 Deployment 2 

Instrument Type Serial Number 

Measured 

Parameters 

Start Date 

Start 

Time 

End 

Date 

End 

Time Latitude Longitude 

Sampling 

Interval 

Samples 

Averaged 

Bin 

Size 

Magnetic 

Declination 

Start Date 

Start 

Time End Date

End 

Time Latitude Longitude 

Mooring 1 SeaBird SBE37 59 c,t,p 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 8 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

StarOddi Hugrun c919 t 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 1 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

SeaBird SBE37 2697 c,t,p 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 8 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

StarOddi Hugrun c926 t 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 1 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

SeaBird SBE37 2698 c,t,p 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 8 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

StarOddi Hugrun c932 t 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 1 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 StarOddi Hugrun c933 t 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 0:30:00 1 n/a n/a 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

TRDI ADCP LR 4487 t,p,u,v 1/21/05 21:00 8/20/05 13:00 28 20.89770 87 32.86178 1:00:00 60 8m -0.87 8/22/05 1:00 1/24/06 12:00 28 20.82604 87 32.83353 

InterOcean S4 7801745 c,t,u,v 1/21/05 22:00 8/20/05 13:00 28 20.89770 87 32.86178 1:00:00 360 n/a -0.87 8/22/05 2:00 1/24/06 13:00 28 20.82604 87 32.83353 

Aanderaa RCM7/8 7223/12805 c,t,u,v/t,u,v 1/21/05 21:59 8/20/05 12:57 28 20.89770 87 32.86178 1:00:00 50 n/a -0.87 8/22/05 1:59 1/24/06 13:00 28 20.82604 87 32.83353 

Aanderaa RCM7/8 7692 t,p,u,v 1/21/05 21:59 8/20/05 12:59 28 20.89770 87 32.86178 1:00:00 50 n/a -0.87 8/22/05 1:59 1/24/06 12:59 28 20.82604 87 32.83353 

Aanderaa RCM7/8 9722 t,u,v 1/21/05 21:59 8/20/05 12:59 28 20.89770 87 32.86178 1:00:00 50 n/a -0.87 8/22/05 1:59 1/24/06 12:59 28 20.82604 87 32.83353 

Aanderaa RCM7/8 10053 t,p,u,v 1/21/05 21:59 8/20/05 12:55 28 20.89770 87 32.86178 1:00:00 50 n/a -0.87 8/22/05 1:59 1/24/06 12:56 28 20.82604 87 32.83353 Aanderaa RCM7/8 12085 t,p,u,v 1/21/05 21:59 8/20/05 12:54 28 20.89770 87 32.86178 1:00:00 50 n/a -0.87 8/22/05 1:40 1/24/06 12:35 28 20.82604 87 32.83353 

Mooring 2 SeaBird SBE37 57/2693 c,t,p 1/20/05 22:00 5/1/05 8:30 27 59.89942 87 50.33546 0:30:00 8 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

StarOddi Hugrun c937 t 1/20/05 22:00 5/1/05 8:30 27 59.89942 87 50.33546 0:30:00 1 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

SeaBird SBE37 2699 c,t,p 1/20/05 22:00 8/24/05 11:00 27 59.89942 87 50.33546 0:30:00 8 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

StarOddi Hugrun c939 t 1/20/05 22:00 5/1/05 8:30 27 59.89942 87 50.33546 0:30:00 1 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

SeaBird SBE37 2700 c,t,p 1/20/05 22:00 8/24/05 11:00 27 59.89942 87 50.33546 0:30:00 8 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

StarOddi Hugrun c940 t 1/20/05 22:00 5/1/05 8:30 27 59.89942 87 50.33546 0:30:00 1 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 StarOddi Hugrun c944 t 1/20/05 22:00 5/1/05 8:30 27 59.89942 87 50.33546 0:30:00 1 n/a n/a 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

TRDI ADCP LR 5165 t,p,u,v 1/20/05 21:00 8/24/05 10:00 27 59.89942 87 50.33546 1:00:00 60 8m -0.617 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

InterOcean S4 8161753 c,t,u,v 1/20/05 22:00 8/24/05 11:00 27 59.89942 87 50.33546 1:00:00 360 n/a -0.617 8/25/05 17:00 1/23/06 18:00 27 59.89942 87 50.33546 

Aanderaa RCM7/8 7507 c,t,u,v 1/20/05 21:59 8/24/05 10:59 27 59.89942 87 50.33546 1:00:00 50 n/a -0.617 8/25/05 16:59 1/23/06 17:59 27 59.89942 87 50.33546 

Aanderaa RCM7/8 7771 t,p,u,v 1/20/05 22:00 8/24/05 10:59 27 59.89942 87 50.33546 1:00:00 50 n/a -0.617 8/25/05 16:59 1/23/06 17:59 27 59.89942 87 50.33546 

Aanderaa RCM7/8 12803 t,u,v 1/20/05 22:00 8/24/05 11:02 27 59.89942 87 50.33546 1:00:00 50 n/a -0.617 8/25/05 16:59 1/23/06 18:01 27 59.89942 87 50.33546 

Aanderaa RCM7/8 9807 t,p,u,v 1/20/05 21:59 8/24/05 10:57 27 59.89942 87 50.33546 1:00:00 50 n/a -0.617 8/25/05 16:59 1/23/06 17:58 27 59.89942 87 50.33546 

Aanderaa RCM7/8 12807 t,u,v 1/20/05 21:59 8/24/05 10:57 27 59.89942 87 50.33546 1:00:00 50 n/a -0.617 8/25/05 16:59 1/23/06 17:58 27 59.89942 87 50.33546 

Mooring 3 SeaBird SBE37 2701 c,t,p 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 8 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

StarOddi Hugrun c946 t 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 1 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

SeaBird SBE37 2702 c,t,p 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 8 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

StarOddi Hugrun c950 t 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 1 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

SeaBird SBE37 2703 c,t,p 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 8 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

StarOddi Hugrun c959 t 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 1 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 StarOddi Hugrun c960 t 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 0:30:00 1 n/a n/a 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

TRDI ADCP LR 5699 t,p,u,v 1/19/05 23:00 8/22/05 11:00 27 36.55084 87 31.95179 1:00:00 60 8m -0.77 8/23/05 18:00 1/24/06 19:00 27 36.38936 87 32.45470 

InterOcean S4 2129/8111780 c,t,u,v 1/20/05 0:00 8/22/05 11:00 27 36.55084 87 31.95179 1:00:00 360 n/a -0.77 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

Aanderaa RCM7/8 12084 c,t,u,v 1/19/05 23:59 8/22/05 10:58 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 18:59 1/24/06 18:58 27 36.38936 87 32.45470 

Aanderaa RCM7/8 10643 t,p,u,v 1/19/05 23:59 8/22/05 10:57 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 18:59 1/24/06 18:57 27 36.38936 87 32.45470 

Aanderaa RCM7/8 9480 c,u,v 1/19/05 23:59 8/22/05 10:57 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 18:59 1/24/06 18:58 27 36.38936 87 32.45470 

Aanderaa RCM7/8 9809 t,p,u,v 1/19/05 23:59 8/22/05 10:59 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 19:00 1/24/06 19:00 27 36.38936 87 32.45470 

Aanderaa RCM7/8 12808 t,u,v 1/20/05 0:00 8/22/05 11:01 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 19:00 1/24/06 19:01 27 36.38936 87 32.45470 

Aanderaa RCM7/8 12809 t,u,v 1/20/05 0:00 8/22/05 11:02 27 36.55084 87 31.95179 1:00:00 50 n/a -0.77 8/23/05 19:00 1/24/06 19:01 27 36.38936 87 32.45470 

Mooring 4 Aanderaa RCM7/8 10112 t,p,u,v 1/19/05 2:59 8/19/05 12:56 27 59.98225 87 33.59521 1:00:00 50 n/a -0.82 8/19/05 23:00 1/23/06 15:57 28 00.00480 87 33.57730 

Aanderaa RCM7/8 12810 t,u,v 1/19/05 3:00 8/19/05 13:01 27 59.98225 87 33.59521 1:00:00 50 n/a -0.82 8/19/05 23:00 1/23/06 16:00 28 00.00480 87 33.57730 

2-7 
2.1.4 Processing and QA/QC of Mooring Measurements 

Initial processing and quality assurance/quality control (QA/QC) of the measurements from the 

four moorings were performed by EHI. This resulted in final edited data sets for the mooring 

measurements being prepared and released to all Science Team PIs for their analyses. EHI also 

formatted the final data sets to NODC standards and provided the data to NODC. 

Initial data processing and QA/QC of the mooring measurements utilized a combination of 

instrument manufacturer software and EHI software. Data processing steps involved conducting 

QA/QC of overall instrument performance (tilt, battery life, etc.), cutting data recorded by the 

instruments out-of-water prior to and after deployment, cutting data from the ADCPs for 

measurement bins near surface, and identifying and removing or providing caveats of bad or 

questionable data. Listed below are the steps involved in the processing and QA/QC of the 

different types of mooring data collected. 

ADCP Data

To help assess overall performance of the ADCP instruments, a series of data plots were viewed 

in the RDI software. These plots included information on the orientation of the meter, water 

temperature, backscatter intensity, vertical velocity, pitch, roll, heading, pressure, battery 

voltage, and other parameters related to the quality of data. 

The parameters used to cut the ADCP data for periods prior to and after deployment, and for 

measurement bins near the surface experiencing acoustic side lobe interference, were percent 

good as well as per-beam values of correlation and echo amplitude. For each data file, the 

percent good cut off value was set so that all data falling below a designated percent good value 

was cut from the data set. The correlation and echo amplitude gate values were set so that all 

data with a per-bin correlation or echo amplitude difference greater than the designated 

respective values were cut from the data set. Because of the presence of both the LC and 

hurricanes during the deployment periods, “maximum magnitude not to exceed” current 

velocities were not used as a cutting parameter. Remaining bad data points not cut by the before 

mentioned procedures were hand-cut from the data set using the above parameters. All remaining 

questionable data were flagged using “999.99”. 

Following are the detailed steps used in the processing and QA/QC of the ADCP data: 

Step 1 Utilizing Teledyne RD Instruments Software:

- Determined first and last good ensembles due to out-of-water times 

- Verified that in- and out-of-water times matched start and end of good data, 

respectively 

- Verified instrument settings 

- Performed initial visual QA/QC of the data 

- Exported all data variables as *.MAT files (The MathWorks, Inc MATLAB 

compatible) 

 2-8 
Step 2 Utilizing EHI Data Cleaning Software:

- Cut bad data using percent good threshold 

- Cut bad data using correlation gate 

- Cut bad data using echo amplitude gate 

- Converted current magnitude from mm s-1 to cm s-1

- Applied mooring location-specific magnetic declination 

- Checked for and flag data file anomalies such as time jumps 

Step 3 Utilizing EHI Data QA/QC and Graphing Software:

- Hand cut bad data near surface that was not caught by the above defined 

parameters values using surface bin differences in per-bin values of percent 

good, correlation, and echo amplitude. 

- Plotted contours of current magnitude and direction 

- Plotted vectors of current magnitude and direction 

- Plotted contours of vertical velocities, average correlation, and average echo 

amplitude 

- Plotted line plots of temperature, pressure, pitch, roll, and heading 

Aanderaa Current Data

Following are the steps used in the processing and QA/QC of the Aanderaa RCM7/8 data: 

Step 1 Utilizing Aanderaa Software:

- Applied calibration information for each sensor per instrument 

- Converted data from raw voltages to engineering units 

- Determined first and last good ensembles due to out-of-water times 

- Verified that in- and out-of-water times match start and end of good data, 

respectively 

- Verified instrument settings 

- Removed instrument time stamps 

- Performed initial visual QA/QC of the data 

- Exported all data into an ASCII format 

Step 2 Utilizing EHI Data Cleaning Software:

- Applied mooring location-specific magnetic declination 

- Checked for and flagged data file anomalies such as time jumps 

Step 3 Utilizing EHI Data QA/QC and Graphing Software:

- Cut bad current speed data due to rotor loss or malfunction 

- Cut bad current direction data due to vane malfunction 

- Checked for and hand cut bad data spikes 

- Plotted vectors of current magnitude and direction 

 2-9 
- Plotted line plots of temperature, and pressure and/or conductivity when 

present 

Interocean S4 Current Data

Following are the steps used in the processing and QA/QC of the Interocean S4 data: 

Step 1 Utilizing InterOcean Systems, Inc. Software:

- Determined first and last good ensembles due to out-of-water times 

- Verified that in- and out-of-water times match start and end of good data, 

respectively 

- Verified instrument settings 

- Performed initial visual QA/QC of the data 

- Exported all data into an ASCII format 

Step 2 Utilizing EHI Data Cleaning Software:

- Applied mooring location-specific magnetic declination 

- Checked for and flagged data file anomalies such as time jumps 

Step 3 Utilizing EHI Data QA/QC and Graphing Software:

- Checked for and hand cut bad data spikes 

- Plotted vectors of current magnitude and direction 

- Plotted line plots of temperature, conductivity, pitch, roll, and heading 

Seabird SBE-37 Single Point CTD Data

Following are the steps used in the processing and QA/QC of the Seabird Instruments SBE-37 

CTD data: 

Step 1 Utilizing SeaTerm Processing Software:

- Exported data to ASCII file 

Step 2 Utilizing EHI Data QA/QC and Graphing Software:

- Determined first and last good data values due to out-of-water times 

- Verified that in- and out-of-water times match start and end of good data, 

respectively 

- Calculated salinity and density from the temperature, conductivity and 

pressure records using the seawater toolbox routines (Phil Morgan ,CSIRO)

- Plotted line plots of temperature, conductivity, calculated salinity, and 

pressure 

- Performed initial visual QA/QC of the data 

- QA/QC the data for spikes in temperature records, removed and interpolated 

across excursions greater than 1.5° C 

 2-10 
Step 3 Additional QA/QC

- Data were further hand checked for spikes in temperature 

Of special note is that during Deployment 1, Mooring 2 lost the top flotation buoy part way 

through the deployment in March, after which the top portion of the mooring down to about 400 

m depth, fell over and hung suspended below that point. For all CTD instruments that did not 

contain a pressure sensor to accurately position their depth after the loss of the buoy, the data 

record for those instruments was cut at the time of the buoy loss because the depth of the 

instruments could not be positively identified for the remainder of the deployment. If an 

instrument did contain a pressure sensor and it did not become over-pressured, two data files 

were written for the instrument, one prior to and one for after the buoy loss. 

Star-Oddi Hugrun Single Point CTD Data

Step 1 Utilizing Seamon Processing Software:

- Exported data to ASCII file 

Step 2 Utilizing EHI Data QA/QC and Graphing Software:

- Determined first and last good data values due to out-of-water times 

- Verified that in- and out-of-water times match start and end of good data, 

respectively 

- Plotted line plots of temperature 

- Performed initial visual QA/QC of the data 

- QA/QC’d the data for spikes in temperature records, removed and interpolated 

across excursions greater than 1.5° C 

- These instruments did not have pressure; therefore, pressure was calculated 

from instruments on the same mooring based on known cable lengths and 

pressure records of those instruments above and below the Hugrun. Given an 

instrument H with no pressure sensor and instruments S1 above and S2 below 

with pressures PS1 and PS2, and given each instrument's mooring cable 

position: MS1, MH, MS2; 

2 1

12 1

1

(*)( )

S S

SS SH

SH MM

MMPP

PP −

− − += , (2.1.1) 

Step 3 Additional QA/QC

- Data were further hand checked for spikes in temperature 

 2-11 
2.1.5 Mooring Data Coverage 

Overall, excellent data coverage was achieved from the moorings. Tables 2.1-4 through 2.1-7 

depict the periods of good data coverage for each instrument over the two deployments. Some 

problems were encountered with particular instruments, and with identifying the measurement 

depth of some instruments after the loss of the top flotation buoy on Mooring 2 during 

Deployment 1. Statistical computations for each deployment of the percent data return by 

instrument type, and per mooring including all instruments on the mooring, are provided in Table 

2.1-8. 

2.1.6 Mooring Data Graphical Products and Analyses 

Utilizing the processed and QA/QC’d mooring measurements data, a number of additional 

analyses were conducted, and graphical and tabular displays of the data prepared. While these 

data products are presented and discussed within Chapter 3, a listing of these products and the 

analyses performed is presented below. 

The graphical and tabular displays of the mooring data include: 

• Vector plots of current speed and direction vs. time for selected 

measurement depths 

• Color contours of current speed and direction vs. time and depth 

• Color contours of water temperature vs. time and depth 

• Color contours of water salinity vs. time and depth 

• Current roses 

• Joint probability distributions of current speed vs. direction 

• Current speed persistence tables 

• Spectral analysis plots for current speeds 

• Basic statistics of the u and v components of the current 

Prior to conducting some of the above analyses, mooring drawdown due to the influence of the 

LC at the mooring sites was assessed. It was determined that when the LC was affecting a 

mooring location, mooring drawdown was significant enough (50 m) to warrant correction for 

those analyses presenting results at defined depths. It was determined that the mooring 

drawdown primarily affected the depth of current measurements and CTD data in the upper 500 

m. ADCP data was therefore corrected by fitting u and v velocity component time series to a 

regular grid. From the gridded fields, a single time series for each 8 m depth range was 

constructed. Because the ADCP was originally configured to record in 8 m bins and the number 

of bins remained constant throughout the deployment, this method assures there is only one 

measurement in a given bin for each sample time 

For those analyses requiring regularly spaced, gapless time series, time series above ~ 60 m were 

excluded from analysis due to gaps longer than 2 weeks resulting in a large portion of the record 

being affected by gaps. For some mooring deployments, the shallowest time series is around 100 

m. 

 2-12 
Table 2.1-4 

Summary of data coverage by each instrument and their sensors for Mooring 1 during January 

2005 to January 2006. 

Mooring Deployment 1 Deployment 2 

Schematic 

Instrument 

Type 

Measured 

Parameters Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Mooring 1 SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

StarOddi Hugrun t 

TRDI ADCP LR t 

 p 

 dir 

 mag 

InterOcean S4 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

 2-13 
Table 2.1-5 

Summary of data coverage by each instrument and their sensors for Mooring 2 during January 

2005 to January 2006. 

Mooring Deployment 1 Deployment 2 

Schematic 

Instrument 

Type 

Measured 

Parameters Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Mooring 2 SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

StarOddi Hugrun t 

TRDI ADCP LR t 

 p 

 dir 

 mag 

InterOcean S4 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 

 

 

 

 

 

 

 mag 

 2-14 
 2-15 

 Table 2.1-6 

Summary of data coverage by each instrument and their sensors for Mooring 3 during January 

2005 to January 2006. 

Mooring Deployment 1 Deployment 2 

Schematic 

Instrument 

Type 

Measured 

Parameters Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Mooring 3 SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

SeaBird SBE37 c 

 t 

 p 

StarOddi Hugrun t 

StarOddi Hugrun t 

TRDI ADCP LR t 

 p 

 dir 

 mag 

InterOcean S4 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 c 

 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 c 

 dir 

 mag 

Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 mag 
Table 2.1-7 

Summary of data coverage by each instrument and their sensors for Mooring 4 during January 

2005 to January 2006. 

Mooring Deployment 1 Deployment 2 

Schematic 

Instrument 

Type 

Measured 

Parameters Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Mooring 4 Aanderaa RCM7/8 t 

 p 

 dir 

 mag 

Aanderaa RCM7/8 t 

 dir 

 

 mag 

 = Good Data 

 = Bad or Missing Data 

 = Current Data: Speed Only 

 = Current Data: Direction Only 

 = CTD Data: Depth Change - Good Data 

 

 = CTD Data: Data not provided due to unknown depth of 

instrument 

 = Instruments with Pressure Sensors 

Table 2.1-8 

Data return statistics for each mooring and each instrument type during both deployments. 

Totals: Deployment 1 Deployment 2 

# Data 

Points 

Exp 

# Data 

points 

Ret 

% 

Return 

# Data 

Points 

Exp 

# Data 

points 

Ret 

% 

Return 

Doppler Data: 61508 61508 100% 44212 44116 100% 

Aanderaa Data: 332932 321450 97% 236796 232029 98% 

S4 Data: 61500 61500 100% 44208 44208 100% 

Hugrun CTD Data: 123000 100901 82% 88416 88408 100% 

SeaBird CTD Data: 276750 260169 94% 198936 198918 100% 

Mooring 1 267919 259372 97% 194457 191893 99% 

Mooring 2 268996 227381 85% 188500 186175 99% 

Mooring 3 283089 283089 100% 203284 203284 100% 

Mooring 4 35686 35686 100% 26327 26327 100% 

As a consequence of this method and the constant bin number, gaps in the surface-most bins 

occur in the velocity data when the mooring was depressed in depth. Temporal gaps in the time 

series that lasted less than 2 weeks and more than 1 day were filled using the spectral method of 

Maximum Likelihood, a method which uses data before and after the gap to weight and predict 

values in the gap that are spectrally consistent with observations surrounding the gap (Nowlin et 

al. 1982). Gaps of less than one day were filled using linear interpolation. The same gap filling 

procedure was performed on the single point current meter data when needed 

 2-16 
Several types of statistical data products were prepared for each current meter file or depth bin 

from the ADCP observations for each deployment period. First, the record length mean, standard 

deviation, and minimum and maximum values were calculated to produce an overall climatology 

of the dataset to help identify the physical processes that occurred during the field study. The 

measurements were then investigated to characterize their record-length structures. As part of 

this effort, joint distributions of direction and speed were tabulated for each deployment period 

using unfiltered hourly versions of the quality-controlled data. The joint speed versus direction 

information indicates the percentage of time the current observations fall within the indicated 

speed range and 45°-intervals of direction centered on the 8-principal compass directions. Speeds 

less than 1 cm s-1 are categorized as calm and not assigned compass direction because those 

directions would likely not be meaningful. Also shown is the percentage of time when the 

currents are within each speed range and each direction bin. The average speed for each direction 

bin is included. From these tabulations, current roses were constructed for each single point 

current meter file and ADCP depth bin. The current roses are a graphical depiction of the joint 

distributions tabulations. On the current roses, the white and stippled segments indicate, from the 

rose center outward, the percentage of the currents that were in speed bins of 5 cm s-1 increments 

up to speeds greater than 75 cm s-1. The length of each segment corresponds to the percentage of 

time the current was in that speed bin; if the percentage is less than 1% for a particular speed bin, 

the corresponding segment is omitted. Calms are indicated in the center of the rose. An example 

is shown in Figure 2.1-2. 

Persistence tables (also known as recurrence and duration statistics) were constructed for each 

current meter file. Persistence statistics were calculated using the unfiltered hourly versions of 

the quality controlled data sets. An example persistence table is shown below in Figure 2.1-3. 

Each persistence interval is defined by speed classes in the table. Speed classes are subdivided 

into several increments ranging from 1 to 10 cm s-1. The duration (termed “run length”) in hours 

was computed for the time while consecutive values of the time series fell within a speed 

interval. Duration intervals are 0-6, 6-12, 12-18, 18-24, 24-32 hours. An occurrence is defined as 

a given speed class persisting for a given duration. The number of occurrences for each speed 

class and run length are shown in the tables. The mean, standard deviation, and maximum 

duration of the run length (in hours) for each interval are then calculated. 

Kinetic energy spectra plots were constructed for each current meter file or ADCP depth bin. As 

for the persistence tables and rose diagrams, the spectral energy plots were generated for each 

deployment period using unfiltered hourly versions of the quality-controlled data. The spectra 

were estimated using Welch’s method using a segment length of 512 points with 50% overlap. A 

Kaiser-Bessel window was applied to the segment (Emery and Thomson 2001) to increase the 

statistical degrees of freedom and insure the greatest statistical reliability of the spectral 

estimates. The velocity vectors were divided into north-south and east-west current components 

prior to analysis. Shown also is the kinetic energy spectrum of a detided version of the data. An 

example of a kinetic energy spectra plot is shown in Figure 2.1-4. 

 2-17 
Figure 2.1-2. Example current rose diagram: Mooring M1, deployment 1. 

 2-18 
Figure 2.1-3. Example persistence table: Mooring M1, deployment 1. 

Figure 2.1-4. Kinetic energy spectra of unfiltered (blue) and detided (red) versions of ADCP 

data during deployment 1 at mooring 1. Bin depth is 52 m. 

 2-19 
When analysis of the tidal components of the currents was needed either to understand the tidal 

currents, or to eliminate the tidal current signal so a to look at low frequency circulation, a 

couple of methods were utilized. Tidal analysis was performed on all current meter data using 

the iterative least squares method of cyclic descent (Bloomfield 1976). The eight tidal 

constituents with the largest gravitational potential were analyzed. Tidal ellipses (major/minor 

axes, ellipse directional orientation) and phase were calculated for each velocity component 

record. 

For the study of low frequency circulation, all time series were filtered using a 96+1+96 point 

40-hr low pass Lanczos-Cosine kernel (Harris 1978), which eliminates tidal and inertial signals 

from the data. For correlation between SSH anomaly and current, and wind and current, current 

data was 40 hour low pass filtered and resampled at 24-hour intervals and 3-hour intervals 

respectively. 

Dynamic modes of the current were also calculated following the method of Klink (1999) using 

both historical hydrographic observations (Nowlin et al. 2001) and new observations collected 

specifically for this project. The dynamic modes give an estimation of the vertical structure of 

currents at a point for a given stability profile. Once identified, the dynamic modes were 

compared to full water column synoptic vertical profiles of current constructed from low-passed 

filtered versions of the upper ocean ADCP data (in the upper 500 m) and single point Aanderaa 

RCM11 current meters (typically below 500 m to near the bottom). The first three dynamic 

modes (barotropic plus first two baroclinic) were then fitted using linear regression at each time 

point. From this a time series of the dynamic modes was constructed and analyzed. The 

statistical significance of each modal time series was tested using a model utility test. The modal 

time series were then correlated and interpreted with respect to independent forcing such as sea 

surface height, sea surface height gradient, and wind speed. Coherency, phase, and gain spectra 

between various forcing and modal time series were computed to identify frequency bands in 

which correlation between parameters exist. 

Additional spectral analysis was performed using wavelets to produce the time evolution of the 

spectral components. Wavelets were used principally to investigate inertial band energy, 

specifically those related to tropical storms. Wavelets associated with subinertial variability of 

about 10 days were also investigated. Long-period variability was addressed using the estimation 

of dynamic mode and empirical orthogonal function (EOF) decomposition of individual velocity 

components. 

2.2 Hydrography 

Three hydrography cruises were planned for the 12-month measurement period of the NE Gulf 

of Mexico Program: at initial deployment of the current meter moorings, at the six month 

servicing of the moorings, and during final retrieval. The hydrography cruises used a 

combination of CTD casts and XBT profiles designed to ensure sufficient data density, 

efficiency of operations during the cruise, and coverage of the study area. 

 2-20 
2.2.1 Survey Pattern and Instrumentation 

A grid pattern of stations (Figure 2.2-1) was devised consisting of deep CTD casts (~2000 m), 

shallow CTD casts (~1000 m), deep XBT profiles (T5 ~1830 m), and shallow XBT profiles (T7 

~760 m). This grid was to be utilized if no LC, LCE, or related features were within or 

approaching the study area at the time of the cruises. Grid spacing between stations was 10 nmi 

in the east to west direction and 5 nmi in the north to south direction. In addition, a grid pattern 

was devised with alternating lines of CTD and XBT stations where each west to east transect line 

would be the same type of probe (e.g., all shallow CTD, all deep XBT, etc). Deep CTD casts 

were to be taken at each mooring and PIES location. 

Prior to each mooring and hydrography cruise, the position of the LC, and any LCEs or frontal 

features was checked using a combination of satellite imagery and altimetry, and other available 

information. If it was found that the LC, and LCE, or frontal features were affecting the study 

area at the time of an upcoming cruise, it was planned to adapt the hydrography cruise grid to 

better align the grid with the location and scale of the feature. Such was the case during the third 

hydrography cruise. 

The CTD used to conduct the casts was CTD system on the R/V Pelican. This unit is a Seabird 

SBE-19. All XBTs used were purchased from Lockheed Martin Sippican. 

The hydrography cruises were conducted as follows: 

Hydrography Cruise 1

The first hydrography cruise was conducted January 17-23, 2005 and followed the initial grid 

design and general station type. The hydrography stations were timed around the daylight 

deployment of the moorings. Due to a lack of time, the far west N-S transect was not sampled. 

Figure 2.2-2 shows the final station grid. 

Hydrography Cruise 2

The second hydrography cruise was conducted August 18-25, 2005 and again followed the initial 

grid design and the general station type. The hydrography stations were timed around the 

daylight mooring retrieval and redeployments and the download of the PIES. The eight day 

cruise allowed sampling of the far west N-S transect not collected during the first cruise. 

Additional XBT profiles were collected every 10 km as the ship crossed the loop eddy on the 

way back to shore (Figure 2.2-3). 

 2-21 
Hydrographic Cruise 2 finished one day ahead of Hurricane Katrina entering the GOM. 

Hurricane Rita followed less than a month later and finally Hurricane Wilma came through the 

southern GOM one month after Rita. Of the three hurricanes, Katrina had the most potential for 

impact to the study area. The storm tracks provided in Appendix A show that hurricane force 

winds covered most of the study area and tropical storm winds covered the remainder during 

Hurricane Katrina. During Hurricane Rita, tropical storm force winds covered the southern half 

of the study area. Hurricane Wilma had the least direct impact to the study area having passed 

well to the south. Because of these major storm events, additional funds were earmarked for a 

post hurricane hydrographic cruise; however, no suitable vessels with appropriate CTD 

instrumentation were available well past the time of all three hurricanes. 

Hydrographic Cruise 3

The third hydrography cruise was conducted January 20-28, 2006 and did not use the initial grid 

design. A decision had to be made on how best to use the additional funds to benefit the 

program. Discussions amongst the study team determined that conducting a fine scale (intensive) 

survey of the edge of the LC and any frontal features within or near the study area would provide 

heretofore unavailable detail on the hydrography of these processes. To conduct such an 

intensive hydrography survey, an eye was kept to the presence of the LC and its frontal features 

within the study area, as well as to the availability of vessels to conduct the cruise. 

Finally, as the time was approaching for retrieval of all the moorings and PIES and the third 

hydrography cruise, satellite imagery showed some interesting features. The edge of the LC was 

moving northeastward toward the study area, and two cold core eddies appeared to be located in 

the southern half of the study area along with some other frontal features. It was also speculated 

that current jets were possibly being produced by water squeezed by bathymetry at the north side 

of study area. 

LUMCON was able to extend our final cruise period by a few days and so final planning for a 

fine scale hydrography survey was commenced. Team members were assembled via 

teleconference to discuss strategies for the cruise plan. The end result was a pin wheel grid of 

stations (Figure 2.2-4) designed to capture in detail the hydrography of the edge of the LC, the 

cold core eddies, and any other frontal features within or near the study area. 

The cruise plan called for starting at the NW corner and following a transect toward the center of 

the grid to find the cold core eddy. Next the vessel would transit directly south until crossing the 

edge of the LC. The vessel would continue transiting the pattern in a clockwise rotation thereby 

sampling “new” water as opposed to the possibility of sampling the same water if a 

counterclockwise rotation was scheduled. Sampling would be a combination of CTD casts and 

XBT profiles. Deep CTD casts were scheduled to be taken at each mooring and PIES location in 

addition to the outer corners of the pinwheel to maximize the area available for deep contours. 

The moorings and PIES would be retrieved as the vessel transited the grid pattern. 

 2-22 
Figure 2.2-1. Grid pattern proposed for hydrography cruises. Legend denotes station type and 

naming scheme. 

 2-23 
Figure 2.2-2. Grid pattern of Hydrography Cruise 1. Line indicates ship track. 

 2-24 
Figure 2.2-3. Grid pattern of Hydrography Cruise 2. Line through stations indicates ship 

track. 

 2-25 
The actual cruise track pattern was modified once the vessel reached the study area (Figure 2.2-

5). The edge of the Loop Current had slid northward so the legs along the south side of the grid 

pattern were shortened. The weather contributed to the modification of the cruise track as well. 

Immediately following completion of the most southern wedge of the pinwheel grid, the vessel 

headed north to take advantage of a good weather window to retrieve all moorings and PIES. 

The station plan was also modified once on site. Deep blue (DB) XBT probes (~870 m range) 

were available for this intensive cruise. At two of the PIES stations (P2 and P5) multiple XBT 

profiles (one each of T7, T5 and DB) were taken in conjunction with a deep CTD cast. Because 

of the modification to the cruise track, some stations were sampled more than once. One example 

is station 16 that was sampled with a T7 on 01/22/06 and again five days later as a shallow CTD 

site. A second example is the same transect line was sampled as the vessel transited into and out 

of the study area (NW quadrant). 

2.2.2 Hydrography Data Processing and QAQC 

The hydrography data were processed using a combination of SeaBird Electronics, Inc. (SBE), 

Sippican, and EHI processing software. The specific processing and QA/QC steps for each type 

of data are provided below. 

Seabird Instruments SBE CTD Cast Data

Initial data processing began with the SBEDataProcessing-Win32 Software. Additional QAQC 

processing was completed using EHI CTD Processing Software. 

Step 1 Data Conversion

- Data were converted from raw data to engineering units and saved as .cnv 

ASCII files. 

- Scans to skip over: 200 (remove a portion of the soak time) 

- Convert data from: Downcast and Upcast 

- Output Variables: 

a) Pressure, Digiquartz (decibars) 

b) Depth (salt water, degrees C) 

c) Primary Temperature (ITS-90, deg C) 

d) Temperature 2 (ITS-90, deg C): (secondary Temp.) 

e) Conductivity (Primary-s/m) 

f) Conductivity 2 (Secondary-s/m) 

g) Oxygen Saturation (mg/L) 

h) Altimeter (m) 

 2-26 
Figure 2.2-4. Pinwheel station grid for intensive Hydrography Cruise 3. 

 2-27 
Figure 2.2-5. Station pattern for Hydrography Cruise 3. 

 2-28 
Step 2 Filter

- Filtering smoothes high frequency data. Pressure data is typically filtered with 

a time constant equal to four times the CTD scan rate1

. 

- CTD scan rate: 24 Hz = 0.0416667 s 

- Pressure: (4)(0.0416667)= 0.167s 

- Temperature: 0 

- Conductivity: 0 

Step 3 Align

- Align CTD aligns temperature, conductivity, and oxygen data relative to 

pressure to ensure calculated parameters such as salinity and dissolved oxygen 

concentration are from the same parcel of water. 

- Shipboard Offsets: Temperature = 0 

Conductivity = 0 

Oxygen = 3 

Step 4 Cell Thermal Mass

- Cell Thermal Mass uses a filter to remove cell thermal mass effects from the 

measured conductivity. In areas with steep temperature gradients, this 

correction is on the order of 0.005 PSU1

. 

- Thermal anomaly amp (alpha): 0.03 

- Thermal anomaly time constant (1/beta): 7.0 

Step 5 Loop Edit

- Loop Edit flags scans as bad that have pressure slowdowns or reversals, 

thereby reducing the effects of ship heave. 

- Minimum velocity type: Fixed 

- Minimum CTD velocity (m s-1): 0.25 

Step 6 Derive

- Using pressure, temperature, and conductivity, Derive calculates parameters 

such as salinity and density. 

Step 7 Sea Plot

- Sea Plot was used to make preliminary plots for QA/QC. 

Step 8 EHI Software

- The EHI CTD processing software QA/QCs the data for spikes in pressure, 

temperature, salinity, density, conductivity, and oxygen. The maximum depth 

was found to cut the upcast from the file. 

 2-29 
Step 9 QA/QC

- The data were hand checked to remove soak times and ensure high quality 

data. 

Step 10. Bin Averaging

- Finalized data were averaged into 0.5 meter bins. 

SIPPICAN XBT Cast Data

XBT data were first exported to ASCII format using the Sippican Winmk12 software. The data 

were then run through a series of checks and smoothing routines. 

Step 1 EHI software

- The EHI CTD processing software QA/QCs the data for spikes in 

temperature. 

Step 2 QA/QC

- The data were hand checked for surface spikes and/or spikes due to the wire 

coming in contact with the hull of the ship, and to ensure high quality data. 

Step 3 Bin Averaging

- Finalized data were averaged into 0.5 meter bins. 

2.2.3 CTD vs XBT Data 

Hydrographic Cruise 3 was the most comprehensive of the three surveys and used several types 

of XBT probes. In addition, several stations were sampled with both the profiling CTD system 

and XBT probes and in some instances two or three types of XBT probe so as to provide an 

inter-comparison of the measurements from the different instruments. Figure 2.2-6 shows the 

comparisons of CTD and XBT multi-probe stations. Although the chief error is depth not 

temperature between the CTD and XBT, temperatures can be compared (Emery and Thomson 

2001). Stations 2, 5, 6, and 12 show very close fits between all profiles. The mean XBT-CTD 

difference for each probe type in the 1-100 m depth range were 0.11° C for a T7 probe, 0.12° C 

for a T5 probe, and 0.18° C for a deep blue probe. These mean temperature differences were 

equal to (T7) or slightly less than the mean difference for the entire profile. The profiles for 

Station 16 differ because although they were taken at the same station, they were collected five 

days apart. The T7XBT was measured on 22 January 2006 and the shallow CTD was measured 

on 27 January 2006. This profile comparison indicates how much the area was changing, 

especially in the surface layers, due to circulation features passing through the area in the short 

time span of the hydrographic cruise. 

 2-30 
Figure 2.2-6. CTD vs. XBT profile information for Hydrographic Cruise 3 January 2006. 

2.2.4 Comparison to Historical Data 

Texas A&M University (TAMU) has gathered the electronic files of CTD profiles for most 

hydrography surveys conducted by researchers in the GOM. After reprocessing the historical 

data files and plotting the results, TAMU determined that all the historical profiles normally fell 

within a specified range when plotted as potential temperature versus salinity. Comparison of the 

CTD data from the present study with the boundaries of the historical data is shown in Figure 

2.2-7. Data for the present study shows good agreement with the historical data in that the 

present data follows the shape of the historical set very closely. Many anomalies during the 

present study (e.g. number and force of storms, northward migration of LC, etc.) may have 

contributed to the slight variations. 

 2-31 
Figure 2.2-7. Profiles from all three hydrographic cruises plotted as potential temperature vs 

salinity superimposed on the historical data boundaries. 

 2-32 
2.3 PIES 

An array of seven inverted echo sounders with pressure gauges (PIES) was deployed late 

December 2004 and recovered in late January 2006 in order to increase the spatial extent to 

which the measurements of the moored current meter array could be applied (Figure 1.2-1). The 

PIES is a bottom-mounted instrument that emits 12 kHz sound pulses and measures the round 

trip travel times or τ (tau) of these acoustic pulses from sea floor to sea surface and back. The 

PIES, equipped with a pressure gauge, also measures bottom pressure. A detailed description of 

instrument and initial processing may be found in Hamilton et al. (2003) and Donohue et al. 

(2006); key steps are discussed in this section. 

Prior to deployment, the PIES were serviced, tested, and mobilized by the University of Rhode 

Island. Deployment of the PIES occurred in late December 2004 on a separate cruise from the 

initial current moorings deployment which occurred in January 2005. 

In late August 2005 during the servicing and redeployment of the current meter moorings, the 

PIES were acoustically interrogated from the ship and daily-averaged pressure and τ data for 

each PIES successfully telemetered to the ship. During this trip, two additional PIES were also 

deployed at sites 4 and 6, denoted as site 4_2 and 6_2. 

During the mooring recovery cruise in January 2006, each of the PIES was again acoustically 

interrogated to download their daily-averaged pressure and τ data, and then acoustically released 

and recovered, with the exception that the PIES at site 7 did not release and was not recovered. 

Data return from the PIES was excellent (Figures 2.3-1 and 2.3-2); full deployment records are 

available from all PIES with two exceptions. First, the initial instrument at PIES site 6 did not 

have valid τ records. The τ record from PIES 6_2 is therefore used for site 6. Second, even 

though the PIES at site 7 was not recovered, a full data set of its daily data was received by 

acoustic telemetery. 

The array of PIES combined with measurements from the current meter moorings enabled a 

quantitative mapping of the regional circulation. The τ measurements from the PIES allowed for 

estimates of vertical profiles of temperature, salinity, and density by utilizing empirical 

relationships (Gravest Emperical Mode) established with historical hydrography. Pressure was 

leveled via geostrophy using the current measurements. Deep pressure records combined with 

estimated horizontal density gradients yielded referenced geostrophic velocities. With this array 

we produced 4-D maps of temperature, salinity, density, and velocity. We mapped the circulation 

for the year, January 21, 2005 to January 20, 2006 that encompasses the current meter records. 

Figures 2.3-3 and 2.3-4 illustrate the various views of temperature and current structure provided 

by the PIES and deep current meter mooring array for August 5, 2005. More details on this 

process are provided in the following sections. 

 2-33 
2.3.1 Gravest Empirical Mode Method 

The initial processing of the PIES data included filtering the time series data with a 72-hour 4th

order Butterworth filter and subsampling the results at 6-hour intervals. Next, the PIES τ

measurements were converted into profiles of temperature, salinity, and specific volume 

anomaly through the use of a look-up table. 

A relationship has been previously established between a τ index and vertical profiles of 

temperature, salinity, and specific volume anomaly using historical hydrography. This is the socalled Gravest Empirical Mode (GEM) representation (e.g., Meinen and Watts 2000). The 

procedure consists of two branches. First an empirical relationship was created. Second we 

converted the PIES measured τ to the τ index of the look-up table. 

2.3.1.1 Determine τ Index 

Round trip travel time between the 150 and 1000 dbar surface, τ(150-1000) was used as the τ

index. The 150 dbar upper limit of the τ integration avoided the influence of the seasonal cycle. 

Further refinements discussed below detail a seasonal correction. The 1000 dbar lower limit of 

the τ integration balanced two needs: to extend the integration below the thermocline and to 

retain as many of the acquired historical hydrocasts as possible. 

2.3.1.2 Assemble Regional Hydrographic Data Set 

The hydrography data set was derived from historical hydrography supplemented by CTD 

hydrocasts taken during the hydrography cruises of this study, and also by hydrocasts from 

profiling floats used in previous studies (Figure 2.3-5). Due to the integral nature of τ we used 

only high vertical resolution CTD hydrocasts. The historical database contains 597 hydrography 

stations from the GOM HYDRO Database compiled by TAMU as part of the BOEMRE-funded 

Deepwater Reanalysis Project as well as additional stations provided by SAIC and EHI. The 

GOM is well sampled; 876 hydrocasts represent about 20 years of sampling; hydrocasts sample 

most of the annual cycle except in May and December; the bulk of casts extend between 1000 to 

2000 dbar with relatively few casts below 2000 dbar. Also included were 242 hydrocasts taken 

by profiling floats used on the MMS sponsored Exploratory Study of Deepwater Currents in the 

Gulf of Mexico (Donohue et al. 2006). They substantially increased the spatial and temporal 

sampling. These casts reached maximum pressures of 1000 m. 

 2-34 
Figure 2.3-1. Time series of τ (tau) anomaly in seconds plotted according to approximate 

geographic location. Instrument number noted in the lower left corner of each 

subplot. Bathymetry contoured every 500 m depth. PIES are denoted as filled 

circles. 

 2-35 
Figure 2.3-2. Time series of bottom pressure anomaly in dbar plotted according to approximate 

geographic location. Instrument number noted in the lower left corner of each 

subplot. Bathymetry contoured every 500 m depth. 

 2-36 
Figure 2.3-3. Two views of the temperature structure in the region for August 5, 2005 provided 

by the PIES. Left panel: Temperature at 200 dbar in plan view. PIES sites denoted 

by the diamonds; current meter moorings indicated by the circles. Right panel: 

Temperature determined from the PIES array at the red dot in the left. 

 2-37 
Figure 2.3-4. Several views of the current structure in the region for August 5, 2005 provided 

by the PIES and current meter measurements. Left two panels: Surface 

geopotential referenced to 2500 m and surface currents (left) and pressure at 2500 

m (right) in plan view. Contour intervals given in the title of each panel. 

Anticyclonic circulations are shown by reddish hues; cyclonic circulations by 

bluish hues. PIES sites denoted by the diamonds; current meter moorings 

indicated by the circles. Right panel: Mapped meridional velocity determined by 

the PIES array at the red dot in the left and middle panels. The blue line indicates 

the baroclinic (geostrophic) shear referenced to zero at 2500 m depth derived 

from the PIES-GEM technique. This shear is referenced by 2500 m mapped 

velocities (light blue) to yield the absolute geostrophic velocity (red line). 

 2-38 
2.3.1.3 Sort Hydrographic Data by τ Index 

Hydrocasts were linearly interpolated to a uniform 10-dbar grid and sorted by τ(150-1000). In 

Figure 2.3-6 we show results for temperature. The methodology was also applied to salinity and 

specific volume. Every 10 dbar, a cubic smoothing spline was fit to temperature as a function of 

τ(150-1000) (Figure 2.3-7). Root-mean-square residual, rms, for each curve provides an 

indication of the departure any individual profile might have from the GEM curve. The rms 

values for temperature were small, 0.25°C, within the thermocline and decrease with increasing 

pressure. The curves showed that a functional relationship exists between the integrated variable, 

τ(150-1000) and vertical profiles of temperature. The two-dimensional GEM fields are shown in 

Figure 2.3-8. Note that there is little structure in the fields below 1000 dbar, and this reflects the 

uniform deep-water properties in the GOM. 

An example of how the GEM look-up table works is illustrated in Figure 2.3-9. τ(150-1000)

calculated from a hydrocast taken during the MMS-sponsored Survey of Deepwater Currents in 

the Northwestern Gulf of Mexico project (Donohue et al. 2008) is plotted as the vertical line in 

the GEM field. The temperature and salinity profiles (blue lines) are ‘looked up’ given the 

calculated τ(150-1000). GEM-determined profiles agreed well with the measured profiles. Note 

that for this illustration the GEM fields did not include this hydrocast. 

2.3.1.4 Seasonal Correction 

Finally, a seasonal correction to the upper 150 dbar of the temperature GEM field was made 

(Figures 2.3-10 and 2.3-11). This procedure utilized all available data and was performed as 

follows. First a cubic spline under tension was fit every 10 dbar from the surface to 150 dbar. 

Next the residual from the cubic spline curve was determined. Lastly, the residual was sorted by 

time of year and created a smoothed empirical relationship for the residual as a function of time 

of year. This became the 'correction' to the profile determined by the GEM field. The amplitude 

of the temperature seasonal correction was about 3°C at the surface and decayed to less than 

0.5°C by 90 dbar. No seasonal correction was applied to salinity because while there was 

variability in the surface layer that did not appear to be seasonal. 

2.3.2 Conversion of Measured τ to τ(150-1000) 

In order to use the GEM fields with the PIES τ measurements, the measured τ was converted to 

τ(150-1000). This was accomplished based on the fact that τ at any deep pressure is linearly 

related to τ at any other deep pressure: 

τ(150-1000) = A×τp1 + B . 

 2-39 
Historical hydrography established the slope of this relationship and hydrocasts taken during the 

PIES deployment and PIES and mooring recovery cruises determined B for each time series. 

Each PIES typically had two calibration casts except for PIES 6 which had a single cast available 

for calibration. Calibrations at each PIES with two hydrocasts agreed with each other within 1.5 

milliseconds. The mean pressure of each instrument was determined from the record average 

pressure adjusted for the vertical offset between the pressure sensor and the transducer (0.6 dbar) 

and mean atmospheric pressure (10.16 dbar). The final τ(150-1000) records are shown in Figure 

2.3-12. 

Before measured τ records were converted to τ(150-1000), a seasonal τ signal was subtracted 

from the τ records. This seasonal signal was determined from the historical hydrography in a 

manner similar to the seasonal temperature adjustment. Here we considered the influence of the 

seasonal cycle in τ between the surface and 150 dbar because the hydrography showed that there 

is little seasonal signal below 150 dbar. The scatter plot of τ(0-150) versus τ(150-1000) was 

largely due to the seasonal cycle and we determined the amplitude of the residual to be 0.3320 

milliseconds (Figure 2.3-13). The correction was small, about 2% of the total range in τ(150-

1000). 

We estimated the error in τ(150-1000) to be near 0.0006 sec. This error derives from the 

measured hourly τ error, 0.0004 sec, a calibration error, 0.0001 sec, the uncertainty in the 

seasonal τ correction, 0.0003 sec, and the uncertainty in the slope of the τ to τ(150-1000) lookup, 0.0003 sec. These errors add independently of each other. The hourly error was estimated as 

follows: individual τ records have an error of 0.002 sec which, when divided by the square root 

of twenty four (the number of samples) yielded 0.0004 sec. Note that we calibrated the CTD τ to 

the hourly measured τ. A potential spatial offset between PIES and the calibration CTD was the 

largest contribution to the calibration error (see Meinen and Watts, 1998) and was estimated as 

0.0001 sec. 

 2-40 
Figure 2.3-5. Spatial and temporal distribution of hydrocasts used to construct the Gravest 

Empirical Mode. Data provided by the GOM HYDRO Database compiled by 

TAMU as part of the MMS-funded Deepwater Reanalysis Project and additional 

stations provided by SAIC, profiling float hydrocasts, and hydrocasts taken during 

this experiment. Top panel: Spatial distribution of the hydrocasts with bathymetry 

contoured every 100 m. Bottom panels: Histograms of the maximum hydrocast 

pressure (bottom left), year of hydrocast (middle), and month of hydrocast (right). 

 2-41 
Figure 2.3-6. Temperature profiles interpolated every 10 dbar and sorted by τ(150-1000). 

 2-42 
Figure 2.3-7. Scatter plots of temperature versus τ(150-1000) for six representative pressure 

levels. At each pressure, the temperature versus τ(150-1000) data were fit by a 

cubic smoothing spline (solid curve). 

 2-43 
Figure 2.3-8. Contour plot of the cubic smoothing spline fits for the temperature GEM field. 

 2-44 
Figure 2.3-9. The GEM-determined temperature and salinity profiles agree well with measured 

profiles. τ(150-1000) from a hydrocast is plotted as a vertical line in the 

temperature GEM field (left panel). Middle and right panels show the temperature 

and salinity profiles from the hydrocast (black). The temperature and salinity 

profiles were ‘looked up’ given the calculated τ(150-1000) and produced 

estimates shown with the blue line. 

 2-45 
Figure 2.3-10. Upper panels: Scatter plots of temperature versus τ(150-1000) for surface 

(left), 50 dbar (middle) and 100 dbar (right) with the cubic spline fit shown as a 

solid dark line. All samples in all panels are color coded by generic yearday 

transitioning from blue in January to red in December. Middle panels show the 

residual from the cubic spline fit. Lower panels: A clear seasonal signal in 

temperature emerges when the residual is sorted by time of year. 

 2-46 
Figure 2.3-11. Seasonal temperature correction/amplitude contoured as function of yearday and 

pressure. The amplitude of the temperature seasonal correction is about 3°C at the 

surface and decays to less than 0.5°C by 90 dbar. 

 2-47 
Figure 2.3-12. τ(150-1000) for each time series. The time series are shown in approximate 

geographic location. Instrument number is in the lower left corner of each subplot. 

Bathymetry contoured every 500 m depth. 

 2-48 
Figure 2.3-13. Upper panel: Scatter plots of τ(0-150) versus τ(150-1000). Each point is color 

coded by generic yearday transitioning from blue in January to red in December. 

The scatter about the spline fit (solid dark line) is largely due to the seasonal 

cycle. Lower panel: The residual from the cubic spline fit shown in the upper 

panel sorted by generic yearday showed a clear annual signal. 

 2-49 
2.3.3 Upper-Ocean Maps 

Maps were produced with optimal interpolation techniques adapted from Bretherton et al. (1976) 

and outlined in Watts et al. (1989, 2001). Optimal interpolation requires that the input fields have 

zero mean and uniform variance. In order to meet this requirement, a mean field must be 

subtracted from the fields before mapping and then added back to produce maps of the total 

field. The mean was removed in such a way that the mapped fields behaved well outside the 

measurement sites. Additionally, the cross-correlations among the measurements determined the 

correlation function and length scales utilized in the optimal interpolation to map anomalies. A 

Gaussian correlation function was employed to construct the maps. A multivariate optimal 

interpolation mapped the geopotential and velocity, which was constrained to be geostrophic. 

The maps of upper-ocean fields such as temperature and geostrophic shear were calculated by 

subtracting a 40-day low-passed field mapped with a correlation length scale of 100 km. We then 

mapped an anomaly field with a shorter correlation length scale of 45 km. Correlation functions 

of the measurement anomalies determined the correlation length scales (Figure 2.3-14). The 

measurement correlation functions were nearly isotropic indicating that the use of an isotropic 

Gaussian correlation function for the objective analysis was appropriate. 

2.3.4 Bottom Pressure 

Several bottom-pressure processing details for the PIES are noteworthy. First, our experience 

indicates that preconditioning of the pressure sensors in the PIES greatly reduces pressure drift. 

Therefore the PIES pressure sensors were subjected to pressures near 3000 dbar for 1-2 months 

in the lab prior to their first deployment. Second, the pressure data were detided. Tidal response 

analysis (Munk and Cartwright 1966) determined the eight major tidal constituents for each 

instrument. Tidal amplitudes are generally small. The largest tidal amplitudes are near 14 cm for 

O1 and K1, near 5 cm for P1, and less than 5 cm for Q1 and for the remaining semidiurnal 

constituents. Estimated tides and phases vary smoothly across the array. Finally, pressure drift 

was removed using techniques found in Watts and Kontoyiannis (1990); an exponential-pluslinear drift curve determined by a least-squares fit was removed from the measurements. The 

instruments experienced small drifts with the maximum drift at 0.06 dbar. 

To achieve mapping the near-bottom circulation, the bottom-pressure measurements must be 

leveled to produce spatially consistent maps since each dedrifted pressure record has an 

undetermined additive constant offset relative to the other records. ‘Leveled bottom pressures’ 

refers to bottom pressures that have been adjusted to the same geopotential surface. Mean nearbottom currents and bottom pressures were dynamically constrained to be in geostrophic 

balance. Watts et al. (2001) provides a detailed description of the leveling procedure; here we 

highlight methods specific to this study. 

 2-50 
Figure 2.3-14. Correlation coefficient between pairs of τ records longer than one year. 

Correlations coefficient plotted as a function of separation distance and binned 

every 10 km (black triangles). Top panel: Time series have been 3-day low-pass 

filtered. A 100 km Gaussian function is plotted with black line. Middle panel: 

Time series have been 40-day low-pass filtered. A 100 km Gaussian function is 

plotted with black line. Lower panel: Time series have been 40-day high-pass 

filtered. A 45 km Gaussian function is plotted with black line. 

 2-51 
First, we chose a deep reference level of 2500 dbar for the pressure records. Any depth could 

serve as the reference level, but a deep reference level reduces error because the level is close to 

the velocity and pressure measurements. Furthermore a deep reference level results in two modes 

that can be identified with physical modes, a baroclinic mode which contains the shear/steric 

signal and a barotropic mode which is depth independent. Thus the methodology yields absolute 

current profiles composed of two vertical modes, a geostrophic shear referenced to zero at the 

reference level and a depth-independent component that is equivalent to the velocity at the 

reference level. Figure 2.3-4 illustrates this approach. The deep reference-level currents were 

derived from the measured 2500 m currents at M1, M3, M4 and the 2000 m currents at M2. The 

M2 2500 m current record was not continuous through January 2005 to January 2006. 

Comparison between common time segments of the 2000 and 2500 m M2 records indicated that 

there was little vertical shear between these depths. 

2.3.5 Reference-Level Maps 

Lower-ocean mapping paralleled the upper-ocean procedure. Before mapping, a common mode 

(array-average pressure) was subtracted from the 2500-dbar pressures (Figure 2.3-15). The 

common mode in the deep pressures simply adds a time-dependent array-wide constant which 

has no dynamical significance for the mesoscale circulation so it is better to subtract it from all 

records prior to mapping. Spectra of the common mode revealed dominant peaks near 32, 14 and 

6 days. The 6-day signal is likely the barotropic oceanic response to the atmospheric RossbyHaurwitz wave (Park and Watts 2006). The 14-day peak had a slightly lower period compared to 

the nearly 16-day period found in the Exploratory Study bottom pressure data set (Donohue et al. 

2006). This signal remains unexplained; however, this signal was coherent and in phase with the 

14-day signal found in deep pressures in the Survey of Deepwater Currents in the Northwestern 

Gulf of Mexico (Donohue et al. 2008) suggesting that it is a basin-wide signal. Figure 2.3-16 

shows the bottom pressure records with the common mode removed. The mean field was derived 

from fitting a plane to the mean 2500-dbar pressures. A 30-km correlation length scale 

determined from the near-bottom-pressure correlations was used to map anomaly fields (Figure 

2.3-17). Similar to the τ time series, the near-bottom-pressure autocorrelations were nearly 

isotropic. Streamfunction maps were created by inputs from both pressure and current meter 

data. The inclusion of the current meter data sharpens the gradients. 

Finally, we compared a 30-day low-pass streamfunction computed with deep current meters 

alone to a 30-day low-pass streamfunction computed only with the pressure gauges. The 

difference between these curves indicated possible errors in our initial dedrift technique. Recall 

that the initial procedure dedrifted bottom pressure by the subtraction of a linear plus exponential 

fit, however this method did not differentiate between short-term pressure drift and real ocean 

signals. Final drift curves changed slightly and the maximum drift remained small, 0.06 dbar. 

 2-52 
Figure 2.3-15. Top Panel: Common mode subtracted from bottom pressure records before 

mapping deepwater dynamical properties. Bottom Panel: Spectra of common 

mode reveal dominant peaks near 32, 14 and 5 days. 

 2-53 
Figure 2.3-16. Time series of bottom pressure anomaly with the common mode removed in dbar 

plotted according to approximate geographic location. Instrument number noted 

in the lower left corner of each subplot. Bathymetry contoured every 500 m depth. 

2.3.6 Total Maps 

The combination of upper and lower circulation maps estimated absolute velocities throughout 

the water column. Upper-ocean relative velocities were created by mapping velocities referenced 

to zero at 2500 dbar. The 2500 dbar-level velocities, created with the bottom pressure and 

current meter records, then referenced these to generate absolute upper-ocean relative velocities. 

Absolute sea surface heights were also determined. First, 2500-dbar pressures were converted to 

their height equivalent (pressure divided by gravity and density). Second, surface geopotentials 

referenced to 2500 dbar were converted to their height equivalent (geopotential divided by 

gravity). The 2500-dbar referenced and 2500-dbar fields were combined to yield absolute sea 

surface height. 

 2-54 
Figure 2.3-17. Correlation coefficient between pairs of pressure 

records. Upper panel: Correlations coefficient 

plotted as a function of separation distance (open 

red circles) and binned every 10 km (black 

triangles). The common mode produces long 

correlations. A 150 km Gaussian function is plotted 

with black line. Lower panel: Correlation 

coefficients contoured as a function of separation 

distance (open red circles) and binned every 10 km 

(black triangles) after the common mode has been 

removed. A 30 km Gaussian function is plotted in 

black. 

2.3.7 Mooring Comparisons 

Measurements of temperature and current from the current meters were compared to PIESderived estimates. This comparison is not strictly a validation of the PIES methodology because 

the design of the array does not lend itself to strict verification as point measurements differ 

intrinsically from mapped estimates. In addition, the mooring measurements have errors as well. 

After accounting for possible differences, the comparisons below show that the measurements 

and PIES-derived estimates track each other and generally agree within anticipated bounds. 

 2-55 
Three tall moorings (M1, M2, and M3) embedded in the middle of the array provided 

measurements to evaluate our PIES-derived fields of temperature. The tall moorings experienced 

some vertical motion when stronger ocean currents caused the sensors on the upper portion of 

the moorings to deviate in depth. The proper comparison was thus between measured and 

estimated T(t,p(t)). The comparison was made at a nominal 450 m depth because the temperature 

sensors at that depth were the most stable in depth of those temperature sensors in the upper 

thermocline level. The temperatures compare well (Figure 2.3-18). Differences derive from 

instrument errors (both from the moorings and the PIES), the GEM parameterization and from 

mapping uncertainty. Table 2.3-1 documents the anticipated differences between the moorings 

and the PIES. The first column indicates the error due to IES instrument noise (0.0006 sec), the 

GEM parameterization, and mapping error. The difference between point measurements and 

mapped estimates was determined by the optimal interpolation mapping error based upon a 

correlation length scale of 45 km (Bretherton 1976). The second column includes the impact of a 

10 dbar uncertainty in the pressure sensor. The final column of Table 2.3-1 shows the rms 

differences between the mooring data and mapped temperature. The observed differences are 

lower for the M1 and M3 mooring time series. In the case of the M2 comparison, the observed 

rms is 0.05°C larger than anticipated. 

Table 2.3-1 

Temperature Differences. 

Predicted differences between measured and PIES-estimated temperature for each mooring at a 

nominal depth of 450 m. The second column presents the predicted difference between mapped 

and measured temperature considering errors in the GEM table look-up due to τ uncertainty, 

scatter in the GEM table and the mapping uncertainty. The third column includes the impact of 

the uncertainty in absolute mooring sensor pressure (column 4). 

Mooring Predicted Difference 

(PIES and mapping 

errors) 

[°C] 

Predicted Difference 

(PIES, mapping and 

mooring errors) 

[°C] 

Observed Difference

[°C] 

M1 0.54 0.62 0.51 

M2 0.56 0.63 0.68 

M3 0.72 0.77 0.64 

The PIES-mapped currents were also compared to the moored currents measurements. Figure 

2.3-19 shows a comparison for the M2 mooring, again at a nominal depth of 450 m. Both series 

track each other well. The rms differences for all mooring current comparisons are listed in Table 

2.3-2 which also includes an estimate of anticipated errors due to instrument error, the GEM 

parameterization, and mapping differences. Ageostrophic motion such as high vertical 

wavenumber inertial currents were not reproduced in the maps of geostrophic velocity. 

Additionally, in regions of strong curvature the gradient wind balance rather than geostrophic 

balance may be more appropriate. Table 2.3-2 does not account for the contribution of 

ageostrophic motion which is hard to anticipate a priori nor does the table include an error in 

mooring velocity due to uncertainty in the sensor pressure record because the velocity shears are 

relatively weak here. 

 2-56 
The observed rms differences are very close to the anticipated differences. Although not 

explicitly tabulated, current meter measurements are not without error. As an example during the 

first deployment of mooring M2 the ADCP record contained gaps owing to cable interference 

during portions of the time when the mooring’s surface buoy was lost. 

Table 2.3-2 

Velocity Differences. 

Predicted differences between measured and PIES-estimated velocity for each mooring at a 

nominal depth of 450 m. The second column presents the predicted difference between mapped 

and measured velocities considering errors in the GEM table look-up due to τ uncertainty, scatter 

in the GEM table and the mapping uncertainty. The third column shows the observed 

differences. 

Mooring Predicted difference 

[cm s-1] 

Observed Difference 

[cm s-1] 

M1 zonal 

 meridional 

8.0 

5.9 

8.5 

5.8 

M2 zonal 

 meridional 

6.4 

7.8 

8.4 

7.2 

M3 zonal 

 meridional 

7.2 

6.3 

7.9 

7.9 

2.4 Remote Sensing 

The remote sensing component of the study acquired remotely sensed (satellite) data to aid in the 

interpretation of mesoscale oceanographic features during the period of time of the physical 

oceanographic measurements in the study area. A combination of satellite observing systems was 

used. 

To carry out this task, the Colorado Center for Astrodynamics Research (CCAR) collected and 

processed a complementary suite of satellite observations from satellite altimeter and radiometer 

remote sensing data systems. This suite incorporated sea surface height (SSH) data with highresolution sea surface temperature (SST) and ocean color imagery. Satellite altimetry provided 

the all-weather multi-satellite monitoring capability required to map mesoscale circulation 

variability in the GOM. During cloud-free conditions, multi-channel radiometry was used to 

supplement the altimetric sampling by providing high-resolution synoptic SST and ocean color 

imagery for monitoring the rapidly evolving LC and its associated eddies including small-scale 

frontal features in and around the study region. 

 2-57 
Figure 2.3-18. Comparison between the moorings (red) and PIES-derived (blue) temperatures 

near 400 m depth. The nominal depth and rms difference between PIES and the 

moorings are noted in the title and top right of each panel, respectively. The 

bottom panel shows the location of the PIES (blue) the moorings (red). 

Bathymetry contoured every 1000 m depth. 

 2-58 
Figure 2.3-19. Comparison between the M2 mooring (red) and PIES-derived (blue) zonal (top) 

and meridional (middle) velocities at 415 m depth. The rms difference between 

PIES and the M2 mooring are noted in the upper left of each panel. The bottom 

panel shows the location of the PIES (blue) and the moorings (red). Bathymetry 

contoured every 1000 m depth. 

 2-59 
2.4.1 Altimetry 

Altimeter data collected and used during the study were the near real-time and archival data 

streams available from TOPEX/Poseidon (TOP/POS), ERS-2, Geosat Follow-on (GFO), Jason1, and Envisat satellite missions. Processing of the SSH data was based on near real-time 

mesoscale analysis techniques designed to exploit the multi-satellite altimetric sampling (Leben 

et al. 2002). This method has been used to operationally monitor the GOM since November 

1995. Altimeter data from a total of five satellites were available during the program time period. 

Basic information on each of the missions is given in Table 2.4-1. The groundtrack coverage 

provided by these satellites in the study region is shown in Figure 2.4-1. 

Table 2.4-1 

Satellite Altimeter Missions during the Eastern Gulf Program. 

Satellite Launch Date Agency Repeat Crosstrack Spacing 

Period 

(days) Degrees of 

Longitude 

km*

TOPEX/Poseidon 10 Sep 1992 NASA/CNES 10 2.83 278 

ERS-2 21 Apr 1995 ESA 35 0.72 71 

Geosat Follow-On 10 Feb 1998 U. S. Navy 17 1.47 144 

Jason-1 18 Dec 1999 NASA/CNES 10 2.83 278 

Envisat 1 Mar 2002 ESA 35 0.72 71 

Tandem/Interleaved Mission: 20 Sep 2000 to 6 Jan 2006. 

TOPEX/Poseidon/Jason-1 Interleaved 10 1.42 140 

*at 28°N 

Note that during the study, the TOP/POS and Jason-1 satellites were in tandem orbits with 

interleaved groundtracks. NASA/CNES scientists selected this configuration to improve the 

sampling of mesoscale ocean circulation by precision altimeters (Fu et al. 2003). The space/time 

sampling provided from the 10-day repeat orbit of the TOP/POS satellite, which was selected to 

map the ocean topography associated with large-scale variations in SSH, is not sufficient for 

monitoring mesoscale variability because of the large distance between neighboring ascending or 

descending tracks. In the GOM, this spacing is 2.83° of longitude or about 278 km at 28°N, 

which is also the distance between crossover points between ascending and descending tracks. 

Moving TOP/POS onto a parallel groundtrack that is midway between two adjacent groundtracks 

of the original TOP/POS orbit, which Jason-1 now occupies, reduced this distance by half to a 

crosstrack spacing of 140 km at 28°N. At latitudes midway between intra- and inter-satellite 

crossover points, the ascending/descending groundtrack sampling improves by another factor of 

two to a crosstrack spacing of just 71 km. Thus, the average crosstrack sampling from the 

tandem mission data alone is 70 to 140 km within the study region. The addition of GFO and 

ERS/Envisat data augments this spatial sampling but at irregular sampling times. 

 2-60 
Figure 2.4-1. Satellite altimeter groundtrack coverage in study region. TOP/POS (thin red), 

Jason-1 (thick red), GFO (green), and ERS-2/Envisat (blue) are shown with a 

schematic of the instrument array. 

 2-61 
Intuitively, sampling should improve by combining data from multiple altimeters. SSH fields 

produced by combining multi-mission altimetry; however, may not be better than those 

constructed from TOP/POS or Jason data alone if uniform errors and wavelength/frequency 

resolution satisfying the Nyquist criteria are required of the space/time gridded product as has 

been proposed by Greenslade et al. (1997). While these metrics may be reasonable for theoretical 

sampling studies or mission design, the constraints are too limiting for mesoscale mapping. 

Operational multiple satellite objective mapping of the mesoscale circulation must therefore rely 

on suboptimal smoothing to resolve eddy-scale wavelength albeit with the commensurate errors 

caused by non-uniform sampling and aliasing. This is true of both formal “optimal” interpolation 

and suboptimal objective analysis schemes. Nevertheless, the efficacy of the suboptimal 

interpolated fields can be evaluated by comparing the interpolated altimetry with coincident in 

situ data to quantitatively assess the processing and gridding strategies. PIES data are an ideal insitu measurement type for these comparisons. PIES deployment locations for the study were 

therefore selected in part to provide in-situ measurements along altimeter groundtracks where 

possible so as to allow accurate assessment of not only the space/time gridded products but the 

alongtrack data as well. 

2.4.1.1 Alongtrack Altimeter Data 

Alongtrack data were collected from the agencies providing archival altimeter geophysical data 

records (GDRs). The TOP/POS and Jason-1 data are from the Physical Oceanography 

Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory. ERS-2 and 

Envisat data are from the "Centre ERS d'Archivage et de Traitement" (CERSAT), the French 

Processing and Archiving Facility for ERS-1, ERS-2, and Envisat data. GFO data are from the 

NOAA/NESDIS Laboratory for Satellite Altimetry. 

All of the altimeter datasets were processed in as consistent a fashion as possible to produce 

accurate analysis maps based on the blended altimetric observations. Standard corrections were 

applied to the alongtrack data including inverted barometer, electromagnetic bias, ionosphere, 

and wet/dry troposphere corrections. Ocean tides were removed using the tide model supplied on 

the GDRs for TOP/POS, Jason, and Envisat. GFO and ERS-2 ocean tides were removed using 

the tide solution derived from the CCAR tide model (Tierney et al. 1998). The alongtrack 

coverage provided by the altimeter satellites during the time period was very good. 

Each cycle of corrected 10-day repeat TOP/POS and Jason, 17-day repeat of GFO, and 35-day 

repeat of ERS-2 and Envisat data was linearly interpolated to reference groundtracks based on 

precision orbit determination ephemeredes for each satellite at once-per-second alongtrack 

spacing. The TOP/POS and Jason reference track used the computed groundtrack for TOP/POS 

cycle 18. The TOP/POS interleaved mission reference groundtrack was the same groundtrack 

with an offset in longitude corresponding to the nominal interleaved orbit. The ERS-2 and 

Envisat 35-day reference groundtracks were based on repeat cycle 6 of the ERS-1 

Multidisciplinary 1 Mission. The GFO reference groundtrack was based on cycle 2 from the 

GEOSAT Exact Repeat Mission. 

 2-62 
2.4.1.2 Mesoscale Analysis 

The processing of the altimeter data was designed to retain mesoscale signals while filtering out 

longer wavelength altimetric errors. This filtering also removed long wavelength oceanographic 

signals. A detailed description of this processing and its implementation and validation in the 

GOM can be found in Leben et al. (2002). The procedure incorporates data from all of the 

available satellites, treating each data set in a consistent fashion as follows: 

1. All sub-satellite data were referenced to an independent gridded mean sea 

surface by subtracting the mean sea surface value at the sub-satellite point 

from each observation.

2. Alongtrack loess filtering was used to remove residual orbit and 

environmental correction errors. The loess filter removes a running least 

squares fit of a tilt plus bias within a sliding window from the alongtrack data. 

The window width is approximately 15° of latitude (200 once-per-second 

alongtrack data points).

3. A multigrid preconditioned Cressman analysis with temporal weighing was 

used to objectively interpolate the alongtrack data to a 1/4° grid.

4. A model mean SSH field was added to the mapped SSH anomaly field to 

provide an estimate of the total SSH in the GOM.

2.4.1.3 Mean Reference Surface and Model Mean SSH 

All alongtrack data were referenced to an existing altimetric mean sea surface. The data were 

treated as non-repeating groundtracks and were referenced directly to the mean sea surface by 

interpolating the mean sea surface value to the sub-satellite point and subtracting it from the sea 

surface height. This applies an implicit crosstrack geoid gradient correction to the alongtrack 

data before interpolation to the reference groundtracks. 

The GSFC00.1_MSS, which was computed by Y. M. Wang of Raytheon ITSS (Wang 2001), 

was used as the reference surface. This mean sea surface is based on 6-years of TOP/POS data 

(Cycles 11 to 232), multiple years of ERS-1&2 35-day exact repeat data (ERS-1 Phase C: Cycles 

1 to 18; Phase G: Cycles 1 to 13; ERS-2: Cycles 1 to 29), Geosat 17-day exact repeat data 

(Cycles 1 to 41), Geosat Geodetic Mission data, and both cycles of the ERS-1 168-day repeat 

data. All the altimeter data used to calculate the mean sea surface came from the GSFC's 

Altimeter Pathfinder products (Koblinsky et al. 1999). 

 2-63 
To calculate the synthetic SSH estimates, we used the model mean sea surface height computed 

for the time period 1993-1999 from a data assimilation hindcast experiment performed by Drs. 

Lakshmi Kantha and Jei Choi for the MMS Deepwater Physical Oceanography Reanalysis and 

Synthesis Program (Nowlin et al. 2001). The data assimilation experiment used the University of 

Colorado-Princeton Ocean Model (CUPOM) and assimilated alongtrack TOPEX and ERS-1&2 

sea surface height anomalies into CUPOM on a track-by-track basis as subsurface temperature 

anomalies (Kantha et al. 2005). Before adding the model mean to the gridded SSH anomaly 

fields, we averaged the 1993-1999 SSH anomaly fields and removed the residual anomalous 

altimetric mean over the time period. This referenced the SSH anomaly fields to a mean 

spanning the same time period as determined from the CUPOM hindcast data assimilation 

experiment. The anomalous altimetric mean reflected the difference between the mean 

circulation contained in the GSFC mean sea surface and the 1993-1999 data assimilation mean. 

More discussion of these differences is found in Leben et al. (2002). 

2.4.1.4 Objective Mapping 

Daily analysis maps of height anomaly relative to the mean sea surface were estimated using an 

objective analysis procedure (Cressman 1959) to interpolate the alongtrack data to a 1/4° spatial 

grid. The method used an iterative difference-correction scheme to update an initial guess field 

and converge to a final gridded map. A multigrid procedure provided the initial guess. Five 

iterations were used with radii of influences of 200, 175, 150, 125, and 100 km while employing 

a 100-km spatial decorrelation length scale in the isotropic Cressman weighting function. The 

data were weighted in time using a 12-day decorrelation time scale relative to the analysis date 

using a ±10 day window for the TOP/POS and Jason data and a ±17 day window for the ERS-2, 

Envisat, and GFO data. The details of the space and time-weighted version of the multigrid 

preconditioned Cressman analysis is described next. The weighted version was based on the 

space-weighting only technique described in Hendricks et al. (1996). 

2.4.1.5 Objective Analysis Procedure 

An objective analysis (OA) procedure is used to interpolate the alongtrack sea surface height 

anomalies onto a regularly spaced 1/4° global grid. The OA algorithm is based on the iterative 

difference-correction scheme of Cressman (1959). The initial guess field for the Cressman 

algorithm was supplied by an efficient multigrid procedure. 

A rough estimate of the 1/4° field was created by collecting the alongtrack SSH anomaly data 

into 1/4°grid cells. In grid cells where at least one SSH measurement was available, the average 

of all measurements within the cell was computed. Some of the grid cells may not contain data 

depending on the spacing of groundtracks. The OA procedure is designed to fill in these data 

gaps by creating an SSH anomaly field that is consistent with the alongtrack measurements. 

 2-64 
The 1/4°-binned data can be used as an initial guess in the Cressman algorithm; however, having 

initial values in the empty grid cells can enhance the efficiency of the iteration procedure. A 

simple multigrid procedure was used to estimate values in cells where no altimeter 

measurements are available. Multigrid methods (Briggs 1987) rapidly solve a set of equations by 

working at several grid resolutions. In this case, if the alongtrack data are binned into 1° or 2°

grid cells, there would be fewer or even no empty ocean grid cells. Using a multigrid 

interpolation strategy to efficiently compute the means, a set of progressively coarser grids (1/2°, 

1°, 2°, ...) are created from the global 1/4° grid, and the average SSH is computed at all coarser 

grid resolutions in each cell containing data. The mean values are transferred back to the original 

1/4° grid from the finest-scale grid containing a mean value coincident with that location. 

Finally, a fast red-black smoothing operator (e.g., see Press et al. 1992) is used on the 1/4° initial 

guess field to smooth high-frequency noise introduced by the multigrid interpolation. 

Cressman objective analysis uses an iterative-difference corrections scheme in which a new 

estimate of the SSH value for a given grid cell is equal to the sum of the previously estimated 

SSH at that location and a correction term. The correction term is forced by the difference 

between the estimated heights and the original data values over all grid cells within a specified 

radius of influence. A weight based on the number of original measurements within a grid cell is 

included in the correction term, as is a weight based on the distance of a grid cell from the point 

being updated. 

The nth iteration for the SSH at grid cell i is computed using: 

hi

n = hin−1 +

wmnm hm − hm

* * n−1

∑ ( )

wmnm

*

∑ , (2.4.1) 

where the sums are taken over all m grid cells within the specified radius of influence R from the 

grid cell i being updated. The variables in (Eq. 2.4.1) are defined as: 

h the nth iteration of SSH at grid cell i; i

n

n−1

*

n−1

*

w

h the (n-1)th iteration of SSH at grid cell i; m

 the average height at grid cell m based on the original data; 

hm

h the (n-1)th iteration of SSH at grid cell m; m

nm the number of original measurements within grid cell m. 

The weights in the correction term are defined by: 

ar

2 /R2

) m for r ≤ R; m = exp(−

w r R; m = 0 for >

 2-65 
where rm is the distance between grid cell m and the grid cell being updated and R is the 

maximum radius of influence. The parameter a is an adjustable weighting factor that scales the 

exponential spatial weighting of the data.

To incorporate weighting of the data in time, the data and the number of original measurements 

within a grid cell are each scaled by the weighting function: 

wt = exp(−bΔtm /T ) 2 2 forΔ ≤t T ; 

w Δt > T ; t = 0 for

where is the difference between the measurement time and the time corresponding to the 

analyzed field. The parameter b is the time weighting factor, and T is the maximum time window 

of influence. 

Δtm

The empirical weighting parameters, a and b, are selected to map the mesoscale structure within 

the limitation of the scales resolvable by the crosstrack altimeter sampling. The mesoscale 

analysis used a = 4 and b = 2, which correspond to decorrelation space and time scales of 100 

km and 12 days, respectively, for R = 200 km and T = 17 days. The maximum radius of 

influence, R, was decreased between the Cressman iterations to allow smaller scales to converge 

more quickly and to increase resolution when alongtrack sampling was available. For this study, 

R was decreased from 200 to 100 km over five iterations giving a decorrelation length scale of 

50 km on the final Cressman iteration. 

2.4.2 Ocean Color Imagery 

Daily ocean color imagery was downloaded from the OceanColor group web and ftp sites 

(http://oceancolor.gsfc.nasa.gov/) at the NASA Goddard Space Flight Center (GSFC). These 

images are a 9-km resolution blended product incorporating data from the Sea-viewing Wide 

Field-of-view Sensor (SeaWiFS) satellite and the Moderate Resolution Imaging 

Spectroradiometer (MODIS) instrument onboard the Aqua satellite. The empirical chlorophyll 

algorithms OC4v4 and OC3M (O’Reilly et al. 1998) are used with measured radiances from 

SeaWiFS and MODIS, respectively, to calculate the individual chlorophyll fields from each 

satellite image. Both SeaWiFS and MODIS data were Level-3 processed before being merged. 

This processing involved the spatial and temporal binning of Level-2 data into 4 and 9-km equirectangular projections and is described in detail by Hooker et al. (1995). Combining the data 

from the two missions increased the coverage over a single mission product, on average, by over 

50% for the daily product and by over 20% for the 8-day composite product. A variety of multiday composites were made to help with the detection and tracking of oceanographic features in 

and around the study region. GSFC MODIS Level-2 ocean color imagery at 2-km resolution was 

also downloaded and used for some of the higher resolution analyses in this report. 

 2-66 
2.4.3 SST Imagery 

SST products were acquired for remote sensing and data synthesis activities. We used Advanced 

Very High Resolution Radiometer (AVHRR) imagery from the Johns Hopkins 

University/Applied Physics Laboratory (JHU/APL) Ocean Remote Sensing Group. Three-day 

warmest pixel composite images in Portable Network Graphics (PNG) format were downloaded 

from the JHU/APL Ocean Remote Sensing Group website. These images have 1-km resolution 

with image values (0-255) corresponding to the rounded integer SST values. The full precision 

values before rounding were calculated by the multi-channel algorithm used in the TerraScan 

software that converts raw antenna brightness temperatures to SST values in the APL ground 

station. Although the rounding limits the accuracy to only 0.5°C, which is less than required for 

most scientific work, the capability to detect spatial features was not compromised, and the data 

was sufficiently accurate for data synthesis activities. The images collected for the study were 

once-per-day 3-day composite images from January 1, 2005 through June 30, 2006. 

2.5 PIES/Altimeter Comparison 

PIES and satellite altimetry are complementary data types. Although the two measurement 

systems measure completely different physical quantities, they both yield an estimate of the 

height of the ocean surface relative to some datum, which is commonly referred to as sea surface 

height (SSH). 

For this study,, we evaluated the altimeter SSH measurement system using PIES data as a 

benchmark for theoretical analyses and for comparison of PIES SSH directly to the coincident 

altimeter-derived SSH collected during the study. This is the third opportunity for these types of 

analyses and comparisons in the GOM, supplementing the results in the central and western Gulf 

reported in the Exploratory and the Northwestern GOM Study technical reports (Donohue et al. 

2006; Donohue et al. 2008). Some of the statistics prepared for those reports will be presented 

again here and discussed in light of the results obtained in eastern GOM. These types of analyses 

and comparisons have the potential to identify problems in current datasets and to develop and 

test improvements in the altimeter data processing techniques used to produce future data 

products. This will facilitate the synthesis of altimetry data and PIES data from current and 

future arrays deployed in the deepwater GOM, which will improve observing and understanding 

of deepwater circulation patterns and dynamics throughout the water column. 

2.5.1 Altimetric Sampling and Aliasing 

Satellite altimeters provide discrete SSH measurements at sub-satellite points spaced 

approximately 5–7 km along groundtracks that repeat every 10, 17, or 35 days for the satellites 

used during the study program (Table 2.5-1). Orbital dynamics determine the space/time 

sampling pattern achieved on orbit, and there is a trade-off between spatial and temporal 

resolution when selecting an orbit during the mission design phase of a satellite program. As an 

example, see the discussion of the TOP/POS mission in Parke et al. (1987). For single satellite 

sampling, high spatial resolution using a nadir pointing altimeter is achieved only at the expense 

of less frequent sampling of the sea surface in time, and vice versa. 

 2-67 
Unlike ground-based instruments where the sampling rate can be selected to satisfy a specific 

Nyquist criterion, satellite-based measurement systems in non-geosynchronous orbits have a 

temporal sampling rate imposed by the period at which a point on the Earth’s surface is sampled 

from orbit. Increasing the temporal sampling rate for a nadir-pointing altimeter requires either 

the addition of more satellites in the same orbit or a shorter repeat period resulting in a loss of 

spatial sampling density. Neither option can usually be justified from an economic, scientific, or 

operational perspective. Anecdotally, when additional sampling became available from 

TOP/POS after the commissioning phase of the TOP/POS and Jason-1 tandem mission, the 

decision made was to increase the spatial sampling density (Fu et al. 2003) and, by default, 

accept the existing level of temporal aliasing of the 10-day repeat sampling. A number of studies 

have addressed spatial/temporal aliasing issues (Schlax and Chelton 1994; Parke et al. 1998) 

including assessment of the aliasing of well known periodic signals such as tides; however, few 

studies have assessed the SSH variance associated with the aliased signal from under-sampled 

SSH ocean measurements. 

The temporal aliasing of ocean signals by satellite altimeter sampling can be addressed using the 

high-rate in-situ SSH data provided by PIES measurements. Hendry et al. (2002) performed the 

first study along these lines using PIES data collected within the North Atlantic Current in the 

Newfoundland Basin. They found that the time scales of motion observed in the region are such 

that 86-95% of the subinertial period SSH variability was not aliased by the approximately 10-

day TOP/POS repeat period sampling. Gille and Hughes (2001) performed an earlier study of 

sampling using only bottom pressure records; however, that type of study would not be 

appropriate in the GOM where the time scales associated with the bottom pressure variability are 

not representative of the time scales of the SSH variability. 

Following the methodology of Hendry et al. (2002), we made an assessment of the SSH signal in 

the Exploratory and Northwest GOM Study regions (Donohue et al. 2006; Donohue et al. 2008), 

and now report similar analyses for the Eastern GOM for the approximately 10-day, 17-day, and 

35-day repeat period sampling available from the ongoing satellite altimeter missions. We 

computed power spectra for each of the SSH time series (barotropic, baroclinic, and combined) 

and calculated the percentage of cumulative power in the spectra up to each of the Nyquist 

frequencies associated with the 10-day, 17-day, and 35-day repeat sampling periods. The periods 

corresponding to the Nyquist frequency for each of the altimeter satellites are tabulated in Table 

2.5-1. Figures 2.5-1, 2.5-2, and 2.5-3 show maps of the unaliased variance associated with 10-

day, 17-day, and 35-day repeat sampling periods in the study region for the current altimeter 

missions from the barotropic, baroclinic, and combined SSH signals, respectively. Eastern GOM 

summary statistics are tabulated in Table 2.5-2 along with the statistics from the Exploratory 

Program and Northwest GOM PIES arrays. Tabulated values for each of the Eastern GOM PIES 

stations are listed in Table 2.5-3. 

 2-68 
The aliasing of the barotropic SSH signal is the most severe because of the shorter time scales 

associated with that signal in the GOM. The mean value over the Eastern GOM array of 10-day 

sampling period unaliased variance was 63%, comparable to the 59% and 62% estimated from 

the Exploratory Program and Northwest GOM PIES arrays. The Eastern GOM individual station 

results ranged from a minimum of 59% at PIES 1 to a maximum of 70% at PIES 7, which is 

comparable to the 56% to 72% range found for the Northwest GOM program. The range, 

however, is smaller than the 44% to 77% range found in the Exploratory program array, which 

covered a larger aerial extent and included instruments above the Sigsbee Escarpment. The 

spatial pattern of aliasing was similar for 17-day sampling, with the least amount of aliasing at 

the southern-most station. However with 35-day sampling, the station with the greatest 

percentage of unaliased signal was station 3, which moves the region with the least amount of 

aliasing to the northeastern part of the array. The overall mean value was 35%, and the individual 

values ranged from a minimum of 31% at PIES 5 to a maximum of 39% at PIES 3. The Eastern 

GOM mean value of 35% is comparable to the Exploratory program and Northwest GOM 

program mean values of 37% and 42%, respectively. The generally low mean values for all of 

the altimetric sampling frequencies in both the NW and central Gulf are attributable to the 

aliasing of the frequencies associated with the 6-day barotropic oceanic response to an 

atmospheric Rossby-Haurwitz wave (Park and Watts 2006) and the 14-day to 16-day Gulf-wide 

common mode. 

The unaliased variance of the baroclinic and total SSH signal was much higher than the 

barotropic-only case because of the longer period baroclinic signals and the dominance of the 

more energetic baroclinic component on the total SSH. Still, there were large differences 

between the 10-day and 35-day patterns, while the 10-day and 17-day patterns were more 

similar. For a 10-day sampling period of the baroclinic signal in the Eastern GOM, the unaliased 

variance mean value over the array was 93% and ranged from a minimum of 84% at PIES 6 to a 

maximum of 97% at PIES 7. The 35-day sampling mean value was only 76% and ranged from a 

minimum of 68% at PIES 6 to a maximum of 85% at PIES 1. The total combined baroclinic and 

barotropic SSH signal showed similar patterns. The SSH 10-day period unaliased variance mean 

value over the array was 92% and ranged from a minimum of 84% at PIES 6 to a maximum of 

97% at PIES 7. The 35-day sampling mean value decreased to 75% and ranged from a minimum 

of 67% at PIES 6 to a maximum of 83% at PIES 1. These overall averages and ranges were 

comparable to those found in our analyses of the Exploratory program and Northwest GOM 

program PIES, further confirming the similarity of the baroclinic signals in the GOM deepwater 

even over separate and distinct observational time periods. 

 2-69 
Table 2.5-1 

Satellite Periods. 

Satellite altimeter mission exact-repeat periods and periods associated with the Nyquist sampling 

frequency. 

Satellite Approximate Repeat Repeat Period 

(days) 

Nyquist Sampling 

Period (days) 

TOPEX/Poseidon 10-day 9.9156 19.8313 

ERS-2 35-day 35 70 

Geosat Follow-On 17-day 17.0505 34.1010 

Jason-1 10-day 9.9156 19.8313 

Envisat 35-day 35 70 

In summary, 84% to 97%, 84% to 98%, and 87% to 99% of the subinertial period SSH 

variability in the Eastern GOM, Northwest GOM, and Exploratory Study regions, respectively, 

are unaliased by the TOP/POS 10-day repeat period sampling. This is comparable to the 86% to 

95% estimated from the Newfoundland Basin array by Hendry et al. (2002). However, the results 

for the 17-day and 35-day repeat sampling show that there can be significant aliasing of the 

GOM SSH signals in satellite altimetry even with the dominance of the longer period baroclinic 

signals associated with the LC and LCEs in the Gulf deepwater. The degree to which this affects 

the space/time interpolated maps of altimetric SSH needs to be investigated in more detail. It is 

also unclear whether the weak surface signature of topographic Rossby waves can be mapped 

effectively using satellite altimetry given the presence of the strong baroclinic SSH and the 

difficulties associated with aliasing of the barotropic signal. Also, the presence of the ubiquitous 

common mode needs to be considered when processing sea surface height. In most cases, this 

signal will be removed by standard altimetric processing techniques, and the aliasing will be 

mitigated. However, the signal may be retained as more sophisticated processing and higher 

frequency corrections are applied to the data. 

 2-70 
Figure 2.5-1. Maps of PIES barotropic unaliased variance for 10-day, 17-day, and 35-day 

sampling. 

 2-71 
Figure 2.5-2. Maps of PIES baroclinic unaliased variance for 10-day, 17-day, and 35-day 

sampling. 

 2-72 
Figure 2.5-3. Maps of PIES SSH unaliased variance for 10-day, 17-day, and 35-day sampling. 

 2-73 
Table 2.5-2 

Variance Statistics. 

Unaliased variance statistics for 10-day, 17-day, and 35-day exact repeat sampling of the PIES 

barotropic, baroclinic, and combined SSH signals. 

Stations Barotropic Signal 

Mean (%) 

Baroclinic Signal 

Mean (%) 

Total SSH Signal 

Mean (%) 

 Repeat: 10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

Eastern Gulf Program 

all stations 63 49 35 93 89 76 92 88 75 

NW Gulf Program 

all stations 62 53 42 97 92 76 94 89 75 

Exploratory Program 

all stations 59 47 37 97 93 78 95 92 78 

above escarpment 56 45 39 96 93 75 94 91 75 

below escarpment 61 49 36 97 93 80 96 93 79 

Stations Barotropic Signal 

Maximum (%) 

Baroclinic Signal 

Maximum (%) 

Total SSH Signal 

Maximum (%) 

 Repeat: 10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

Eastern Gulf Program 

all stations 70 55 39 97 92 85 97 93 83 

NW Gulf Program 

all stations 72 64 47 99 97 90 98 95 87 

Exploratory Program 

all stations 77 60 45 99 98 93 99 98 93 

above escarpment 60 50 42 99 98 90 97 96 90 

below escarpment 77 60 45 99 98 93 99 98 93 

Stations Barotropic Signal 

Minimum (%) 

Baroclinic Signal 

Minimum (%) 

Total SSH Signal 

Minimum (%) 

 Repeat: 10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

Eastern Gulf Program 

all stations 59 44 31 84 79 68 84 80 67 

NW Gulf Program 

all stations 56 47 36 93 86 52 84 79 53 

Exploratory Program 

all stations 44 38 29 92 86 54 87 82 54 

above escarpment 51 42 36 92 86 54 87 82 54 

below escarpment 44 38 29 93 87 56 92 85 56 

 2-74 
Table 2.5-3 

PIES Statistics. 

PIES SSH, baroclinic, and barotropic statistics and percent of unaliased variance measured by 

satellites in 10-day, 17-day, and 35-day exact repeat orbits. The time series’ length, standard 

deviation (std), and half power period (T0.5) are also shown. 

PIES Signal Length Std T0.5 Unaliased Variance (%) 

(days) (cm) (days) 10-day 17-day 35-day 

SSH 397 15.8 158 95 91 83 

Baroclinic 397 15.9 158 96 92 85 

1 

Barotropic 397 2.7 16 59 46 33 

SSH 397.5 11.0 102 90 86 73 

Baroclinic 397.5 10.7 108 93 90 78 

2 

Barotropic 397.5 2.6 16 60 49 35 

SSH 398.5 12.5 102 92 88 68 

Baroclinic 399 12.2 108 93 89 71 

3 

Barotropic 398.5 2.7 21 63 51 39 

SSH 397 13.4 128 94 89 76 

Baroclinic 397 13.6 128 95 89 78 

4 

Barotropic 397 2.8 21 63 49 37 

SSH 394 18.1 146 95 90 81 

Baroclinic 390.5 18.9 137 95 89 79 

5 

Barotropic 390.5 3.1 21 63 44 31 

SSH 397.5 16.5 102 84 80 67 

Baroclinic 288.5 16.8 102 84 79 68 

6 

Barotropic 288.5 2.9 23 66 51 37 

SSH 393 20.6 108 97 93 76 

Baroclinic 391 21.4 108 97 92 74 

7 

Barotropic 391 3.3 25 70 55 34 

2.5.2 Signal-to-Noise 

A useful metric for assessing the accuracy of altimeter-derived estimates of SSH is the ratio of 

the unaliased variance to the aliased variance of the SSH signal, which is an estimate of the 

signal-to-noise ratio (SNR) of a perfect on-orbit measurement system. The amount of aliasing is 

also a function of the repeat sampling period of the satellite altimeter as can be seen in Figure 

2.5-4. Note that we do not consider the barotropic and baroclinic components separately because 

they cannot be distinguished from on-orbit measurements alone. Also, the “noise” in the 

unaliased to aliased SNR is colored noise associated with undersampled geophysical signals that 

are very difficult to remove without excessive smoothing or filtering of the alongtrack data 

before interpolation. This is the primary reason that the requirement of uniform errors and 

wavelength/frequency resolution satisfying the Nyquist criteria as proposed by Greenslade et al. 

(1997) for gridded altimeter products is unrealistic in practice. 

 2-75 
Table 2.5-4 shows a summary of the SNR statistics estimated from the Eastern GOM, Northwest 

GOM, and Exploratory Study PIES data. In nearly all cases, the Eastern GOM SNR is lower than 

both the Northwest GOM and Exploratory Study statistics for all three sampling scenarios. 

Nevertheless, the SNR in all of the study regions was very good for 10-day and 17-day altimetric 

sampling. The 35-day sampling was more problematic. The 35-day sampling spatial map (Figure 

2.5-4 lower panel) shows SNR ratios in the low single digits over much of the Eastern GOM 

array, which would make it difficult to distinguish between signal and aliased signal at that 

sampling frequency from a single-point measurement. Similar low SNR regions were found in 

the western and central GOM. Quantifying the SNR for combined sampling by multiple 

altimeters will be reported in future work. 

Table 2.5-4 

SNR Statistics. 

Signal-to-noise ratio (SNR) statistics for 10-day, 17-day, and 35-day exact repeat sampling of the 

PIES barotropic, baroclinic and combined SSH signals. 

Stations Mean SNR Minimum SNR Maximum SNR 

 Repeat: 10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

10-

day 

17-

day 

35-

day 

Eastern Gulf Program 

all stations 16 8 3 5 4 2 32 13 5 

NW Gulf Program 

all stations 22 11 4 5 4 1 49 19 7 

Exploratory Program 

all stations 28 16 5 7 5 1 99 49 13 

above escarpment 20 13 4 7 5 1 32 24 9 

below escarpment 33 19 5 12 6 1 99 49 13 

 2-76 
Figure 2.5-4. Maps of PIES SSH signal-to-noise ratio (SNR) for 10-day, 17-day, and 35-day 

sampling. SNR is estimated from the ratio of unaliased to aliased variance. 

 2-77 
2.5.3 Sea Surface Height Time Scales 

Following the methodology of Hendry et al. (2002), the period corresponding to the frequency at 

which the cumulative power spectrum reaches 50% of the total variance, the half-power period 

(T0.5), was determined from the spectral analysis of each of the PIES SSH anomaly time series. 

T0.5 is a more robust measure of time scale than the temporal autocorrelation zero crossing, T0, 

and is the preferred scale to be used to define the effective degrees of freedom of a time series 

(Fofonoff and Hendry 1985). This robustness is due in large part to the global and integral nature 

of the T0.5 metric which is less sensitive to competing time scales within the time series. In 

contrast, the calculation of T0 is a less robust measure because the first zero crossing of the 

temporal autocorrelation function is quite sensitive to the presence of multiple time scales and/or 

secular trends in the time series. 

The half-power periods were computed from the 13-month Eastern GOM, 9-month Northwest 

GOM, and 12-month Exploratory Study PIES barotropic, baroclinic, and SSH anomaly time 

series. Spatial maps of T0.5 in the Eastern Gulf for each of the three signals are shown in Figure 

2.5-5. We did not detrend the time series before calculating the spectra because of the relatively 

short duration of the records. This allowed estimation of the longer time scales of variability 

associated with the LC and LCEs that occurred in most of the records. Mean T0.5 values are listed 

in Table 2.5-5 for each program showing the average time scales for each of the signals at all 

PIES stations. The Exploratory Study averages for stations above and below the Sigsbee 

Escarpment are also shown. 

The mean half-power periods of the barotropic signals were quite similar between the three 

regions and were dominated by the Gulf-wide common mode. The spatial distributions were 

notably different. In the Eastern GOM, the longer period signals were located along the southeast 

margin of the array located in the deepest water. This was similar to the central GOM where the 

longer period signals were in the south-central part of the Exploratory array in the deepwater 

below the Sigsbee Escarpment. In contrast, the longer period barotropic signals in the Northwest 

GOM were on the upper slope. 

The time scales of the baroclinic and combined barotropic and baroclinic SSH anomaly signals 

were very similar because of the small contribution by the barotropic mode to the total signal. 

The long half-power periods associated with these signals show the dominance of the lowfrequency LC and LCE variability observed in the three regions during the observational records. 

In the Eastern GOM, the 150-day and longer periods were located on the western margin of the 

array where LC and LCE variability reached into the array during the LC intrusion that 

ultimately formed LCE Vortex. The shortest half-power periods, less than 150 days, were found 

over much of the Eastern GOM array. The higher frequency signals associated with these shorter 

periods likely arise from the SSH variability generated by frontal or filament eddies on the 

periphery of LC and detached LC eddies. 

 2-78 
Figure 2.5-5. Spatial maps of the half-power period, T, computed from the PIES barotropic, 

baroclinic, and combined SSH anomaly time series. Mean values over all stations 

are also shown. 

 2-79 
Table 2.5-5 

Half-power Period of PIES Barotropic, Baroclinic, and Total SSH Signals. 

Stations Barotropic Signal 

Half-Power Period 

(days) 

Baroclinic Signal 

Half-Power Period 

(days) 

Total SSH Signal 

Half-Power Period 

(days) 

mean max min mean max min mean max min 

Eastern Gulf Program 

all stations 20 25 16 121 158 102 121 158 102 

NW Gulf Program 

all stations 21 47 14 155 293 66 148 293 66 

Exploratory Program 

all stations 19 34 12 230 34 12 232 512 60 

above escarpment 16 18 14 188 18 14 195 341 64 

below escarpment 21 34 12 262 34 12 260 512 60 

2.5.4 Comparison of CCAR Mesoscale and PIES SSH 

The CCAR mesoscale SSH gridded altimeter data product that was distributed and used for data 

synthesis activities in this report was evaluated by comparison with the coincident PIES SSH 

time series at each of the PIES stations in the Eastern Gulf array. A spatial map of the 

CCAR/PIES correlation is shown in Figure 2.5-6. The nearest 1/4° grid point from the CCAR 

product was used to calculate the temporal correlation coefficient. The overall mean correlation 

for the Eastern GOM program datasets was 87%, which was better than both the Northwest 

GOM program and Exploratory program mean values of 76% and 82%, respectively. The lowest 

correlations were in the northeastern corner of the study array. The correlations were highest 

along the eastern and southern margins of the array where LC and LCE influences were more 

pronounced during the measurement time period. 

Taking advantage of the placement of PIES on satellite groundtracks (Figure 2.4-1), we 

compared the alongtrack detrended SSH anomaly data from each altimeter to the coincident 

PIES SSH data gathered on collocated groundtrack points. Scatterplots and correlation 

coefficients for the collocated altimeter and PIES measurements are shown in Figure 2.5-7 for 

each of the four satellites that flew directly over a PIES station location during the study 

program. Note that no PIES were placed on a TOP/POS groundtrack during the Eastern GOM 

program. In all cases, the correlations during the Eastern GOM program were as good as or 

better than the Northwest Gulf and Exploratory Programs (Table 2.5-6). This is attributed to the 

longer time scales and higher amplitude signals associated with the primarily deepwater 

measurements made during the Eastern GOM program. 

 2-80 
Figure 2.5-6. Spatial map of the CCAR/PIES SSH temporal correlation. Average over all 

stations of the correlation of the CCAR gridded mesoscale SSH data product to 

the collocated PIES time series is 87%. The 2000-m isobath is shown. 

 2-81 
Figure 2.5-7. Scatterplot and correlation values of PIES time series points located on altimeter 

groundtracks with the coincident points from the along-track detrended altimeter 

data. Results derived from all four satellites that overflew a PIES station: Envisat, 

ERS-2, GFO, and Jason. 

 2-82 
Table 2.5-6 

Satellite Altimeter and PIES SSH Correlation. 

Satellite altimeter and PIES SSH correlation at groundtrack points coincident with PIES stations 

during the Eastern Gulf, NW Gulf, and Exploratory Programs. 

Satellite Eastern Gulf 

Program 

NW Gulf 

Program 

Exploratory 

Program 

Envisat 88% 81% 79% 

ERS-2 93% 73% 72% 

GFO 89% 78% 81% 

Jason-1 86% 86% 77% 

TOP/POS NA 63% 56% 

As we noted in the Northwest GOM and Exploratory Study reports, the correlation values are 

very sensitive to the alongtrack smoothing/gridding employed to interpolate the raw sub-satellite 

measurement points to a reference groundtrack. The CCAR alongtrack gridding technique does 

not smooth the raw alongtrack data and uses linear interpolation between sub-satellite points. 

This method was consistently applied to produce all of the alongtrack data for each satellite. The 

Cressman objective analysis that was used to interpolate the alongtrack data to a regular 

space/time grid does apply some filtering/smoothing to the data, which is why the gridded 

product correlations with the PIES SSH time series can, in some cases, be higher than the 

alongtrack correlations. The low correlation found between the TOP/POS alongtrack and PIES 

SSH data may be residual geoid error caused by referencing the alongtrack data to the GSFC 

mean sea surface. This mean sea surface predates the Tandem Mission therefore no SSH data 

along the TOP/POS interleaved groundtrack was used in the estimation of the mean. Updated 

mean sea surfaces that include TOP/POS Tandem Mission data in the estimation procedure are 

now becoming available. When one of these updated mean sea surfaces is incorporated into the 

CCAR data processing system, an improvement in the TOP/POS correlation with the PIES 

should be observed. Thus, PIES data can help to improve satellite altimeter data processing and 

to evaluate the performance of the satellite-based observing systems. 

Ongoing work at the University of Colorado is directed toward improving the CCAR SSH 

product by using optimal interpolation techniques and space/time correlation functions tuned to 

the SSH variability in the Gulf. The ultimate goal is to combine altimeter and PIES SSH in a 

single data product exploiting the full sampling capabilities of both systems. 

2.6 Ancillary Data 

Ancillary data for river discharge, coastal and offshore winds, and coastal water levels were 

obtained as available from public sources. These data were used to assist in assessing if coastal 

influences significantly influenced the circulation structure in the study area. 

 2-83 
2.6.1 River Discharge 

River discharge data was obtained from the US Geological Survey (USGS) website 

http://waterdata.usgs.gov/nwis/rt for major rivers discharging into the central and eastern GOM 

north of the study area (Figure 1.2-1). Time series of these discharge data are shown in Figures 

2.6-1 through 2.6-4. Timing of tropical storms and hurricanes is depicted on the plots. These 

discharge data provide an excellent perspective on the dominance of the Mississippi River 

discharge over the other sources, requiring some changes in the discharge scale so as to plot the 

data. The greatest river discharge occurred in April for most rivers. For the Wax Lake Outlet and 

the Lower Atchafalaya River, the greatest discharge occurred from January through April. The 

Mississippi River consistently had a higher discharge than all other rivers in the area followed by 

the Wax Lake Outlet, Lower Atchafalaya River and the Alabama River. 

2.6.2 Coastal and Offshore Winds 

Coastal wind data was obtained from the National Data Buoy Center (NDBC) website 

http://www.ndbc.noaa.gov for several coastal and offshore locations (Figure 1.2-1). Time series 

vector plots of these data are provided in Figures 2.6-5 through 2.6-8. Timing of tropical storms 

and hurricanes is depicted on the plots. Wind sensors 3 and 5-8 were located offshore on buoys 

surrounding the study area while the other sensors were located on or near-shore from Louisiana 

to Alabama. Some datasets were sparse after hurricane events. Sensors 4-8 had the highest wind 

speeds. The highest wind speeds approached 70 mph during Hurricane Katrina at sensors 6 and 

7. For each sensor, the highest wind speeds occurred during hurricane events. 

2.6.3 Coastal Water Levels 

Coastal water level data was obtained from the National Oceanic and Atmospheric 

Administration (NOAA) website http://tidesandcurrents.noaa.gov for several coastal locations 

(Figure 1.2-1). Time series plots of these data are provided in Figures 2.6-9 and 2.6-10. Timing 

of tropical storms and hurricanes is depicted on the plots. Tidal variation was similar for each 

location. The largest differences between predicted and measured tide height occur during or 

shortly after hurricane events; however, the measured tide height varied from the predicted 

height at other times as well. 

2.6.4 Hurricanes and Tropical Storms 

Five hurricanes and one tropical storm passed through the GOM during the measurement 

program in 2005. A listing of the storms and dates is provided in Table 2.6-1. Information on the 

tracks of the storms was obtained from the National Hurricane Center (NHC) website 

http://www.nhc.noaa.gov. The paths and timing of all six storm events are shown in Figure 2.6-1. 

The aerial extent of the tropical storm and hurricane winds for each storm, as provided by the 

NHC, and their position versus our study area and moorings, is displayed in Appendix A. Timing 

of these tropical storms and hurricanes has also been depicted on various data plots in 

Appendices B and C. 

 2-84 
Figure 2.6-1. River discharge in m3 s-1 during the first deployment 

(Rivers 1-7). Note Mississippi River is at larger scale. 

Figure 2.6-2. River discharge in m3 s

-1 during the first deployment 

(Rivers 8-15). 

 2-85 
Figure 2.6-3. River discharge in m3 s-1 during the second deployment 

(Rivers 1-7). Note Mississippi River is at larger scale. 

Figure 2.6-4. River discharge in m3 s

-1 during the second deployment 

(Rivers 8-15). 

 2-86 
Figure 2.6-5. Vector plots of wind speed (mph) and direction (degrees 

from) for the first deployment (Winds 1-5). 

Figure 2.6-6. Vector plots of wind speed (mph) and direction (degrees 

from) for the first deployment (Winds 6-10). 

 2-87 
Figure 2.6-7. Vector plots of wind speed (mph) and direction (degrees 

from) for the second deployment (Winds 1-5). 

Figure 2.6-8. Vector plots of wind speed (mph) and direction (degrees 

from) for the second deployment (Winds 6-10). 

 2-88 
Figure 2.6-9. Predicted and measured tide height (m) from gauges located on the coast from 

Louisiana to Florida for deployment 1. 

Figure 2.6-10. Predicted and measured tide height (m) from gauges located on the coast from 

Louisiana to Florida for deployment 2. 

 2-89 
2.6.5 Horizon Marine Eddy Watch and Drifting Buoys 

Horizon Marine, Inc. produces a proprietary operational oceanographic product called Eddy 

Watch that tracks, maps, and forecasts the LC and its eddies and frontal features. Horizon Marine 

uses a variety of information to create this oceanographic product, including satellite imagery 

and altimetry information, circulation modeling output, as well as trajectories from satellitetracked drifting buoys that they deploy into the LC. The Eddy Watch product and the drifting 

buoys trajectory information are proprietary products with non-disclosure rules for a period of 

one year. The study team secured a limited use license to obtain and utilize both the Eddy Watch 

reports and the drifting buoy trajectory data for the period of 2005 for the purpose of performing 

some additional analyses on LC and LCE metrics and kinematics. 

Table 2.6-1 

Storm Events. 

A list of the storm events that passed near the study area during the study period. 

Storm Name Category at Site Date in Gulf 

Date Closest to 

Site 

Landfall 

Date 

Tropical Storm Arlene Tropical Storm 6/10/2005 6/11/2005 6/11/2005 

Hurricane Cindy Tropical Storm 7/4/2005 7/5/2005 7/5/2005 

Hurricane Dennis Category 4 7/8/2005 7/10/2005 7/10/2005 

Hurricane Katrina Category 5 8/26/2005 8/28/2005 8/29/2005 

Hurricane Rita Category 5 9/20/2005 9/22/2005 9/24/2005 

Hurricane Wilma Category 3 10/21/2005 10/23/2005 10/24/2005 

 2-90 
Figure 2.6-11. Timing and paths of all six storm events that passed near the study area during the 

study period. 

 2-91 
3.0 LOOP CURRENT EVENTS AND HISTORICAL 

PERSPECTIVE 

3.1 Loop Current and Loop Current Eddies 

The Loop Current dominates the upper ocean circulation in the eastern deepwater basin of the 

GOM; therefore, no description of observations in the Eastern GOM study region is complete 

without accounting for the position and movement of the LC and its associated eddies. In this 

section, we describe the LC and LCE events impacting the study array during the program time 

period to put into perspective the results obtained from the measurement array. Remote sensing 

data were used to monitor oceanographic conditions in and around the array to achieve this 

perspective. The remote sensing data also allowed the measurement year to be placed into the 

context of "typical" conditions in the Eastern GOM. This could be achieved because continuous 

altimeter mapping of the sea surface height in the Gulf has been conducted since 1993 which 

provides this historical perspective. We used the available satellite altimeter time series to 

monitor the position of the LC and track individual LCEs over the 13.5-year altimeter record 

covering 1 January 1993 through 30 June 2006 and then compared those results with similar 

analyses made during the study time period from 1 January 2005 through 15 January 2006. 

3.1.1 LC and LCEs During the Study Period 

Sea surface temperature (SST) and ocean color images overlaid with sea surface height (SSH) 

contours provided synoptic views of the ocean surface thermal and color patterns associated with 

the altimeter-inferred circulation during the study program. These satellite images overlaid with 

altimetric SSH provided a basic overview of LC intrusion and LCE detachment and separation 

events during the study time period. 

LCE separation events were identified by the breaking of the 17-cm SSH contour that closely 

tracks the edge of the high-velocity core of the LC. This is an objective method for tracking the 

LC and detecting LCE separation events that gives separation periods comparable to those 

determined by subjective tracking methods (Leben 2005). The day that the tracking contour 

breaking occurs is identified as the “time” of eddy separation. Occasionally a detached eddy will 

reattach to the LC. In those cases, the time associated with the final detachment of the LCE from 

the LC is referred to as the eddy separation time. We selected an exact day of separation 

determined by the breaking of the tracking contour; however, estimated uncertainties in the 

separation period may be as great as one month. Although eddies may detach from and reattach 

to the LC during intrusion, the ultimate detachment or separation occurs most frequently at 

intervals of about 6, 9 and 11.5 months based on the available historical measurements (Leben 

2005). 

 3-1 
During the Eastern GOM program only a single large anticyclonic eddy, which was given the 

name “Vortex”, separated from the LC. LCE Vortex nominally separated from the LC on 13 

September 2005. Figure 3.1-1 shows an 8-day composite color image overlaid with SSH on 15 

September 2005 just days after eddy separation. Negative SSH contour levels are shown by 

dashed lines, positive by solid. The contour increment is 5 cm and the 17-cm LC tracking 

contour is shown by the thick, solid contour line. The extended intrusion of the LC into the 

northern GOM associated with LCE Vortex was one of the most northerly on record; it was only 

exceeded by the intrusion that generated LCE Sargassum during the Exploratory Study. This far 

northerly intrusion of the LC and LCE Vortex during late summer 2005 contributed to the 

intensification of Hurricanes Katrina and Rita (Walker et al. 2005). After the separation of LCE 

Vortex, the LC did not retreat substantially to the south. As a result the LC remained intruded 

into the eastern-central GOM during the rest of the program time period. Although the LC later 

reintruded into the north-central Gulf, it did not directly intrude into the study region again after 

the separation of LCE Vortex. The next two LCEs, Walker and Xtreme, separated on 6 Feb 2006 

and 7 Mar 2006, respectively, after the program instruments were retrieved in January 2006. 

Before ultimately separating from the LC in September 2005, LCE Vortex detached from and 

reattached to the LC a total of four times based on the 17-cm LC tracking contour depicted in the 

SSH maps. This was the largest number of detachment/reattachment events observed during a 

single LC intrusion cycle within the historical altimeter record. The first detachment was on 21 

February 2005 and occurred shortly after the reintrusion of the LC into the northern GOM six 

months after the separation of the preceding LCE, Ulysses, from the LC in August 2004. Since 

the detachment/reattachment event occurred during late winter and early spring, SST imagery 

provides good contrast for identifying the surface signature of the upper ocean circulation during 

the event, as is seen in the series of 3-day composite SST images overlaid with SSH shown in 

Figures 3.1-2 and 3.1-3. This sequence of images at 10-day intervals clearly shows the 

detachment and reattachment of the eddy from the LC in the surface thermal signature of the 

eddy and current over the time period. During this detachment/reattachment event, the 

anticyclonic eddy remained detached from the LC for 52 days based on the altimeter tracking. 

The reconnection of the detached anticyclonic eddy to the LC in early April is confirmed by the 

wrapping of warm LC waters around the periphery of the eddy in the sequence of images shown 

in Figure 3.1-3. Only one other LCE detachment and reattachment event observed in the 13.5-

year altimeter record exhibited a longer time period of detachment. That detachment event 

spanned 65 days and was associated with the LC intrusion that ultimately produced LCE Titanic 

in 2004, which was very well observed during the Exploratory Program (Donohue et al. 2006). 

 3-2 
Figure 3.1-1. Eight-day composite image of chlorophyll concentration overlaid with the SSH 

contour map from 15 September 2005 showing the recent separation of LCE 

Vortex from the LC. The 17-cm LC tracking contour is the thick contour line. 

Current vectors from the study moorings at 50 and 250 m depth are also shown. 

 3-3 
Figure 3.1-2. Three-day composite SST images overlaid with SSH contour maps showing the 

detachment of LCE Vortex from the LC in late February 2005. The interval 

between images is 10 days. The 17-cm LC tracking contour is shown by the thick 

line. Current vectors from the study moorings at 50 and 250 m depth are also 

shown. 

 3-4 
Figure 3.1-3. Three-day composite SST images overlaid with SSH contour maps showing the 

reattachment of LCE Vortex to the LC in early April 2005. The interval between 

images is about 10 days. The 17-cm LC tracking contour is shown by the thick 

line. Current vectors from the study moorings at 50 and 250 m depth are also 

shown. 

 3-5 
After this initial detachment and reattachment, LCE Vortex detached and reattached three more 

times before ultimately separating from the LC in September. These detachment events were of 

shorter duration, lasting only one to three weeks. Satellite images with overlaid SSH 

corresponding to the detachment and reattachment times for each of the four events are shown in 

Figures 3.1-4 and 3.1-5. In all four detachment/reattachment events the LC was well intruded 

into the northern deepwater basin as eddy detachment occurred. As a result, in three of the four 

cases (#1, #2 and #3) the LC intruded directly into the study area. In the one case where intrusion 

did not occur (#4), the LC was positioned too far to the west of the study region to directly 

impact the observation array. Thus, the direct intrusions of the LC into the study region were 

confined to the time period before August 2005. Energetic events observed in the remainder of 

the observational record were associated with circulation peripheral to the LC, which in most 

cases was cyclonic. 

The dates of all four Vortex detachment/reattachment events and their durations are listed in 

Table 3.1-1. Note that these dates were determined using the 17-cm LC tracking contour and the 

algorithm described in section 3.1.2 of this report. Because of the actual SSH contouring and 

masking algorithm applied in the MATLAB code used for automatic tracking, there are small 

differences in the configuration of the LC when SSH contours are plotted using the Generic 

Mapping Toolbox (GMT) contouring routine that was used to plot the figures shown. Dates 

nearest the MATLAB-determined dates were selected so that the plotted contours show a 

detached or attached eddy consistent with the automatic tracking results. In most cases, the GMT 

contouring causes differences of one day for the dates of detachment and reattachment when 

compared with the automated tracking results; the largest difference was only two days. 

Table 3.1-1 

LCE Vortex Detachment and Reattachment Events. 

LCE Vortex detachment and reattachment events that occurred during the EGOM Study 

Program. 

Event Detachment 

Date 

Reattachment 

Date 

Duration 

(days) 

Confirmation 

#1 20 Feb 2005 12 Apr 2005 51 SST 

#2 13 May 2005 20 May 2005 7 Not Confirmed 

#3 15 Jun 2005 29 Jun 2005 14 Color/LSU Mooring 

#4 01 Aug 2005 20 Aug 2005 19 Color 

 3-6 
Figure 3.1-4. Three-day composite SST images overlaid with SSH contours showing LCE 

Vortex detachment (upper panels) and reattachment (lower panels) for events #1 

and #2. The 17-cm LC tracking contour is shown by the thick contour line. 

Current vectors from the study moorings at 50 and 250 m depth are also shown. 

 3-7 
Figure 3.1-5. Eight-day composite chlorophyll concentration images overlaid with SSH 

contours showing LCE Vortex detachment (upper panels) and reattachment 

(lower panels) for events #3 and #4. The 17-cm LC tracking contour is shown by 

the thick contour line. Current vectors from the study moorings at 50 and 250 m 

depth are also shown. 

 3-8 
Confirmation of the detachment of the eddy from the LC in the surface circulation was possible 

for three of the four eddy detachment events. SST and color images overlaid with SSH (Figure 

3.1-6) show disconnection of the surface eddy signature from the LC in detachment events #1, 

#3, and #4. Further confirmation was found for detachment event #3 from the LSU mooring, 

which measured strong counter-current flow between the eddy and the LC at both 50 and 250-

meter depths as shown in Figure 3.1-6. Only event #2 showed no clear evidence of the 

detachment of the eddy in the surface thermal or color patterns resolved in the SST or color 

images. Ancillary data including drifters were checked, but no clear evidence of detachment was 

found. Some displacement of closed eddy SSH contours relative to the LC was observed, which 

might be evidence of increasing disconnection between the eddy and the LC at depth, 

nevertheless, the displacement was apparently insufficient to completely detach the eddy. 

The extended LC intrusion associated with the repeated detachment and reattachment of LCE 

Vortex before ultimate separation in September 2005 significantly impacted the study region 

upper ocean circulation during the first half of the eastern GOM program. Once LCE Vortex 

separated, the character of the circulation returned to conditions more typical of this northern 

location in the eastern deepwater GOM basin. This historical perspective is discussed in more 

detail in section 3.1.3 where the entire 13.5-year altimetry record of LC and LCE activity is 

presented. 

3.1.2 Loop Current Metrics and Statistics 

In addition to the objective identification of LCE separation, the objective tracking of the LC 

using the 17-cm SSH contour also allows detailed monitoring of LC metrics such as extent, 

boundary length, enclosed area, volume, and circulation. Previous studies (Hamilton et al. 2000; 

Leben et al. 2002; Leben 2005), developed and validated this objective tracking technique 

through qualitative and quantitative comparisons with satellite imagery and by direct 

comparisons with published subjective tracking results. 

The altimeter dataset and objective tracking technique used to estimate the altimeter-derived LC 

metrics is described in detail in Leben (2005). The dataset used in this study is similar to that 

used for the revised estimates of the frequency of LCE shedding events published in Sturges and 

Leben (2000) with two notable improvements. First, we reprocessed the historical altimeter data 

using a new mean surface as described in Leben et al. (2002). Second, we incorporated altimeter 

data from the Envisat, Geosat Follow-On, Jason-1, and TOPEX/POSEIDON (TOP/POS) tandem 

missions to improve sampling during the time periods when those data are available. 

The procedure for computing the metrics from the SSH fields has been automated by a 

MATLAB® program that accesses the GOM altimeter data archive and computes the values. 

Daily values for each metric were computed using the following algorithm: 

1. Load the 0.25° gridded SSH field and generate the coordinates of the 17-cm 

contours within the Gulf. 

2. Identify the Loop Current core, which is defined as the continuous 17-cm 

contour that enters the Gulf through the Yucatan Channel and exits through 

the Florida Straits. 

 3-9 
Figure 3.1-6. SST and chlorophyll concentration images overlaid with SSH showing the four 

LCE detachment events identified in the altimeter record. Three of the four 

detachments were confirmed by the coincident imager, only the second event (#2) 

was not. Current vectors from the study moorings at 50 and 250 m depth are also 

shown. 

 3-10 
3. Find the maximum west longitude and north latitude coordinates to determine 

the extent of westward and northward penetration of the Loop Current. 

4. Compute the length of the Loop Current by summing the distances between 

the coordinates on the 17-cm contour. 

5. Identify all 0.25° grid cells bounded by the 17-cm contour and compute the 

total Loop Current area by summing the areas of the individual cells. 

6. Estimate the Loop Current volume, assuming a one and a half-layer ocean and 

a reduced gravity approximation, by evaluating the following area integral 

over the region bounded by the 17-cm contour: 

g

g' ∫∫ hdxdy

, (3.1.1) 

where h is the sea surface height; g is the acceleration of gravity; and g' the 

reduced gravity. (A value of 0.03 m s-2 was used for g'.) 

7. Estimate the Loop Current circulation by the line integral of the geostrophic 

velocity along the 17-cm contour: 

∫ V ⋅ ds = ∫ udx + ∫ vdy,

 (3.1.2) 

where u and v are the geostrophic velocity components and dx and dy are the 

coordinate spacing in the east/west and north/south directions, respectively. 

The geostrophic velocity components at the midpoint locations are found by 

bilinear interpolation from the gridded geostrophic velocity components 

computed from the height field. (The sign convention employed here is such 

that the anticyclonic vorticity associated with the Loop Current is positive and 

therefore in positive correlation to the other metrics.) 

The 13.5-year time series of LC maximum latitude/longitude extension and length are shown in 

Figure 3.1-7 and area, volume, and circulation in Figure 3.1-8 with the time period spanning the 

Exploratory Study program highlighted in black. Separate time series plots of the respective 

metrics during the program time period (1 January 2005 through 15 January 2006) are shown in 

Figures 3.1-9 and 3.1-10. Histograms of each metric are shown in the lower panels of each of the 

figures. 

Histograms from the program record were overlaid on the histograms from the historical record 

(Figure 3.1-11) to allow direct comparison of the distribution of the LC metrics during the 

program and historical time periods. In general, the distributions were quite different, which was 

expected given the relatively short time period of the observational program and the energetic 

LC events that occurred therein. The mean LC values were also significantly different for the 

two time periods (Table 3.1-2). This was a result of the extended time period of LC intrusion 

associated with the repeated detachments and separation of LCE Vortex as well as the modest 

retreat and subsequent reintrusion of the LC after LCE Vortex separation. 

 3-11 
3.1.3 Loop Current Eddy Metrics and Statistics 

The primary goal of the objective LC tracking technique is to monitor the time-dependent 

behavior of the LC and its associated anticyclonic LCEs. As discussed previously, we identified 

the timing of LCE separation events using the LC length time series. The breaking of the 17-cm 

contour between the Loop and a detaching LCE into separate contours causes a discrete change 

in the LC length that is equal to the circumference of the separating eddy. The time associated 

with the final detachment of the eddy is referred to as the eddy separation time. The exact timing 

of a separation event is therefore dependent on the criteria selected to define separation and is 

complicated by the ambiguity of associating an exact time with what is clearly a continuous and 

complicated process. The tracking contour also impacts LC and LCE statistics, such as aerial 

extent, that are estimated using the tracking contour. Nevertheless, an objective definition of 

separation provides a useful benchmark for comparing LCE separation events that occurred 

during the study with those observed in the prior ten-year altimeter record. 

Table 3.1-2 

Altimeter-derived Summary Statistics. 

Summary statistics for altimeter-derived LC metrics computed from the historical and eastern 

GOM program records. 

Maximum 

West 

Longitude 

Maximum 

North 

Latitude 

Length 

(km) 

Area 

(km2) 

Volume 

(m3) 

Circulation 

(m2sec-1) 

 Historical Record: 1 January 1993 through 30 June 2006 

Mean 88.01°W 26.28°N 1400 149,331 2.27x1013 1,408,600

Std. Dev. 1.25° 0.94° 369 28,989 0.36x1013 329,500 

Maximum 93.07°W 28.10°N 2494 213,540 3.08x1013 2,311,200 

Minimum 85.80°W 24.10°N 614 55,840 0.85x1013 611,420 

 EGOM Program Record: 1 January 2005 through 15 January 2006 

Mean 89.20°W 26.92°N 1678 170,077 2.44x1013 1,555,410 

Std. Dev. 1.47°W 0.73° 346 21,398 0.23x1013 243,460 

Maximum 92.80°W 28.07°N 2418 207,391 2.91x1013 2,134,550 

Minimum 87.08°W 25.07°N 1017 124,488 1.86x1013 1,031,120 

 3-12 
Figure 3.1-7. Loop Current maximum northern/western extension and length time series with 

percent occurrence histograms. The horizontal red lines identify the 20 LC eddy 

separation events and vertical red lines are the mean of the time series. The study 

time period is highlighted. 

 3-13 
Figure 3.1-8. Loop Current area, volume, and circulation time series with percent occurrence 

histograms. The horizontal red lines identify the 20 LC eddy separation events 

and vertical red lines are the mean of the time series. The study time period is 

highlighted. 

 3-14 
Figure 3.1-9. Loop Current maximum northern/western extensions and length time series with 

percent occurrence histograms during the EGOM study. Horizontal magenta, 

cyan, and red lines identify LCE Vortex detachment, reattachment and separation 

events, respectively. The vertical red lines are the means of the time series. 

 3-15 
Figure 3.1-10. Loop Current area, volume, and circulation time series with percent occurrence 

histograms during the EGOM study. The horizontal magenta, cyan, and red lines 

identify LCE Vortex detachment, reattachment, and separation events, 

respectively. The vertical red lines are the means of the time series. 

 3-16 
Figure 3.1-11. Histograms of Loop Current metrics during the EGOM study (red bars) versus the 

historical time period (blue bars). The vertical green and red lines are the mean 

values from the program and historical time periods, respectively. See Table 3.1-1 

for tabulated values. 

 3-17 
Twenty LCE separation events were identified in the 13.5-year altimeter record, which includes 

the study time period. The LC length time series and SSH maps of each of these events at the 

time of separation are shown in Figure 3.1-12. The separation date, separation period, eddy 

name, and eddy area at the time of separation are tabulated for each of the 20 observed events in 

Table 3.1-3. Horizon Marine, Inc. (HMI) names the eddies in alphabetical order as anticyclones 

shed from the LC. A complete list is published on the web at 

http://horizonmarine.com/namedlces.html. The names appear in the weekly EddyWatchTM 

reports provided to the GOM offshore oil and gas industry by subscription from HMI. All 

separation events identified using the SSH 17-cm tracking contour were monitored by the 

EddyWatchTM program, although a number of smaller anticyclonic eddies (7 total) were also 

named, causing breaks in the alphabetical sequence. Only one marginal eddy separation event 

was identified by the objective tracking procedure (Eddy Odessa/Nansen, Eddy 12), which 

dissipated so quickly that an estimate of the eddy area could not be made. These smaller eddies 

are of LC origin, but formed on the outer edge of the LC through the interaction of frontal 

cyclones with the current. This type of small anticyclonic eddy was observed in the northeast 

GOM during the DeSoto Canyon Eddy Intrusion Study (Hamilton et al. 2000). Other small 

anticyclonic eddies may originate as primary LCEs split and/or form smaller anticyclonic eddies 

after separation. An example of this type of event is the unnamed anticyclonic eddy that split off 

from the southwest quadrant of Eddy Sargassum during the final detachment of Sargassum from 

the LC during the Exploratory Program (Donohue et al. 2006). 

Table 3.1-3 

Ring Separation Events from the Altimetric Record: 1 January 1993 through 30 June 2006. 

Eddy 

Number 

Separation 

Date 

Separation 

Period 

(months) 

Industry 

Eddy Name 

Area 

(km2) 

Eddy 

Maximum SSH 

(cm) 

1 11 Jul 1993 11.5 Whopper 24,183 33 

2 10 Sep 1993 2.0 Xtra 38,481 39 

3 27 Aug 1994 11.5 Yucatan 43,022 39 

4 18 Apr 1995 7.5 Zapp 21,337 36 

5 8 Sep 1995 4.5 Aggie 24,899 36 

6 14 Mar 1996 6 Biloxi 24,912 32 

7 13 Oct 1996 7 Creole 49,644 69 

8 30 Sep 1997 11.5 El Dorado 49,229 56 

9 22 Mar 1998 5.5 Fourchon 89,143 72 

10 2 Oct 1999 18.5 Juggernaut 40,325 39 

11 10 Apr 2001 18.5 Millennium 45,705 44 

12 22 Sep 2001 5.5 Odessa/Nansen ? 12 

13 28 Feb 2002 5.5 Pelagic 22,119 41 

14 13 Mar 2002 0.5 Quick 49,936 41 

15 5 Aug 2003 17 Sargassum 25,302 49 

16 31 Dec 2003 5 Titanic 33,278 43 

17 23 Aug 2004 8 Ulysses 68,633 42 

18 13 Sep 2005 12.5 Vortex 29,541 38 

19 6 Feb 2006 5 Walker 11,366 29 

20 7 Mar 2006 1 Xtreme 22,111 37 

 3-18 
Figure 3.1-12. LCE separation events identified in the altimeter record. SSH maps on the 

separation dates are shown in the panels to the right (values above 40 cm and 

below-30 cm have been clipped). The LC length time series is overlaid with red 

lines corresponding to the separation dates. 

 3-19 
3.1.4 Loop Current Frontal Eddies and Other Cyclonic Eddies 

Cyclonic perturbations and eddies are common along the outer edge of the LC. Several 

observational studies have noted that these peripheral features, including LC frontal eddies 

(Vukovich and Maul 1985), Tortugas eddies (Lee et al. 1995; Fratantoni et al. 1998) and 

Campeche Bank eddies (Zavala-Hidalgo et al. 2003), are often associated with eddy separation 

events and are therefore thought to play a role in the detachment and/or separation of LCEs. 

The combination of SSH maps and SST imagery has proven to be useful for detecting and 

tracking cyclonic features. This was demonstrated during the Desoto Canyon Eddy Intrusion 

Study when 12 LC frontal eddies were detected and tracked, 11 of which influenced the study 

region (Hamilton et al. 2000). In general, SST images are more useful for tracking LC frontal 

eddies because synoptic sampling is often required to map the rapid evolution of the features as 

they propagate around the LC at translation velocities of up to 25 km day-1. Ocean color imagery 

is also useful for detecting and tracking cyclones because of the higher chlorophyll 

concentrations typically associated with upwelling within the eddy. 

Continuous monitoring using SST or color radiometry imagery is not possible because of the 

frequent clouds over the GOM and the seasonal degradation of the surface thermal and biological 

signals. Even under good observing conditions, the surface temperature or color signature of an 

eddy in imagery can be difficult to interpret because the surface cyclonic circulation associated 

with a cyclonic eddy may advect filaments of warm chlorophyll-poor waters that mask the cold 

nutrient–rich conditions typical of cyclones. The cyclonic spiral of a warm filament within the 

eddy frequently identifies the presence of a cyclone. On the other hand, satellite altimetry can 

unambiguously detect cyclones by their lower SSH; however, the relatively small size of the 

eddies and their often rapid evolution can make detecting and tracking of these features difficult 

because of the non-synoptic sampling of the ocean surface by satellite-borne radar altimeters. 

Therefore, no systematic census of cyclones in the GOM, such as those performed for LCEs, has 

been attempted given the imaging and sampling limitations of the current operational satellite 

systems, although some topographically isolated features such as the Campeche Bank (ZavalaHidalgo et al. 2003) and Tortugas Eddies (Fratantoni et al. 1998) have been studied in detail. 

Systematic comparisons of the cyclones observed during the program with those in the historical 

record will not be attempted. Nevertheless, cyclones are an important dynamical component of 

the general circulation of the GOM and significantly impacted the study region during the 

eastern GOM program. They are also quite common along the boundary of the LC during 

intrusions into the north-central GOM as was the case during nearly the entire eastern GOM 

program time period. As an example, in Figure 3.1-13 we identify a number of cyclones in the 22 

April 2005 night time composite SST image from GOES-12 courtesy of Nan Walker of 

Louisiana State University. 

 3-20 
Figure 3.1-13. Nighttime composite SST image from 22 April 2005 showing the LC and its 

associated cyclonic features. The image is from the GOES-12 satellite and is 

courtesy of Nan Walker of Louisiana State University. 

 3-21 
3.2 Study Time Period in the Context of the Historical Record 

In this section, we give an overview of the eastern GOM program time period in the context of 

the 13.5-year altimeter record to gain a historical perspective on the LC and LCE activity in and 

around the study region. 

3.2.1 Loop Current 

The extended LC intrusion into the north-central GOM during the eastern GOM program, 

although not record-setting in terms of the maximum values of the LC metrics over the historical 

record (Table 3.1-2), was one of the most significant in terms of the overall extent of LC 

intrusion during the yearlong observational record. 

The extent of LC penetration into the north-central Gulf during the program record is clearly 

demonstrated using yearlong running averages of the daily LC metric time series. Histograms of 

the running-averaged metrics are shown in Figure 3.2-1, overlaid with the yearlong mean values 

for 2005 representing the mean during the eastern GOM observational record. The total time 

where the yearlong running average values were greater than the mean over the observational 

record was quoted as a percent of the total occurrence for each of the metrics. The percentage 

occurrence exceeding the program record time period values range from 15.3% for LC 

circulation to only 4.2% for LC area, highlighting the remarkable extent of the LC intrusion over 

the yearlong eastern GOM program. In fact, the eastern GOM program yearlong averages of LC 

area and latitude of northern extent were not exceeded throughout the entire prior altimeter 

record. Average length and longitude were only exceeded briefly during a yearlong time period 

associated with the LC intrusion that formed LCE Millennium, the most westward intrusion on 

record. The remaining LC statistics, circulation and volume, were only exceeded during yearlong 

time periods immediately preceding the separation of LCEs Juggernaut, Millennium, and 

Sargassum. 

Another way to characterize the extent of the LC intrusion during the eastern GOM program is 

by using the 13.5-year altimeter record in concert with automated LC tracking. Dates were 

identified in the historical record when altimeter-derived SSH values were greater than 17 cm at 

any of the eastern GOM PIES station locations. These events were categorized as a LC intrusion, 

a separated LCE, a detached LCE, or an anticyclonic eddy based on the configuration of the 17-

cm LC and LCE tracking contour. A summary of these events is listed in Table 3.2-1. 

Remarkably, only one event of the 12 observed in the study region over the altimeter record was 

not directly related to the LC or a LCE. That singular event was a compact energetic anticyclonic 

eddy that formed in the northeastern corner of the Gulf and propagated through the study region 

in late July 1998. The remaining 11 intrusion events included 3 LC intrusions, 3 separated LCEs, 

and 5 mixed LC intrusions and LCE detachment/separation events. In summary, a total of 302 

days occurred with SSH greater than 17 cm at the eastern GOM PIES station locations. LC or 

LCE intrusions were associated with a total of 296 days, which was approximately 6% of the 

4929-day historical record, or an average of about 22 days per year where a LC or LCE was 

present in the array. This is less than half of the 52 days total in 2005 where the LC or a LCE 

intruded into the PIES array during the eastern GOM study program. Only one other calendar 

year had a greater occurrence of intrusion, which was 91 days in 2003 associated with LCE 

Sargassum during the Exploratory Study program. 

 3-22 
Table 3.2-1 

Intrusion Events. 

Dates that the 17-cm SSH tracking contour intruded into eastern GOM study region based on the 

1 January 1993 through 30 June 2006 altimetry record. Events are categorized as a LC intrusion, 

a separated LCE, a detached LCE, or an anticyclonic eddy based on the configuration of the 17-

cm LC and LCE tracking contour. 

Start Date End Date Duration Event Type Name 

10 May 1993 19 May 1993 10 days LC Intrusion Whopper 

14 Sep 1993 26 Sep 1993 13 days Separated LC Eddy Xtra 

29 Aug 1994 4 Sep 1994 6 days Separated LC Eddy Yucatan 

24 Feb 1995 14 Apr 1995 50 days LC Intrusion/ 

Detached LC Eddy/ 

LC Intrusion 

Zapp 

27 Jul 1998 1 Aug 1998 6 days Anticyclonic Eddy 

18 Aug 1999 9 Sep 1999 23 days LC Intrusion Juggernaut 

16 Oct 1999 4 Nov 1999 20 days Separated LC Eddy Juggernaut 

6 May 2003 4 Aug 2003 91 days LC Intrusion/ 

Detached LC Eddy/ 

LC Intrusion 

Sargassum 

22 Aug 2004 13 Sep 2004 23 days LC Intrusion/ 

Separated LC Eddy 

Ulysses 

14 Feb 2005 14 Mar 2005 29 days LC Intrusion/ 

Detached LC Eddy 

Vortex 

3 Jun 2005 25 Jun 2005 23 days LC Intrusion/ 

Detached LC Eddy 

Vortex 

23 Jun 2006 30 Jun 2006 8 days LC Intrusion Yankee 

3.2.2 Loop Current Eddies 

The altimeter-derived statistics provided a useful 13.5-year benchmark to compare the LCEs that 

occurred during the eastern GOM program to those of the historical record. An even longer time 

period can be addressed with LCE separation periods estimated using SST imagery available 

since 1973 (Vukovich 1988). The combined 33-year compilation of LCE separation periods from 

July 1973 through June 2006 is listed in Table 3.2-2. A total of 43 continuous events have been 

observed. A histogram of the distribution is shown in the upper panel of Figure 3.2-2. The 20 

LCE separation events observed during the altimeter record are shown in red to highlight the 

contribution of the more recent events to the distribution of the entire observational record. The 

histograms of events before and after 1993 are shown in the middle and lower panels, 

respectively. The mean for the entire compilation of separation periods was 9.5 months and the 

mode was 6 months. Using only the pre-1993 record, the mean was 9.96, and the mode was 6 

and 9 months over a range from a minimum of 6 to a maximum of 15 months. For the 

distribution of separation periods since 1993, which were based on altimeter-derived separation 

periods, the mean was 8.2, and mode was 5.5 and 11.5 months over a range from a minimum of 

0.5 to a maximum of 18.5 months. The differences between the two measurement time periods 

were probably not significant; nevertheless, the change in the actual distribution was striking. 

This attests to the remarkable variability of the LCE separation period. 

 3-23 
Figure 3.2-1. Histograms of yearlong running averages of Loop Current metrics from the 

historical altimetry record. Mean values during the Eastern Gulf program (annual 

mean from 2005) are shown along with the percent of historical values exceeding 

the program mean. 

 3-24 
Zoomed maps of the SSH fields at the time of separation, including the maximum SSH values 

within the eddy and the 17-cm tracking contour (Figures 3.2-3 a, b, & c) are shown for all of the 

20 LCEs observed in the altimeter record from 1 January 1993 through 30 June 2006. A 

composite of the tracking contours at the time of separation are shown in the upper panel of 

Figure 3.2-4. The three LCEs, Vortex, Xtreme, and Walker, that separated from the LC during or 

just after the eastern GOM program are highlighted in the bottom panel. These eddy separation 

locations show that the Vortex and Walker separation events were associated with some of the 

most western LC intrusions observed in the altimeter record, with only LCE Millennium 

separating farther to the west. Xtreme was also one of the more northern and western separation 

events relative to the historical distribution. In terms of eddy area and maximum SSH at the time 

of separation, these LCEs were some of the smaller area and weaker amplitude eddies observed 

in the altimeter record: LCE Vortex (#18) ranked 11th in eddy area and 13th in eddy maximum 

SSH, LCE Xtreme (#19) ranked 17th in eddy area and 14th in eddy maximum SSH, and LCE 

Walker (#20) ranked 19th in both eddy area and eddy maximum SSH. 

Table 3.2-2 

LCE Separation Periods. 

A compilation of the 33-year record of separation periods for LCEs from July 1973 through June 

2006 is tabulated below. A total of 43 consecutive events are listed. Entries through October 

1986 are from Vukovich (1988); other entries prior to July 1992 are from Table 1 of Sturges 

(1994) using corrections based on Berger (1993). The separation event in July 1992 is from 

Sturges and Leben (2000). Data beginning in 1993 are based on objective tracking of the Loop 

Current using satellite altimeter data (Leben 2005). 

Date Separation 

Period 

(months) 

Date Separation 

Period 

(months) 

Date Separation 

Period 

(months) 

July 1973 July 1985 11 13 Oct 1996 7 

April 1974 9 January 1986 6 30 Sep 1997 11.5 

January 1975 9 October 1986 9 22 Mar 1998 5.5 

July 1975 6 September 1987 11 2 Oct 1999 18.5 

August 1976 13 May 1988 8 10 Apr 2001 18.5 

March 1977 7 May-June 1989 12.5 22 Sep 2001 5.5 

June 1978 15 August 1990 14.5 28 Feb 2002 5 

April 1979 10 Aug- Sep 1991 12.5 13 Mar 2002 0.5 

January 1980 9 19 July 1992 11.5 5 Aug 2003 17 

March 1981 14 11 Jul 1993 11.5 31 Dec 2003 5 

November 1981 8 10 Sep 1993 2 23 Aug 2004 8 

May 1982 6 27 Aug 1994 11.5 13 Sep 2005 12.5 

March 1983 10 18 Apr 1995 7.5 6 Feb 2006 5 

February 1984 11 8 Sep 1995 4.5 7 Mar 2006 1 

August 1984 6 14 Mar 1996 6 

 3-25 
More important to the general circulation observed by the Eastern Gulf study array was the 

repeated detachment and reattachment of LCE Vortex during the observational record. 

Composites of the LCE tracking contour at detachment times and the LC tracking contour at 

reattachment times are shown in the upper and lower panels of Figure 3.2-5, respectively, along 

with mooring locations where subsurface currents were measured during the Eastern Gulf 

program including the LSU mooring. At the time of detachment, two of the four detached LCEs 

were located over the Eastern Gulf mooring locations based on the 17-cm tracking contour 

(upper panel of Figure 3.2-5). Given that the 17-cm tracking contour was offset from the surface 

thermal front by approximately 50 km (Leben 2005), each of these detachment events occurred 

with the LC/LCE surface circulation very near or over the moorings. Upon detachment from the 

LC, the eddies drifted westward due to the beta-effect and were found westward of the Eastern 

Gulf moorings when reattachment to the LC occurred (lower panel of Figure 3.2-5). In the 

historical record, time periods when a LCE detaches and reattaches to the LC are common even 

with the stringent definition of detachment based on the breaking of the 17-cm tracking contour. 

Eight of the 20 LCEs observed in the 13.5-year altimeter record detached and reattached before 

final separation (LCEs #1, 4, 7, 9, 11, 15, 16, and 18) including LCE Vortex (#18). No LCE, 

however, was observed to detach and reattach to the LC as frequently as LCE Vortex. 

 3-26 
Figure 3.2-2. Histogram of the LCE separation period using data from Table 3.2-2 are shown 

for selected time intervals. The 20 LCE separation events observed during the 

altimeter record are shown in red, the prior in gray. 

 3-27 
Figure 3.2-3a. Zoomed SSH maps of LCEs 1 through 8 at the time of separation from the LC. 

The17-cm tracking contour and maximum SSH are shown for each eddy. Plots 

are equal area. 

 3-28 
Figure 3.2-3b. Zoomed SSH maps of LCEs 9 through 16 at the time of separation from the LC. 

The 17-cm tracking contour and maximum SSH are shown for each eddy. Plots 

are equal area. Eddy #12 (Odessa/Nansen) dissipated rapidly and contained no 

tracking contour at the time of separation. 

 3-29 
Figure 3.2-3c. Zoomed SSH maps of LCEs 17 through 20 at the time of separation from the 

LC. The 17-cm tracking contour and maximum SSH are shown for each eddy. 

Plots are equal area. 

 3-30 
Figure 3.2-4. The 17-cm tracking contour at the time of separation for all 20 LCEs observed 

from1 January 1993 through 30 June 2006. The LCEs that separated during or just 

after the Eastern Gulf study are highlighted in the bottom panel. 

 3-31 
Figure 3.2-5. Composite of LCE Vortex detachment and reattachment events. The 17-cm LCE 

tracking contour at detachment and the 17-cm LC tracking contour at 

reattachment times are shown in the upper and lower panels, respectively. 

 3-32 
4.0 LC AND LCE DYNAMICS 

Two complementary approaches, one kinematic and one dynamic, were used to analyze LC and 

LCE dynamics and their affect upon the upper ocean circulation in the eastern GOM study array 

during the study time period. The kinematic analysis was performed using satellite-tracked 

drifter trajectories in combination with satellite altimetry to derive the kinematic properties of the 

dominant anticyclonic and cyclonic circulation events in the study region. The drifting buoy data 

used to perform this analysis were obtained from Horizon Marine, Inc. The dynamical analysis 

was performed based on vorticity calculated from the PIES array. 

4.1 Kinematic Analysis 

4.1.1 Drifting Buoy Data and Analysis Approach 

Horizon Marine deployed over 200 drifting buoys during 2005 that tracked near surface currents 

in the GOM. The buoys had drogues at 50 m depth. Most of the buoys had relatively short lives 

or did not enter interesting features; however, the buoys that did orbit within cyclonic or 

anticyclonic eddies can be used to model and track individual eddies using the kinematics of the 

observed drifting buoy trajectories and a simplified feature model. 

The feature model describes eddies as a translating and rotating ellipse. The model equations for 

the components of the position of the buoy x and y are 

 0 x(t) = x + ut + acosθ cos(−ωt + φ) − bsinθ sin(−ωt + φ)

y(t) = y + vt + asin

, (4.1.1) 

 0 θ cos(−ωt + φ) + bcosθ sin(−ωt + φ), (4.1.2) 

where u and v are the components of the center propagation velocity, xo and yo are the position of 

the center at time t = 0, a and b are semi-axis lengths of the ellipse, ω is the angular frequency of 

rotation of the buoy around the ellipse, θ is the angle between the x-axis and the a-axis of the 

ellipse, and φ is a phase angle. Note that the x-axis is toward the east and θ is measured counterclockwise from east. Thus, θ = 90° means that the long axis is oriented north to south. The 

parameters of this model were found using least squares fits to the observed positions as 

described by Glenn et al. (1990). Data from slightly more than one orbit of the center were used 

to give stable solutions to the least squares fit. The fits were made at one-day intervals and the 

resulting parameters were plotted at the center time of the data used in each fit. 

Elliptical fits were found for Eddy Ulysses (Figures E-1 – E-5), Eddy Vortex, Eddy Walker, four 

small cyclonic eddies, and a brief period of closed circulation in the Loop Current. Graphs of the 

fit parameters for all of the features are included in Appendix E. The following sections present 

kinematic information for Eddy Vortex and two small cyclonic eddies, Cold Eddy 3 and 4, that 

impacted the study area. Graphs referred to in the summaries are included in Appendix E. 

 4-1 
4.1.2 Eddy Vortex 

The graphs for Eddy Vortex, shown in Appendix E, are broken into two sections. Figures E-6–E10 describe the eddy from the end of February through the middle of April. Figures E-11–E-15 

show its evolution from June through November. From April through June, the eddy reattached 

to the LC and there were no closed buoy orbits. During March, Eddy Vortex moved to the 

northwest. In the process, it got unusually close to the Mississippi Delta. At the end of April, the 

center of circulation moved back to the southeast as the eddy re-attached to the LC. The orbital 

period when the eddy was detached from the LC in March was rather low, only about 7 days. 

During that period, it was fairly elongated with an eccentricity of about 0.6. The long axis of the 

ellipse rotated clockwise at about 4° per day. The sense and speed of the rotation are as predicted 

for an isolated eddy by Cushman-Roisin et al. (1985). 

After Eddy Vortex’s separation in June, there are some gaps in the record because the eddy 

reattached to the LC several times, but the center of circulation moved steadily to the southwest. 

The various buoys gave very similar center positions. From June through August (Yeardays 160–

240, 9 Jun through 28 Aug 2005) the orbital period was long for a fresh eddy, but during this 

time the eddy was rather large. The orientation of the ellipse changed rapidly during June and the 

early part of July (Yeardays 160 – 200, 9 Jun through 19 Jul 2005) but after that the regular 

clockwise rotation set in. Finally, buoy 1669 made a closed orbit in the middle of the Loop 

Current during the last half of September 2005 after Eddy Vortex separated. At first the center of 

circulation moved to the northwest, but then it moved to the northeast as the Loop Current leaned 

to the east. The change of the orientation of the ellipse from north-northwest to north was 

consistent with this lean. The period of rotation lowers as the orbit becomes more circular. 

4.1.3 Cyclones 

Several of the drifting buoys became trapped in small cyclonic (cold) eddies in and around the 

study array. The first cold eddy identified in the drifter data near the study region, Cold Eddy 3, 

was a persistent feature in drifter trajectories from the first of August through the middle of 

September. The eddy was located on the northeast edge of Eddy Vortex during the last 

detachment event and as Vortex was separating from the LC. The cyclone moved with Vortex as 

Vortex separated from the LC and moved to the west. There was a gap in the solution from 

Yeardays 238 – 248 (26 Aug through 5 Sep 2005), but the cyclonic circulation during the two 

time periods was apparently the same feature. The feature was small and its orbital period low 

until late in the record when the buoy moved out to a larger orbit. 

Cold Eddy 4 was the final cold eddy that had closed buoy orbits. It was directly north of Eddy 

Walker as it began to separate from the LC in December 2005. This feature moved north as the 

LC extended and east as its meander propagated clockwise around the northern edge of what 

would become Eddy Walker. It was a small feature with an orbital period of only 4 days. 

 4-2 
4.1.4 Combined Kinematic and Altimetric Analysis 

A significant shortcoming of a kinematic feature model using only drifting buoy trajectories is 

that the area of eddy circulation is not uniquely determined by the trajectories of the drifters 

within the eddy. Differing estimates of eddy aerial extent or radius are obtained depending on the 

distance that a drifting buoy orbits relative to the eddy center. In view of this deficiency, a 

combined kinematic and altimetric analysis technique was developed to estimate eddy aerial 

extent to better determine the movement and extent of large closed anticyclonic circulation in 

and around the study region. The combined analysis used the eddy aerial extent estimated from 

daily altimeter-derived SSH maps to resize the elliptical eddy model parameters to equal area. 

After rescaling, the parameters estimated from each of the fit trajectories within the eddy were 

averaged to obtain a composite estimate of the size, shape, and orientation of the eddy for each 

day. 

The altimeter-derived area was determined using an eddy-tracking program that automatically 

tracks SSH contours within an eddy. Once the eddy of interest was identified, the maximum 

height within that eddy was found along with all positive contours encircling the maximum. The 

area enclosed by each contour was calculated and a corresponding circular region was generated 

of equal area. The percentage of each contour that fits inside the corresponding circular area gave 

a measure of the circularity of the closed circulation. This percentage typically increased rapidly 

when the contour value increased to the level where secondary extrema, which were not part of 

the eddy, were no longer captured within the contour. This rapid change in percent of circularity 

was used to objectively identify the tracking contour to compute eddy area. When the maximum 

height in the eddy was at or above 30 cm, the automatic tracking contour level tended towards 17 

cm, the level used for LC tracking (Leben 2005). When the maximum height dropped below 30 

cm, the tracking contour tended toward values about half of the maximum height. This adaptive 

tracking was preferable to using a fixed tracking contour for calculating the area, especially as 

closed eddy circulation developed and decayed. 

Figures 4.1-1 – 4.1-4 show 8-day composite ocean color images overlaid with SSH at 3-day 

intervals from 9 July 2005 through 23 Aug 2005. On each of the images, the rescaled ellipses 

and eddy centers determined from eddy tracking are plotted as red, green, and white dashed 

ellipses and crosses, respectively, to show the locations 3 days before (red), 3 days after (green), 

and on the analysis date (white). The 200 and 2000 meter isobaths are also shown. During this 

time period, Eddy Vortex was located in the north-central GOM to the west-southwest of the 

study area and was still attached to the LC. Tracking of the eddy centers showed that there was 

little movement of Eddy Vortex during July; however, the eddy underwent signification 

deformation, becoming elongated along a southeast to northwest oriented major axis. This 

elongation brought the northwest flank of the eddy onto the continental slope, which induced a 

cross-slope flow that showed up well in the ocean color imagery as a stream of high chlorophyll 

concentration water flowing along the northeast flank of the eddy. In early August, the eddy 

became more circular and moved to the west-southwest, detaching from the LC. The detached 

eddy elongated along a southwest to northeast oriented major axis, once again interacting with 

the continental slope. This produced a cyclonic eddy along the northeast flank of Vortex that was 

well sampled by the Horizon Marine drifters and identified above as Cold Eddy 3. The detached 

and elongated Eddy Vortex rotated clockwise and subsequently reattached to the LC after which 

kinematic tracking was no longer possible. 

 4-3 
Figure 4.1-1. Ocean color images overlaid with SSH at 3-day intervals 

from July 9-18, 2005. Rescaled ellipses and eddy centers 

are plotted as red, green, and white dashed ellipses and 

crosses, respectively to show the eddy locations 3 days 

before (red), 3 days after (green), and on the analysis date 

(white). 

 4-4 
Figure 4.1-2. Ocean color images overlaid with SSH at 3-day intervals 

from July 21-30, 2005. Rescaled ellipses and eddy 

centers are plotted as red, green, and white dashed 

ellipses and crosses, respectively, to show the eddy 

locations 3 days before (red), 3 days after (green), and on 

the analysis date (white). 

 4-5 
Figure 4.1-3. Ocean color images overlaid with SSH at 3-day intervals 

from August 2-11, 2005. Rescaled ellipses and eddy 

centers are plotted as red, green, and white dashed 

ellipses and crosses, respectively, to show the eddy 

locations 3 days before (red), 3days after (green), and on 

the analysis date (white). 

 4-6 
Figure 4.1-4. Ocean color images overlaid with SSH at 3-day intervals 

from August 14-23, 2005. Rescaled ellipses and eddy 

centers are plotted as red, green, and white dashed 

ellipses and crosses, respectively, to show the eddy 

locations 3 days before (red), 3days after (green), and on 

the analysis date (white). 

 4-7 
4.2 Dynamic Analysis 

The dynamic analysis is based on relative vorticity calculated from the sea surface height 

estimates made using measurements from the PIES array. This analysis was used to objectively 

identify the dominant anticyclonic and cyclonic events sampled by the PIES array during the 

observational record. 

4.2.1 Mapped Surface Circulation and Sea Surface Height from PIES 

Time-averaged mapped surface currents and sea surface height determined from the PIES are 

shown in Figure 4.2-1. During the year-long observational period, the mean surface current was 

mainly to the east in the southern half of the array with mean speeds typically less than 25 cm s-1. 

Currents in and above the thermocline tended to exhibit an "equivalent barotropic" structure, in 

which the currents decrease their speed with increasing depth but remain aligned in the same 

direction. The currents were observed to turn markedly with depth when subthermocline currents 

were strong, these events are discussed further in Chapters 6 and 7. Time-average currents were 

dominated by a few strong events; mean maps should not be interpreted as representative of the 

long-term mean. This point is emphasized by the comparison between the mean-surface 

circulation calculated over different time periods with nearly the same length. The mean from the 

first six months (January 27, 2005 to July 4, 2005; left panel of Figure 4.2-1) reveals southeast 

flow that results from the presence of Eddy Vortex within the southwestern portion of the array; 

the mean from the last six months (July 4, 2005 to January 19, 2006; right panel of Figure 4.2-1) 

has comparatively weaker currents and the mean cyclonic flow pattern results from several 

frontal cyclones. 

The structure of the array-mean current can be clarified by looking at the major events. First, we 

determined current variability as expressed by mean eddy kinetic energy, 

 EKE = (1/2)<(u’)2

 + (v’)2>, (4.2.1) 

where < > was the one-year mean. Figure 4.2-2 shows surface EKE superimposed on the mean 

surface current. The highest EKE values occurred in the middle of the array, slightly offset to the 

west. Current variance ellipses are also shown. The time history of the spatially-averaged EKE 

revealed four episodes of high EKE lasting 15-30 days, indicative of an event-dominated time 

series. The first three events occurred during an Eddy Vortex detachment and reattachment and 

more specifically when Eddy Vortex intruded into the array. After mid-July 2005, Eddy Vortex 

and the LC remained south of the array, the fourth event described here was a strong frontal 

cyclone. In order to capture these events, we mapped surface circulation at 4-day intervals over a 

12-day period for each event (Figures 4.2-3 to 4.2-6, upper panels). In addition, we calculated 

surface relative vorticity (ζ=∂v/∂x-∂u/∂y) divided by the Coriolis parameter (Figures 4.2-3 to 4.2-

6, lower panels). Note that we mapped relative vorticity with optimal interpolation with a 50 km 

Gaussian correlation function. 

 4-8 
These four events share the following characteristics: surface speeds in excess of 100 cm s-1 and 

absolute relative vorticity values that often exceed 0.4. A gradient-wind, rather than a 

geostrophic balance, may be a more appropriate balance in this region. Geostrophic wind 

overestimates (underestimates) velocity in strong cyclonic (anticyclonic) regimes by a factor on 

the order of the Rossby number (ζ/f). Here our calculation of relative vorticity did not distinguish 

between curvature and relative vorticity due to the limited spatial extent of the array. Figures 4.2-

3 through 4.2-5 show the surface circulation during the major intrusions of the LC or LCE into 

the array. In these cases the PIES array was only influenced by the periphery of the LC/LCE. 

The following cases were noted: 

16 through 28 February 2005, Eddy Vortex detachment #1: The LC extended northward and 

turned clockwise as Eddy Vortex formed and detached on February 21. We note the rapid change 

in ζ/f in the array center which changed from -0.4 to 0.7 in 4 days from February 24 to February 

28. In addition, ζ/f spanned a range of 0.8, with values near 0.4 at PIES05 and values near -0.4 at 

PIES03. Mapped circulation for this day suggests that curvature dominated shear vorticity. 

22 through 31 May 2005, Eddy Vortex reattachment #2: On May 21, Eddy Vortex reattached to 

the LC for a second time. Mapped currents reached peak values near 150 cm s-1, and ζ/f values 

along the cyclonic side of the LC were near -0.8. 

15 through 27 June 2005, Eddy Vortex detachment #3: A lobe of Eddy Vortex extended into the 

array and then retreated southward. Although Eddy Vortex extended furthest into the array 

during this time, vorticity values were weak compared to the other ‘big’ events. 

12 through 24 December, Cyclone #2: Strong cyclonic vorticity associated with the frontal 

cyclone reached ζ/f values near 0.5, not quite as high as those associated with LC or LCE shears. 

The PIES array captured the mesoscale frontal meanders along the periphery of the Loop 

Current. The array, while well resolved, provided a limited window. 

 4-9 
Figure 4.2-1. Top Panel: Time-average mean sea surface height (contours) and currents (black 

vectors) at the surface. Averaging period is from 27 January 2005 to 19 January 

2006. Sea surface height is contoured every 2 cm with low (high) values shown 

with blue (red) hues. Current vectors plotted at 10-km spacing. PIES sites 

indicated by diamonds, current meters denoted by circles. Vector key is shown in 

lower left corner. Bathymetry contoured every 500 m depth with gray lines. 

Bottom Panels: Same as top panel except for the averaging period. Right Bottom 

Panel: 27 January 2005 to 4 July 2005. Right bottom panel: 4 July 2005 to 19 

January 2005. 

 4-10 
Figure 4.2-2. Upper panel: Mean surface eddy kinetic energy averaged between 27 January to 

19 January 2006 contoured every 200 cm2

s

-2. Bathymetry contoured every 500 m 

depth with gray lines. PIES sites indicated by diamonds, current meters denoted 

by circles. Bottom panel: Array-average mean surface eddy kinetic energy. The 

four strongest events are highlighted by the red line along the x-axis and labeled 

consistently with the EGOM Upper Ocean Events Timeline. 

 4-11 
Figure 4.2-3. 16 February 2005 to 28 February 2005. Upper panels: Sea 

surface height (contours) and currents (black vectors) at the 

surface. Map date is stated in each panels’ title. Sea surface 

height is contoured every 2.0 cm with low (high) values shown 

with blue (red) hues. Current vectors plotted at 10-km spacing. 

Vector key is shown in lower left corner Bottom panels: relative 

vorticity scaled by local Coriolis parameter. Low (high) values 

shown with magenta (green) hues. In all panels PIES sites 

indicated by diamonds, current meters denoted by circles and 

bathymetry contoured every 500 m depth with gray lines. 

 4-12 
Figure 4.2-4. 19 May 2005 to 31 May 2005. Upper panels: Sea surface height 

(contours) and currents (black vectors) at the surface. Map date is 

stated in each panels’ title. Sea surface height is contoured every 

2.0 cm with low (high) values shown with blue (red) hues. 

Current vectors plotted at 10-km spacing. Vector key is shown in 

lower left corner Bottom panels: relative vorticity scaled by local 

Coriolis parameter. Low (high) values shown with magenta 

(green) hues. In all panels PIES sites indicated by diamonds, 

current meters denoted by circles and bathymetry contoured 

every 500 m depth with gray lines. 

 4-13 
Figure 4.2-5. 15 June 2005 to 27 June 2005. Upper panels: Sea surface height 

(contours) and currents (black vectors) at the surface. Map date is 

stated in each panels’ title. Sea surface height is contoured every 

2.0 cm with low (high) values shown with blue (red) hues. 

Current vectors plotted at 10-km spacing. Vector key is shown in 

lower left corner Bottom panels: relative vorticity scaled by local 

Coriolis parameter. Low (high) values shown with magenta 

(green) hues. In all panels PIES sites indicated by diamonds, 

current meters denoted by circles and bathymetry contoured 

every 500 m depth with gray lines. 

 4-14 
Figure 4.2-6. 12 December 2005 to 24 December 2005. Upper panels: Sea 

surface height (contours) and currents (black vectors) at the 

surface. Map date is stated in each panels’ title. Sea surface 

height is contoured every 2.0 cm with low (high) values shown 

with blue (red) hues. Current vectors plotted at 10-km spacing. 

Vector key is shown in lower left corner Bottom panels: relative 

vorticity scaled by local Coriolis parameter. Low (high) values 

shown with magenta (green) hues. In all panels PIES sites 

indicated by diamonds, current meters denoted by circles and 

bathymetry contoured every 500 m depth with gray lines. 

 4-15 
4.2.2 Relative Vorticity Calculated from the PIES 

The relative vorticity was calculated from the PIES sea surface height time series by assuming 

geostrophy and using Stokes’ theorem. The velocity and the vorticity are related through Stokes’ 

theorem: 

 

v ⋅ dx r 

C

∫ = ∇× r

v ⋅ n ⋅ da

A

∫ = r

ω ⋅ n ⋅ da.

A

∫ (4.2.2) 

Assuming that the vorticity and area were constant over the region of interest, the above 

equations simplify to: 

r ∑(v ⋅ ds)

A

ω = , (4.2.3) 

for the vertical component of relative vorticity, ω. The horizontal components of the velocity 

field, u and v, are calculated from the sea surface height from the geostrophic approximation: 

u = − f

g ∂h

∂y

 , v = f

g ∂h

∂x

. (4.2.4) 

By combining equations 4.2.3 and 4.2.4, the relative vorticity can be calculated directly from the 

PIES sea surface height. Diagram 1 in the upper panel of Figure 4.2-7 shows the configuration of 

the PIES used for the calculation. The method made use of triangles constructed between 

neighboring PIES stations and the center PIES station #4. PIES #6 was not used in these 

calculations because the sea surface height data from that instrument were only available during 

the second half of the year-long observational record. Based on the configuration of the 

individual PIES stations and the method used (see again Diagram #1), PIES #4 was selected as 

the location at which to find the vorticity since a circuit around a station is needed to evaluate the 

line integral of velocity defined by Stokes’ theorem. The velocities in the direction along each 

face of the circuit were also needed to evaluate the integral. Diagram 2 (in Figure 4.2-7) shows 

the geometric configuration used to calculate the velocity between PIES stations #1 and #2. The 

velocity along each edge of the PIES array was calculated from the sea surface slope 

perpendicular to the line between each pair of PIES stations on the perimeter of the circuit. The 

steps below outline the process for completing the calculation of the velocities and the vorticity: 

1. Found the locations of PIES #1 (x1,M1,h1) and PIES #2 (x2,M2,h2) relative to 

PIES #4 (0,0,h4) after moving the origin of the x, y coordinate system to the 

PIES #4 location. 

2. Found the midpoint of the line connecting PIES #1 and PIES #2: 

[(x1+x2)/2,(M1+M2)/2,(h1+h2)/2]. 

3. Set the point of intersection of the perpendicular (in red in Diagram #2) and 

the line connecting PIES #2 and PIES #4 to be (a,b,c). 

 4-16 
4. The line connecting PIES #2 to PIES #4 is given by the equation: 

 

r

y = (0,0,h4 ) + t(x2, y2,h2 )

The point (a,b,c) will be a point on this line for some t, providing the three 

following equations: 

a = x2

b = y2t

c = h4 + h2t

t

5. A fourth equation was obtained using the Pythagorean theorem with the 

midpoint of the line connecting PIES #1 and PIES #2, the point at PIES #2, 

and the point (a,b,c). This equation along with the 3 in step 4 is solved to 

obtain values for a,b,c and t. 

6. Calculated the slope of the line connecting the midpoint between PIES #1 and 

PIES #2 and the point (a,b,c), and multiplied by (g/f) which gives the velocity 

along the segment between PIES #1 and PIES #2. 

7. Repeated steps 1 through 6 to find the velocities along all five line segments 

along the perimeter defining the path of integration around the PIES array. 

8. Multiplied the velocity along each segment by the distance between the two 

respective PIES stations defining the individual segments and sum to calculate 

the total circulation around the full circuit of the array. 

9. Divided the result from step 8 by the total area within the perimeter of the 

array to estimate the area-averaged vorticity. 

10. Repeated the procedure for all times to calculate the time series of relative 

vorticity for the array. 

 4-17 
Figure 4.2-7. Diagrams #1 and #2 show schematics used to compute relative vorticity from the 

Eastern Gulf PIES stations. The lower panel shows the relative vorticity time 

series and the dates of selected events. Thick black lines span the time periods 

when the altimeter-derived SSH was above 17 cm within the PIES array. 

 4-18 
4.2.3 Anticyclonic and Cyclonic Events in PIES Relative Vorticity Time 

Series 

The time series of relative vorticity normalized by the planetary vorticity, f, is shown in the lower 

panel of Figure 4.2-7. The dates of selected anticyclonic and cyclonic events are identified by 

labels on the time series. Thick black lines show the time periods when the altimeter-derived 

SSH was above 17 cm within the PIES array, which corresponds to the strongest anticyclonic 

events observed in the record. The first time period of the 17-cm contour intrusion into the PIES 

array, from 14 Feb 2005 through 14 Mar 2005, was associated with the first detachment of Eddy 

Vortex (see Tables 3.1-1 and 3.2-2). The second time period of intrusion, from 3 June 2005 

through 25 June 2005, was associated with the third detachment of Eddy Vortex. In these two 

cases, the peak anticyclonic vorticity events occurred just before a large anticyclonic eddy 

detached from the LC. Figures 4.2-8 and 4.2-9 show the altimeter-derived SSH overlaid on 

coincident chlorophyll concentration images on the dates of peak anticyclonic vorticity in the 

array: 16 February 2005 and 15 June 2005. Peak values during these events were of the same 

order of magnitude as the planetary vorticity. The two other LC intrusion and Eddy Vortex 

detachment events, which were in late May and early August, also influenced the anticyclonic 

vorticity observed in the array. In the last half of the record, the anticyclonic events were much 

less frequent and significantly weaker because of the more westward intrusion and ultimate 

retreat of the LC associated with the separation of Eddy Vortex on 13 September 2005. 

Cyclonic events occurred more frequently than anticyclonic events in the eastern GOM vorticity 

record. In the first half of the time series, these events were associated with cyclonic frontal 

instabilities or eddies propagating in a clockwise direction along the frontal boundary of the 

intruded LC or detached Eddy Vortex. Figure 4.2-10 shows altimeter-derived SSH overlaid on 

coincident chlorophyll concentration images for four of the events with cloud-free imagery 

during this time period. A key feature in each of the images is the strong chlorophyll signature 

associated with the cyclonic frontal events. These plumes of enhanced chlorophyll originated 

upstream of the array through the interaction of the LC/LCE with the continental shelf/slope. In 

the latter half of the time series, the configuration of the LC in the eastern GOM changed as the 

LC retreated to just south of the study array following the separation of Eddy Vortex. The 

cyclonic events during this time period were associated with relatively stationary cyclones 

located along the northern frontal boundary of the retreated LC. Strong circulation events within 

the array, in these cases, were caused by the movement of large frontal eddies over and back into 

the array as they were jostled around by the LC that remained well-intruded, but south of the 

study region. Figure 4.2-11 shows altimeter-derived SSH overlaid on coincident chlorophyll 

concentration images for the four strongest events observed during this time period. 

 4-19 
Figure 4.2-8. Altimeter-derived SSH overlaid on 8-day composite chlorophyll-concentration 

image from 16 Feb 2005. This day corresponds to the peak anticyclonic relative 

vorticity during the LC intrusion associated with the first detachment of Eddy 

Vortex. 

 4-20 
Figure 4.2-9. Altimeter-derived SSH overlaid on 8-day composite chlorophyll-concentration 

image for 15 June 2005. This day corresponds to the peak anticyclonic relative 

vorticity during the LC intrusion associated with the third detachment of Eddy 

Vortex. 

 4-21 
Figure 4.2-10. Altimeter-derived SSH overlaid on 8-day composite chlorophyll-concentration 

images for selected dates before Eddy Vortex separation. The dates correspond to 

the peak cyclonic vorticity events identified in the vorticity time series shown in 

the lower panel of Figure 4.2-7. 

 4-22 
Figure 4.2-11. Altimeter-derived SSH overlaid on 8-day composite chlorophyll-concentration 

images for selected dates after Eddy Vortex separation. The dates correspond to 

the peak cyclonic vorticity events identified in the vorticity time series shown in 

the lower panel of Figure 4.2-7. 

 4-23 
5.0 MOORING AND HYDROGRAPHY RESULTS 

5.1 Mooring Measurements 

As described previously herein, the mooring measurements were collected over two deployments 

spanning one year from January 2005 to January 2006. Servicing of the moorings occurred in 

August immediately prior to the arrival of Hurricane Katrina in the GOM. As shown in Chapters 

3 and 4, portions of the study area experienced the influence of either the LC, Eddy Vortex, or 

frontal features associated with them multiple times. In addition, several hurricanes and a 

tropical storm passed through the GOM during 2005, some of them close enough to the study 

area (Appendix A) to result in distinguishable impacts to the currents measurements by the 

eastern GOM moorings. The end result is that the moorings captured a robust set of 

measurements showing the impacts to the eastern GOM circulation by both the LC, an LCE, 

frontal features, and hurricanes. 

5.1.1 Velocity Time-Series 

Velocity time series of the current measurements at multiple depths on the tall moorings M1, 

M2, and M3 for both the first and second deployments are shown in Appendix B. The time series 

are presented as vector plots, with the length of the vectors equal to the speed scale, and the 

direction of the vector pointed in the direction of current flow, with north toward the top of the 

page. A solid line superimposed on the vector plots also denotes the current speed. Data are 

presented for selected depths from the ADCPs, as well as from all single point current meters, so 

as to provide an initial full water column perspective on the timing and depths associated with 

stronger current events during each deployment. The depth axis is not to scale. Vertical lines 

represent the general timing of LC, LCE, frontal feature, or storm effects upon the currents. 

As can be seen in these plots, a significant portion of the first deployment at all three tall 

mooring locations experienced stronger currents primarily but not entirely generated by LC, 

Eddy Vortex, or LC or LCE frontal features. At M3, nearly the entire first deployment contained 

stronger currents. Currents at M2 were quite similar to those at M3, whereas the strength and 

duration of stronger currents at M1 was reduced as compared to those at M2 and M3 during the 

first deployment. During the second deployment, periods of stronger currents were normally 

shorter, and current strengths reduced as compared to the first deployment, although Mooring 

M3 continued to show influences on the currents due to both hurricanes and the LC/LCE/frontal 

features for most of its record. 

The effect on the currents by LC/LCE/frontal features and hurricanes is most prominent in the 

top 500 m of water depth. Color contours of the current speed, current direction and water 

temperature versus depth and time were created and analyzed to assess the periods of most 

impact by the different features. In these contours, thin horizontal lines depict the depth of 

various instruments that contained pressure sensors from which the mooring drawdown due to 

the currents was calculated. The depth of the current measurements was then adjusted as 

displayed in these contours. It is interesting to note that while hurricanes at times generated some 

higher current speeds, they caused minimal mooring drawdown as compared to the influence of 

the LC or and LCE. LC or LCE intrusions generated the strongest upper layer currents and 

caused more significant mooring blow-over, as is illustrated in some of the following figures. 

 5-1 
Figure 5.1-1. Color contour of speed (top) and direction (bottom) for M1 during deployment 1 

showing the effects of mooring draw down due to high currents. Dark horizontal 

lines through the contours indicate the depth of each sensor on the mooring line 

including the ADCP. 

For instance, Figure 5.1-1 shows a period when these currents pulled the mooring over compared 

with times that storms and hurricanes passed through the GOM. Note the large draw down in 

mid June between Tropical Storm Arlene and Hurricane Cindy. This is when Eddy Vortex is 

calculated to have detached for the third time from the LC. Also of note is the drawdown in the 

later part of February when Eddy Vortex detached for the first time from the LC. In one instance 

the blow over caused by the LC could be seen in the depth measurement for a current meter at 

nearly 200 m depth (Figure 5.1-2). 

For perspective, an initial view of the influence of Hurricane Katrina which occurred in late 

August 2005 can be seen in Figure 5.1-3. Inertial oscillations of currents generated by Katrina 

are quite evident, yet are not as strong nor have the same drawdown effect on the moorings as 

the LC events. The effects of hurricanes on the circulation will be described in more detail in 

later sections of this Chapter. 

 5-2 
Figure 5.1-2. Color contour of temperature for M3 during deployment 1. Of note is the draw 

down effect on the meters by the Loop Current such as in early August (circled). 

In all of these appendices, the variation in the depth of the measurements is displayed. The 

temperature data show best the influence of LC and LCE events. The pressure readings on the 

instruments, as depicted by the thin horizontal lines, provide good perspective on the periods 

within the mooring records showing the influence of the various tropical storms and hurricanes. 

An initial understanding of the nature of the physical processes which occurred during the 

measurement period can be obtained by simple visual inspection of the moored time series data 

plotted in composite form at several depths that span the entire water column. Gridded, 

interpolated current speed at five ADCP depths and all single point current meters for each 

mooring deployment are illustrated in Figure 5.1-4a-c. Tick marks along the y axis are spaced at 

50 cm s-1 intervals, tick labels indicate record depth. Clearly, currents during both deployments 

in this region showed a high degree of coherency at water depths above 500 m. High-speed 

current events (near surface speeds exceeding 100 cm s-1) were strongest and more frequent at 

M3 than at M1 in particular due to the LC impacting M3 more frequently due to its position 

farther south in the study area. 

 5-3 
Figure 5.1-3. Color contour of speed (top) and direction (bottom) for M3 during deployment 2 

showing inertial oscillations on the mooring due to hurricanes. Dark horizontal 

lines through the contours indicate the depth of each sensor on the mooring line 

including the ADCP. 

Occasionally, the observations indicated a strong barotropic component to the flow structure. For 

example, in mid-August 2005, at mooring M3, there was a barotropic event associated with the 

detachment and reattachment of an LCE. The feature was coherent throughout the water column 

and peaked in the upper ocean with only gradual diminishment with depth. In October through 

mid-December 2005, there was a second barotropic current event that was seen in the velocity 

data collected at M2 and M3. During this second event, the increase in current speed was 

associated with a LC meander into the study area. 

Large-amplitude inertial oscillations excited immediately after the passages of Hurricanes 

Katrina in late August 2005 and Rita on 21 September 2005, are easily identified in the time 

series. The current oscillations persisted for at least two weeks after the passage of the storms. 

Inertial motions were strongest at M3 and penetrated down to 500 m. Hurricane Dennis, which 

entered the Gulf on July 9th, and later passed very close to the study area, was evidenced in the 

less intense inertial oscillations at M1 around this time. A more detailed discussion of the effects 

on the circulation of the passage of these hurricanes is presented later in this Chapter. 

 5-4 
Figure 5.1-4a. Gap-filled, gridded current speed from five moored ADCP depths and moored 

current meters M1 for deployments 1 (left) and 2 (right). Instrument depth is 

indicated on the y-axis. 

Figure 5.1-4b. Gap-filled, gridded current speed from five moored ADCP depths and moored 

current meters M2 for deployments 1 (left) and 2 (right). Instrument depth is 

indicated on the y-axis. 

 5-5 
Figure 5.1-4c. Gap-filled, gridded current speed from five moored ADCP depths and moored 

current meters M3 for deployments 1 (left) and 2 (right). Instrument depth is 

indicated on the y-axis. Black arrow indicates barotropic event during August 

2005. The flat periods in the current meter record at 997 m are periods of no data. 

5.1.2 Current Roses, Joint Probability Distributions of Speed by Direction 

Calculations of current speed within 5 cm s-1 speed ranges by eight directional quadrants were 

performed for all measurement depths for all moorings. These calculations were performed for 

each deployment period separately. From these, current roses were developed to aid 

interpretation of the current meter data. 

5.1.3 Current Speed Persistence Tables 

The persistence of various current speed ranges over five duration periods spanning up to 42 

hours duration was also computed for all measurement depths for all moorings. Again, these 

calculations were performed for each deployment period separately. 

 5-6 
5.1.4 Velocity Spectra 

Power spectral density profiles for velocity components at all depth levels, for both mooring 

deployments, were generated using Fast Fourier Transform (FFT) methods. Following Welch’s 

Method, the velocity time series were subsampled into overlapping segments of 512 points. 

Segments were preconditioned using a 512-point Kaiser-Bessel window; segments overlapped 

by 50%. The periodogram for each segment was computed using the FFT and then all 

periodograms for a given record were averaged to produce the spectra discussed in this section. 

A convenient property of the Kaiser-Bessel window is that it allows each 512-segment to be 

treated as statistically independent. This technique significantly increases the degrees of freedom 

and, therefore, the statistical confidence of each spectra estimate. If the size of the longest, 

gapless segment of the time series was less than 512 points, which was the case for some records 

at the surface, the data were sub-sampled, and a Kaiser-Bessel window the size of the subsample was used for preconditioning. As previously stated, records were corrected for mooring 

drawdown, interpolated, and eight tidal constituents were removed using the method of cyclic 

descent before analysis. 

Spectra (non-variance preserving) estimates for moorings M1, M2, and M3 for u and v velocity 

components are presented at selected depths throughout the water column in loglog form for 

each deployment in Figures 5.1-5, 5.1-6, and 5.1-7, respectively. The purpose of these figures is 

to investigate how the spectral character of current velocity at each mooring location changes 

with depth. 

The typical velocity spectrum derived from the velocity time series of historical GOM 

measurements display a red energy distribution (weighted to low frequencies), with a peak 

centered near the inertial frequency (i.e., close to 1 cpd). There is an energy minimum commonly 

seen in the 5 cpd range as well. Near-surface motions having periods ranging from 2-15 days are 

usually attributable to atmospheric weather conditions. Velocity spectra from the Eastern GOM 

moorings followed this energy partitioning. 

5.1.4.1 Upper Ocean Spectra 

In general, spectral energy throughout the frequency domain shown in Figures 5.1-5, 5.1-6 and 

5.1-7 were greatest in the shallow ocean (< 300 m depth). As expected, surface records (~ 50 m) 

contained larger weather-band variance than deeper records since the influence of winds on 

currents generally diminishes with depth. This was especially true at moorings M2 and M3, 

where the variance steadily increased between 0.9 cpd and 0.1 cpd. Spectral peaks at periods of 

seven to eight days were evidenced in some near-surface records, in particular mooring M1 

during deployment 2. Inertial band energy was present throughout the water column; however, 

the amplitude of the inertial peak tended to narrow and decrease with depth. During the first 

deployment, the moorings each had similar inertial energy amplitudes. Spectral estimates based 

on data from the second deployment show moorings M2 and M3 had significantly more energy 

in the inertial band than mooring M1, again owing to the closer proximity of these mooring to 

the centers of Hurricanes Katrina and Rita. 

 5-7 
Figure 5.1-5. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M1 from 

deployment 1. Deployment 2: Panels C and D. 

 5-8 
Figure 5.1-6. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M2 from 

deployment 1. Deployment 2: Panels C and D. 

 5-9 
Figure 5.1-7. Panels A and B give power spectral density of detided, gap-filled u and v 

velocity components, respectively, at 6 depths at mooring M3 from 

deployment 1. Deployment 2: Panels C and D. 

 5-10 
Near-surface spectral variance associated with periods of 20-60 days were typically associated 

with mesoscale processes such as the LC or its associated eddies. Low-frequency spectral 

estimates in the upper ocean at moorings M1, M2, and M3 were roughly equal. There was 

slightly more sub-inertial energy present during deployment 1, especially at the 20 – 60 day 

period. This is likely attributable to the penetrations of the LC and Eddy Vortex into the study 

area multiple times during deployment 1. 

The super-inertial domain, i.e., frequencies greater than 1 cpd, generally decreased with 

increasing frequencies. There was some evidence of semi-diurnal variance, likely associated with 

semi-diurnal tides; however, the variance associated with the semi-diurnal tides rarely raised 

above background levels. 

5.1.4.2 Deep Ocean Spectra 

Relative to the surface, spectral estimates found in deeper records of the Eastern GOM moorings 

were less energetic. The overall shapes of the trends of the spectra estimates of the deeper 

records closely resembled those estimated from records of the upper ocean. Generally, estimates 

at super-inertial frequencies tended to decrease faster with increasing frequency in the deeper 

records. Subinertial variability, particularly in the lowest bands shown, decreased from south to 

north, i.e., from mooring M3 to M1. This may be attributed to the motions associated with the 

LC and LCE events at each mooring. There were some cases where low frequency variance (20 

– 60 day period band) in the deepest record (usually 2500 m) was greater than the energy in the 

record at ~ 1000 m, which could be evidence of topographic Rossby waves. This is further 

considered in Chapter 6. 

5.1.5 Coherency Spectra 

5.1.5.1 Current – Wind Coherence 

Coherency, coherence of spectral estimates of independent records, was estimated for all 

combinations of u and v wind velocity and u and v current velocity at all ADCP depths for all 

gapless time-series. In general, no statistical coherency of currents with wind was observed, 

except for incidental coherency near the inertial frequency. The coherency at this frequency was 

associated with random phase and were not seen deeper than the shallowest two or three velocity 

time-series for each mooring. The coherency near the inertial frequency was present at all 

moorings from data collected during deployment 2. This was likely related to the occurrences of 

Hurricanes Katrina and Rita, which caused high amplitude inertial currents in the study region 

for weeks after their passage. 

At mooring M1, during deployment 1, there was a weak low frequency correlation between 

current and wind. The coherency between north-south current velocity and north-south wind 

velocity showed significant peaks at ~ 50 day period with constant phase. The coherency 

penetrated downward into the water column. 

 5-11 
5.1.5.2 Vertical Current – Current Coherence 

The coherency spectrum was estimated for current velocity components at different depths, i.e., 

vertically relative to the uppermost time-series at each mooring and horizontally between 

velocity components at similar depths at different moorings. To increase statistical reliability, the 

coherency spectra were smoothed in the frequency domain over 9 points. 

The vertical coherence at low frequencies between velocity time-series at 100 m and records to 

depths of ~500 m depth were mostly significant for every mooring deployment. Coherency was 

also observed at near-inertial frequencies. Coherency in the inertial band between near-surface 

velocity and records between 100 – 200 m diminished owing to the location of the pycnocline at 

these depths. Below this depth, inertial motions may be attributable to other forcing processes 

such as eddy features. Inertial oscillations at the surface and at depth therefore would not be 

expected to be coincident or phase locked. The exception to this is when a powerful hurricane is 

able to affect layers below the pycnocline. 

At mooring M1, deployment 1, there was significant low frequency coherency between current 

velocity at 100 and 428 m depth at periods above 7 to 8 days as evidenced by a comparison of 

the individual time series (Figure 5.1-8). The coherency spectrum (Figure 5.1-9: upper left) 

clearly shows significant coherency at the low frequencies (<0.2 cpd). The coherency phase 

spectrum (Figure 5.1-9: lower left) shows that the phase between the low frequency components 

being close to zero indicating in-phase oscillations. The admittance spectrum (Figure 5.1-9: 

upper right) shows the gain between the spectral components of the two series and indicates that 

the variance in the 428 m record was about 10% of that of the record at 100 m. The admittance at 

super-inertial frequencies was close to one, indicating nearly equal variances. Deployment 2 data 

indicated weaker low frequency coherency; however, the coherency was significant only at the 

lowest frequency, around 80 days, with zero phase difference. 

At mooring M2, deployment 1, significant coherency was distributed similar to that seen at 

mooring M1. In the upper layer, low frequency coherency was seen at periods longer than about 

eight days and at near inertial peaks. This coherency extended deeper than at mooring M1. For 

example, north-south velocity was coherent with the surface at depths reaching 1244 m and eastwest velocity was coherent with surface east-west velocity down to 750 m. For the second 

deployment, north-south velocity at mooring M2 was coherent throughout the upper water 

column (to about 500 m depth) at low frequencies with zero phase lag, which implied a 

significant correlation at zero lag between surface data and data throughout the upper 500 m, as 

seen in Figure 5.1-10. This was not the case for the east-west velocity component, as it was only 

correlated at the lowest frequency estimate (~80 days). The near-inertial correlation in both 

velocity components, between the surface and at depth, diminished around 120 m at mooring M2 

during deployment 2. 

Vertical coherency at mooring M3 during deployment 1 presented a similar picture to moorings 

M1 and M2, with significant zero lag low frequency correlation throughout the upper water 

column (to ~500 m) for east-west velocity component, but only to 350 m for the north-south 

velocity component. Data at mooring M3 from deployment 2 were only significantly correlated 

down to 300 m for the east-west velocity component and 100 m for the north-south velocity 

component. 

 5-12 
Figure 5.1-8. Detided, gap-filled, gridded u velocity time-series at mooring 1 during 

deployment 1 at 100 m and 428 m. Strong low frequency in phase coherency 

indicates significant correlations between currents at these two depths. 

 5-13 
Figure 5.1-9. (Clockwise from top left) Coherence, admittance, power, and phase spectra 

between u velocity components at 100 m and 428 m at mooring 1 during 

deployment 1. Magenta asterisks in the phase spectrum indicate significant 

coherency at the corresponding frequency. 

 5-14 
Figure 5.1-10. (Clockwise from top left) Coherence, admittance, power, and phase spectra of 

north-south (v) velocity components at 70 m and 494 m at mooring M2 during 

deployment 2. Magenta asterisks in the phase spectrum indicate significant 

coherency and phase at the corresponding frequency. 

 5-15 
5.1.5.3 Horizontal Current – Current Coherency Spectra 

Estimates of the coherency spectra for horizontal separations were calculated between moorings 

for all velocity combinations at the same depth. East-west velocity at moorings M1 and M2 were 

coherent at the lowest frequency band (~90 days) and with zero phase lag. Near the inertial 

frequency in the upper water column, coherency was found at 750 m, 1244 m, and 1492 m. The 

phase of the correlation at the near inertial peak was variable with depth. The east-west velocity 

component at mooring M1 and north-south velocity component at mooring M2 were also 

coherent at low frequencies but with a phase difference of about 1 radian (~90°) at the lowest 

frequency, which indicated that the M1 velocity lead the M2 velocity. Coherency between 

mooring M1 v velocity and mooring M2 u velocity, as well as coherency between v velocity at 

both moorings indicated coherency at low frequency with a phase of ~-1.0 radian, which meant 

that M2 lead M1. The phase relationship of the two components likely indicated the influence of 

the eddy fields. Deeper current meter records, except for the records at 1995 m, were only 

significantly correlated between north-south velocity components at both moorings in the inertial 

band and at low frequencies (~ 80 - 90 days), as seen in Figure 5.1-11. This may be an indication 

of topographic steering along the bathymetry. 

Mooring M1 and mooring M3 east-west velocities were coherent at near-inertial frequencies at 

every depth in the upper layers. M1 u and M3 v were correlated at the fundamental frequency 

(~90 days) at a phase of ~2 radians (180°) throughout the water column and near inertial peaks 

were present down to 998 m. v velocity at M1 and M3 were correlated at low frequencies down 

to 998 m with zero phase difference. Only near-inertial correlation was present between M1 v

and M3 u. 

East-west velocity at moorings M2 and M3 illustrated very little significant coherency beyond 

some intermittent near-inertial correlations in the upper water column; however, the east-west 

velocity was coherent between moorings M2 and M3 in all current meter records in the deep 

ocean at periods of about 50 days (Figures 5.1-12 and 5.1-13). North-south velocity was 

correlated at low frequencies in the upper water column, and there was correlation at 20-day 

periods and above between the data from the deep current meters at 750, 998, and 1245 m. There 

were some near-inertial peaks in the upper water column between M2 east-west (north-south) 

velocity and M3 north-south (east-west) velocity. 

 5-16 
Figure 5.1-11. (Clockwise from top left) Coherence, admittance, power, and phase spectra 

between v velocity components at 749 m at mooring M1 and mooring M2 during 

deployment 1. Magenta asterisks in the phase spectrum indicate significant 

coherency at the corresponding frequency. 

5.1.6 Mean, Minimum and Maximum Currents 

Standard statistics were calculated for the current meter records, including the record-length 

mean current, its standard deviation, and the minimum and maximum currents that occurred in 

each record. Vertical profiles of the record-length mean, mean plus and minus one standard 

deviation, and minimum and maximum values for the u (east-west) and v (north-south) velocity 

components for all instruments and ADCP depth bins on moorings M1, M2, and M3 are plotted 

in Figures 5.1-14, 5.1-15 and 5.1-16, respectively. Appendix C contains the basic statistics in 

tabular form. The basic pattern revealed in this series of figures is that current velocity was 

generally greatest near-surface and decreased with depth. The statistics below depths of 1000 m 

were typically constant to the bottom. Some of the profiles showed that for the uppermost 

surface velocity bins the record-length mean, standard deviation, and minimum/maximum 

envelopes tended to have a slightly different character than measurements at deeper bins, i.e., 

around 100 m. This may have been because fewer observations were associated with the surface 

bins due to instrument drawdown and the effects of gridding the data to non-overlapping depth 

bins. This effect was particularly relevant since most data dropout at these levels occurred during 

strong current events. 

 5-17 
Figure 5.1-12. Detided, gap-filled, gridded east-west velocity time-series at mooring M2 and 

mooring M3 during deployment 1 at 1995 m and 2699 m respectively. 

The mean current velocity at mooring M3 (Figure 5.1-16) was predominantly to the southeast 

during deployment 1 and eastward during deployment 2. We attribute this to the relative location 

of the mooring to the northern edge of the LC and the developing anticyclonic eddies during the 

early months of 2005. The southern limb of a frontal cyclonic eddy passed over this region 

during a large period of deployment 2 producing mostly eastward-directed currents. The 

southward velocity at M3 was attributed to the position of the LC relative to the mooring in early 

April 2005. In May, the northeastern limb of the LC moved into the study area, producing large 

southward current velocities. During the second deployment, the mean north-south velocity 

component at M3 was close to zero. Mooring M3 was also closest to Hurricanes Katrina and 

Rita; therefore, the minimum/maximum current velocity envelopes were greatest here than for 

any other mooring deployment. 

 5-18 
Figure 5.1-13. (Clockwise from top left) Coherence, admittance, power, and phase spectra 

between u velocity components at mooring 2 and mooring 3 during deployment 1 

at 1995 m and 2699 m respectively. Magenta asterisks in the phase spectrum 

indicate significant coherency at the corresponding frequency. 

Indications of energetic current events near the ocean surface were present at moorings M1 

(Figure 5.1-14) and M2 (Figure 5.1-15) however to a lesser degree than that seen at M3. During 

deployment 1, current velocity was primarily southeastward at mooring M2, and to the east at 

mooring M1. However, during the second deployment, currents were dominated by various cold 

core frontal eddies moving in and out of the study area, and the result were relatively small mean 

current velocities. 

At mid-water depths, i.e., around 750 m, the magnitude of the minimum and maximum currents 

for deployment 2 at mooring M1 was a maximum. An examination of the time series showed 

that the large currents associated with this peak occurred in early September 2005 as a long 

period oscillation with inertial motions superimposed. Comparison with records above and below 

showed little phase-locked or lagged correlation to any one particular event. The timing of these 

inertial oscillations at this depth were consistent with the interpretation that they were initiated at 

the surface by Hurricane Katrina on August 26 and propagated downward in the water column; 

however, the forcing of the longer period oscillation was not certain. Inertial band energy was 

seen at these depths at Moorings M2 and M3; however, there are no low frequency motions and 

therefore no mid-water peak in basic statistics. 

 5-19 
Near-bottom (~2500 m) statistics from deployment 2 at mooring M1 showed slightly larger 

extreme values than values 500 m above bottom. This is the only deployment showing evidence 

of bottom intensification. We note that at M1 there was no indication of low-frequency 

oscillations that extended throughout the water column and that bottom motions were not 

coherent with surface motions. 

Basic statistics for M4 were not plotted; a table containing these values was included in 

Appendix C. Record-length mean and standard deviation at M4 were near zero for both 

deployments and were consistent with values at similar depths at other moorings. 

5.1.7 Extreme Current Value Distributions 

In practical engineering applications, one often needs an estimate of the extreme value of the 

current speed over some return interval. In this section, we give examples of how that might be 

done for the measurements made by the Aanderaa current meters on the moorings. 

Extreme value theory assumes that the sample distribution is made up from independent and 

identically distributed random variables. The hourly values of measured current speed are 

serially correlated so they cannot be used directly. Two methods are commonly used to produce 

independent variables from a serially correlated time series. The peaks over threshold (POT) 

method finds the peak values in intervals that exceed some specified threshold. The POT method 

is not very well suited to the Aanderaa current meter data because there are many closely spaced 

peaks that are likely not independent. The block maximum method finds the maxima in intervals 

of a specified duration. In cases where long time series are available, yearly maxima are often 

specified, such as for flood data. We only had one year of data, but the signal was highly variable 

on short time scales. It appeared that something like weekly maxima were statistically 

independent. Tests showed that taking maxima for a range of intervals around seven days did not 

change the results very much. 

We fit the weekly maxima to the generalized extreme value distribution (GEV). The GEV is the 

limit distribution of the maxima of a sequence of independent and identically distributed random 

variables. The cumulative distribution function of the GEV is given by: 

−1/ξ

( ) exp 1 x F x μ ξ

σ

⎧ ⎫ ⎪ ⎡ −⎤ ⎛ ⎞ ⎪ = −+ ⎨ ⎢ ⎜ ⎟ ⎬ ⎣ ⎦ ⎝ ⎠⎥ ⎪⎩ ⎭⎪

, (5.1.1) 

where μ is the location parameter, σ is the scale parameter, and ξ is the shape parameter. 

If ξ is negative the maximum value of x is bounded by μ – σ/ξ. If ξ is positive the distribution is 

unbounded. The fits of the weekly maxima to equation 5.1.1 were made by the maximum 

likelihood method. 

 5-20 
Figure 5.1-14. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M1 (left: east-west 

component; right: north-south component). Top row: Deployment 1. 

Bottom row: Deployment 2. 

 5-21 
Figure 5.1-15. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M2 (left: east-west 

component; right: north-south component). Top row: Deployment 1. 

Bottom row: Deployment 2. 

 5-22 
Figure 5.1-16. Vertical profiles of record-length mean, standard deviation, minimum, and 

maximum velocity components for mooring M3 (left: east-west 

component; right: north-south component). Top row: Deployment 1. 

Bottom row: Deployment 2. 

 5-23 
The results of the fits are shown in Tables 5.1-1 – 5.1-4. The first three lines of the tables give 

the fitted parameters in equation 5.1.1 for each depth. N was the number of weekly maxima, 

generally 52. In some cases, the number was considerably lower. In those cases, the sample 

distribution was truncated below some speed because the higher maxima appeared to come from 

a different distribution than the lower maxima. Due to instrument failure, there was too little data 

at the 1995 m depth on mooring 1 and the 2499 m depth on mooring 2 for reliable fits. The row 

labeled Max is the maximum speed observed during the year of measurements. The last five 

lines of the tables give the extrapolated return period extreme values. 

Table 5.1-1 

Extreme current speed distributions at Mooring 1. 

Depth 749 997 1244 1492 1995 2499 

μ 15.74 7.87 7.63 6.31 -- 9.34 

σ 5.03 5.65 2.47 2.43 -- 3.22 

ξ 0.0799 -0.1249 0.0606 -0.1720 -- 0.0300 

N 52 52 52 52 -- 51 

Max 45.7 30.7 19.4 14.3 -- 30.7 

1 Yr 38.9 25.4 18.6 13.3 -- 22.8 

5 Yr 50.7 30.5 24.0 15.0 -- 31.4 

10 Yr 56.2 32.4 26.4 15.6 -- 31.4 

50 Yr 70.3 36.2 32.6 16.8 -- 37.8 

100 Yr 76.9 37.5 35.4 17.2 -- 40.7 

Table 5.1-2 

Extreme current speed distributions at Mooring 2. 

Depth 749 997 1244 1492 1995 2499 

μ 18.38 12.17 11.62 7.89 16.78 -- 

σ 5.60 4.28 4.10 2.87 3.90 -- 

ξ -0.2393 -0.3269 -0.1515 0.0239 -0.0260 -- 

N 52 52 52 49 24 -- 

Max 36.3 22.6 23.3 28.2 31.2 -- 

1 Yr 32.7 21.7 23.8 19.6 28.6 -- 

5 Yr 35.6 23.1 27.0 24.8 34.3 -- 

10 Yr 36.6 23.6 28.2 27.1 36.7 -- 

50 Yr 38.2 24.3 30.4 32.5 42.0 -- 

100 Yr 38.8 24.5 31.3 35.0 44.2 -- 

 5-24 
Table 5.1-3 

Extreme current speed distributions at Mooring 3. 

Depth 750 997 1245 1492 1996 2499 2699 

μ 21.16 14.80 11.40 19.38 20.02 20.55 20.04 

σ 5.87 5.87 3.41 3.66 4.51 4.51 4.01 

ξ -0.1979 -0.2161 -0.0122 -0.0714 -0.1707 -0.1481 -0.0279 

N 52 52 50 12 14 15 16 

Max 37.1 35.8 32.0 32.0 32.2 33.1 33.1 

1 Yr 37.2 30.4 24.4 27.6 29.5 30.5 30.6 

5 Yr 41.0 33.8 29.6 32.3 33.6 34.9 36.6 

10 Yr 42.2 34.9 31.8 34.2 35.1 36.5 39.0 

50 Yr 44.6 37.0 36.9 38.2 37.8 39.6 44.5 

100 Yr 45.4 37.7 39.0 40.0 38.8 40.7 46.8 

Table 5.1-4 

Extreme current speed distributions at Mooring 4. 

Depth 2530 2630 

μ 9.05 8.92 

σ 2.95 3.24 

ξ -0.0788 -0.1534 

N 52 52 

Max 18.0 17.8 

1 Yr 19.0 18.5 

5 Yr 22.3 21.0 

10 Yr 23.6 21.9 

50 Yr 26.3 23.7 

100 Yr 27.4 24.3 

Plots of the fits are shown in Figures 5.1-17 – 5.1-21. In general, the fitted distributions agreed 

reasonably well with the sample distributions. But there are some cases, for example the 2499 m 

depth at Mooring 1 where there were a couple of large maxima that did not agree with a smooth 

curve through the rest of the data. The maximum likelihood method did its best to honor all of 

the data, but recognized that the last few data points have a very large statistical uncertainty. The 

extrapolations to 100 years of 1 year of data also had a large uncertainty, but engineering 

calculations require answers. 

Most of the fitted distributions had negative ξ values, showing that the distributions had an upper 

limit. On the other hand, the ξ values were generally rather close to zero, so that the limit was 

rather large compared to the extrapolated values. 

 5-25 
In general, the extreme values near 750 m depth and near the bottom were largest, with smaller 

values at intermediate depths. By far the largest were at 749 m depth on Mooring 1. The 

extrapolated near-bottom current speeds at Mooring 1 near the Florida Escarpment were no 

larger than those at Mooring 3 on the abyssal plane. This was an interesting contrast to nearbottom currents near the Sigsbee Escarpment farther west, where bottom currents were much 

stronger in proximity to the Escarpment. 

5.1.8 Responses to Hurricanes 

During the Eastern GOM Study mooring deployments, five hurricanes and one tropical storm 

traversed the GOM; the most severe being Hurricanes Katrina and Rita, which caused 

devastating loss of life and property damage to the Gulf coast. Hurricane Katrina entered the 

GOM August 26, 2005 and was nearest to the study area on August 28, 2005; Hurricane Rita 

entered the GOM on September 20, 2005 and was nearest to the study region on September 22, 

2005. As mentioned earlier, the paths of all the storms are presented in Appendix A. 

5.1.8.1 Inertial Oscillations 

A direct response of the ocean to this atmospheric forcing was a wake of near-inertial 

oscillations, characterized by the downward propagation of energy and upward propagation of 

leading phase. Near-inertial motions are an essential and ubiquitous element of ocean circulation. 

These motions were investigated herein using multiple methods. 

The period in hours of inertial oscillations per hour as a function of latitude φ is given by 

12 / sin( ) TI = φ , (5.1.2) 

At the latitude of moorings M1, M2, and M3, this period is close to 24 hours. A high-pass 9-pole 

Butterworth filter with a cutoff period of 48 hours followed by a low-pass 9-pole Butterworth 

filter with a cutoff period of 12 hours was used to isolate near-inertial oscillations in the data. 

The filter was run forward and backward to eliminate any phase lags. The filter was applied to 

the vector components of the measured currents in each ADCP bin. The currents were then 

interpolated to a uniform depth grid taking into account the measured set-down of the mooring. 

Figures 5.1-22 – 5.1-27 show the total current speed and the band-passed current speed for the 

two deployments at each of the three ADCP moorings. The presentations show current speed 

instead of current components because the inertial oscillations usually rotate clockwise with 

slowly varying speed. During the first deployment (Figures 5.1-22 – 5.1-24) the strongest total 

current speeds were caused by incursions of the LC and Eddy Vortex. These features had the 

strongest effects on the southern-most mooring, M3, although strong currents from Eddy Vortex 

penetrated as far north as M1. The inertial band-passed speeds were generally small except for 

brief bursts at M3 at the end of the LC and Eddy Vortex events. 

During the second deployment (Figures 5.1-25 – 5.1-27) the passages of Hurricanes Katrina and 

Rita occurred. The total current speeds were not as strong nor did they penetrate as deeply as the 

LC and Eddy events. On the other hand, these hurricanes produced by far the strongest inertial 

oscillations. 

 5-26 
5-27 

Figure 5.1-17. Extreme value fits for current speeds at Mooring 1, Depths 749 – 1492 m. 
5-28 

Figure 5.1-18. Extreme value fits for current speeds at Mooring 1, depth 2499 m and Mooring 2, depths 749 – 12
5-29 

Figure 5.1-19. Extreme value fits for current speeds at Mooring 2, depths 1492 – 1995 m and Mooring 3, Depths 
5-30 

Figure 5.1-20. Extreme value fits for current speeds at Mooring 3, depths 1245 – 2499 m. 
Figure 5.1-21. Extreme value fits for current speeds at Mooring 3, depth 2699 m, and Mooring 4, depths 2530 – 

5-31 
Figure 5.1-22. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 1. 

Figure 5.1-23. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 2. 

 5-32 
Figure 5.1-24. Total current speed and diurnal bandpass current speed for the first 

deployment at mooring 3. 

Figure 5.1-25. Total current speed and diurnal bandpass current speed for the 

second deployment at mooring 1. 

 5-33 
Figure 5.1-26. Total current speed and diurnal bandpass current speed for the 

second deployment at mooring 2. 

Figure 5.1-27. Total current speed and diurnal bandpass current speed for the 

second deployment at mooring 3. 

 5-34 
Figures 5.1-28 – 5.1-30 show the response to Hurricane Katrina in more detail. The storm came 

closest to all three moorings late on August 28. All the moorings were to the right of the storm 

track and roughly the same distance from it. The resulting clockwise rotating wind stress vector 

had about the same potential for generating inertial oscillations at all the moorings. The initial 

response was confined above 50 m depth and thus not measured at the uppermost ADCP bins. 

After about a day, inertial pumping pushed the oscillations down to levels that were clearly 

registered by the ADCPs. These oscillations can be seen in the panels showing the total current 

(top) because the mean current is not zero, but they are more clearly seen on the panels that show 

only the band-passed current (bottom). The inertial oscillations were much stronger at M3 than at 

the other moorings. This difference in strength cannot be explained by any large difference in the 

wind forcing at the moorings. The very strong inertial response at M3 was caused by the 

coincidence of the hurricane and a cyclonic eddy. The combination of clockwise rotating winds 

and a pre-existing eddy was responsible for the strongest inertial response in these 

measurements. 

Figure 5.1-28. Total current speed and diurnal bandpass current speed during 

Hurricane Katrina at mooring 1. 

 5-35 
Figure 5.1-29. Total current speed and diurnal bandpass current speed during 

Hurricane Katrina at mooring 2. 

Figure 5.1-30. Total current speed and diurnal bandpass current speed during 

Hurricane Katrina at mooring 3. 

 5-36 
Figures 5.1-31 – 5.1-33 show the total and band-passed current speeds during Hurricane Rita. 

Again, the only significant total currents and inertial oscillations were at M3. The track of Rita 

was farther to the south of the moorings than the track of Katrina. Moorings M2 and M3 were 

just inside the extent of tropical storm winds while M1 was outside. In addition, M3 was very 

near the northern edge of the Loop Current. Again, the combination of strong winds and a preexisting feature lead to the strongest inertial oscillations. 

Figures 5.1-34 – 5.1-37 are scatter plots comparing the magnitude of the band passed currents to 

the total current magnitude at several depths. It was apparent that there was no correlation 

between the total current speed and the band passed speed. This was reasonable, because most of 

the strong currents were due to the LC or eddies. Strong inertial oscillations only occur under 

strong clockwise rotating winds, and the wind events were statistically independent from the LC 

and eddy events. 

The statistics in Figure 5.1-38 show a more interesting pattern. The ratio of the band passed 

speed to the total current speed is plotted as a function of depth. All ADCP measurements from 

the three moorings were combined. The small circles show the mean band passed speed divided 

by the mean total current speed at the same time. The lines show various percentiles of band 

passed speed divided by the same percentiles of the total current speed. All of the curves are very 

similar. They show that the inertial oscillations become an increasingly large fraction of the total 

current speed as the depth increases. Inertial oscillations penetrated with less attenuation than the 

total currents. 

Figure 5.1-31. Total current speed and diurnal bandpass current speed during 

Hurricane Rita at mooring 1. 

 5-37 
Figure 5.1-32. Total current speed and diurnal bandpass current speed during 

Hurricane Rita at mooring 2. 

Figure 5.1-33. Total current speed and diurnal bandpass current speed during 

Hurricane Rita at mooring 3. 

 5-38 
Figure 5.1-34. Scatter plot of band passed current speed vs. total current speed at 

100 m depth. 

Figure 5.1-35. Scatter plot of band passed current speed vs. total current speed at 

200 m depth. 

 5-39 
Figure 5.1-36. Scatter plot of band passed current speed vs. total current speed at 

300 m depth. 

Figure 5.1-37. Scatter plot of band passed current speed vs. total current speed at 

400 m depth. 

 5-40 
Figure 5.1-38. Ratio of band passed speed to total current speed. 

 5-41 
5.1.8.2 Wavelet Analysis of the Inertial Oscillations 

These inertial motions generated by the passage of Hurricane Katrina and Rita were also 

investigated using the wavelet transform. This method estimates the temporal variability of 

energy in specified frequency bands. Wavelet power spectra were generated for all detided, gapfilled, gridded ADCP and current meter records using a Morlet basis function. We used the 

method described in Torrence and Compo (1998) to transform observed time-series into Fourier 

space. 

The wavelet power spectrum of the normalized east-west velocity component at ~80 m at 

mooring M3 during deployment 2 is presented in Figure 5.1-39, along with the global wavelet 

spectrum and average variance in the inertial band (0.5 – 2 day period). As seen previously using 

the Fourier-derived spectrum, the wavelet power spectrum illustrated a red spectrum throughout 

deployment, with minimal energy in the 2 – 4 day period range and a clear diurnal peak. The 

inertial energy was best represented by the peak around 1 cpd in the global wavelet spectrum, 

which is the integration of the wavelet power spectrum through time. Looking at the wavelet 

power spectrum, it was clear that inertial motions were excited immediately following hurricanes 

Katrina and Rita and persisted for around 2 weeks at this depth. Not only did the storms amplify 

inertial motions; energy was elevated throughout the sub-inertial frequency domain. There was 

also a local maximum of sub-inertial energy at ~ 4 – 6 day period that started in mid November 

and continued through early December that can be attributed to the presence of the Loop Current 

extending into the study region. The average variance in the inertial band time-series was 

constructed by integration of the wavelet power spectrum in the period band 0.5 – 2 days 

throughout the observational period. This panel illustrated the variance in the inertial band 

caused by storms as well, indicated by the significant peaks in August and September. 

Contours of the average variance in the inertial band for time-series in the upper water column at 

each mooring are given in Figure 5.1-40. The downward propagation of inertial energy after 

Katrina and Rita to 500 m is indicated in this figure. The strongest response to the storms was 

seen at moorings M2 and M3, as the storm track was just south of the moorings. Note that there 

were generally two subsurface maxima of energy present after the storms and two paths for 

inertial energy were revealed. There was a direct influence on the entire water column that 

occurred during or immediately after the storm due to the storm’s intensity, evidenced by the 

nearly vertical column of high inertial energy around September 1, 2005. There was also the 

downward propagation of inertial energy, evidenced by the diagonal streak of high energy 

following the storm. It seemed that the initial response to the storms was strongest at M3, while 

the propagation response was strongest at M2. Inertial waves after Katrina were present more 

than 2 weeks after the storm and penetrated quickly to the base of the upper layer. It was 

interesting to note that the energy minimum between 200 and 300 m at mooring M3 may have 

represented the effect of the pycnocline on the downward energy propagation. The amplitudes of 

the inertial oscillations after Hurricane Rita were not as large as the motions excited by 

Hurricane Katrina and didn’t penetrate as deep, but appeared to persist at the surface longer. The 

presence of a cold core eddy in the study region during the passage of these storms likely 

affected the inertial motions greatly. The rate of downward inertial energy propagation was 

roughly 30 m day-1. 

 5-42 
Figure 5.1-39. (Top left) Wavelet power spectrum of the hourly east-west current time-series at ~ 

80 m depth at mooring 3 during deployment 2. The contours are at normalized 

variances of 0.062, 0.125, 0.25, 0.5, 1, 2, 3, and 6, with red being the highest and 

blue being the lowest variance. The black semicircle at the bottom of the figure 

indicates the cone of influence, where the ends of the time-series contaminate the 

signal. (Top right) The global wavelet spectrum gives the time-averaged wavelet 

power over the frequency domain. The blue dashed line is the 90% confidence 

level. (Bottom) The average variance time series gives the frequency-averaged 

wavelet power in the inertial band (0.5 – 2 day period) during the observational 

period. The blue dashed line is the 90% confidence level. 

 5-43 
Figure 5.1-40. Contours of the frequency-averaged wavelet power in the inertial band (0.5 – 2 

day period) during the weeks after Hurricanes Katrina and Rita in the upper 500 

m of the water column at moorings M1 (top), M2 (middle), and M3 (bottom). 

A full water column vertical EOF of the average variance in the inertial band was executed using 

ADCP and current meter speed records from the three moorings. Figures 5.1-41 and 5.1-42 show 

the Principal Component (PC) time series and the vertical amplitudes for the three leading EOF 

modes. Modes 1, 2, and 3 explain ~71%, ~8%, and ~4% respectively of the variance in the 

inertial band energy. It was clear from the timing of the peak values in the PC time series that the 

three modes were related to the tropical storms in the GOM. Mode 1 was closely associated with 

the envelope of inertial energy following Hurricanes Katrina and Rita. Amplitudes of this mode 

decreased away from the storm tracks from M3 to M2 to M1. At mooring M3, the inhibiting 

effect of the thermocline on inertial oscillations was evident, as seen in the minimum amplitudes 

of the first mode around 200 m. Mode 2 had the opposite amplitude for M1 and M2 compared 

with M3. Mode 3 was mostly driven by mooring M3 particularly at depths between 200-500 m. 

 5-44 
Figure 5.1-41. Principal component time-series for the leading modes from the combined threemooring, full water column vertical EOF analysis of the frequency-averaged 

wavelet power in the inertial band (0.5 – 2 day period) during deployment 2. 

Mode one: 71 % of variance (top), mode two: 7.7% of variance (middle), mode 

three: 4.3% of variance (bottom). 

 5-45 
Figure 5.1-42. Amplitudes of leading modes for moorings M1 (left), M2 (center), M3 (right), for 

combined three-mooring full water-column vertical EOF analysis of the 

frequency-averaged wavelet power in the inertial band (0.5 – 2 day period) during 

deployment 2. 

 5-46 
5.1.8.3 1-D Turbulence Closure Model 

The oil industry uses current measurements to design facilities and plan for operations. Strong 

currents are the main concern. Similar to what was experienced during the Eastern GOM Study, 

historical measurements have shown that the main sources of strong currents in the GOM are: 

• The LC and its eddies 

• Hurricanes 

• Bottom currents enhanced by topography (TRWs) 

These phenomena are generally considered in isolation, but operations are now far enough out in 

the GOM that attention is being paid to the possibility that a hurricane and eddy could affect a 

location at the same time. This in fact occurred in the study area during the passage of Hurricane 

Katrina. 

Hurricane Katrina passed near the Eastern GOM moorings while a cold core eddy was sitting 

over the southern portion of the study area, plus was located on the periphery of a strong LCE, 

Eddy Vortex. Figure 5.1-43 shows the locations of Eddy Vortex, as well as the location of a cold 

core eddy sitting over the southern portion of the study area, and their positions relative 

moorings M1, M2, and M3 just prior to the passage of Hurricane Katrina. Figure 5.1-44 shows 

the current speed measured at mooring M3 during Katrina. The measurements were compared to 

the results of a one dimensional turbulence closure model. The initial response on August 29 was 

modeled rather well, but the one dimensional model cannot represent the inertial oscillations 

after the storm passage. 

The inertial oscillations are shown in more detail in Figure 5.1-45. The pass band was from 12 to 

48 hours. As expected, the oscillations had an upward phase propagation and downward energy 

propagation. Figure 5.1-46 shows the oscillations at Mooring 1, just a few miles north of M3. 

The initial response was about the same, but the oscillations were much stronger at M3 than at 

M1. Hurricane Katrina passed about the same distance from the two moorings, but they were in a 

different situation with respect to Eddy Vortex and the cold core eddy shown in Figure 5.1-43, as 

M3 was in the middle of the cold core eddy. The measurements from M3 show that the site 

experienced enhanced inertial oscillations which were likely caused by non-linear interaction 

between the eddy and the hurricane. Figure 5.1-47 shows the lowpass and bandpass speeds at M3 

for the entire second deployment. The lowpass currents were dominated by several intrusions of 

the LC or eddies, but strong diurnal currents only appeared with the combination of an eddy and 

a hurricane. 

The concept that the interaction of the hurricane with the cold core eddy resulted in enhanced 

inertial oscillations was of high interest to the oil and gas industry’s CASE joint industry project. 

With the permission of BOEMRE and the authors, current measurements from the moorings 

during the period of inertial oscillations generated by Hurricane Katrina were provided to 

researchers for that program. In return, their analysis was made available to this study team. The 

analysis is presented in a report (Accurate Environmental Forecasting, Inc. 2007) which is 

contained herein in Appendix F. 

 5-47 
Seattle, December 6, 2006

Figure 5.1-43. Eddy Vortex just before Hurricane Katrina. Mooring 1 is the northern red star and 

Mooring 3 is the southern red star. 

 5-48 
Figure 5.1-44. Measurements at Mooring 3 compared to a one dimensional turbulence model. 

 5-49 
Figure 5.1-45. Diurnal bandpass currents at Mooring 3. 

 5-50 
Figure 5.1-46. Diurnal bandpass currents at Mooring 1. 

 5-51 
Figure 5.1-47. Lowpass current speed at Mooring 3 compared to the diurnal bandpass speed. 

5.2 Hydrography Measurements 

As discussed earlier, the LC and Eddy Vortex impacted the study area and surrounding water 

several times during the measurement period. The impact on the currents in this area have been 

presented earlier. In this section, we discuss evidence of these LC and LCE features on the 

hydrography when the warm surface waters extend below 100m. 

During all three hydrography cruises, the presence of the LC or mesoscale eddy features were 

evident by the depth of the 20° isotherm. These features were discernable when the 20° isotherm 

reached 150-200m depth. During Hydrography Cruise 1 (17-23 January 2005) the southwest 

section of the study area was impacted by a warm water mesoscale feature (Figure 5.2-1). During 

Hydrographic Cruise 2 (18-25 August 2005) the 20° isotherm remained fairly shallow (~100m) 

throughout much of the study area until the conclusion of the cruise. However, as the ship 

steamed toward the northwest, it appeared to have passed near the edge of Eddy Vortex (Figure 

5.2-2). Here the 20° isotherm reaches to approximately 150m depth. 

 5-52 
Figure 5.2-1. Color contour of the depth of the 20° isotherm during Hydrographic Cruise 1 in 

January 2005. Depth scale ranges from near surface (deep blue) to 300 m (dark 

red). 

Hydrographic Cruise 3 (20-28 January) saw the most dramatic and intensive influence from the 

LC (Figure 5.2-3). The same transect line was sampled as the vessel transited into and out of the 

study area (Transects 1 and 2, respectively). These transects gave an indication of how far the 

edge of the LC had migrated north during the cruise. Comparing vertical profiles of these two 

transects further illustrated the presence of the LC. Figure 5.2-4 shows the contour along transect 

1. The 20° isotherm remains at 100 m and above. Figure 5.2-5 shows the contour along transect 

2. Here the 20° isotherm is deep at 150 m at the start of the transect (SE) and rises to above 100 

m going northwestward. Most of the area south of a line bisecting the study area along these two 

transects was sampled in the later part of the cruise. The 20° isotherm has deepened to 150-250 

m, a clear indication of the LC migrating into the study area. 

In the eastern section of the study area (center to east edge) there may have been an indication of 

a possible cold core eddy (Figure 5.2-6). The 15° isotherm rose in the water column as the 

transect moved from the center to the eastern edge of the study area. However, the 15° isotherm 

never rose above 150m. 

 5-53 
Figure 5.2-2. Color contour of the depth of the 20° isotherm during Hydrographic Cruise 2 in 

August 2005. Depth scale ranges from near surface (deep blue) to 300 m (dark 

red). 

 5-54 
Figure 5.2-3. Color contour of the depth of the 20° isotherm during Hydrographic Cruise 3 in 

January 2006. Depth scale ranges from near surface (deep blue) to 300 m (dark 

red). Transect lines (1 through 3) indicate locations of the vertical color contours 

of temperature. 

 5-55 
Figure 5.2-4. Hydrocruise 3 Transect 1 temperature from XBT and CTD casts. Inset shows the 

transect path. 

 5-56 
Figure 5.2-5. Hydrocruise 3 Transect 2 temperature from XBT and CTD casts. Inset shows the 

transect path. 

 5-57 
Figure 5.2-6. Hydrocruise 3 Transect 3 temperature from XBT and CTD casts. Inset shows the 

transect path. 

 5-58 
6.0 DEEP CIRCULATION 

6.1 Overview of Observations of Topographic Rossby Waves in the 

Deep Gulf 

6.1.1 Background 

Comprehensive long-term deep current measurements from moorings in the GOM were not 

made until the 1980’s. These were analyzed by Hamilton (1990) who showed that the variability 

under the LC, in the north-central and northwest Gulf had the characteristics of topographic 

Rossby waves (TRWs) including high coherence through the lower water column, bottom 

intensification, and period and wavevector agreements with the dispersion relation as given by 

Rhines (1970). Hamilton (1990) speculated that pulsations of the LC were the primary source of 

the lower-layer TRWs, and evoked the Malanotte-Rizzoli et al. (1987) model of broad-band 

radiation from a pulsating meander in a channel over a sloping bottom as an explanation of the 

observations. A significant correlation, with a lag of 106 days, was found between deep currents 

under the east side of the LC and a mooring in the northwest GOM that implied a minimum 

group speed of ~ 9 km d-1 in rough agreement with group speeds estimated from the dispersion 

relation (Hamilton 1990). The dispersion relation indicated that TRW-trains propagate generally 

westward at higher group speeds than LC anticyclonic eddies, which translate westward and 

southwestward, at ~ 3 to 6 km d-1, into the western GOM (Elliott 1982; Kirwan et al. 1984). 

Therefore, motions in the lower layer are largely decoupled from the eddy currents in the upper 

layer. Numerical modeling studies of Oey (1996) and Oey and Lee (2002) showed that simulated 

deep currents could be interpreted as TRWs, and the results suggested that TRWs radiated 

towards the northern slope as LC eddies translated across the western basin. Oey and Lee (2002) 

also suggested that the topography and the anticlockwise deep mean flows along the northern 

slope provided sufficient refraction of the TRWs that most energetic deep waves were confined 

to the deep basin. 

 6-1 
Deep currents were previously measured due south of the Mississippi delta at the base of a steep 

500-m escarpment (the Sigsbee escarpment) in 2000 m water depth (I1 in Figure 6.1-1) between 

September 1999 and September 2001 (Hamilton 2007). The flows were highly energetic; a 

maximum speed of 90 cm s-1 was observed 100 m above the bottom (Hamilton and LugoFernandez 2001) with characteristic periods of ~ 10 to 20 days, which were much shorter than 

the previously observed ~ 20 to 100 days (Hamilton 1990). Moreover, a characteristic of these 

currents were that 4 to 5 wave trains were observed over the 2-year interval generally beginning 

with a high-energy burst (speeds > 50 cm s-1) and decaying over the next 3 to 4 months. Each 

wave train had slightly different characteristic wavelengths and periods, indicating different 

geographical source regions. Some could be associated with the presence of LC eddies; however, 

at least one occurred when upper layer eddy activity was weak. Hamilton (2007) speculated that 

these short period waves were being reflected from the steep escarpment rather than refracted by 

the changing bottom slopes, and suggested that the TRWs were locally generated and possibly 

trapped by the bathymetry. Mizuta and Hogg (2004) theoretically modeled TRWs propagating 

onto a shoaling slope. The shoaling slope induced a reflected wave component and a principal 

result was that a mean flow developed over the slope, forced by convergence of boundary layer 

Reynolds' stresses. DeHaan and Sturges (2005) came to similar conclusions in that they 

attributed the observed anticlockwise (i.e. westward) deep mean flow along the base of the 

northern slope to rectification of incident TRWs. 

Malanotte-Rizzoli et al. (1995) proposed wavenumber coupling between a propagating surface 

feature, such as a frontal eddy, and deep flows as an alternate generation mechanism for TRWs. 

Pickart (1995) showed that this mechanism could account for the generation of 40-day TRWs 

that are observed at Cape Hatteras by 40-day eastward propagating meanders of the Gulf Stream. 

Wave trains of TRWs propagate westward and southwestward along the slope in the northwest 

Atlantic, with phase propagation southeastwards toward deeper water. The coupling to eastward 

propagating meanders requires that the bottom slope have a direction such that a 40-day TRW 

wavenumber has an eastward component that matches the eastward wavenumber of the 

meanders. This coupling mechanism may be important for short period TRWs in the GOM 

because energetic cyclonic eddies are observed on the LC front and on the edges of LC eddies 

(Vukovich 1986; Zavala-Hidalgo et al. 2003. However, because waves are observed to have 

wide range of periods between ~ 10 and 100 days, the generation of broadband TRW radiation 

by the large scale movements of the LC and LC eddies (Malanotte-Rizzoli et al. 1987) should 

not be discounted. Hogg (2000) indicated that energetic near bottom currents, with TRW 

characteristics, observed over the tail of the Grand Banks seemed to better agree with broadband 

radiation by the Gulf Stream and warm rings, rather than through meander coupling. 

As noted previously, over the past several years, three major observational programs have taken 

place in the deep waters of the north-central, northwest and the northeast GOM. These studies 

deployed closely spaced arrays of current meter moorings and inverted echo sounders with 

pressure sensors (PIES). The central Gulf study also deployed 36 RAFOS floats at depths 

between 1000 m and the bottom. These observations allow a more comprehensive analysis of 

deep-water circulations, and an extended and refined description of the lower-layer TRW regime 

in the GOM. Thus, the aim of this overview is to review these new data as they pertain to the 

lower-layer below 1000 m, particularly in regard to the generation, propagation and dissipation 

of TRWs, deep mean flows, and possible couplings to upper-layer LC and LCE circulations. 

 6-2 
Figure 6.1-1. Locations of the principal full-depth moorings used in the analyses. The SST 

image is a 3-day composite centered on February 5, 1998, and shows an extended 

LC and a detached LCE (named eddy El Dorado). Image courtesy of John 

Hopkins University Applied Physics Laboratory. 

 6-3 
6.1.2 Data 

Because this overview uses observations from a number of recent MMS studies, as well as from 

this eastern GOM study, the databases will be briefly reviewed here. 

6.1.2.1 Moorings 

The majority of recent full-depth sub-surface, taut-line moorings deployed in the GOM have 

been instrumented with combinations of ADCPs, single point current meters, and temperature 

and salinity sensors. Generally ADCPs are deployed in the upper layer with a common 

configuration being an upward-looking 75 kHz at 450 to 500 m, and below this, point current 

measurements at fixed intervals of 250 m and 500 m above and below 1000 m, respectively. 

Moorings in Mexican waters (W2, W3, W4, W5 and L6: Figure 6.1-1) were also instrumented 

with upward-looking 75 and 300 kHz ADCPs at ~1200 m and ~10 m above bottom, respectively. 

Table 6.1-1 lists the observational studies, their originating institutions, and a subset of these 

moorings are located in Figure 6.1-1. Some of these studies also deployed bottom moorings with 

either 1 or 2 current meters at 500 and/or 100 m above the seabed (MAB) and PIES as part of 

their array designs. Moorings G and GG (Figure 6.1-1) were deployed prior to 1990, and were 

previously analyzed by Hamilton (1990). 

All these records were treated in a uniform manner, similar to the methodologies discussed in 

Chapter 2. In this chapter, current meter moorings will be referred to by a 2 character ID, where 

the first letter is a transect or group identifier, and the second character is the mooring number 

within the group (Figure 6.1-1 and Table 6.1-1). Groups with the same first letter were deployed 

at similar times. Because various subsets of the observations are used in the following sections, 

the depth levels will be identified as they are employed. 

6.1.2.2 RAFOS Floats 

RAFOS floats were deployed in the Exploratory program, and this was the first time such 

instruments had been used in the GOM. RAFOS floats (Rossby et al. 1986) are neutrally buoyant 

glass-tube floats that can be ballasted in the laboratory to drift with the currents below the 

surface at a user selected pressure (roughly depth) or density for extended periods. The floats are 

equipped with temperature and pressure sensors, and with an acoustic hydrophone that listens to 

the arrival times of acoustic signals sent from pre-deployed sound sources. In the Exploratory 

study, the floats received acoustic signals from three sound sources deployed at the sites shown 

in Figure 6.1-2. The sound sources were programmed to transmit every 8 hours. At the end of the 

deployment, the floats surfaced and transmitted their data to shore via satellite. The focus of the 

study was on deep currents, so all the floats were configured to follow pressure as opposed to 

density surfaces. The initial deployment of 30 floats was in April 2003, followed by 6 more in 

October 2003. The former surfaced in April 2004, and the latter at the end of May 2004. The 

floats were launched on a grid pattern over the lower slope in the region encompassed by the L1 

to L4 moorings (Figure 6.1-1). Nominal launch depths were at 500-m intervals between 1000 

and 3000 m, with the majority (15 out of 36) at 1500 m. 

 6-4 
During the course of the Exploratory study, monitoring showed that two of the sound sources 

were failing after 3 months in the water. They were replaced about 6 months into the study. 

Therefore, most of the float tracks have two sections, the first 3 months and the last 6 months of 

the one-year deployments. Again, more details of the RAFOS float part of the Exploratory 

program can be found in Donohue et al. (2006). 

Table 6.1-1 

Moorings Deployed by Observational Studies in the Deep GOM. 

Name Numbers 

Reference 

Institution Dates Locations 

(Fig. 6.1-1) FullDepth 

Bottom PIES 

DeSoto Extn. 

Hamilton et al., (2003) 

SAIC 8/99-8/01 I1 1 4 3 

Exploratory 

Donohue et al., (2006) 

SAIC 4/03-4/04 L1 to L4 4 15 27 

Exploratory LSU 4/03-6/04 L5 1 - - 

Canekito 

Sheinbaum et al., 

(2007) 

CICESE 5/03-8/04 L6 1 - - 

SEBSEP 

Donohue et al., (2006) 

Industry 4/03-5/04 Escarpment 

Transect North of 

L4 

- 6 - 

LSU Long-Term LSU 4/03-6/04 L7 1 - - 

NW GOM 

Donohue et al., (2008) 

SAIC 4/04-7/05 T5 to V4 13 - 10 

W GOM CICESE 8/04-11/05 W2 to W5 5 - - 

NE GOM EHI 1/05-1/06 M1 to M3 3 1 8 

Institutions listed above: 

SAIC – Science Applications International Corporation, Raleigh, NC 

EHI – Evans Hamilton Inc., Seattle, WA 

LSU – Louisiana State University, Baton Rouge, LA 

CICESE – Centro de Investigación Científica Y Educación Superior de Ensenada, Ensenada, 

Mexico 

Industry – DEEPSTAR Oil Industry Consortium 

After the travel times were converted to geographical positions, individual float tracks were 

smoothed using the successive corrections method of Pedder (1993) using a time scale of 1 day, 

and resampled at 6 hour intervals. This was the same as the procedures used by Hamilton et al. 

(1999) for near-surface drifters in the GOM. A spaghetti diagram of all the smoothed tracks 

produced by the 36 floats is given in Figure 6.1-2. 

 6-5 
Figure 6.1-2. Spaghetti plot of all 36 RAFOS float smoothed trajectories at all depths (1000 to 

2500 m) in the Exploratory Study. Sound sources are given by the large 

diamonds, and the beginning of each track is indicated by a square. Arrow heads 

are at 10-day intervals. Most floats have two tracks because of sound source 

failures in the first 3 months of the program (from Donohue et al. 2006). 

6.1.3 Gulf-Wide Overview of Deep Currents 

Generally, in the GOM, the current velocity variability is highly coherent through the lower 

water column at depths greater than 1000 m. One of the fundamental questions is the spatial 

distribution of the depth-integrated eddy kinetic energy (EKE) over the lower water column that 

can be attributed to TRWs. This quantity is a more complete measure of wave EKE than using 

EKE at a single depth level. The former was estimated for each full-depth mooring that was 

deployed in water depths of 2000 m or greater, by calculating the first complex empirical 

orthogonal function (CEOF) using the available velocities from depth levels in the lower part of 

the water column (Table 6.1-2). Thus, 

U(z,t) An (t) en (z)

n

= ⋅ ∑ , (6.1.1) 

 6-6 
where all quantities are complex and the mode amplitude, An, is normalized to unit variance. The 

record means of U were removed before the analysis. The mode amplitudes and eigenvectors, en, 

are relative to an arbitrary reference, and the usual practice (Merrifield and Winant 1989) is to 

rotate the spatial eigenvector into the frame of the semi-major principal axis of the corresponding 

amplitude time series. The depth-integrated EKE between 1000 m and 50 meters above bottom 

(MAB) is given by: 

EKE H = 1

2 ∫ U Udz = 12

* An (t)A(t)

n

*

∑ en (z)en (z)dz

1000

* H−50 ∫

, (6.1.2) 

where the integral was approximated by using the trapezium rule for the discrete measurement 

levels. The integral was terminated 50 m above bottom (H) so as to exclude the bottom boundary 

layer, and for the practical reason that the majority of moorings had no measurements there. In 

the following analysis, only the first mode (n = 1) was used because for most moorings, this 

accounted for a high percentage of the total variance of the input records (Table 6.1-2). The first 

mode also has the characteristics of TRWs with bottom intensification, vertically coherent 

fluctuations (guaranteed by the use of a single CEOF mode), and principal axes that are at a 

small angle to the general trend of the local isobaths. The use of depth levels above 1000 m was 

sometimes necessary to properly characterize the lower-layer velocity profile. In these cases, the 

percent of total variance accounted for by the mode was reduced somewhat over other similar 

locations, because these upper-levels contain some surface layer eddy signals (e.g., GG and L7 in 

Table 6.1-2). 

The lower-layer depth-integrated EKEH for the locations in Table 6.1-2 are given in Figure 6.1-3, 

which also shows the depth-mean standard deviation ellipses obtained from the eigenvectors. 

The highest EKEH was under the LC at G and L7, with the west side having the maximum 

observed energy. Energy levels reduced towards the west and also north of L7; however, 

relatively higher energy levels were observed moving into the escarpment from L7 through L3 

and L5, suggesting a wave propagation path with lower EKEH to the north (M3) and south (L6). 

The base of the escarpment was approximately delineated by I1, L5, L4, GG and V4. It was 

somewhat surprising that the energy level at M3, which was close to the northern LC front for 

most of 2005, was less than at the escarpment further to the west. Moreover M1, which was near 

the steep west Florida escarpment, had essentially negligible lower-layer EKEH. In the west, the 

two deeper locations at V4 and W2 had EKEH comparable to that at 92°W (GG), but again the 

moorings at the base of the steep Mexican slope had small variances with W5 also being 

essentially negligible. Oey and Lee’s (2002) numerical model studies had the result that 20 to 

100 day deep energy was primarily restricted to a band across the northern GOM between the ~ 

3000 and 3500 m isobaths, which had some correspondence to Figure 6.1-3. Radiation by the 

model LC and westward translating LCEs was the attributed source of this deep energy. The 

standard deviation ellipses (Figure 6.1-3) tend to show major principal axes approximately 

aligned with the isobaths near the escarpment and steep topography. On the abyssal plain the 

fluctuations were less rectilinear and the principal axes were at small angles to the isobaths. This 

was particularly evident at L3. 

 6-7 
The normalized amplitude time series for each location are given in Figure 6.1-4. TRW theory 

(Rhines 1970) defines a cut-off frequency, Nα, where N is the lower-layer Brunt-Vaisala 

frequency and α, the local bottom slope, above which waves are not supported by these 

dynamics. The deep GOM topography is roughly bowl shaped; therefore, locations with the 

deeper water depths should tend to have the largest fluctuations at longer periods. This rule holds 

quite well in both the eastern and western parts of the GOM basin, with the dominant periods 

being shorter closer to the continental slope (e.g. W2, M2 and I1) and longer in deeper water 

(e.g., L7, L6, M3 and W3). The spectra of the normalized amplitudes are given in Figure 6.1-5, 

where the relative contributions to the variance clearly show that longer periods tend to dominate 

in deeper water. Two dominant peaks of 50 to 60 days, and 25 to 30 days can be identified with 

water depths of > ~ 3000 m, and ~ 2500 to 3000 m, respectively. The latter peak was prominent 

in the early central and western GOM deep current data (Hamilton 1990), and clearly the 

yearlong records resolve most of the variance at these sites. This was not the case for the very 

deep locations, including the site in the western GOM (W3), where the low frequency tails, with 

periods longer than 100-days, were not resolved. Some of these deep records (W3 and L6) had 

energy also at the 25 to 30 day period peak. In the eastern GOM, the LC pulsation and eddy 

shedding had irregular intervals ranging from about 3 to 18 months (Sturges and Leben 2000), 

and it would be expected that some of this variability would be transferred to the lower-layer. 

The amplitudes at I1, M2 and L3 did not fit into these frequency band classifications. I1 and M2 

had prominent peaks shorter than 30 days. The short period waves at I1, and associated near 

bottom moorings, had been previously analyzed by Hamilton (2007) who suggested that wave 

trains with periods of ~ 8 to 12 days were generated fairly local to the eastern Sigsbee 

escarpment and were trapped there by the topography. The amplitude at L3 is the only one that 

shows fairly uniform energy over a broad band with periods from 10 to ~ 100 days. 

Based on this analysis, frequency domain EOFs were calculated, in a similar manner to the 

CEOFs above, for some or all of three frequency bands, 0.01 – 0.03, 0.024 – 0.05, and 0.05 – 0.2 

cpd based on the spectral content at each location (Figure 6.1-5). Table 6.1-2 gives the 

percentages of total variance in each frequency band, accounted for by the modes, for each 

mooring. In most cases one mode sufficed, but in a few cases two modes were significant 

according to the eigenvalue criteria of North et al. (1982). The depth integrated EKEH and depth 

mean standard deviation ellipses were calculated using similar formulae to those used for the 

time domain CEOF analyses, and are given in Figure 6.1-6. The distribution of EKEH confirmed 

the qualitative evaluation of dominant periodicities from Figure 6.1-4 with the lowest frequency 

(52-day) band tending to have the most energy at 3000 m depth or more with decay towards the 

west from the west side of the LC (L7). The center frequency band (29-day) also had some 

power at L7 and had a more uneven distribution with most of the larger relative contributions to 

the total energy being near the escarpment (e.g., L5, GG and V4, but not L4). The shortest period 

(10-day) band was mainly significant in a small region south of the delta (L3, I1, and L5). 

 6-8 
Table 6.1-2 

Lower-Layer EOF Analysis of Currents by Mooring. 

Mode 1 Percent of Total Variance 

Frequency Bands (cpd) 

Mooring Depth 

Levels (m) CEOF 

0.01-

0.03 

0.024-

0.05 

0.05-0.2 

Start Date 

(yy-mm-dd) 

Length 

(days) 

G 1565, 2364, 

3174 

97.7 63.2/ 

35.3a 

77.3/ 

20.9a 

- 84-07-24 552 

GG 725, 1650 71.8 71.6 80.8 87-11-15 346 

I1 1000, 1200, 

1600, 1800 

88.9 83.7 87.9 84.8 99-09-02 525 

L3 1000, 1500, 

2000, 2500, 

2900 

97.7 94.0 83.2 73.5 03-04-09 363 

L4 1000, 2000, 

2500, 2900, 

3250 

97.0 97.8 77.0 - 03-04-05 365 

L5 1165, 1415, 

1677, 1925, 

2175, 2625, 

2925 

95.0 96.1 96.7 84.4 03-04-22 411 

L6 1005, 1479, 

1985, 2490, 

2995, 3308 

97.2 80.6 87.9 - 03-05-16 465 

L7 500, 2000, 

3000, 3187, 

3256 

85.5 70.4/23.

6a 

69.9/21/6

a 

- 03-04-24 410 

V3 1000, 1500, 

2000, 2400 

77.3 79.9 92.8 - 04-03-25 456 

V4 1000, 1500, 

2000, 2500, 

3000 

92.5 84.5 92.4 - 04-03-24 456 

W2 1000, 1110, 

1544, 1965 

76.4 83.0 83.3 - 04-08-31 431 

W3 1007, 1541, 

2048, 3038, 

3518 

90.9 89.9 62.4/33.4

a 

- 04-08-31 431 

W4 1572, 1941 84.4 - - - 04-08-30 433 

W5 1025, 1125, 

1572, 1998 

61.8 - - - 04-08-30 434 

M1 729, 1224, 

1472, 2479 

84.5 - - - 05-01-26 276 

M2 1037, 1284, 

1532, 2035 

81.0 66.6/20.

0a 

76.9/14.0

a 

53.3/28.4

a 

05-01-25 359 

M3 987, 1234, 

1482, 1985, 

2489, 2689 

92.7 89.2 78.8 - 05-01-24 361 

a

 = Mode 2 

 6-9 
The depth-average modes (Figure 6.1-6b) contained a great deal of information on rms particle 

displacements as a function of frequency. The hodograph ellipses were much more rectilinear 

than their equivalent CEOF modes (Figure 6.1-3), and this is to be expected as TRWs are 

frequency dependant transverse waves (Rhines 1970). Other properties were obtained from the 

dispersion relation under the assumption that fα/H >> β, where β is the gradient of the Coriolis 

parameter, f. For the wavevector, K, with components (k, l), directed parallel and perpendicular 

to the bottom isobaths (α = dH/dy), the wave frequency, ω, is given by: 

ω = −kα N Kcoth(NHK f), (6.1.3) 

The along-isobath wavenumber, k, must be negative, so the wavevector must point into the 2nd 

or 3rd quadrants with the y-axis directed up-slope. It can be shown that the wavevector is 

perpendicular to the transverse velocities and therefore perpendicular to the major axes of the 

ellipses in Figure 6.1-6b. The group velocity, cg (= ∂ω/∂k, ∂ω/∂l) is directed normal to the 

wavevector, such that cg is directed clockwise (upslope) or anticlockwise (downslope) with 

respect to K when the latter points downslope (i.e., into the 3rd quadrant) or upslope (i.e., into 

the 2nd quadrant), respectively. Therefore, the energy propagates along rays that coincide with 

the direction of the major axes of the ellipses in Figure 6.1-6b such that shallower water is to the 

right (Oey and Lee 2002). Another consequence of equation 6.1.3 is that the wavevector rotates 

such that it becomes more perpendicular to the isobaths as the frequency decreases. At the cutoff frequency, Nα, the wavevector points along the negative x-axis and the wave velocities are 

normal to the isobaths. This rotation of the wavevector with frequency is one of the diagnostics 

of TRWs and occurred at locations with gentle bottom slopes such as L3, L6, and L7 (Figure 6.1-

6b). Closer to the escarpment, the ellipse major axes were more constrained to be along the trend 

of the steep slope, as has been noted in previous studies (Hamilton 2007). This implied that the 

wave energy propagated along, rather than across, the escarpment slope. 

Unlike the CEOF modes, some locations, particularly under the LC at G and L7, had more than 

one significant mode (Table 6.1-2) in some of the frequency bands. The inclination of the 

ellipses at L3 implied energy flux towards the northwest and the escarpment at 52 and 29 days. 

At 52 days this was compatible with the mode 2 ellipse at L7, and this mode had about the same 

EKEH as the 52-day mode 1 at L3. Therefore, part of the L7 fluctuations at this period could be 

contributing to the northwest propagation of TRWs towards the escarpment. However, the larger 

proportion of the 52-day energy was in mode 1, and this ellipse and the 29-day mode 1 ellipse 

implied energy flux towards the Campeche Bank, where the topography slopes up to the south 

and TRWs would presumably refract into the southeast corner of the eastern basin. It is possible 

that the lower magnitude northeastward 52-day and the northwestward 29-day fluxes at G may 

have originated from such TRWs on the west-side of the LC, propagating anticlockwise around 

the deep southern half of the eastern basin. If the direction of cg at L3 was towards the 

escarpment, then the direction at L6 of the much weaker fluctuations was southwestward towards 

the center of the western basin and therefore may be a manifestation of reflected TRWs from the 

northward shoaling topography (Mizuta and Hogg 2004). 

 6-10 
Figure 6.1-3. Depth-integrated EKE for the CEOF mode 1 lower-layer currents at the locations 

identified in Table 6.1-2 (thick vertical bars). The standard deviation ellipses are 

representations of the depth-average lower-layer mode 1 currents (scale given by 

the arrow). 

The overall view of TRWs in Figure 6.1-6 suggests considerable complexity in both the 

frequency and energy content of the fluctuations, and it also suggests possible propagation paths 

of wave packets. The indication from the available observations is that the deepwater region on 

the west side of the LC, just north of the Campeche Bank, had very high lower-layer kinetic 

energy which may be radiating towards both the west and south. The escarpment between 90 and 

92°W turned the northwestward propagating waves into along-slope fluctuations. In the 

northwest corner, energy levels were small compared to the eastern GOM and the central parts of 

the escarpment. 

 6-11 
Figure 6.1-4. CEOF mode 1 normalized amplitudes for lower-layer currents. The abscissa is 

elapsed time in days from the beginning of each time series. The depths below the 

mooring IDs are the lower-layer integration depths below 1000 m. 

 6-12 
Figure 6.1-5. Spectra, in variance preserving form, for the normalized CEOF mode 1 

amplitudes of the lower-layer currents. The color codes give the mooring location 

and lower-layer thickness, and red is used for the largest depth-integrated EKE in 

each group. The thick gray lines are the subjectively averaged spectra. 

Further evidence for the dominance of TRWs in the lower-layer came from the deep Lagrangian 

float tracks of the Exploratory Study. If linear TRWs were the only process operating in the 

lower-layer, then to first order, floats placed in such a field would simply oscillate in a rectilinear 

fashion about their deployment point with the direction and amplitude of the displacements 

changing with changing period of the waves propagating through the area. This would be a 

completely different pattern to that shown by near-surface drifters deployed in the cores of 

upper-layer eddies, which had the characteristics of translating loops (e.g., Kirwan et al. 1984; 

Hamilton et al. 1999). Examination of Figure 6.1-2 shows that the deep float tracks more closely 

resembled the former rather than the latter. This was most noticeable in the eastern basin, under 

the LC, where the large amplitude displacements had both clockwise and anticlockwise motions 

that were often adjacent in time. There are several tracks that began less than half a degree apart, 

and after six months, ended in the same vicinity, still less than half a degree apart. Of the 36 

floats deployed, only one had a section of track that was consistent with a translating cyclonic 

eddy. In Figure 6.1-2, three anticlockwise loops were observed moving in towards the western 

slope between 24 and 25°N, and 93 to 96°W. This apparent deep eddy is discussed in Donohue 

et al. (2008). The other exceptions to the general meandering over the same region were the 

tracks that moved close to the escarpment where they were transported westwards in a relatively 

narrow stream. This appeared to be the main route by which floats, initially deployed around 

91°W, get to the western part of the basin. It was also noteworthy that almost no floats crossed 

the escarpment from the abyssal plain to the northern slope. The 4 tracks north of the escarpment 

in Figure 6.1-2 were all at 1000 m and therefore were more likely to be influenced by the lower 

circulations of surface-layer eddies. 

 6-13 
Figure 6.1-6. a) Depth-integrated EKE as a function of frequency band. Where more than 1 

mode is present, the height of the bar represents the total EKE, and the colors 

show the split between the modes. b) Depth average mode eigenvectors 

represented as hodographs for each frequency band. Mode and band colors are the 

same as for a). 

 6-14 
Mizuta and Hogg (2004) modeled the refraction and reflection of upslope propagating TRWs 

onto uniform shoaling topography. Their principal result was that incident and reflected waves 

produced a convergence of Reynold’s stresses in the bottom boundary layer that forced an alongslope mean current that would be concentrated where the bottom slope (α) began to increase. 

The depth structure of this mean flow was similar to, but not necessarily exactly the same as the 

incident TRWs. DeHaan and Sturges (2005) used more heuristic arguments on the rectification 

of TRWs by a topographic slope to explain the limited observations of cyclonic mean flow along 

the base of the northern slope in the GOM. The present expanded currents database, including 

the deep Lagrangian floats, can be used to extend and further confirm the existence of substantial 

westward mean flows along the Sigsbee escarpment. 

Means and standard deviations of float velocities were calculated by defining rectangular areas 

that were adjacent to and aligned along the escarpment. The sections of all smoothed float tracks 

which passed through and were within the rectangle, excluding the two deployed at 1000 m, 

were used to calculate velocities using centered finite differences. The ensemble average of these 

velocity estimates produced the statistics for the box location. The method is similar to DiMarco 

et al.’s (2005) estimation of gulf-wide velocity statistics using near-surface drifters. In addition, 

Lagrangian velocity statistics were estimated for 1° latitude-longitude squares centered on 

selected mooring locations for the purpose of forming a comparison with Eulerian estimates 

using current meter measurements. The nearly barotropic nature of the flows below 1000 m 

meant that mixing floats from 1500, 2000, 2500 and 3000 m depth, into a single lower-layer 

estimate, was unlikely to bias the results. The means and standard deviation ellipses from both 

floats and moorings are shown in Figure 6.1-7, with supporting data in Table 6.1-3. The degrees 

of freedom (dof) were estimated using velocity time series from nearby moorings to calculate the 

autocorrelation time scales. Given the varying dominant periodicities with location, the estimates 

were less reliable at deeper water depths. The standard error of the mean is given by: 

SE = σ v / dof , (6.1.4) 

where σv is the standard deviation along the principal major axis of the ellipse. For the western 

boxes 1 and 2, the time scale was interpolated from moorings W2 and W3 to the 3000 m isobath 

(Figure 6.1-7). 

Mean currents from both moorings and floats showed consistent westward flows along the 

escarpment that seemed to form a continuous current from around 89°W to below 24°N on the 

Mexican slope. The variances were also reasonably consistent between floats and moorings even 

where the measurements were taken in different years. In the western GOM, the float mean for 

box 2 was in the same direction (SSW) as that at W2, but had a smaller magnitude, which was 

either a consequence of different measurement periods or the mean flows were concentrated 

close to the base of the slope. Jet-like mean flows over the steepest part of the escarpment were 

analyzed in Donohue et al. (2006) for a transect around 91°W. Of interest is that floats that 

moved southwards from the northwest corner near 26°N followed the 3000 m isobath (Figure 

6.1-2). This helps to explain why the EKE at W5 was so weak since the source of the energy was 

in the northwest corner and also followed the general direction of the 3000 m isobath leaving 

shallower areas of the lower western slope in a shadow zone. 

 6-15 
Figure 6.1-7. Lower-layer mean currents from RAFOS floats (red) and lower-layer current 

meters (purple). Mean velocity scale is 5 cm s-1. The dashed boxes are the 

averaging areas for the floats, and the escarpment box location numbers refer to 

Table 6.1-3. The float (blue) and current meter (cyan) standard deviation ellipses 

use a scale of 10 cm s-1. The light gray shaded area shows the steepest slope (500 

m descent) of the Sigsbee escarpment. 

 6-16 
Table 6.1-3 

Time Scales and Degrees of Freedom for Lagrangian and Eulerian Velocity Statistics 

Location Longitude 

Latitude 

Box 

Size 

Number 

Tracks 

in Box 

Mean 

Float/CM 

Depth 

(m) 

Number 6-h 

Velocity 

Estimates 

Autocorrelation 

Time Scale 

(hours) 

dof SE 

(cm s-1)

1-L 95.60°N 

23.37°W 

1.5°

x.5° 

23 2053 2810 60 28

1 

0.2 

2-L 95.42°W 

25.18°N 

1.5°

x.5° 

15 1796 1577 60 15

8 

0.5 

3-L 93.70°W 

25.99°N 

1.5°

x.5° 

25 2108 1468 95 93 0.5 

4-L 92.16°W 

25.67°N 

1.5°

x.5° 

22 1810 1151 100 69 0.7 

5-L 90.66°W 

26.28°N 

1.5°

x.5° 

34 1761 1375 122 68 0.9 

L5-E 90.82°W 

26.34°N 

2625 1644 122 81 1.5 

L7-L 

L7-E 

86.97°N 

25.52°N 

1°x1

° 

29 1656 

3187 

1465 

1642 

240 37 

41 

1.8 

2.2 

M3-L 

M3-E 

87.53°W 

27.61°N 

1°x1

° 

12 1856 

2689 

1071 

1436 

140 46 

62 

1.1 

1.0 

M1-E 87.55°W 

28.35°N 

2479 1444 79 11

0 

0.3 

L1-E 89.22°W 

27.60°N 

1400 1523 62 14

7 

0.8 

L2-E 91.11°W 

27.10°N 

1650 1485 45 19

8 

0.3 

L3-E 88.96°W 

26..09°N 

2900 1451 61 14

3 

1.0 

L4-E 91.13°W 

25.92°N 

3250 1462 100 88 0.9 

L6-E 90.50°W 

25..09°N 

2995 1861 190 59 0.9 

V3-E 94.95°W 

26.05°N 

2400 1823 90 12

2 

0.5 

V4-E 94.09°W 

26.04°N 

3000 1823 95 11

5 

0.7 

W2-E 95.44°W 

25.39°N 

1965 1725 40 25

9 

0.3 

W3-E 94.89°W 

25.27°N 

3518 1727 175 59 0.8 

W5-E 96.30°W 

24.04°N 

1998 1735 35 29

7 

0.2 

-L = Estimated from Lagrangian floats. 

-E = Estimated from moored current measurements. 

 6-17 
6.2 Basic Statistics from Moorings 

The basic statistics of the deep moored 40-HLP currents for the Eastern GOM Study are 

presented in Figure 6.2-1. This figure includes the nine-month records (May 2005 to January 

2006) from the LSU mooring at L7, and two deep 6 month long (July 2005 to January 2006) 

records from bottom mounted 37.5 kHz ADCPs on the Alabama – Mississippi lower slope. The 

latter were from the MMS Notice to Lessee’s (NTL) program and were collected by industry at 

drilling platform locations as reported to NDBC. The data were archived by NDBC, who 

performed the initial QA/QC. The data are for NDBC platform numbers 42374 and 42375, in 

1670 and 1950 m water depths, respectively. No useable upper-layer currents were available 

from these platforms. The L7 LSU mooring was deployed at the same site, and was similarly 

configured to the earlier mooring discussed in Section 6.1. The statistics for L7 and the NTL 

ADCPs were calculated for the longest possible records that overlap the Eastern GOM Study 

deployments (January 2005 to January 2006). 

Because of the high vertical coherence in the lower water column, only two levels are given in 

Figure 6.2-1. The upper level was at a nominal 1200 m depth and is just below any direct 

influence of upper-layer LC flows. The near-bottom vectors were from the closest measurement 

from the seabed that would not be influenced by the frictional bottom boundary layer, i.e., at 

least ~ 100 m above bottom. In some cases (e.g., at M2) the instrument at 500 m from the bottom 

was used because of instrument problems with the bottom-most level. 

The deep mean flows were northward at L7, and were similar to the 2003-2004 results for this 

same location (Figure 6.1-7). This implies fairly consistent mean flows occurred at this location 

during the two study periods. However, the LC was similar in its location during both studies, 

being in a generally extended state while these moorings were deployed. The fluctuations, 

however, had less variance than for the earlier interval, though they were still more energetic 

than the M locations further north. The lower water column still contained considerably more 

EKEH because of the approximate doubling of the thickness of the lower water column between 

M3 and L7. The L7 fluctuations were also bottom intensified between 1200 and 3000 m. Nearbottom mean flows at M3 and M4 were westward towards the escarpment south of the delta. At 

M3, and to a lesser extent at M2, the mean currents at 1200 m were essentially negligible, which 

was a contrast to the more depth independent means at L7. Where the slope was steeper (M1, 

42374 and 42375), the means tended to follow the isobaths. 

The standard deviation ellipses at M2 and M3 clearly showed evidence of bottom intensification, 

with principal axes directed westward and southwestward, respectively, across the isobaths into 

shallower water, which is characteristic of TRW motions. The moorings on the steep slope had 

low energy, except that 42374 was slightly more energetic; however, this site seemed to be in a 

different slope regime than the lower slope moorings M1 and 42375 (see below). Previous deep 

measurements on the lower Alabama – Mississippi slope, between the 1500 and 2000 m 

isobaths, have shown very weak currents there. 

 6-18 
Figure 6.2-1. Mean (LH panel) and standard deviation ellipses (RH panel) for currents 100 to 

500 m above bottom (red) and ~ 1200 m depth (blue) except for 42375 where the 

upper level is at 1560 m. Note the change in velocity scales between the panels. 

6.2.1 Event Analysis 

The stick plots of the low-frequency deep velocities for the moorings in Figure 6.2-1 are given in 

Figure 6.2-2. Only two or three depths below 1200 m are plotted because of the very high 

coherence of the observations in the lower water column. Under the LC at L7, the fluctuations of 

the currents were predominantly northwards with few reversals, were depth independent from 

1200 to 3200 m, had relatively long periods (~ 30 days or more), and had the maximum speeds 

(~ 30 cm s-1 in late December 2005) of all these measurements. For the M2, M3 and M4 

moorings, the fluctuations were more variable in amplitude, had more frequent reversals, and had 

somewhat shorter characteristic periods. There was clearly a decrease in energy moving from 

south to north over the 45 km spacing from M3 to M4 and M2. On and near the slope, at M1, 

42374 and 42375, the fluctuations were much less energetic, with amplitudes mostly less than 5 

cm s

-1, and their characteristic periods were much shorter, generally less than ~ 20 days. 

The summer and fall of 2005 was one of the most active hurricane seasons on record. A number 

of very strong hurricanes passed fairly close to the moorings as shown in Appendix A and in 

Figure 6.2-3. The center of Hurricane Katrina passed close to L7 on August 28, 2005 at which 

time it was classified as a category 4 hurricane. In the deep current records, there was evidence 

of low-frequency pulses at some of the deep-water moorings when the storms were intense and 

passed fairly close to the moorings. A short-lived northward pulse of ~ 20 cm s-1 was observed in 

the lower water column at L7, which stood out from the background flows. A month later, a 

similarly intense Rita passed by L7 at a greater distance, but there was no obvious pulse from the 

hurricane. 

 6-19 
 6-20 

In contrast, moorings M2, M3 and M4 on the abyssal rise showed no discernable response to the 

passage of these major storms. However, the continental slope near-bottom currents at M1, 

42374 and 42375, did show consistent short period pulses or rotary fluctuations (e.g., at 42375) 

at the times of the closest approaches of the major hurricanes Dennis, Katrina and Rita. The 

strongest response was at the shallowest site 42374, and here the initial amplitude was clearly 

proportional to the distance of the paths from the location. Previous measurements by Teague et 

al. (2007) on the upper Alabama – Mississippi slope during the passage of hurricane Ivan in 

2004 had shown a short period (2 to 5 days) TRW wave response of the slope to this storm. It is 

reasonable that the lower slope could be part of the same slope wave-guide that facilitates a lowfrequency response to these intense storms. It is noteworthy that all three of the 2005 hurricanes 

that generated slope TRWs passed over the edge of the west Florida shelf break near the dry 

Tortugas where the slope turns eastward into the Florida Straits entrance. Thus, short period 

disturbances could propagate along the slope to the measurement sites on the Alabama – 

Mississippi slope as suggested by Hetland et al. (1999). 

Deep circulation was punctuated by a number of energetic low-frequency events. Figure 6.2-4 

shows deep EKE and variance ellipses from the combined PIES and deep current meters. As 

noted above, EKE within the array increased to the south. The lower panel of Figure 6.2-4 shows 

the array-averaged EKE as a function of time. The six largest EKE peaks identified six deep 

events referred to here as events a through f. Figure 6.2-2 also shows these energetic lowfrequency events. Maps of altimeter-derived SSH for the eastern basin put the measurements in 

context of the larger-scale LC, and the high resolution lower-layer streamlines and geostrophic 

bottom currents overlaid with PIES derived SSH showed the local relation of the bottom flows to 

the upper-layer. These maps are provided (Figures 6.2-5a-f) for each event indicated in Figures 

6.2-4 and 6.2-2, generally centered about the middle of the local EKE maxima. In addition, 

Figure 6.2-6 presents a hovmuller plot of lower-layer streamfunction and upper-layer 

geopotential height along a transect that coincided with a deep eddy propagation route within the 

array. In the discussion below of the deep events, references will be made to deep cyclones and 

anticyclones. This is just shorthand for deep cyclonic and anticyclonic circulations for which 

there is little evidence that they contain translating closed cores in the same sense that upper 

layer eddies do. As discussed extensively in Donohue et al. (2008), the present view is that 

apparent deep cyclones and anticyclones are primarily the result of packets of dispersive TRWs. 
6-21 

Figure 6.2-2. Stick plots of the 40-HLP currents for the indicated moorings and depths. The event lines (co

storms and shaded for strong low frequency fluctuations) are discussed in the text. The labeled correspond to the events marked in Figure 6.2-4, and are further illustrated in Figures 6.2-5a-fmoorings 74, 75, and M1 is at 15 cm s-1 (top) and the other moorings are at a speed scale of 30 cm 
Figure 6.2-3. Tracks of the center low pressures of tropical storms and hurricanes that passed 

over the Gulf of Mexico in 2005. 

 6-22 
The late April 2005 event, with south or southwestward flows over the main part of the array and 

northwest flows at M1, occurred when the LC was extended well towards the delta. During this 

time the study region was dominated by a LCFE with southeastward flows at M2 and M3 along 

the LC front and reversed flows on the north side of the cyclone at M1 (Figure 6.2-4a). The 

lower layer streamlines were approximately normal to the upper-layer flows and the strong 

currents are caused by a deep cyclone in the southern part of the array. The LC remained in this 

configuration for most of April, May and June, though the cyclonic LCFE propagated along the 

front towards the southeast and possibly merged with another cyclone during this interval. The 

persistence of the upper-layer flows at M3 through this interval is shown in Figure 6.2-7 and as 

the LC front moved further over the site in May, the southeastward currents at M3 strengthen. 

M3 was within the LC when the salinity at 125 or 200 m depth was greater than 36.7 indicating 

the presence of subtropical underwater (SUW) that constitutes the core of the LC and LC eddies. 

In the lower-layer, the deep anticyclone in the northeast part of the study area strengthened and 

moved southeastward. The cyclone decayed in early May or possibly moved out of the study 

area towards the southeast, which was approximately in the direction of the surface LC front. 

The deep cyclone either moved into the study area from the east at the beginning of the event or 

intensified in place. The apparent growth and decay of deep vortexes without any direct 

connection to upper-layer forcing could be considered evidence for the planetary wave-like 

nature of lower-layer circulations. 

The three following events, in May, August and early December, at M3 had similar behavior to 

each other (Figure 6.2-2) which was a northward pulse accompanied by a cyclonic rotation of the 

velocity vectors. This was very similar to the characteristic velocity signal produced by a Gulf 

Stream cyclonic frontal eddy at the shelf break in the south Atlantic Bight (Lee and Atkinson 

1983; Bane et al. 1981). The corresponding spatial maps are given in Figures 6.2-5b, c and d, 

respectively. In all three cases the events’ cyclonically rotating velocity vectors were caused by 

an anticyclone-cyclone pair translating fairly rapidly southeastward through the array (Figure 

6.2-6). This was again the general direction of the surface LC front, and the M moorings were on 

the northeast edge of this front. In all these three cases the cyclone – anticyclone pair appeared to 

propagate southeastward, intensify in the southeast corner of the array and possibly decay in 

place. There was an intriguing consistency with the surface layer LC flows, because the deep 

cyclone tended to follow and remain locked to an upper-ocean high (Figure 6.2-6 and Figure 6.2-

5b through d). Note that in each case the PIES maps revealed a richer structure (more curvature) 

along the cyclonic edge of the LC than the satellite SSH maps. The connection to the upper-layer 

flow was difficult to discern due to the limited window of the array and the inability of the 

satellite SSH product to resolve the small spatial and rapid time scales associated with frontal 

perturbations and/or instabilities of the LCFE flows. 

 6-23 
The event at the end of December (Figure 6.2-2) had very similar characteristics, for both upper 

and lower layer flows, to the event in April (compare Figures 6.2-5e with 6.2-5a and note the 

lack of southwestward propagation of these features in Figure 6.2-6). The LC and an incipient 

LC eddy extended to the northwest, and a fairly stationary cyclonic frontal eddy dominated the 

upper-layer flows in the study area (Note the presence of cold, less saline water at M3 in Figure 

6.2-7). This cyclone was larger and more vigorous than the one in April-May. The lower layer 

flows at M3 and M4, and to a lesser extent at M2 were dominated by a cyclone, which, similar to 

the event in April, intensified in place and then decayed while moving out of the study area 

towards the southeast. At the same time, the deep anticyclone to the north began to strengthen. 

The deep strong northward flows at L7 that began in the middle of December, appeared to be 

unrelated to the deep circulations in the study area. The upper layer at L7 was clearly within the 

main part of the LC front (Figure 6.2-5e). By the middle of January 2006, the upper-layer 

circulation had not changed much (Figure 6.2-5f); the LC eddy was still attached but had moved 

westward, and the LC front was further north and the study area moorings were primarily on the 

northern side of the cyclonic frontal eddy. In the lower-layer however, the cyclone and 

anticyclone were in the reversed positions with the cyclone to the northeast of the anticyclone, 

which produced the large northeast flows at M2 (Figure 6.2-2). The deep cyclone may have 

moved in from the west and intensified. The deep eddy pair began to move southwards just 

before the end of the data records. 

The common characteristics of these events were the presence of deep high and low pressure 

centers with separation length scales of ~ 50 to 100 km that intensified and decayed while 

propagating south or southeastwards in the general direction of the overlying front of the eastside of the LC. Lower and upper layer streamlines invariably crossed at right angles during the 

more energetic lower-layer events. The significance of this is not clear at present; however, a 

more quantitative analysis of possible upper-lower layer connections is given in Chapter 7. 

6.3 Topographic Rossby Waves North of the Loop Current 

Kinetic energy spectra for the lower-layer currents from the study area moorings (M1-M4) plus 

L7 are given in Figure 6.3-1. The latter had an 8-month record compared to the 12-month records 

of the M moorings, so spectral resolution was not as good at L7. For the analysis, 3 or 4 depth 

levels were used beginning at ~ 750 m, which was likely to be influenced by upper-layer LC 

currents. However, most of these 750 m spectra showed energy at the same frequencies as the 

deeper spectral peaks, indicating that there may be connections between upper and lower layer 

regimes. The M1 spectra showed very low energy and have very little in common with the 

moorings further south. M2, M3, and M4 had a prominent peak at 20 days; M3 and L7 had 

energy at longer periods with peaks at 30 to 35 days. M2, M3 and L7 showed bottom 

intensification at depths below 1000 m, whereas at M4 the fluctuations were essentially depth 

independent through the 100 m separation of the measurements. Therefore, except for M1, the 

lower layer signals had spectra characteristic of TRWs. Low frequency near-bottom EKE 

increased towards the west and south from M4, which was noted also in the overview analysis. 

This is made clearer in Figure 6.3-2, where the highest energy near-bottom spectra from each 

mooring are plotted on one graph and common peaks at ~ 30, 25 and 20 days are highlighted. 

 6-24 
Figure 6.2-4. Upper panel: Mean lower-layer (2500 m) eddy kinetic energy averaged between 

27 January to 19 January 2006 contoured every 20 cm2

s

-2. Bathymetry contoured 

every 500 m depth with gray lines. PIES sites are indicated by diamonds, and 

current meters denoted by circles. Bottom panel: Array-average mean lower-layer 

eddy kinetic energy. The six strongest events are highlighted by the red line along 

the bottom x-axis and labeled consistently with Figures 6.2-5a-f. 

 6-25 
Figure 6.2-5a. The LH panel shows the 3-day composite SST overlaid with CCAR altimeterderived SSH for April 25, 2005. Upper layer 1-day averaged currents at 50 and 

250 m depth are given for the moorings. The RH panels show PIES-derived SSH 

(thick lines) and the stream function (solid color; blue shades cyclonic, pink 

shades anticyclonic) and currents at 2500 m. The blue and black arrows are 

observed and mapped geostrophic currents, respectively. 

TRW wavelengths were estimated by calculating the frequency domain EOF modes for the 

records at 100 to 500 m above bottom (MAB) on moorings M2, M3 and M4. The horizontal 

wavenumbers were found by least-square fits to the mode phase angle differences across the 

array in the same manner as Hamilton (1990). Based on the spectra, two frequency bands were 

analyzed, and the results are given in Table 6.3-1. Also in Table 6.3-1, the results of the vertical 

analysis of the 2005 - 2006 L7 lower-layer velocities are given, and for convenience, the similar 

results are repeated, from Table 6.1-2, for L7 from the 2003 – 2004 interval. 

 6-26 
Figure 6.2-5b. The LH panel shows the 3-day composite SST overlaid with CCAR altimeterderived SSH for May 22, 2005. Upper layer 1-day averaged currents at 50 and 

250 m depth are given for the moorings. The RH panels show PIES-derived SSH 

(thick lines) and the stream function (solid color; blue shades cyclonic, pink 

shades anticyclonic) and currents at 2500 m. The blue and black arrows are 

observed and mapped geostrophic currents, respectively. 

 6-27 
Figure 6.2-5c. The LH panel shows the 3-day composite chlorophyll concentration overlaid with 

CCAR altimeter-derived SSH for August 1, 2005. Upper layer 1-day averaged 

currents at 50 and 250 m depth are given for the moorings. The RH panels show 

PIES-derived SSH (thick lines) and the stream function (solid color; blue shades 

cyclonic, pink shades anticyclonic) and currents at 2500 m. The blue and black 

arrows are observed and mapped geostrophic currents, respectively. 

 6-28 
Figure 6.2-5d. The LH panel shows the 3-day composite SST overlaid with CCAR altimeterderived SSH for December 6, 2005. Upper layer 1-day averaged currents at 50 

and 250 m depth are given for the moorings. The RH panels show PIES-derived 

SSH (thick lines) and the stream function (solid color; blue shades cyclonic, pink 

shades anticyclonic) and currents at 2500 m. The blue and black arrows are 

observed and mapped geostrophic currents, respectively. 

 6-29 
Figure 6.2-5e. The LH panel shows the 3-day composite SST overlaid with CCAR altimeterderived SSH for December 26, 2005. Upper layer 1-day averaged currents at 50 

and 250 m depth are given for the moorings. The RH panels show PIES-derived 

SSH (thick lines) and the stream function (solid color; blue shades cyclonic, pink 

shades anticyclonic) and currents at 2500 m. The blue and black arrows are 

observed and mapped geostrophic currents, respectively. 

 6-30 
Figure 6.2-5f. The LH panel shows the 3-day composite SST overlaid with CCAR altimeterderived SSH for January 16, 2006. Upper layer 1-day averaged currents at 50 and 

250 m depth are given for the moorings. The RH panels show PIES-derived SSH 

(thick lines) and the stream function (solid color; blue shades cyclonic, pink 

shades anticyclonic) and currents at 2500 m. The blue and black arrows are 

observed and mapped geostrophic currents, respectively. 

 6-31 
Figure 6.2-6. Snapshot of upper and lower layer circulation on 

May 23 (bottom panel) with surface geopotential 

referenced to 2500 m denoted by colored lines and 

bottom streamfunction indicated by filled colored 

contours. PIES sites are diamonds, current meters 

are circles. The thick black line represents the 

frequent translation route of deep cyclones. Upper 

(middle) panel: Hovmuller plot of lower-layer 

streamfunction (surface geopotential) along the 

transect shown in the circulation map (bottom 

panel). Six strong lower-layer events (a through f) 

labeled and denoted by black stars correspond to the 

strongest EKE events shown in Figure 6.2-4. 

Contour intervals and color scales for upper and 

lower layer circulation are consistent between the 

Hovmuller plots and the circulation map. 

 6-32 
Figure 6.2-7. Upper layer 40-HLP currents, temperatures (solid contours) and salinities 

from mooring M3. The gray shading corresponds to the deep current events (a 

through e) marked in Figures 6.2-2 and 6.2-4. 

 6-33 
Table 6.3-1 

EOF and Wavenumber Analysis of Eastern GOM Deep Currents 

Mooring 

Group 

(with depths 

(m)) 

Analysis 

Interval 

Dates 

Frequency 

Band 

(cpd) 

Center 

Period 

(days) 

Mode 

Number 

% Total 

Variance 

Wavelength

(km) 

1 64.1 222 0.033-0.045 25 

2 30.0 146 

1 62.7 162 

M2 (2035), 

M3 (2489), 

&M4 (2530) 

2005-01-27 

2006-01-19 

0.010-0.033 60 2 17.6 338 

0.033-0.045 25 1 78.9 

1 72.7 

L7 

(875,1200,1500, 

2000,2500,3000) 

2005-06-03 

2006-01-28 0.010-0.033 60 2 25.1 

0.024-0.050 27 1 69.9 

1 70.4 

L7 

(500,2000,3000, 

3187,3256) 

2003-04-24 

2004-06-07 0.010-0.030 61 2 23.6 300† 

†Estimated from backward ray trace given in Figure 6.3-3. 

The results of the Eastern GOM Study analysis for the 60-day period band are shown in Figure 

6.3-3. This figure also shows the EKE and the velocity hodographs for the mode 1 EOF analysis 

of the near-bottom currents in the Exploratory array (redrawn from Donohue et al. 2006). In the 

M2, M3 and M4 moorings, the highest 60-day energy was at M3 and mode 1 reflected this. The 

wavelength calculated from the phase differences was 162 km, which was within the range of 

previously derived estimates in the deep GOM (Hamilton 1990; 2007). The direction of the 

major axes of the 1st mode ellipses indicated that phase propagation was south or southeastwards 

and thus corresponded to the propagation direction of the deep eddies described in Section 6.2.1. 

The second mode was barely significant and the derived wavelength was larger than expected, 

suggesting that this weak signal was not a propagating wave. TRW ray tracing from the full 

dispersion relation, employing the same methods described in Donohue et al. (2006) and 

Hamilton (2007) and using the 162 km initial wavelength and a 60-day period, showed that a 

TRW could reach the upper escarpment in about 40 to 45 days, but the region of impact was an 

area of low energy as measured by the earlier study. However, if the ray is moved slightly 

southward so that it favors the larger fluctuations at M3, then it is apparent that this northeastern 

OMf region could potentially supply some energy to the northern part of the high EKE region 

below the escarpment. Southward displacement of the ray could also be caused by the westward 

mean flow along the escarpment as discussed by Oey and Lee (2002). This effect was not 

included in the ray tracing calculations given here. Hamilton (2007) did attempt to crudely model 

a mean escarpment current and found some displacement of the rays near the escarpment; 

however, not including this effect did not significantly change the results. The long transit times 

and the relatively low energy compared to the southern edge of the exploratory array probably 

favored dissipation of these 60-day TRWs before they impacted the escarpment region. 

Backward ray tracing of this 60-day wave indicated that the source region was probably between 

the 3000 and 2500-m isobaths, because at depths deeper than 3000 m the group velocities 

become very small which caused the ray to be terminated. The direction of this backward ray 

was similar to the direction of the eastern LC front as described in Section 6.2.1. 

 6-34 
Figure 6.3-1. Variance preserving kinetic energy spectra for selected lower-layer 

velocity observations at moorings M1-M4 and L7. 

 6-35 
Figure 6.3-2. Variance preserving kinetic energy spectra for near-bottom 

velocity observations on the indicated moorings. Note the 

L7 spectra is for a different time interval than those for the 

M moorings. 

 6-36 
In the Exploratory program, a wavelength of 203 km was determined for a 61 day TRW 

originating in the southeast corner of the array where the 1st mode signal was large (Figure 6.3-

3). The path of the forward ray corresponded nicely to the high-energy region below the 

escarpment, particularly if reflection is assumed at the point where the ray encounters the steep 

slope. The 60-day period energy above the escarpment was essentially negligible and the energy 

along the transmitted forward ray was rapidly attenuated to the west. A backward ray-trace 

showed that L7 lied on the energy propagation path, and the mode 2 oscillations from the L7 

lower layer analysis from the same interval as the Exploratory program (Table 6.3-1 and Figure 

6.3-3) lined up with ray quite closely. The wavelength at L7 from the backward ray path was 300 

km, and this was consistent with the almost depth independent nature of the fluctuations of both 

modes, which implied a trapping depth (1/λ) on the order of the water depth (3340 m). The 

trapping depth is related to the wavelength for constant N by: 

NK f , (6.3.1) λ =

Using a wavelength of 300 km, and N = 10-3 s-1, gave an estimated 1/λ of ~ 3000 m. The transit 

time from L7 to the escarpment was ~ 25 days, which was much less than the transit time from 

the northern M array. 

A similar EOF analysis for the 2005-2006 interval at L7 also showed two modes with the major 

axes of the ellipses normal to each other, but at approximately 45° to the modes of the earlier 

interval. In 2003 and 2004, the LC axis was more northerly directed (Donohue et al. 2006) than 

the more northwesterly trend in 2005, and this perhaps had an influence on the genesis of the 

TRW modes along the west side of the LC. The slightly differing results at L7 suggested, not 

surprisingly, that there was inter-annual variability in the deep TRW regime. If the west side of 

the LC is the primary generation zone for longer period TRWs then the northern and southern 

rays in Figure 6.3-3 implied a reduction in horizontal area between the rays as they approached 

the escarpment. This would indicate an increase in energy if dissipation is disregarded and could 

account for the large amplitude 60-day fluctuations observed next to the escarpment in Figure 

6.3-3. 

 6-37 
The EOF analysis of wavelengths were also conducted for 20 to 25 day periods (Table 6.3-1 and 

Figure 6.3-4). In the horizontal EOF analysis of the three M moorings, the first two modes were 

significant and the directions of the major axes of the ellipses at M3 and M4 implied that energy 

was propagating up-slope (mode 1) and down-slope (mode 2). With the estimated wavelengths 

from the phase analysis, the ray tracing produced two similar ray paths towards the escarpment 

because the down-slope ray was reversed by the topography. The backward ray paths were also 

similar and pointed to the M1 location, which had very low energy in this frequency band 

(Figure 6.3-2). This implied again that the generation zone was fairly local to the deeper parts of 

the study area. The 25-day forward ray paths implied that the M moorings could be an upstream 

source for the relatively weak fluctuations at the shallower eastern end of the escarpment. Transit 

times would be in the range of ~ 12 to 15 days. The mode 1 EKE and hodograph ellipses for the 

Exploratory program (Figure 6.3-4) again showed that the largest amplitude fluctuations were 

below the escarpment between 90 and 91.5°W. The 22.4-day ray paths initiated in the southeast 

corner of the Exploratory array aligned nicely with the more energetic ellipses, with an 

indication that both reflected and transmitted rays contributed to the variance in the west. Again 

the effects of persistent mean flows near the escarpment have been neglected. The rapid damping 

of the fluctuations above the escarpment seemed to show that the transmitted ray was dissipated 

by the rough topography there. The backward ray path implied that the L7 site was too far east to 

contribute to the 20 to 25-day energy at the escarpment. At L7 during 2005 mode 1 dominated, 

and the direction of the ellipse major axis implied that TRWs with this period at this location 

were primarily propagating towards the Campeche Bank and were likely to be refracted into the 

southern part of the eastern basin as discussed in Section 6.1. Therefore, these shorter period 

TRWs in the Exploratory region appeared to have more than one source with the shallower part 

of the escarpment most likely influenced by the northeast, and the deeper part seemed to have 

source regions further south but not under the LC, as seemed to be the case for the longer period 

waves. 

6.3.1 Wavelet Analysis 

Wavelet transforms are localized functions of time-scale and frequency that are used to expand 

time series into time-frequency space, and therefore, can find localized intermittent periodicities. 

In this investigation, Continuous Wavelet Transforms (CWT), specifically the complex Morlet 

transform, were used because they are better for feature extraction and revealing patterns. The 

time-scale of a Morlet wavelet very nearly equates to its equivalent Fourier period. The analysis 

follows Torrence and Combo (1998), where the significance levels for the wavelet power 

spectrum are calculated using the theoretical red-noise spectrum for a univariate lag-1 

autoregressive process. The lag-1 autocorrelation coefficient (α) in this study was estimated by 

the non-linear least-square fit of the Fourier spectrum of the time series to the theoretical rednoise spectrum. The time-averaged or global wavelet spectrum has been shown to provide an 

unbiased and consistent estimation of the true Fourier power spectrum of a time series. Torrence 

and Combo (1998) also define a “cone of influence” where end of time series effects can distort 

the analysis, and the regions of the time-frequency space where this occurs increase with the time 

scale of the wavelet. 

 6-38 
Figure 6.3-3. West of 89°W, the near-bottom (100 to 500 MAB) EKE is contoured for the 335-

33 day EOF mode 1 velocities from the Exploratory Program. The elliptical 

hodographs show the mode 1 currents at each mooring with arrow heads giving 

relative phase. The EOF modes for similar near-bottom currents at the M 

moorings in the eastern GOM are also shown. At L7, the red and orange modes 1, 

and the blue and green modes 2 ellipses are for the lower-layer velocities for the 

Eastern GOM Study and Exploratory Study time intervals, respectively. The thick 

black lines are TRW ray traces initiated at the blue dots with the indicated periods 

and wavelengths. The reflected ray is given by the dashed line. Arrow heads are 

every 5 days. 

 6-39 
Figure 6.3-4. West of 89°W, the near-bottom (100 to 500 MAB) EKE is contoured for the 33-

17 day EOF mode 1 velocities from the Exploratory Program. The elliptical 

hodographs show the mode 1 currents at each mooring with arrow heads giving 

relative phase. The EOF modes for similar near-bottom currents at the Y 

moorings in the eastern GOM are also shown. At L7, the 3000-m ellipse is from 

the 25-day EOF analysis of the lower-layer currents using the Eastern GOM 

Study time interval. The thick lines are TRW ray traces initiated at the blue dots 

with the indicated periods and wavelengths. The reflected ray is given by the 

dashed line. Arrow heads are every 5 days. 

 6-40 
The wavelet power spectra were calculated for the cross (u) and along (v) isobath components of 

the 2500 m currents at M3 (Figure 6.3-5). The distribution of power with time and frequency 

showed that there was more significant variance at shorter periods in the u- than the vcomponent, and that the v-component dominated at longer periods. This was expected from the 

dispersion relation (6.1.3) for TRWs, because the principal major axis of the fluctuations rotates 

from across- to along-isobath as the wave period increases. This further confirmed that the 

lower-layer motions in the study area were dominated by TRWs as such a pattern would not be 

expected from translating eddies. The global spectra showed little significant power at periods 

longer than 80 days and the ~ 60 and 25-day peaks corresponded to the Fourier spectra in Figure 

6.3-1 and the ray tracing given above. Figure 6.3-5 also shows that the fluctuations were 

intermittent but that times of significant power occurred throughout the summer (May through 

August, 2005) when the LC was extended to the northwest and Eddy Vortex was undergoing a 

sequence of detachments and reattachments. After the final separation and the rapid translation 

of Eddy Vortex to the west at the beginning of September, the power decreased below the 95% 

significance levels, particularly at shorter periods. This suggested that the presence of the LC or 

a LCE over the study area had a direct influence on the amplitudes of the lower-layer TRWs. 

A similar wavelet analysis was performed for the 2500 m currents at L3 for the Exploratory 

Study. As shown by Figure 6.3-3, L3 can be considered to be downstream of the LC, and it was 

of interest to see if similar patterns were observed there as compared to the northeast side of the 

LC front where M3 was situated for much of 2005. The u and v-component wavelet power 

spectra for L3 are given in Figure 6.3-6. The cross-isobath u-component had significant power at 

shorter periods compared with the along isobath component. The EKE spectrum for L3 (Figure 

6.1-5) was noteworthy in that it had fairly broad power over periods from 10 to 100 days. The 

global power in Figure 6.3-6 shows that the u- and v-components dominated at periods of 10 to 

30 days and 40 to 100 days, respectively. The power in both period bands had higher amplitudes 

from June to September 2003, while Eddy Sargassum formed and separated. Eddy Sargassum 

was similar to Eddy Vortex in that its initial location, before translating into the western GOM, 

was in the northern part of the eastern basin. Eddy Titanic on the other hand, detached in January 

2004 much closer to the Campeche Bank, and its initial southwestward path was close to and 

parallel to the steep southern slope. The wavelet power at L3 showed some increase around the 

time of Titanic’s separation, particularly in the u-component, but the amplitudes were not 

significant at the 95% level. Therefore, there were some indications that TRW activity north and 

west of the LC increases during LC extensions and LCE separations as would be expected from 

the models of TRW generation by a pulsating meander over a uniform sloping bottom 

(Malanotte-Rizzoli et al. 1987). It is however, by no means conclusive because of the limited 

number of events observed by these studies. 

 6-41 
Figure 6.3-5. RH panels show the local wavelet power spectrum of the velocity components 

from M3 at 2490 m for the indicated time interval using the Morlet wavelet 

normalized by the variances of the respective series. The thick solid contours 

encloses regions of greater than 95% confidence for a red-noise process with the 

indicated lag-1 (α) coefficients. The lighter shades indicate the “cone of 

influence” where edge effects become important. Separation events for LCE 

Vortex are shown by thick vertical lines, with final detachment in red. The LH 

panels show the respective global (time-averaged) wavelet spectrum (solid lines). 

The dashed lines show the mean red noise spectrum (lower), and the 95% 

confidence levels (upper) for the global wavelet spectra, given their respective 

α’s. 

 6-42 
Figure 6.3-6. RH panels show the local wavelet power spectrum of the velocity components 

from L3 at 2500 m for the indicated time interval using the Morlet wavelet 

normalized by the variances of the respective series. The thick solid contours 

encloses regions of greater than 95% confidence for a red-noise process with the 

indicated lag-1 (α) coefficients. The lighter shades indicate the “cone of 

influence” where edge effects become important. The red event lines show the 

detachment dates of LCE’s Sargassum and Titanic. The LH panels show the 

respective global (time averaged) wavelet spectrum (solid lines). The dashed lines 

show the mean red noise spectrum (lower), and the 95% confidence levels (upper) 

for the global wavelet spectra, given their respective α’s. 

 6-43 
7.0 VERTICAL COUPLING 

Establishing relationships between observations of upper and lower circulations in the deep 

GOM has proved to be difficult over the years. Generally, currents above 800 m and below 1200 

m have not been correlated at significant time scales. There have been intriguing events where 

flows appear to be similar through the whole water column; however, they were not long lasting 

and generally quite rare. A few examples of these events are noted for the I1 mooring in 

Hamilton (2007), where they were mostly associated with peripheral cyclones or frontal eddies 

on LCEs. To further evaluate potential vertical coupling between the upper and lower layers, an 

approach was taken to use CEOF analysis in the time domain of the depth profiles of currents, 

which further established the two-layered nature of the flows, followed by an examination of 

relative vorticity, ζ, and potential vorticity (PV) in these layers. 

7.1 CEOFs 

The CEOF analysis is similar to that employed for the lower-layer currents in Chapter 6. Time 

domain CEOFs are used rather that frequency domain EOFs because the 1-year time series of 

upper-layer currents do not resolve the ~ 6 to 18 month fluctuations of the LCE shedding cycle. 

Another approach using dynamical normal modes, which are a theoretical decomposition of 

current profiles based on the vertical profiles of the Brunt-Vaisala (buoyancy) frequency, is also 

used. This analysis has many similarities to the purely statistical CEOFs. A limitation of dynamic 

modes is that the bottom is assumed to be level, and this precludes any bottom intensification of 

the currents. 

The analysis of the vertical currents profiles concentrates on the M3 mooring, because it had the 

best one-year coverage of all the full-depth moorings in the Eastern GOM Study area. Similar 

analyses for the M1 and M2 moorings were qualitatively the same as for M3. Initially upper and 

lower layer CEOFs were calculated for 6 levels of demeaned currents in each layer with the 987 

m level being common to both. The results are given in Figure 7.1-1a and the first mode for each 

layer accounted for > 90% of the total variance of each set of 6 records. The upper-layer mode 

was strongly sheared, and approximately unidirectional with the principal axis directed 

approximately north – south. Clearly the 987 m level currents were only weakly coherent with 

the mode. The lower-layer currents were highly coherent with the lower-layer mode 1 from 1000 

m to the bottom. The mode CEOFs were again unidirectional, with the principal axes being more 

along the isobaths trending southwest to northeast and showed an increase in amplitude towards 

the bottom. Therefore, it was reasonable to associate the upper-layer mode 1 fluctuations with 

the LC and its peripheral cyclones, and the lower-layer mode 1 with TRWs. 

The complex amplitude time series of the modes (normalized to unit variance) are given in 

Figure 7.1-2, which also shows the observed 40-HLP currents at M3. Apart from visual 

differences arising from the different axis rotations, it can be seen that the upper and lower layer 

modes closely resembled the observed currents from the upper layer (179 m) and lower layer 

(987 and 1985 m), respectively. Correlations between the modes were not significant for the vcomponent at any lag and barely significant (-0.26: 99% significance level = 0.16) at zero lag for 

the u-component. 

 7-1 
Figure 7.1-1. Depth profiles of CEOF amplitudes (cm/s) from a) separate analyses of upper and 

lower layer currents at M3, and b) full water column analysis of normalized 

currents at M3. The solid and dashed lines are the denormalized and normalized 

amplitudes, respectively. 

 7-2 
Figure 7.1-2. Mode 1 amplitude vector time series (top panel: upper-layer; bottom panel: lowerlayer) from the M3 CEOF layer analysis. The middle panels show 40-HLP current 

observations from 3 depths on M3. 

 7-3 
This two-layer analysis indicated that there was minimal connection between the modes that 

accounted for > 90% of the variance in each layer. To analyze the total water column at M3, the 

CEOFs were calculated for 5 levels in each layer and at the 987 m level. Because the velocity 

variances were an order of magnitude larger in the upper water column than near the bottom, the 

complex velocities were normalized to unit variance, so that each level was equally weighted and 

the parts of the water column above and below 1000 m had the same number of records. Two 

modes accounted for 93.3% of the total normalized variance of the 11 velocity records (Figure 

7.1-1b). The mode velocity profiles were plotted with normalized magnitudes and also 

“denormalized” by multiplying by the standard deviation of each velocity record. Currents at 983 

m and below were highly coherent with mode 1. The correlations then decayed towards the 

surface. Therefore, this was essentially the bottom trapped TRW signal, even though the upperlayer denormalized magnitudes increased towards the surface. The latter was not significant and 

was a result of weighting by the much larger upper layer variances. However, this mode did 

indicate that some of the signal above 1000 m was attributable to TRW motions. 

Mode 2 was primarily surface intensified and was clearly similar to the upper-layer mode 1 in 

Figure 7.1-1a. However, it also had a weak almost depth-independent expression, in the opposite 

direction below1000 m, that had small, barely significant correlation coefficients. The zero 

crossover point was at about 800 m, and this mode closely resembled the dynamical normal 

mode 1, discussed in Section 7.2. The lower layer had a small contribution from upper-layer LC 

or eddy fluctuations through dynamical coupling, just as the upper layer had a small contribution 

from TRW flows decaying upwards through the water column. Therefore, the separate layer and 

full water column CEOF velocity modes were essentially equivalent and indicated only very 

weak interactions. 

7.1.1 Potential Vorticity 

The measurements on the three full-depth moorings allowed for calculations of layer potential 

vorticity. The Ertel potential vorticity (PV) for a layer bounded by isopycnals is conserved in the 

absence of dissipation, and is defined as: 

ζ + f

h , (7.1-1) 

PV =

where ζ = ∂v /∂x −∂u /∂y

u(

 is the relative vorticity, ƒ is the Coriolis parameter, and h is the layer 

thickness, bounded by isopycnal surfaces. The relative vorticity, ζ, is calculated for fixed depth 

levels from current measurements by fitting planes to the three measurements. Thus, 

x, y,z,t) = u0 + x∂u /∂x + y∂u /∂y

v(x, y,z,t) = v 0 + x∂v /∂x + y∂v /∂y , (7.1-2) 

where (x,y) are measured from the center position of the subset of the array used for the 

estimates. The results are normalized by the local Coriolis parameter (ƒ = ~ 6.5 10-5 s-1). The 

north-south and east-west extents of the array are 82 and 30 km respectively, and therefore the 

calculation of ζ has these implicit scales that are appropriate for the larger frontal or peripheral 

eddies. The potential vorticity anomaly is defined as: 

 7-4 
PVA = ζ + f

h − fH , (7.1-3) 

where H is a constant and represents the thickness of the layer at rest. Normalizing by H/ƒ, 

PVA = h

H ζ

f

+

h

H −1 ⎛

⎝ ⎜ ⎞ 

⎠

⎟ 

, (7.1-4) 

where the term in parentheses represents the stretching effect (sometimes defined as the 

Sverdrup PVA) as a fraction of ƒ/H. PVA is a linear function of PV and is therefore also a 

conserved quantity. 

Layer thicknesses, h, were estimated by averaging isotherm depths, calculated by linear 

interpolation between temperature sensors at the M1, M2 and M3 locations, and the appropriate 

ζ was found by vertically averaging ζ(x,y,z,t) between delineating isotherms, using common 

depths for the three moorings and equation 7.1-2 for the horizontal velocity gradient estimates. 

Common velocity depths were between 76 and 428 m with 8 m spacing, and at a nominal 750, 

1500 and 2300 m. In the calculations below, only two layers were considered: between the 

surface and the 8 °C isotherm, and between the 8 °C isotherm and the bottom. The statistics for 

the two layers are given in Table 7.1-1. 

Time series of ζ, for the upper and lower layers, along with the depths of the 15 and 8 °C 

isotherms are given in Figure 7.1-3, where the color shading differentiates between cyclonic 

(cold) and anticyclonic (warm) eddies (ζ > and < 0, respectively). These time series were 

compared with the surface relative vorticity calculated from the PIES array, which put the major 

events in a larger scale context (Note that the opposite sign convention was used here than for ω

calculated from the PIES. The PIES derived ζ resolved smaller horizontal scales, but were 

calculated using surface geostrophic velocities rather than observed sub-inertial velocities as was 

done here. However, the results were quite similar. The relative vorticity was at a maximum near 

the surface and decreased with depth through the upper layer. It then showed a slight increase 

towards the bottom, similar to the vertical profile of velocity variances. There was some 

correspondence between the lower and upper layer peaks in ζ, indicating a connection that was 

not apparent in the velocity fluctuations. The depth of the 8 °C isotherm had been used to 

delineate the lower parts of LC eddies, and here it was a reasonable choice for the interface 

between the upper and lower layers, given the vertical distribution of temperature observations 

on the three moorings. A slightly better choice would have been the 6 °C isotherm depth, which 

was used for the layer PV analysis from the PIES given below. However, in the moored 

temperature measurements, the depth of the 6 °C isotherm was not as well resolved as the 8 °C. 

For the most part the 8 °C isotherm lies between 400 and 750 m where ζ has smaller magnitudes, 

and showed the expected relations with deep and shallow excursions corresponding to 

anticyclonic and cyclonic flows, respectively. Mean relative vorticity in both layers was positive. 

In the upper layer the relatively large mean value (5% of ƒ) was a consequence of the array being 

on the east and cyclonic side of the LC front for most of the study interval, as well as from the 

frequent passage of cyclonic frontal eddies. 

 7-5 
Table 7.1-1 

Potential Vorticity Parameters 

Layers 

Mean 

Thickness 

H (m) 

Depths of 8 °C 

Isotherm (m) 

Layer 

Mean Layer Std. Dev. 

< ς f > < ς ′ 2 f 2

( )>1/2

Maximum 

Correlation 

Coefficient 

Lag 

(days) 

Surface to 

8°C 550 Minimum 428 0.052 0.103 

8°C to 

Bottom 2150 Maximum 758 0.008 0.021 

0.42 

(0.16)† 

1 

(Surface 

Lags) 

†99% Significance Level 

The upper and lower layer vertically averaged relative vorticities were significantly correlated 

(Table 7.1-1), though some of the correlation was caused by the upper layer ζ leaking below the 

8 °C isotherm depth (Figure 7.1-3). The coherence squared and phase differences between the 

upper and lower layer averaged ζ, as well as ζ at the 300 and 2300 m depth levels, are given in 

Figure 7.1-4. There was significant coherence at TRW frequencies in the 20 to 35 day period 

band, with the upper layer lagging the lower layer by ~ 90°, that was suggestive of baroclinic 

instability mechanisms (McWilliams 2006). 

Time series of PVA (Equation 7.1-4) and its constituent terms (ζ and stretching: H/h-1) are given 

for both layers in Figure 7.1-5, which showed that for many events the stretching term dominated 

(e.g., the warm and cold eddy events in May-June and October-November, respectively), and 

because the stretching terms were inversely correlated in the two layers, this contributed to the 

overall coherence of the total PVA of the layers. However, there were other events when the 

stretching was weak and ζ dominated the total PVA (e.g., the events in March-April, and at the 

beginning of August and the middle of December). 

The coherence squared and phase differences between the layer PVA, and for each layer between 

ζ and the stretching term (Figure 7.1-5) showed that, for the upper layer, ζ correlated quite well 

with stretching, as can be visually ascertained in Figure 7.1-3. In the lower layer, only the 25-30 

day period band was coherent, which corresponded to the same frequencies for which ζ was 

coherent between the layers (Figure 7.1-4). The relation between lower layer stretching and 

relative vorticity at 25 to 30 days indicated active TRW generation by the upper layer, because 

the total layer PVAs were coherent at these frequencies (Figure 7.1-5). In the Chapter 6 analysis 

of lower layer currents at M3, the wavelet power (Figure 6.3-5) showed that 16 to 32 day period 

fluctuations were prevalent and significant during June to August when Eddy Vortex was 

attaching and detaching from the extended LC. Therefore, there is some evidence that eddies, 

and their local upper-layer PV fluctuations that have a substantial stretching component, have a 

relation to 25-30 day TRWs in the lower layer. The latter will radiate westward towards the 

escarpment as indicated by the ray paths in Figure 6.3-4. 

 7-6 
Figure 7.1-3. Relative vorticity (as a fraction of f) contoured for the upper layer, and as time 

series for the lower layer (1500 and 2300 m) calculated for the M1, M2 and M3 

moorings. The upper layer contour plot is overlaid with the depths of the 15 and 

8°C isotherms. 

 7-7 
Figure 7.1-4. Coherence squared and phase differences 

between upper and lower layer averaged ζ

(red lines), and ζ at 300 and 2300 m (blue 

lines). 

7.2 Dynamic Modes 

7.2.1 Vertical Structure of Low-Frequency Variability 

7.2.1.1 Empirical Orthogonal Function (EOF) Analysis 

Empirical orthogonal function (EOF) analysis, also known as principal component analysis is an 

accepted tool to quantify patterns of variability in large sets of time-series data that are of 

sufficient spatial distribution (Emery and Thomson 2001; Preisendorfer 1988). We employed an 

EOF analysis to the Eastern GOM Study current meter data in a manner consistent with previous 

studies in the GOM (Nowlin et al. 2001). In those previous studies, mooring locations which had 

at least 5 depth levels distributed throughout the water column were chosen for analysis. At the 

time, only one mooring containing high vertical resolution from a moored current profiler was 

publicly available. EOF analysis was also performed on current output from a three-dimensional 

general circulation model of the full GOM basin (Kantha et al. 2005). The general conclusion of 

the previous studies showed consistent vertical modal structure at several locations across the 

northern slopes of the GOM. The structure was consistent for coarse and fine vertically resolved 

current observations. 

 7-8 
Figure 7.1-5. Potential vorticity anomalies and their component relative vorticity and stretching 

terms for the upper and lower layers with interface defined by the 8 °C isotherm 

(lower panel). The upper panel shows coherence squared and phase differences 

for the indicated upper and lower layer quantities. 

 7-9 
Nowlin et al. (2001) found that the first mode, Mode 1, defined as the mode with the greatest 

percentage of variance, had a surface maximum that decreased exponentially with depth. Mode 

2, containing the second largest percentage of variance, was bottom intensified with a zerocrossing or minimum in the upper 500 meters and barotropic (nearly constant) at depth. The 

interpretation of these previous results concluded that the dynamics of the low-frequency 

variability of the GOM can be interpreted as a two-layer system. The dynamics of the upper 

layer were associated with the exponentially decaying with depth motions of the LC and LCEs. 

The depth defining the transition to the lower layer was coincident with the sill depth of the 

Florida Straits. The bottom intensification for these analysis was attributed to the influence of the 

sloping topography on available normal dynamic modes estimated from stability theory 

(Charney and Flierl 1981). This interpretation was supported by the conclusion drawn from the 

spectral character and vertical profiles of the basic statistical parameters presented in Chapter 5 

of this report. 

It is important to recall however, that EOF modes are purely statistical constructs and in 

themselves do not represent physical processes. Therefore, the decomposition of statistically 

derived EOF modes are typically regressed onto dynamic modes to refine their interpretation. 

We begin this section by describing the EOF calculation performed for this study. Then, a 

description of the dynamic mode analysis of the Eastern GOM Study hydrographic data is given. 

Next, time series of dynamic modal amplitudes are estimated by regressing dynamic modes onto 

vertical profiles of current observations. Finally, correlations of sea surface height gradient and 

dynamic mode time series are estimated and presented. 

The vertical EOF decomposition of east-west and north-south velocity component data was 

performed at each mooring, for each deployment, using data at approximately 12 depth levels 

that were distributed throughout the water column. Due to computation considerations of 

memory and computing time, data from each gap-filled single point current meter and five depth 

levels of the ADCP data were used in the calculation. All current data were 40-hr low-passed 

filtered and decimated to daily values to remove tidal, inertial, and other high frequency motions. 

The sequence of plots shown in Figures 7.2-1 – 7.2-6 shows the results of the EOF. These plots 

affirmed that the horizontal current structure in this region of the GOM resembles a 2-layer 

system. The eddy field caused intensification of the surface currents, which exponentially 

decayed in magnitude with depth to ~ 800 m. This structure was observed in the Mode 1 

amplitudes, which contained the largest percentage of variance (~ 80 - 95 %) (Table 7.2-1). This 

mode showed maximum amplitudes at the surface that decreased with depth to nearly zero below 

1000 m. The dynamic effect of eddies were rarely seen below 800 m; the sill depth of the Florida 

Straits. An energy minimum was present at 800-1000 m, evidenced by the small amplitudes of 

the prevalent first mode at this depth. 

 7-10 
Table 7.2-1 

EOF Mode Variance 

Percentage of variance in EOF Modes 1, 2, and 3 for mooring M1, M2, and M3 for velocity 

components during deployment 1 and deployment 2 (in parentheses). 

Mode 1 Mode 2 Mode 3 

M1 

u-component 96.51 (88.12) 2.33 (6.38) 0.47 (2.62) 

v-component 95.43 (88.37) 2.80 (6.44) 0.72 (2.21) 

M2 

u-component 93.53 (79.48) 3.24 (12.77) 1.81 (5.82) 

v-component 95.58 (96.06) 2.52 (1.98) 0.86 (1.24) 

M3 

u-component 84.67 (88.47) 10.36 (6.83) 3.23 (3.18) 

v-component 87.66 (85.96) 8.09 (11.49) 2.85 (1.43) 

The second mode, Mode 2, explained the second largest percentage of variance. In general, the 

amplitude crossed zero near 200 m depth and was nearly constant or gradually increasing with 

increasing depth. During deployment 1, the amplitude of Mode 2 at mooring M1 showed a midwater maximum at 300 and 1000 m. The structure of this mode however, was more similar to the 

vertical structure found in Mode 3 at moorings M2 and M3. Further, the percentage of variance 

in the second and third modes increased from M1 to M3, indicating more variance in the higher 

order modes closer to the Loop Current. During the second deployment, Mode 2 at mooring M1 

again resembled higher order modes at M2 and M3. However, the percentage of variance in 

modes 2 and greater was a maximum in the east-west velocity component of mooring M2 and 

was generally greater during deployment 2 than for deployment 1. 

The vertical structure of Mode 3 was more complex, with two zero crossings typically in the 

upper 1000 m and relatively constant in water depths below 1000 m. The amount of variance 

contained in this mode was a small fraction of the current variance (< 4 %). 

 7-11 
Figure 7.2-1. Vertical EOFs of east-west and north-south current velocity at 

mooring M1 during deployment 1. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-12 
Figure 7.2-2. Vertical EOFs of east-west and north-south current velocity at 

mooring M1 during deployment 2. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-13 
Figure 7.2-3. Vertical EOFs of east-west and north-south current velocity at 

mooring M2 during deployment 1. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-14 
Figure 7.2-4. Vertical EOFs of east-west and north-south current velocity at 

mooring M2 during deployment 2. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-15 
Figure 7.2-5. Vertical EOFs of east-west and north-south current velocity at 

mooring M3 during deployment 1. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-16 
Figure 7.2-6. Vertical EOFs of east-west and north-south current velocity at 

mooring M3 during deployment 2. Top three panels: Principal 

component (PC) time series of first three empirical modes. Bottom 

panel: Amplitudes of empirical modes corresponding to PC time 

series. 

 7-17 
7.2.1.2 Dynamical Mode Analysis 

The estimation of dynamic modes was motivated by the desire to identify horizontally 

propagating wave solutions under the Boussinesq approximation for a rotating fluid (LeBlond 

and Mysak 1978). The method solves an eigenvalue equation for a prescribed stability profile, 

N(z). The resulting vertical eigenfunctions are the allowable structures for that stability. “The 

eigenfunctions are real, orthogonal with real eigenvalues. The gravest mode is identified as the 

barotropic mode, and the modes n=1,2,3,... are the sequence of baroclinic modes” (LeBlond and 

Mysak 1978). The calculations which follow presumed a flat ocean bottom. 

Stability profiles were derived from temperature and salinity (CTD) data from hydrographic data 

collected adjacent to mooring sites M1, M2, and M3 during the Eastern GOM Study. The CTD 

data were used to calculate vertical buoyancy modes that represent the mean horizontal current 

structure at the three mooring locations. Note that the modes were calculated using a discretized 

version of the Taylor-Goldstein equation for a linear, flat-bottomed ocean (Klinck 1999). 

Temporal and spatial means were not removed from the CTD data prior to mode calculation. 

Although the theoretical modes are based on a resting ocean, neutral modes of an ocean with a 

surface-intensified mean flow are important for studies of baroclinic instability. The results 

should vary significantly when mean flow is included in the model, as the modes in this case 

become dependent on lateral scales of motion (Gill et al. 1974; Wunsch 1997). The density field 

in the upper 500 m is vital to the determination of mode structure (Wunsch 1997). Because 

hydrographic data was only available from three Eastern GOM Study cruises at two different 

times of the year in a region where the LC is constantly altering the density field, hydrographic 

cruise data evaluated in the MMS Deepwater Physical Oceanography Reanalysis and Synthesis 

of Historical Data Study (Nowlin et al. 2001) were also analyzed for comparison, and yielded 

similar results. 

Figure 7.2-7 shows locations of the Eastern GOM Study mooring sites and the locations of 

historical casts that were averaged to create mean temperature and salinity profiles for the 

Eastern Gulf (east of 89° W). Figure 7.2-8 shows the temperature and salinity relationship in the 

waters of the eastern GOM, and clearly indicates water masses of Caribbean origin. Subtropical 

Under Water (SUW), is identified by salinity values greater than 36.5 at depths of ~ 200 m 

(sigma-theta between 25 and 26 kg/m3

), and is associated with the presence of the Loop Current 

and young warm core eddies in the study region. Vertical profiles of Brunt-Vaisala frequency, 

shown in Figure 7.2-9, were found to be a maximum between 100 - 200 m during the winter and 

near the surface (< 20 m depth) during the summer. Dynamic modes calculated from CTD casts 

at (or closest to) the mooring sites during deployment, maintenance, and recovery cruises were 

used to create an average set of modes to fit to the velocity data collected during mooring 

deployment. 

 7-18 
Figure 7.2-7. Location of BOEMRE Eastern Gulf of Mexico Circulation Study (EGOM) 

moorings and MMS Deepwater Physical Oceanography Reanalysis and Synthesis 

of Historical Data stations in the eastern Gulf of Mexico (east of 89° W) that were 

used to estimate dynamic modes. 

Figures 7.2-10 – 7.2-15 give the normalized dynamic modes constructed from the casts at each 

mooring deployment. The barotropic mode was simply equal to one throughout the water 

column. First and second baroclinic modes had similar shapes at each mooring. The first mode 

crossed zero around 600 m; the second mode crossed zero twice, around 200 and 900 m. Below 

1200 m all modes were barotropic, i.e., nearly constant with increasing depth. As can be seen, 

the general shape of these modes was the same for each deployment. The relative amplitudes 

were nearly identical; the principal difference between casts was the depth of zero-crossing of 

the modes. 

 7-19 
Figure 7.2-8. T-S plot of CTD, XBT, and Nansen/Niskin bottle data collected between 1915 

and 2000 and analyzed in the MMS-funded Physical Oceanography Reanalysis 

and Synthesis of Historical Data Report (Nowlin et al. 2001) and CTD cast data 

from three EGOM cruises taken near each of the three EGOM mooring sites. 

Density as sigma-theta (kg m-3) is also depicted on this plot. 

 7-20 
Figure 7.2-9. Vertical profiles of Brunt-Vaisala frequency at 

or nearest to each mooring site based on three 

EGOM hydrographic cruises in January 2005, 

August 2005, and January 2006. 

 7-21 
Figure 7.2-10. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at mooring M1 from 

cruises in January and August of 2005. 

Figure 7.2-11. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at mooring M1 from 

cruises in August 2005 and January 2006. 

 7-22 
Figure 7.2-12. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at mooring M2 from 

cruises in January and August of 2005. 

Figure 7.2-13. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at mooring M2 from 

cruises in August 2005 and January 2006. 

 7-23 
Figure 7.2-14. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at M3 from cruises in 

January and August of 2005. 

Figure 7.2-15. Normalized barotropic and first two baroclinic modes 

calculated with averaged casts at M3 from cruises in 

August 2005 and January 2006. 

 7-24 
The temporal variation of the barotropic and first two baroclinic modes were estimated using a 

least squares minimization that fits the calculated set of vertical modes to synoptic vertical 

profiles of the moored ADCP and single-point current meter data. Three modes were used in the 

least squares fit. The modes were not normalized prior to the fitting. The sequence of Figures 

7.2-16 – 7.2-27 shows a three-panel representation of the results of the least squares fit of the 

first three dynamic modes to the current profiles. Each figure corresponds to a single 

deployment, mooring, and velocity component. The top panel represents the spatial (vertical) 

correlation of the fit with the observed profile. Correlations of one indicated a perfect fit with no 

residual error, less than one indicated higher order (n > 2) modal variability. The bottom panel 

shows the time-series of the first three dynamic mode amplitudes resulting from the fitting 

procedure. The right panel shows the time correlation between the observed and modeled time 

series at a particular depth. This was an indication of the vertical structure of the goodness of fit. 

Generally, the barotropic time series amplitudes were significantly smaller than the baroclinic 

amplitudes at all moorings, both deployments, and both velocity components. As found 

previously in the EOF analysis, most of the variance in the observed velocity data can be 

explained by a surface trapped mode that decays exponentially with depth. Therefore, we expect 

that the temporal amplitudes of the first baroclinic mode to be large and to indicate the presence 

of surface trapped, i.e., eddy related, motions. The amplitudes of the second dynamic mode were 

more variable, i.e., possessed higher frequency motions, than the first baroclinic mode and were 

small relative to the amplitudes of the first baroclinic mode. During the first deployment, the 

east-west velocity amplitudes were mostly positive, i.e., eastward, because of the location of the 

mooring relative to the location of the northeastern edge of the LC. In general, mode amplitudes 

were greater during the first deployment, as more surface intensified, high-speed current eddy 

events were encountered in the spring and summer of 2005 than during the fall and winter of 

2005–2006. The high correlation between mode 1 amplitudes and CTD pressure records, which 

fluctuated due to mooring draw down, were also validation of the first baroclinic mode 

amplitudes as indicators of eddy activity in the eastern GOM. 

Spatial correlation at every sample time between observed and modeled velocity from the least 

squared fit of dynamic modes showed that when the first baroclinic mode amplitudes were close 

to zero, the correlation was poor. The low correlation could possibly indicate times of relative 

quiescence in the wake of eddies, that higher-order modes characterize the vertical structure. 

Correlations in the time domain were determined between record length velocity data and 

modeled velocity at every current meter depth and five ADCP layer depths. The model fits well 

above 500 m, and below 500 m, the correlation decreased. In some cases, e.g., the fit to velocity 

components collected during the second deployment, the correlation was a minimum between 

800 – 1000 m, and may be associated with the kinetic energy minimum at this level in the GOM. 

 7-25 
Figure 7.2-16. (Top) Spatial correlation between observed u velocity 

at mooring M1 from deployment 1 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between modeled and observed velocity. 

Figure 7.2-17. (Top) Spatial correlation between observed v velocity 

at mooring M1 from deployment 1 and the modeled v 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

 7-26 
Figure 7.2-18. (Top) Spatial correlation between observed u velocity 

at mooring M1 from deployment 2 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

Figure 7.2-19. (Top) Spatial correlation between observed v velocity 

at mooring M1 from deployment 2 and the modeled v 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

 7-27 
Figure 7.2-20. (Top) Spatial correlation between observed u velocity 

at mooring M2 from deployment 1 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

Figure 7.2-21. (Top) Spatial correlation between observed v velocity 

at mooring M2 from deployment 1 and the modeled v 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

 7-28 
Figure 7.2-22. (Top) Spatial correlation between observed u velocity 

at mooring M2 from deployment 2 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

Figure 7.2-23. (Top) Spatial correlation between observed v velocity at 

mooring M2 from deployment 2 and the modeled v 

velocity from CTD cast data on the EGOM hydrographic 

cruises. (Bottom) Amplitudes of the first three theoretical 

modes based on the least squares regression. (Right) 

Temporal correlation between the modeled and observed 

velocity. 

 7-29 
Figure 7.2-24. (Top) Spatial correlation between observed u velocity 

at mooring M3 from deployment 1 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

Figure 7.2-25. (Top) Spatial correlation between observed v velocity 

at mooring M3 from deployment 1 and the modeled v 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

 7-30 
Figure 7.2-26. (Top) Spatial correlation between observed u velocity 

at mooring M3 from deployment 2 and the modeled u 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

Figure 7.2-27. (Top) Spatial correlation between observed v velocity 

at mooring M3 from deployment 2 and the modeled v 

velocity from CTD cast data on the EGOM 

hydrographic cruises. (Bottom) Amplitudes of the 

first three theoretical modes based on the least 

squares regression. (Right) Temporal correlation 

between the modeled and observed velocity. 

 7-31 
7.2.1.3 Model Utility Test for Dynamic Modes 

Two types of model utility tests were performed on the modal fit to the observed currents in the 

space domain. The first test utilized the F statistic to assess whether a useful relationship between 

the observed data and any of the modal predictors existed. The null hypothesis for this test was 

that the coefficient of all modes included in the model equals zero was to be rejected if the test 

statistic, which is a function of the degrees of freedom, the number of modes included in the fit, 

and spatial correlation, is greater than or equal to the F critical value found in an F distribution 

table, determined by the degrees of freedom, the number of modes included in the fit, and the 

significance level, α. For these data, the significance level of α = 0.05 was chosen. The 

goodness of fit test confirmed that the barotropic and at least one of the baroclinic modes are 

necessary to the regression approximately 80 – 90 % of the time. 

The second statistical test is an inference for a single mode coefficient, which determines if a 

certain mode needs to be included in the fit. This test is a two-tailed test using the t statistic to 

reject or accept the null hypothesis that the targeted mode coefficient is equal to zero, i.e., it is 

not necessary in the multiple regression. The null hypothesis is rejected if the test statistic, 

calculated from the amplitude of the mode, the error sum of squares, and the error degrees of 

freedom, falls outside of the rejection region determined by the critical values, which are given 

in a t table, determined by the degrees of freedom and the significance level α. This test 

indicated that the first baroclinic mode was the only mode necessary to explain the current 

structure at moorings M1, M2, and M3 during most of their deployment; however, the second 

baroclinic mode was necessary to the fit of velocity data during portions of the deployments, and 

particularly to the data collected at mooring M3 during periods within its second deployment. 

7.2.1.3.1 Temporal Correlation of First Baroclinic Mode and Sea Surface Height 

Gradient 

This section investigates potential causes of the observed current structure. Since geostrophic 

current velocity should be perpendicular to the sea surface height gradient we expected a 

relationship between the sea surface height gradient and the first baroclinic mode. We calculated 

the time series of sea surface height gradient in the north-south and east-west directions in the 

vicinity of each mooring and correlated that with the time series of the first baroclinic mode for 

the perpendicularly oriented velocity component. In general, a significantly large correlation was 

found between the orthogonal SSH gradient and the first baroclinic mode amplitudes. East-west 

velocity mode 1 amplitudes were compared to the sea surface height gradient in the north-south 

direction (even numbered Figures 7.2-28 – 7.2-50), and the north-south velocity mode 1 

amplitudes were compared to sea surface height gradient in the east-west direction (odd 

numbered Figures 7.2-29 – 7.2-51). The coherency spectra showed that the coherency was 

significant only at low frequencies, thus reinforcing that mode 1 amplitudes are related to the 

pressure gradient, indicating geostrophic currents. 

 7-32 
Figure 7.2-28. Temporal amplitudes of first baroclinic (bc) mode of the 

east-west velocity at M1 during deployment 1 (blue) and 

the SSH gradient in the north-south direction (green). 

Figure 7.2-29. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the east-west 

velocity at M1 during deployment 1 and the SSH gradient 

in the north-south direction. 

 7-33 
Figure 7.2-30. Temporal amplitudes of first baroclinic mode of the northsouth velocity at mooring M1 during deployment 1 (blue) 

and the SSH gradient in the east-west direction (green). 

Figure 7.2-31. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the north-south 

velocity component at mooring M1 during deployment 1 

and the SSH gradient in the east-west direction. 

 7-34 
Figure 7.2-32. Temporal amplitudes of first baroclinic mode of the eastwest velocity at mooring M1 during deployment 2 (blue) 

and the SSH gradient in the north-south direction (green). 

Figure 7.2-33. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the east-west 

velocity component at mooring M1 during deployment 2 

and the SSH gradient in the north-south direction. 

 7-35 
Figure 7.2-34. Temporal amplitudes of first baroclinic mode of the northsouth velocity at mooring M1 during deployment 2 (blue) 

and the SSH gradient in the east-west direction (green). 

Figure 7.2-35. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the north-south velocity first baroclinic mode 

at M1 during deployment 2 and the SSH gradient in the 

east-west direction. 

 7-36 
Figure 7.2-36. Temporal amplitudes of first baroclinic for the east-west 

velocity mode at mooring M2 during deployment 1 (blue) 

and the SSH gradient in the north-south direction (green). 

Figure 7.2-37. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode of the east-west 

velocity component at mooring M2 during deployment 1 

and the SSH gradient in the north-south direction. 

 7-37 
Figure 7.2-38. Temporal amplitudes of first baroclinic mode of the northsouth velocity at mooring M2 during deployment 1 (blue) 

and the SSH gradient in the east-west direction (green). 

Figure 7.2-39. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the north-south 

velocity component at mooring M2 during deployment 1 

and the SSH gradient in the east-west direction. 

 7-38 
Figure 7.2-40. Temporal amplitudes of first baroclinic mode for the eastwest velocity at mooring M2 during deployment 2 (blue) 

and the SSH gradient in the north-south direction (green). 

Figure 7.2-41. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the east-west 

velocity component at mooring M2 during deployment 2 

and the SSH gradient in the north-south direction. 

 7-39 
Figure 7.2-42. Temporal amplitudes of first baroclinic mode for the northsouth velocity at mooring M2 during deployment 2 (blue) 

and the SSH gradient in the east-west direction (green). 

Figure 7.2-43. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the north-south 

velocity component at mooring M2 during deployment 2 

and the SSH gradient in the east-west direction. 

 7-40 
Figure 7.2-44. Temporal amplitudes of first baroclinic mode for the eastwest velocity at mooring M3 during deployment 1 (blue) 

and the SSH gradient in the north-south direction (green). 

Figure 7.2-45. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the east-west 

velocity component at mooring M3 during deployment 1 

and the SSH gradient in the north-south direction. 

 7-41 
Figure 7.2-46. Temporal amplitudes of first baroclinic mode for the northsouth velocity at M3 during deployment 1 (blue) and the 

SSH gradient in the east-west direction (green). 

Figure 7.2-47. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the north-south 

velocity at M3 during deployment 1 and the SSH gradient 

in the east-west direction. 

 7-42 
Figure 7.2-48. Temporal amplitudes of first baroclinic mode for the eastwest velocity at M3 during deployment 2 (blue) and the 

SSH gradient in the north-south direction (green). 

Figure 7.2-49. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic mode for the east-west 

velocity at M3 during deployment 2 and the SSH gradient 

in the north-south direction. 

 7-43 
Figure 7.2-50. Temporal amplitudes of first baroclinic (bc) mode for the 

north-south velocity at M3 during deployment 2 (blue) and 

the SSH gradient in the east-west direction (green). 

Figure 7.2-51. Coherency (top) and phase (bottom) spectra of the temporal 

amplitudes of the first baroclinic (bc) mode for the northsouth velocity at M3 during deployment 2 and time series 

of the SSH gradient in the east-west direction. 

 7-44 
7.2.1.3.2 Spectra and Temporal Scales of Modes 

Power spectra and autocorrelation functions were generated for the dynamic mode time series 

using FFT methods as discussed previously. The results from these analyses were consistent 

between data from each mooring deployment. An example of this calculation for the mode fit to 

mooring M3 velocity data during deployment 1 are presented in Figure 7.2-52. Spectra for mode 

fits to u and v velocity exemplified a typical energy and enstrophy-conserving velocity spectrum, 

with an energy cascade in the red direction, i.e., from high to low frequencies. The barotropic 

amplitudes exhibited less energy than the first baroclinic modes at low frequencies. Also recall 

that variance at frequencies greater than 1 cpd was small because 40-hour low-passed filtered 

versions of the data were used in these calculations. The second baroclinic mode spectra are 

nearly white (constant) at frequencies less than 1 cpd. 

A scales analysis was performed by estimating the first zero-crossing of the normalized 

autocovariance function (NACF) derived for each modal time series. This calculation quantifies 

the temporal lag in which the data becomes decorrelated from previous observations. Results 

showing the NACF for the fit to the velocity data from mooring M3 during deployment 1 are 

presented in Figure 7.2-53. The first baroclinic mode amplitudes had the longest time scales (13-

39 days), and the second baroclinic mode amplitudes have the shortest time scales (6-7 days). 

For most of the moored data, the barotropic and first baroclinic mode time series displayed eddy 

time scales (~ 25 days), which was expected because of the active eddy regime in the East Gulf. 

7.3 Upper/Lower-Layer Coupling Analysis Using PIES Data 

An analysis of upper and lower layer potential coupling was also performed using primarily the 

PIES data. The array-averaged EKE for the upper (surface) and deep (2500 m) levels are shown 

in Figure 7.3-1. The upper and lower layer EKE did not indicate a direct one-to-one 

correspondence between the surface and deep energetic current events. During the measurement 

period, the variability in both layers appeared to be associated with features that propagated into 

the region from outside, i.e., much of the variability was remotely generated. Recall that the 

upper EKE reflects primarily the propagation of LC, LCEs and frontal cyclones into and out of 

the array area. 

The mix of locally and remotely generated variability, each with similar magnitudes, can obscure 

the evidence of upper and lower-layer interactions. Therefore, the lower-layer potential vorticity 

was analyzed to help elucidate potential vertical coupling. The resolution of the PIES and 

moorings array allowed investigation of both the advective and tendency terms in the deep 

potential vorticity budget. In addition, a potential vorticity case study is presented of a deep 

cyclone (event c) where the production of relative vorticity was balanced by lower-layer 

stretching as the cyclone propagated southeastward into deeper water. 

 7-45 
Figure 7.2-52. Power spectra of the time-series amplitudes of the first three theoretical modes 

(top: barotropic mode; middle: first baroclinic mode; bottom: second baroclinic 

mode) time-series for fits to the east-west (left) and north-south (right) velocity 

data at mooring M3 during deployment 1. 

 7-46 
Figure 7.2-53. Normalized autocovariance function (NACF) of mode amplitudes from the fit to 

east-west and north-south velocity component data at mooring M3 during 

deployment 1. 

Lower-layer potential vorticity q was calculated as the sum of the Coriolis parameter f and 

relative vorticity, ζ=∂v/∂x-∂u/∂y, divided by lower layer thickness h: 

f + ζ

h q = , (7.3.1) 

The distance between the ocean bottom H and the 6°C isotherm depth h6 defines lower-layer 

thickness. In the absence of external torques, lower-layer potential vorticity will be conserved: 

Dq

Dt = ∂q

∂t

+ u

∂q

∂x

+ v

∂q

∂y

+ w

∂q

∂z

= 0, (7.3.2) 

The advective terms can present a challenge because they require a highly-resolved array of 

measurements to determine the spatial gradients of a second-order term q. The measurement 

array contained the resolution required to calculate these terms. 

 7-47 
Figure 7.3-1. Measurement array mean eddy kinetic energy (EKE) at the surface (blue) and at 

2500 m (red). The six major deep events are denoted by letters along the top of 

the time axis. 

Figures 7.3-2, 7.3-3, and 7.3-4 show the mean and standard deviation of lower-layer potential 

vorticity, thickness, and relative vorticity, respectively, calculated from the PIES data. 

Topography greatly influenced the mean potential vorticity. The largest contribution to mean 

lower-layer thickness derived from H rather than h6. Mean relative vorticity was weak. Scaled 

by the Coriolis parameter, ζ/f expressed the Rossby number and had an absolute range near 0.02 

within the array with negative (anticyclonic) values mainly in the northwest and the most 

positive (cyclonic) values in the southern portion of the array. Lower-layer potential vorticity 

was calculated as the Laplacian of the lower-layer streamfunction through optimal interpolation 

using a Gaussian correlation scale of 60 km. 

Lower-layer potential vorticity exhibited the largest fluctuations along the southwestern edge of 

the array and was coincident with large fluctuations in lower-layer thickness. Temporal 

variability in lower-layer thickness at any site was due to changes in the thermocline depth. In 

the southern portion of the array, thermocline depth varied by 470 m (peak-to-peak in the bottom 

panel of Figure 7.3-3). Lower layer relative vorticity exhibited the largest variability in the 

southern portion of the array where the Rossby number reached maximum values near 0.28 in 

the strong cyclonic events and varied from -0.12 to 0.28. 

In order to separate the contributions of lower-layer stretching and vorticity, we expanded q 

using a binomial series expansion, 

 7-48 
f +

 

q = ζ

H − h6

q =

f (1+ ζ

f

)

H − h6

q = f (1+ ζ

f

)( 1

H

+

h6

H2 +

h62

H3 +K)

q = f

H

+ ζ

H

+

h6 f

H2 + ζ h6

H2 +

h62 f

H3 + ζ h62

H3 +K

q  ̃ = f

H

+ ζ

H

+ Hterms

Hterms = h6 f

H2 +

h62 f

H3 +K+

h610 f

H11 .

In the bottom two lines we define a modified lower-layer potential vorticity, q , which 

approximates q and does not contain any joint h6 and ζ terms. Interestingly, while these terms 

were found to be small, they were not insignificant; see for example the difference between q

(red line) and (blue line) shown the middle panel of Figure 7.3-5. 

 ̃

q ̃

The experimental design allowed us to calculate the terms in the lower-layer potential vorticity 

equation. Here we show the results for the location shown as the orange diamond in Figures 7.3-

3 and 7.3-4 and the red star in Figures 7.3-5 and 7.3-6. Both thickness and relative vorticity 

variability contributed to the local rate of change in total potential vorticity. The bottom panel of 

Figure 7.3-6 shows that the tendency term and the advective terms nearly balanced. This kind of 

analysis lends itself to parallel diagnostics between model and observational data sets. A next 

step is to decompose the potential vorticity into mean and eddy components for further 

diagnosis. 

The deep cyclone events discussed in Chapter 6 shared similar characteristics. First, they 

propagated across the southwestern portion of the array from west to east. Second, they appeared 

to be locked behind an eastward propagating upper-ocean anticyclone. Third, the deep cyclones 

intensified as they moved eastward. Here we investigate the potential vorticity associated with 

the deep cyclone of event c as a case study. Again, a binomial expansion was used to separate 

stretching and relative vorticity. We define HL as the cyclones mean lower-layer thickness and h’

as the deviation of lower-layer thickness from HL. The potential vorticity of the cyclone, qL, and 

its binomial expansion from HL is 

f +

 

qL = ζ L

HL − h'

qL = f

HL

+ ζ L

HL

− fh'

HL

2 +K

and we retain the first three terms to define an approximate potential vorticity, 

 7-49 
f

HL

+ fh'

HL

2 . ζ L

HL

q  ̃ L = −

In order to view the cyclone’s potential vorticity in a Lagrangian framework the local minimum 

associated with the cyclone for each half-day map was determined and then the thickness and 

relative vorticity values were interpolated to the cyclone position. The cyclone’s potential 

vorticity was nearly constant as expected (Figure 7.3-7, panel A); its relative vorticity (panel B) 

and thickness (panel B) increased over time. The thickness increase was due almost entirely to 

the change in ocean depth as the eddy propagated to the southeast. The depth of the thermocline 

showed no discernable increase over time (panel C). The cyclone spun up over time as a 

consequence of its propagation into deeper ocean depths. This result was similar to the other two 

cyclone events, not shown. 

These results provide an intriguing but limited view of the dynamics and potential vorticity 

development in upper layer and deep features propagating around the edges of the LC. The 

results are highly suggestive of upper and deep layer coupling under certain conditions not yet 

well understood. The results also demonstrated that a measurement array with the resolution and 

site-spacings utilized in the Eastern GOM Study is both necessary and well-suited to diagnose 

these types of events. However, to develop a much broader and in-depth understanding of the 

development and life of such couplings, the region covered by future measurement arrays would 

need to be much larger. 

 7-50 
Figure 7.3-2. Top (bottom) panel: Mean (standard deviation) lower-layer potential vorticity. 

Topography contoured every 250 m depth denoted by gray lines in each panel. 

PIES denoted by diamonds, current meter moorings denoted by circles. 

 7-51 
Figure 7.3-3. Top (middle) panel: Mean (standard deviation) of lower-layer thickness. 

Topography contoured every 250 m depth denoted by gray lines in each panel. 

PIES denoted by diamonds, current meter moorings denoted by circles. Bottom 

panel: Time series of lower-layer thickness at the site shown with the orange 

diamond in the middle panel. 

 7-52 
Figure 7.3-4. Top (middle) panel: Mean (standard deviation) of lower-layer relative vorticity 

divided by the local Coriolis parameter (f). Topography contoured every 250 m 

depth denoted by gray lines in each panel. PIES denoted by diamonds, current 

meter moorings denoted by circles. Bottom panel: Time series of lower-layer 

thickness at the site shown with the orange diamond in the middle panel. 

 7-53 
Figure 7.3-5. Top panel: Snapshot of upper and deep circulation on August 3, 2005. PIES 

derived SSH (thick lines) and 2500 m streamfunction (solid color; blue shades 

cyclonic, pink shades anticyclonic). The blue and black arrows are observed and 

mapped geostrophic currents, respectively. Topography contoured every 500 m in 

gray. Middle panel: Time series of total lower layer potential vorticity (red) and 

approximated lower layer potential vorticity (blue) as described in the text for the 

red star in the top panel. Bottom panel: Contribution of thickness (blue) and 

relative vorticity variability to total lower-layer potential vorticity for the red star 

in the top panel. 

 7-54 
Figure 7.3-6. Top panel: Snapshot of upper and deep circulation on August 3, 2005. PIES 

derived SSH (thick lines) and 2500 m streamfunction (solid color; blue shades 

cyclonic, pink shades anticyclonic). The blue and black arrows are observed and 

mapped geostrophic currents, respectively. Topography contoured every 500 m in 

gray. Middle panel: Time series of total lower layer potential vorticity (red) and 

approximated lower layer potential vorticity (blue) as described in the text for the 

red star in the top panel. Bottom panel: Contribution of tendency (red) and 

advective terms multiplied by -1 (blue) to the total rate of change in potential 

vorticity at the red star in the top panel. 

 7-55 
Figure 7.3-7. Properties of event c cyclone. Panel A: Lower layer potential vorticity. Panel B: 

Lower-layer relative vorticity scaled by the Coriolis parameter. Panel C: Lowerlayer thickness. Panel D: Depth of the thermocline. Panel E: Relative vorticity 

(thickness) contribution to potential vorticity in black (gray). 

 7-56 
8.0 SUMMARY AND CONCLUSIONS 

Prior to this study, few deep water current measurements had been collected in the eastern GOM, 

especially in the area of the BOEMRE Eastern Gulf Lease Sale 181. To further the understanding 

of the circulation and its drivers in this region, BOEMRE commissioned the present Survey of 

Deepwater Currents in the Eastern Gulf of Mexico. The study consisted of a collection and 

analysis of a suite of both in-situ and remote sensing measurements. Measurements from PIES 

spanned December 2004 – January 2006. Measurements from three tall and one near-bottom 

current meter moorings spanned January 2005 – January 2006. Satellite remote sensing 

measurements spanned the entire field measurement period. Additional ancillary data such as 

coastal winds, runoff, and tides, Eddy Watch maps and drifting buoy tracks, and measurements 

available from other researchers or historical data sets, were all utilized to help analyze the new 

measurements and place them in historical perspective. 

8.1 Summary of the Results 

Prior to the study, the deep water portion of the eastern GOM was thought to be impacted less 

frequently by the LC and LCEs or their frontal features, resulting in less energetic circulation 

than is found in the north-central GOM where the LC and LCE’s often penetrate. On a quasiannual basis, the northern edge of the Loop Current reaches between 24° and 28° N into the Gulf 

of Mexico (Sturges and Evans 1983), yet for the majority of the field measurement period, the 

northern edge (as the LC or Eddy Vortex) remained between 27° and 28° N, and impacted the 

study area for much of the measurement period. 

During the study, the LC spawned Eddy Vortex. Using metrics applied to historical altimetry 

data to evaluate eddy separations (Leben, 2005), Eddy Vortex detached and reattached from the 

LC a total of four times, prior to final separation. This was the largest number of 

detachment/reattachment events observed during a single LC intrusion cycle within the historical 

altimeter record. Final detachment occurred on 13 September 2005. During this period of 

detachment and reattachment, the extended intrusion of the LC and an associated eddy was one 

of the most northerly intrusions on record. It was only exceeded by the intrusion that generated 

Eddy Sargassum during the Exploratory Study. As a result of the detachment and reattachment 

process, Eddy Vortex resided in the northern GOM, and impacted the circulation in the study 

area, for much of the field measurement period. The greatest influence was observed during 

deployment 1, with less but still significant influence, especially to the southernmost mooring 

M3 during deployment 2. 

In addition, during the mooring deployments, five hurricanes and one tropical storm traversed 

the Gulf; the most severe being Hurricanes Katrina and Rita. Hurricane Katrina entered the Gulf 

of Mexico on August 26, 2005 and was nearest to the study area on August 28, 2005; Hurricane 

Rita entered the Gulf of Mexico on September 20, 2005 and was nearest to the study region on 

September 22, 2005. 

The combination of the extended stay of the LC and Eddy Vortex in the northern GOM, and the 

number of severe storms passing near the study area, resulted in extensive periods of energetic 

currents within the study area during the measurement period. 

 8-1 
In Chapter 3, details of the metrics of the LC and Eddy Vortex are provided. These metrics are 

also placed in perspective based on the historical altimetry record that now spans 13.5 years from 

1 January 1993 through 15 January 2006. During the study period, the LC year-long area and 

latitude of northern extent were maximums for the entire period of the altimeter record. The 

average LC length and westward longitude were only exceeded by one prior intrusion that 

formed, Eddy Millennium. The LC statistics concerning LC volume and circulation were near 

the upper historical ranges. The metrics also calculated that the LC or Eddy Vortex intruded into 

the PIES array for this study a total of 52 days during 2005, which is quite an extensive visit as 

the historical average is 22 days per year. 

In Chapter 4, the dynamics of Eddy Vortex and some cold core eddies were examined using both 

a kinematic and a dynamic approach. These analyses provided some guidance on the formation 

and characteristics of Eddy Vortex and some of its frontal features. Mean surface circulation 

over the first six months of measurements shows southeast flow resulting from the presence of 

Eddy Vortex. Three episodes of high EKE lasting 15-30 days occurred during Eddy Vortex 

detachment and reattachment. Mean flow during the last six months has weaker currents dir to 

several frontal cyclones. Only one episode of high EKE occurred during a strong frontal cyclone. 

Chapter 5 presented a basic overview of the measurement results from the moorings. A variety of 

analyses were performed to provide perspectives on the basic structure, vorticity, and dynamics 

of the currents that were measured. Due to the significant presence of the LC and Eddy Vortex, 

along with cold core eddies and other frontal features, a significant portion of the entire 

measurement record contains very energetic currents in the upper layer. This was more prevalent 

during the first deployment. However, during the second deployment, the passage of both 

Hurricane Katrina and Hurricane Rita created energetic inertial oscillations. The passage of 

Hurricane Katrina coincided with the presence of a cold core eddy situated over the southern 

portion of the study area, and the resulting current measurements show an enhanced inertial 

oscillation strengths. This provided a rare opportunity to view the effects of combined forces of a 

cold core eddy and a hurricane on exciting the circulation. 

Chapter 6 focuses on the deep circulation seen in the eastern GOM during the study, and 

compares it to the historical knowledge of deep circulation in the GOM. Much of the focus is on 

TRWs and their potential generation and translation from the study area. The deep currents at 

moorings M2 and M3 showed evidence of bottom intensification of the currents, with principal 

axes of standard deviation ellipses directed westward and southwestward, respectively. These 

directions are across the isobaths towards shallower water, which is characteristic of TRW 

motions. The deep circulation was punctuated by a number of energetic low-frequency events 

that were typical of TRW presence. 

 8-2 
In Chapter 7, potential vertical coupling of the upper and lower layers of the GOM in the study 

area were investigated. Some sophisticated analyses were performed to assess the dominant 

modes controlling the circulation, and to evaluate the extent of coupling. Specific short duration 

periods of similar flow through a majority of the water column have been previously seen 

(Hamilton 2007), and were again seen in this study’s measurements. While the analyses showed 

there was minimal connection between the upper and lower layers, it also showed that the lower 

layer had a small contribution from upper-layer LC or LCE dynamics through dynamic coupling, 

and the upper layer had a small contribution from TRW flows decaying upwards through the 

water column. 

8.2 Conclusions 

Prior to the study, the study team had a significant concern if the eastern GOM would experience 

any sizable current energetics. The primary conclusion from the study is that the eastern GOM is 

a very active region in terms of circulation, especially when the LC or an LCE is present. The 

circulation characteristics of the region are very similar to those in the north-central GOM when 

similar processes are at work, whether they be the presence of the LC, and LCE, frontal features, 

or major storms. Significant advancement in the understanding of the circulation in the eastern 

GOM was achieved including: 

• Extended LC intrusion significantly impacted the study area upper ocean 

circulation during the first half of the EGOM program. Once Eddy Vortex 

finally separated, fewer LC or frontal features impacted the circulation and 

the character of the circulation returned to conditions more typical for this 

region. 

• Cyclones are an important dynamical component of the general circulation 

of the GOM and significantly impacted the study region during the 

program. 

• Comparisons were drawn between the mean surface circulation over the 

first six months of measurements versus the last six months. The mean for 

the first six months revealed southeast flow from the presence of Eddy 

Vortex while the last six months had comparatively weak circulation. 

• The PIES array captured the mesoscale frontal meanders along the 

periphery of the LC and while well resolved provided a limited window. 

• Cyclonic events occurred more frequently than anticyclonic events in the 

EGOM vorticity record. 

• Currents during both deployments at all three tall moorings showed a high 

degree of coherency at water depths above 500 m, with weaker coherence 

extending down to 750 m, and with only occasional coherence at deeper 

depths. 

• Large amplitude inertial oscillations are evident immediately after the 

passages of Hurricanes Katrina and Rita. These current oscillations 

persisted for at least two weeks after the passage of these storms. 

• The passage of Hurricane Katrina near the study’s moorings while a 

cyclonic (cold core) eddy was sitting over the southern portion of the 

study area, is believed to have generated stronger than normal currents. 

 8-3 
• In general, spectral energy was greatest in the shallow ocean depth (<300 

m). Surface records (~ 50 m) contained larger weather-band variance than 

deeper records. 

• The extrapolated near-bottom current speeds at M1 near the Florida 

Escarpment were no larger than those at M3 on the abyssal plane. This 

was an interesting contrast to near-bottom currents near the Sigsbee 

Escarpment farther west, where bottom currents were much stronger in 

proximity to the Escarpment. 

• The lower-layer motions in the study area are dominated by TRWs. The 

presence of the LC or LCE over the study area had a direct influence on 

the amplitudes of the lower-layer TRWs. 

• Deep circulation experiences TRW packets, though generation of TRWs 

that translate into the north-central GOM do not appear to be generated in 

this region. TRW generated currents are also not affected significantly by 

steep bathymetry in this region. 

• The lower layer had a small contribution from upper LC or eddy 

fluctuations through dynamical coupling, just as the upper layer had a 

small contribution from TRW flows decaying upwards through the water 

column. 

• The horizontal current structure in this region of the Gulf resembles a 2-

layer system. The eddy field causes intensification of the surface currents, 

which exponentially decay in magnitude with depth to ~ 800 m., while the 

lower layer was influenced primarily by TRWs propagating through the 

region. 

8.3 Recommendations 

The one year measurement program in the eastern GOM was judicious in timing in that it caught 

significant penetrations of the LC and an LCE into the region, as well as multiple large storms. 

The study region, however, was actually fairly small, and fairly limited in measurement 

locations, to extrapolate the study results to a much larger portion of the eastern GOM. The 

primary recommendations for future studies to further assess the larger eastern GOM circulation 

features, and to better explore the dynamics and interactions of the water column with the LC 

and its eddies, are as follows: 

• Conduct a larger-scale circulation study of the eastern GOM spanning 

more of this area to better assess the geographic extent of the circulation 

and processes found during this study. 

• Conduct in-situ measurements at both small (25km) and large (50-100km) 

scales so as to observe currents over a wider area, yet maintain the ability 

to calculate vorticity, coherence between measurement sites, and to assess 

the small scale interactions at the edges of the LC and LCEs which are 

imparting significant energy into the water column. 

 8-4 
 8-5 

• Add gliders so as to better map hydrography changes in critical areas, such 

as the LC and LCE edges, and so as to provide hydrography 

measurements over much longer time scales than can be achieved by 

hydrography cruises using CTDs and XBTs. 

• Concentrate a set of moorings in the path of, and at the boundaries of, the 

LC and LCEs, as best as they can be positioned, to improve understanding 

of the frontal features and how they affect and control LC movements and 

eddy shedding. 

• Continue to employ remote sensing (satellite measurements) in future 

studies, as these provide such a great basis of understanding of the features 

that affect specific in-situ measurement sites. 

• Conduct coordinated programs geographically to obtain measurements in 

the southern portion of the LC as well as the northern portion so as to 

better understand what drives and controls its northward intrusions and 

southward retractions. 

• Conduct coordinated programs with other institutions, in particular those 

institutions conducting oceanographic measurements of major storms, so 

as to make use of their fast response measurement capabilities in front of 

the storms. 

• Finally, keep funding quality research in the GOM. 
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APPENDIX A 

Hurricanes and Tropical Storm Events 

 A-1 
Figure A-1. Storm track and wind extent of tropical storm Arlene. 

 A-3 
Figure A-2. Storm track and wind extent of hurricane Cindy. 

 A-4 
Figure A-3. Storm track and wind extent of hurricane Dennis. 

 A-5 
Figure A-4. Storm track and wind extent of hurricane Katrina. 

 A-6 
Figure A-5. Storm track and wind extent of hurricane Rita. 

 A-7 
Figure A-6. Storm track and wind extent of hurricane Wilma. 

 A-8 
APPENDIX B 

Color Vector Plots of Current Magnitude and Direction 

 B-1 
 B-2 

Currents as measured from the ADCP and single point current meters are displayed as vector 

plots of current speed (cm s-1) and direction. This displays the magnitude and direction the 

current is going toward from both the ADCP and single point instruments on Moorings 1-4. 

These plots cover the entire length of the mooring. The bins selected for display are referenced to 

meters depth. 

Grey lines in the figures show the closest passing of storms and loop current events. A list of the 

events can be found in Table 3.1-3. Abbreviations used in the figure annotations are as follows: 

E for Eddy, D for detachment, R for reattachment, FD for final detachment, LC for Loop 

Current, and LCFE for Loop Current Frontal Eddy. Multiple events of the same type are 

numbered in chronological order (i.e. LC1 is Loop Current event 1). 
Figure B-1. Mooring 1 current vectors for Deployment 1. 

 B-3 
Figure B-2. Mooring 1 current vectors for Deployment 2. 

 B-4 
Figure B-3. Mooring 2 current vectors for Deployment 1. 

 B-5 
Figure B-4. Mooring 2 current vectors for Deployment 2. 

 B-6 
Figure B-5. Mooring 3 current vectors for Deployment 1. 

 B-7 
Figure B-6. Mooring 3 current vectors for Deployment 2. 

 B-8 
Figure B-7. Mooring 4 current vectors for Deployment 1. 

 B-9 
Figure B-8. Mooring 4 current vectors for Deployment 2. 

 B-10 
APPENDIX C 

Basic Statistics for Current Measurements 

 C-1 
 C-2 

Statistics for the u and v components of the current speed are presented as tables for Moorings 

1-4. The statistics calculated were minimum, maximum, mean and standard deviation. 
Table C-1 

Statistics from Mooring 1 Deployment 1 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 1307 40 - 48 m 0 u (cm/s) ********** ********** * ********* ********

Long-Ranger ADCP v (cm/s) ********** ********** * ********* ********

RDI Broadband 75 kHz 1307 48 - 56 m 4059 u (cm/s) -50.06 74.82 1.831 21.676

Long-Ranger ADCP v (cm/s) -63.05 62.8 5.92 20.839

RDI Broadband 75 kHz 1307 56 - 64 m 4392 u (cm/s) -49.25 94.02 4.807 24.208

Long-Ranger ADCP v (cm/s) -86.03 77.1 5.185 23.211

RDI Broadband 75 kHz 1307 64 - 72 m 4646 u (cm/s) -44.7 113.22 8.177 28.235

Long-Ranger ADCP v (cm/s) -75.97 78.52 4.981 23.86

RDI Broadband 75 kHz 1307 72 - 80 m 4893 u (cm/s) -44.51 119.95 11.01 31.34

Long-Ranger ADCP v (cm/s) -96.34 87.13 3.582 25.041

RDI Broadband 75 kHz 1307 80 - 88 m 4965 u (cm/s) -43.14 119.57 11.35 31.686

Long-Ranger ADCP v (cm/s) -92.42 86.6 3.187 24.839

RDI Broadband 75 kHz 1307 88 - 96 m 5001 u (cm/s) -44.55 120.15 11.292 31.536

Long-Ranger ADCP v (cm/s) -92 80.83 2.939 24.13

RDI Broadband 75 kHz 1307 96 - 104 m 5019 u (cm/s) -40.68 135.86 10.89 30.863

Long-Ranger ADCP v (cm/s) -90.71 69.06 2.836 23.45

RDI Broadband 75 kHz 1307 104 - 112 m 5039 u (cm/s) -41.13 131.67 10.367 30.35

Long-Ranger ADCP v (cm/s) -90.28 67.62 2.823 22.907

RDI Broadband 75 kHz 1307 112 - 120 m 5050 u (cm/s) -37.33 130.51 9.816 29.561

Long-Ranger ADCP v (cm/s) -92.16 63.62 2.886 22.178

RDI Broadband 75 kHz 1307 120 - 128 m 5057 u (cm/s) -39.68 129.23 9.326 28.642

Long-Ranger ADCP v (cm/s) -95.15 63.54 2.802 21.324

RDI Broadband 75 kHz 1307 128 - 136 m 5057 u (cm/s) -45.89 121.9 8.771 27.45

Long-Ranger ADCP v (cm/s) -92.6 60.73 2.717 20.526

RDI Broadband 75 kHz 1307 136 - 144 m 5057 u (cm/s) -41.06 116.53 8.22 26.309

Long-Ranger ADCP v (cm/s) -89.56 60.85 2.707 19.892

RDI Broadband 75 kHz 1307 144 - 152 m 5057 u (cm/s) -41.35 114.15 7.642 25.222

Long-Ranger ADCP v (cm/s) -83.49 60.05 2.682 19.231

RDI Broadband 75 kHz 1307 152 - 160 m 5057 u (cm/s) -42.7 109.83 7.145 24.324

Long-Ranger ADCP v (cm/s) -71.8 59.7 2.727 18.462

RDI Broadband 75 kHz 1307 160 - 168 m 5057 u (cm/s) -38.36 109.37 6.755 23.474

Long-Ranger ADCP v (cm/s) -68.52 53.92 2.754 17.811

RDI Broadband 75 kHz 1307 168 - 176 m 5057 u (cm/s) -37.66 112.45 6.526 22.901

Long-Ranger ADCP v (cm/s) -64.92 52.27 2.725 17.429

RDI Broadband 75 kHz 1307 176 - 184 m 5057 u (cm/s) -37.17 106.98 6.136 22.196

Long-Ranger ADCP v (cm/s) -62.19 51.35 2.68 17.018

RDI Broadband 75 kHz 1307 184 - 192 m 5057 u (cm/s) -34.95 103.96 5.823 21.534

Long-Ranger ADCP v (cm/s) -61.25 51.21 2.635 16.633

RDI Broadband 75 kHz 1307 192 - 200 m 5057 u (cm/s) -35.8 105.98 5.573 21.032

Long-Ranger ADCP v (cm/s) -63.71 50.31 2.636 16.178

RDI Broadband 75 kHz 1307 200 - 208 m 5057 u (cm/s) -34.05 106.51 5.39 20.36

Long-Ranger ADCP v (cm/s) -62.78 51.43 2.575 15.749

RDI Broadband 75 kHz 1307 208 - 216 m 5057 u (cm/s) -35.2 102.85 5.167 19.568

Long-Ranger ADCP v (cm/s) -63.39 50.51 2.426 15.151

RDI Broadband 75 kHz 1307 216 - 224 m 5057 u (cm/s) -37.75 102.11 4.776 19.257

Long-Ranger ADCP v (cm/s) -61.48 47.97 2.472 14.956

RDI Broadband 75 kHz 1307 224 - 232 m 5057 u (cm/s) -39.3 100.7 4.589 18.838

Long-Ranger ADCP v (cm/s) -60.27 48.58 2.469 14.691

RDI Broadband 75 kHz 1307 232 - 240 m 5057 u (cm/s) -41.37 97.11 4.361 18.309

Long-Ranger ADCP v (cm/s) -58.69 46.31 2.497 14.353

RDI Broadband 75 kHz 1307 240 - 248 m 5057 u (cm/s) -36.94 94.81 4.194 17.824

Long-Ranger ADCP v (cm/s) -55.2 48.98 2.467 13.94

 C-3 
Table C-1. Statistics from Mooring 1 Deployment 1 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 1307 248 - 256 m 5057 u (cm/s) -36.99 90.21 3.945 17.346

Long-Ranger ADCP v (cm/s) -53.56 46.22 2.392 13.417

RDI Broadband 75 kHz 1307 256 - 264 m 5057 u (cm/s) -36.79 90.7 3.797 16.812

Long-Ranger ADCP v (cm/s) -55.87 49.83 2.408 13.011

RDI Broadband 75 kHz 1307 264 - 272 m 5057 u (cm/s) -32.93 80.5 3.539 16.211

Long-Ranger ADCP v (cm/s) -50.14 47.41 2.399 12.639

RDI Broadband 75 kHz 1307 272 - 280 m 5057 u (cm/s) -33.29 80.12 3.475 15.786

Long-Ranger ADCP v (cm/s) -50.48 47.33 2.38 12.307

RDI Broadband 75 kHz 1307 280 - 288 m 5057 u (cm/s) -33.86 75.3 3.233 15.397

Long-Ranger ADCP v (cm/s) -49.64 43.1 2.31 12.004

RDI Broadband 75 kHz 1307 288 - 296 m 5057 u (cm/s) -34.41 73.89 3.018 15.013

Long-Ranger ADCP v (cm/s) -46.45 41.99 2.238 11.739

RDI Broadband 75 kHz 1307 296 - 304 m 5057 u (cm/s) -33.23 68.6 2.895 14.724

Long-Ranger ADCP v (cm/s) -45.32 40.37 2.236 11.585

RDI Broadband 75 kHz 1307 304 - 312 m 5057 u (cm/s) -32.98 66.55 2.774 14.401

Long-Ranger ADCP v (cm/s) -43.03 38.64 2.218 11.423

RDI Broadband 75 kHz 1307 312 - 320 m 5057 u (cm/s) -32.55 64.42 2.654 14.219

Long-Ranger ADCP v (cm/s) -41.48 39.11 2.198 11.246

RDI Broadband 75 kHz 1307 320 - 328 m 5057 u (cm/s) -32.56 59.84 2.575 13.934

Long-Ranger ADCP v (cm/s) -39.08 40.02 2.202 11.033

RDI Broadband 75 kHz 1307 328 - 336 m 5057 u (cm/s) -32.47 56.88 2.422 13.751

Long-Ranger ADCP v (cm/s) -37.32 38.75 2.187 10.896

RDI Broadband 75 kHz 1307 336 - 344 m 5057 u (cm/s) -31.84 52.66 2.304 13.502

Long-Ranger ADCP v (cm/s) -35.29 37.27 2.196 10.759

RDI Broadband 75 kHz 1307 344 - 352 m 5057 u (cm/s) -32.41 49.6 2.243 13.275

Long-Ranger ADCP v (cm/s) -35.9 37.94 2.142 10.605

RDI Broadband 75 kHz 1307 352 - 360 m 5057 u (cm/s) -30.42 49.42 2.169 13.129

Long-Ranger ADCP v (cm/s) -36.29 36.61 2.084 10.329

RDI Broadband 75 kHz 1307 360 - 368 m 5057 u (cm/s) -28.11 48.04 2.17 13.002

Long-Ranger ADCP v (cm/s) -36.84 34.66 2.088 10.18

RDI Broadband 75 kHz 1307 368 - 376 m 5057 u (cm/s) -29.21 49.54 2.11 12.792

Long-Ranger ADCP v (cm/s) -33.91 34.87 1.932 10.049

RDI Broadband 75 kHz 1307 376 - 384 m 5057 u (cm/s) -28.81 47.91 2.079 12.497

Long-Ranger ADCP v (cm/s) -35.42 35.2 1.917 9.893

RDI Broadband 75 kHz 1307 384 - 392 m 5057 u (cm/s) -28.43 48.1 1.939 12.173

Long-Ranger ADCP v (cm/s) -32.73 36.5 1.882 9.775

RDI Broadband 75 kHz 1307 392 - 400 m 5057 u (cm/s) -28.7 43.25 1.795 11.926

Long-Ranger ADCP v (cm/s) -31.67 41.09 1.949 9.642

RDI Broadband 75 kHz 1307 400 - 408 m 5057 u (cm/s) -27.88 44.33 1.717 11.669

Long-Ranger ADCP v (cm/s) -30.03 37.8 1.915 9.495

RDI Broadband 75 kHz 1307 408 - 416 m 5057 u (cm/s) -28.66 41.64 1.636 11.455

Long-Ranger ADCP v (cm/s) -27.66 38.81 1.852 9.324

RDI Broadband 75 kHz 1307 416 - 424 m 5057 u (cm/s) -30.18 41.37 1.591 11.209

Long-Ranger ADCP v (cm/s) -26.74 38.87 1.849 9.041

RDI Broadband 75 kHz 1307 424 - 432 m 5057 u (cm/s) -29.35 41.27 1.542 10.982

Long-Ranger ADCP v (cm/s) -28.26 34.95 1.782 8.844

 C-4 
Table C-2 

Statistics from Mooring 1 Deployment 1 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 78017 0749 m 5056 u (cm/s) -22.28 22.87 -0.201 6.552

v (cm/s) -19.62 24.3 1.222 5.561

Aanderaa RCM 7 7223 0997 m 1563 u (cm/s) -12.52 10.35 0.218 2.755

v (cm/s) -13.08 10.5 0.569 3.467

Aanderaa RCM 7 7692 1244 m 5056 u (cm/s) -11.56 9.16 -0.141 2.693

v (cm/s) -16.06 10.22 0.553 2.618

Aanderaa RCM 7 9722 1492 m 5056 u (cm/s) -9.66 8.36 -0.022 2.159

v (cm/s) -14.27 10.56 0.378 2.209

Aanderaa RCM 8s 10053 1995 m 0 u (cm/s) ********** ********** ********** ********

v (cm/s) ********** ********** ********** ********

Aanderaa RCM 8 12085 2499 m 5056 u (cm/s) -9.46 12.85 0.047 2.965

v (cm/s) -14.97 12.82 0.479 2.97

 C-5 
Table C-3 

Statistics from Mooring 2 Deployment 1 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5165 30 - 38 m 0 u (cm/s) ********** ********** ********** ********

Long-Ranger ADCP v (cm/s) ********** ********** ********** ********

RDI Broadband 75 kHz 5165 38 - 46 m 2882 u (cm/s) -47.66 84.31 19.744 21.21

Long-Ranger ADCP v (cm/s) -105.29 41.58 -12.678 21.955

RDI Broadband 75 kHz 5165 46 - 54 m 3721 u (cm/s) -51.21 93.53 25.216 25.831

Long-Ranger ADCP v (cm/s) -123.75 95.71 -11.723 27.366

RDI Broadband 75 kHz 5165 54 - 62 m 4172 u (cm/s) -52.68 106.22 27.551 28.372

Long-Ranger ADCP v (cm/s) -126.53 110.94 -10.742 32.463

RDI Broadband 75 kHz 5165 62 - 70 m 4591 u (cm/s) -55.98 107.04 29.754 29.91

Long-Ranger ADCP v (cm/s) -125.61 107.09 -10.358 36.158

RDI Broadband 75 kHz 5165 70 - 78 m 4904 u (cm/s) -55.16 125.15 31.772 31.296

Long-Ranger ADCP v (cm/s) -129.13 111.76 -8.007 37.525

RDI Broadband 75 kHz 5165 78 - 86 m 5065 u (cm/s) -57.06 131.02 32.438 32.219

Long-Ranger ADCP v (cm/s) -122.63 114.81 -6.601 37.167

RDI Broadband 75 kHz 5165 86 - 94 m 5111 u (cm/s) -55.65 122.53 31.853 32.254

Long-Ranger ADCP v (cm/s) -114.28 111.91 -6.361 36.117

RDI Broadband 75 kHz 5165 94 - 102 m 5153 u (cm/s) -57.02 121.34 31.285 32.434

Long-Ranger ADCP v (cm/s) -111.58 103.08 -5.986 35.1

RDI Broadband 75 kHz 5165 102 - 110 m 5174 u (cm/s) -55.47 116.12 30.363 32.232

Long-Ranger ADCP v (cm/s) -106.3 98.3 -5.565 34.137

RDI Broadband 75 kHz 5165 110 - 118 m 5174 u (cm/s) -53.86 110.87 29.159 31.708

Long-Ranger ADCP v (cm/s) -102.82 92.26 -5.089 33.269

RDI Broadband 75 kHz 5165 118 - 126 m 5174 u (cm/s) -52.56 107.58 27.826 31.058

Long-Ranger ADCP v (cm/s) -99.94 89.98 -4.691 32.393

RDI Broadband 75 kHz 5165 126 - 134 m 5174 u (cm/s) -54.93 107.25 26.621 30.284

Long-Ranger ADCP v (cm/s) -93.31 80.66 -4.226 31.46

RDI Broadband 75 kHz 5165 134 - 142 m 5174 u (cm/s) -54.53 106.64 25.349 29.441

Long-Ranger ADCP v (cm/s) -89.29 74.32 -4.008 30.457

RDI Broadband 75 kHz 5165 142 - 150 m 5174 u (cm/s) -53.41 102.33 24.07 28.627

Long-Ranger ADCP v (cm/s) -87.27 73.18 -3.675 29.373

RDI Broadband 75 kHz 5165 150 - 158 m 5174 u (cm/s) -54.28 96.34 22.912 27.735

Long-Ranger ADCP v (cm/s) -85.75 70.41 -3.366 28.525

RDI Broadband 75 kHz 5165 158 - 166 m 5174 u (cm/s) -52.23 93.77 21.776 26.843

Long-Ranger ADCP v (cm/s) -83.23 70.02 -3.107 27.851

RDI Broadband 75 kHz 5165 166 - 174 m 5174 u (cm/s) -51.85 96.05 20.722 26.101

Long-Ranger ADCP v (cm/s) -80.45 70.84 -2.797 27.213

RDI Broadband 75 kHz 5165 174 - 182 m 5174 u (cm/s) -53.6 89.31 19.852 25.426

Long-Ranger ADCP v (cm/s) -81.96 72.89 -2.53 26.583

RDI Broadband 75 kHz 5165 182 - 190 m 5174 u (cm/s) -51.74 88.31 18.997 24.793

Long-Ranger ADCP v (cm/s) -81.67 75.46 -2.304 25.966

RDI Broadband 75 kHz 5165 190 - 198 m 5174 u (cm/s) -52.55 89.27 18.162 24.229

Long-Ranger ADCP v (cm/s) -80.54 76.95 -2.141 25.349

RDI Broadband 75 kHz 5165 198 - 206 m 5174 u (cm/s) -53.69 90.06 17.424 23.713

Long-Ranger ADCP v (cm/s) -78.12 73.46 -2.082 24.764

RDI Broadband 75 kHz 5165 206 - 214 m 5174 u (cm/s) -52.66 90.13 16.856 23.323

Long-Ranger ADCP v (cm/s) -74.46 70.5 -2.006 24.227

RDI Broadband 75 kHz 5165 214 - 222 m 5174 u (cm/s) -50.27 85.9 16.161 22.952

Long-Ranger ADCP v (cm/s) -72.57 69.32 -1.884 23.641

RDI Broadband 75 kHz 5165 222 - 230 m 5174 u (cm/s) -50.8 85.68 15.529 22.478

Long-Ranger ADCP v (cm/s) -70.41 74.87 -1.758 23.019

RDI Broadband 75 kHz 5165 230 - 238 m 5174 u (cm/s) -48.38 81.99 15.09 21.995

Long-Ranger ADCP v (cm/s) -67.4 77.66 -1.649 22.529

 C-6 
Table C-3. Statistics from Mooring 2 Deployment 1 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5165 238 - 246 m 5174 u (cm/s) -47.1 83.03 14.599 21.489

Long-Ranger ADCP v (cm/s) -64.3 73.06 -1.563 22.018

RDI Broadband 75 kHz 5165 246 - 254 m 5174 u (cm/s) -47.56 81.43 14.099 21.012

Long-Ranger ADCP v (cm/s) -62.11 75.14 -1.388 21.715

RDI Broadband 75 kHz 5165 254 - 262 m 5174 u (cm/s) -46.75 81.69 13.709 20.758

Long-Ranger ADCP v (cm/s) -61.1 76.72 -1.198 21.475

RDI Broadband 75 kHz 5165 262 - 270 m 5169 u (cm/s) -49.15 80.23 13.355 20.719

Long-Ranger ADCP v (cm/s) -57.44 76 -1.108 21.053

RDI Broadband 75 kHz 5165 270 - 278 m 5113 u (cm/s) -48.43 84.75 12.617 20.252

Long-Ranger ADCP v (cm/s) -57.09 67.4 -0.86 20.283

RDI Broadband 75 kHz 5165 278 - 286 m 4915 u (cm/s) -45.14 78.17 11.075 18.791

Long-Ranger ADCP v (cm/s) -52.51 67.02 -0.541 19.44

RDI Broadband 75 kHz 5165 286 - 294 m 4800 u (cm/s) -48.4 76.2 10.449 17.585

Long-Ranger ADCP v (cm/s) -51.69 65.34 -0.492 18.927

RDI Broadband 75 kHz 5165 294 - 302 m 4899 u (cm/s) -45.76 71.8 10.937 17.607

Long-Ranger ADCP v (cm/s) -51.51 64.56 -0.812 18.94

RDI Broadband 75 kHz 5165 302 - 310 m 5009 u (cm/s) -45.23 74.14 11.089 18.042

Long-Ranger ADCP v (cm/s) -51.46 60.97 -1.156 18.801

RDI Broadband 75 kHz 5165 310 - 318 m 5042 u (cm/s) -43.86 73.88 11.098 17.917

Long-Ranger ADCP v (cm/s) -48.96 58.12 -1.17 18.607

RDI Broadband 75 kHz 5165 318 - 326 m 5087 u (cm/s) -45.24 70.87 10.774 17.561

Long-Ranger ADCP v (cm/s) -51.13 56.33 -1.049 18.235

RDI Broadband 75 kHz 5165 326 - 334 m 5158 u (cm/s) -44.96 68.6 10.413 17.447

Long-Ranger ADCP v (cm/s) -47.29 55.09 -0.881 18.045

RDI Broadband 75 kHz 5165 334 - 342 m 5171 u (cm/s) -42.44 65.95 10.062 17.133

Long-Ranger ADCP v (cm/s) -48.19 53 -0.735 17.816

RDI Broadband 75 kHz 5165 342 - 350 m 5173 u (cm/s) -45.77 63.7 9.806 16.745

Long-Ranger ADCP v (cm/s) -46.05 54.45 -0.661 17.455

RDI Broadband 75 kHz 5165 350 - 358 m 5174 u (cm/s) -45.79 63.17 9.568 16.405

Long-Ranger ADCP v (cm/s) -45.69 51.2 -0.613 17.195

RDI Broadband 75 kHz 5165 358 - 366 m 5174 u (cm/s) -47.57 59.74 9.348 15.995

Long-Ranger ADCP v (cm/s) -44.98 50.77 -0.581 16.918

RDI Broadband 75 kHz 5165 366 - 374 m 5174 u (cm/s) -44.17 59.41 9.116 15.733

Long-Ranger ADCP v (cm/s) -45.25 49.29 -0.594 16.565

RDI Broadband 75 kHz 5165 374 - 382 m 5174 u (cm/s) -40.45 56.81 8.788 15.38

Long-Ranger ADCP v (cm/s) -44.69 49.56 -0.535 16.2

RDI Broadband 75 kHz 5165 382 - 390 m 5174 u (cm/s) -38.94 56.09 8.467 15.008

Long-Ranger ADCP v (cm/s) -42.39 45.61 -0.457 15.911

RDI Broadband 75 kHz 5165 390 - 398 m 5174 u (cm/s) -39.43 58.12 8.287 14.719

Long-Ranger ADCP v (cm/s) -44.04 45.39 -0.396 15.529

RDI Broadband 75 kHz 5165 398 - 406 m 5174 u (cm/s) -37.77 53.73 8.027 14.417

Long-Ranger ADCP v (cm/s) -39.66 42.74 -0.359 15.131

RDI Broadband 75 kHz 5165 406 - 414 m 5174 u (cm/s) -39.19 54.22 7.755 14.053

Long-Ranger ADCP v (cm/s) -39.73 43.59 -0.355 14.736

RDI Broadband 75 kHz 5165 414 - 422 m 5174 u (cm/s) -38.8 54.25 7.485 13.554

Long-Ranger ADCP v (cm/s) -37.05 43.26 -0.385 14.253

 C-7 
Table C-4 

Statistics from Mooring 2 Deployment 1 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 81617 0749 m 5174 u (cm/s) -23.48 27.26 2.601 7.574

v (cm/s) -27.22 35.52 -0.062 8.115

Aanderaa RCM 7 7507 0997 m 5174 u (cm/s) -16.55 16.41 0.579 5.071

v (cm/s) -13.27 22.48 -0.055 5.161

Aanderaa RCM 8s 7771 1244 m 5174 u (cm/s) -21.81 21.18 -0.205 6.658

v (cm/s) -20.17 20.34 -0.783 5.929

Aanderaa RCM 8 12803 1492 m 5174 u (cm/s) -14.54 14.39 -0.449 4.13

v (cm/s) -10.46 9.77 -0.419 2.955

Aanderaa RCM 8s 9807 1995 m 5174 u (cm/s) -20.3 21.97 -1.053 6.675

v (cm/s) -19.6 20.92 -0.91 5.301

Aanderaa RCM 8 12807 2499 m 2240 u (cm/s) -10.73 13.53 -0.335 3.546

v (cm/s) -9.57 7.62 -0.043 2.734

 C-8 
Table C-5 

Statistics from Mooring 3 Deployment 1 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5699 38 - 46 m 1737 u (cm/s) -34.55 64.43 15.652 18.119

Long-Ranger ADCP v (cm/s) -70.26 33.84 -11.52 20.988

RDI Broadband 75 kHz 5699 46 - 54 m 2688 u (cm/s) -28.22 78.65 23.931 21.669

Long-Ranger ADCP v (cm/s) -89.47 44.84 -13.777 22.557

RDI Broadband 75 kHz 5699 54 - 62 m 3702 u (cm/s) -33.58 110.63 31.145 25.578

Long-Ranger ADCP v (cm/s) -103.9 50.61 -14.957 25.284

RDI Broadband 75 kHz 5699 62 - 70 m 4278 u (cm/s) -34.22 119.15 34.292 28.156

Long-Ranger ADCP v (cm/s) -122.83 56.78 -17.844 29.467

RDI Broadband 75 kHz 5699 70 - 78 m 4703 u (cm/s) -32.71 113.44 35.223 29.021

Long-Ranger ADCP v (cm/s) -135.97 58.59 -19.13 32.147

RDI Broadband 75 kHz 5699 78 - 86 m 4902 u (cm/s) -27.86 118.95 36.288 30.052

Long-Ranger ADCP v (cm/s) -124.66 64.97 -18.191 32.421

RDI Broadband 75 kHz 5699 86 - 94 m 5063 u (cm/s) -28.23 128.35 37.155 31.023

Long-Ranger ADCP v (cm/s) -119.43 83.82 -17.094 33.028

RDI Broadband 75 kHz 5699 94 - 102 m 5125 u (cm/s) -32.3 133.1 37 31.544

Long-Ranger ADCP v (cm/s) -115.73 80.95 -16.095 32.733

RDI Broadband 75 kHz 5699 102 - 110 m 5149 u (cm/s) -36.5 131.53 36.32 31.468

Long-Ranger ADCP v (cm/s) -109.92 78.81 -15.138 32.006

RDI Broadband 75 kHz 5699 110 - 118 m 5149 u (cm/s) -31.94 128.44 35.127 30.821

Long-Ranger ADCP v (cm/s) -104.49 81.45 -14.241 31.33

RDI Broadband 75 kHz 5699 118 - 126 m 5149 u (cm/s) -33.63 128.89 33.918 30.076

Long-Ranger ADCP v (cm/s) -102.7 85.1 -13.318 30.466

RDI Broadband 75 kHz 5699 126 - 134 m 5149 u (cm/s) -30.72 124.54 32.727 29.179

Long-Ranger ADCP v (cm/s) -102.21 82.61 -12.538 29.482

RDI Broadband 75 kHz 5699 134 - 142 m 5149 u (cm/s) -33.26 122.61 31.609 28.138

Long-Ranger ADCP v (cm/s) -100.4 80.34 -11.966 28.627

RDI Broadband 75 kHz 5699 142 - 150 m 5149 u (cm/s) -33.5 114.78 30.36 26.873

Long-Ranger ADCP v (cm/s) -98.48 73.52 -11.495 27.828

RDI Broadband 75 kHz 5699 150 - 158 m 5149 u (cm/s) -35.6 108.5 29.02 25.645

Long-Ranger ADCP v (cm/s) -96.42 70.86 -10.886 27.089

RDI Broadband 75 kHz 5699 158 - 166 m 5149 u (cm/s) -31.45 99.45 27.758 24.63

Long-Ranger ADCP v (cm/s) -90.1 66.3 -10.186 26.34

RDI Broadband 75 kHz 5699 166 - 174 m 5149 u (cm/s) -36.76 97.37 26.534 23.841

Long-Ranger ADCP v (cm/s) -87.04 55.83 -9.572 25.603

RDI Broadband 75 kHz 5699 174 - 182 m 5149 u (cm/s) -35.13 100.09 25.442 23.213

Long-Ranger ADCP v (cm/s) -87.71 51.23 -9.058 24.818

RDI Broadband 75 kHz 5699 182 - 190 m 5149 u (cm/s) -32.06 102.82 24.541 22.616

Long-Ranger ADCP v (cm/s) -86.64 50.4 -8.611 24.047

RDI Broadband 75 kHz 5699 190 - 198 m 5149 u (cm/s) -24.09 97.67 23.554 21.982

Long-Ranger ADCP v (cm/s) -84.7 49.07 -8.055 23.508

RDI Broadband 75 kHz 5699 198 - 206 m 5149 u (cm/s) -27.75 94.2 22.624 21.457

Long-Ranger ADCP v (cm/s) -82.75 51.38 -7.52 22.971

RDI Broadband 75 kHz 5699 206 - 214 m 5149 u (cm/s) -31.02 96.86 21.858 21.092

Long-Ranger ADCP v (cm/s) -80.29 54.85 -7.15 22.396

RDI Broadband 75 kHz 5699 214 - 222 m 5149 u (cm/s) -31 98.76 21.185 20.683

Long-Ranger ADCP v (cm/s) -77.79 54.63 -6.787 21.819

RDI Broadband 75 kHz 5699 222 - 230 m 5149 u (cm/s) -32.73 94.34 20.658 20.264

Long-Ranger ADCP v (cm/s) -73.43 54.34 -6.557 21.336

RDI Broadband 75 kHz 5699 230 - 238 m 5149 u (cm/s) -30.04 91.71 20.032 19.839

Long-Ranger ADCP v (cm/s) -73.36 53.17 -6.235 20.865

RDI Broadband 75 kHz 5699 238 - 246 m 5149 u (cm/s) -24.15 91.98 19.392 19.395

Long-Ranger ADCP v (cm/s) -73.56 52.15 -6.025 20.272

 C-9 
Table C-5. Statistics from Mooring 3 Deployment 1 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5699 246 - 254 m 5149 u (cm/s) -23.08 91.66 18.913 19.066

Long-Ranger ADCP v (cm/s) -68.89 51.43 -5.76 19.686

RDI Broadband 75 kHz 5699 254 - 262 m 5149 u (cm/s) -22.65 91 18.477 18.664

Long-Ranger ADCP v (cm/s) -70.34 50.95 -5.424 19.204

RDI Broadband 75 kHz 5699 262 - 270 m 5149 u (cm/s) -22.13 92.32 18.071 18.348

Long-Ranger ADCP v (cm/s) -64.12 50.71 -5.105 18.806

RDI Broadband 75 kHz 5699 270 - 278 m 5149 u (cm/s) -20.79 89.76 17.699 18.003

Long-Ranger ADCP v (cm/s) -63.25 49.79 -4.833 18.444

RDI Broadband 75 kHz 5699 278 - 286 m 5149 u (cm/s) -21.51 87.63 17.273 17.708

Long-Ranger ADCP v (cm/s) -63.14 49.32 -4.591 18.138

RDI Broadband 75 kHz 5699 286 - 294 m 5149 u (cm/s) -21.19 86.92 16.778 17.371

Long-Ranger ADCP v (cm/s) -60.69 51.91 -4.432 17.888

RDI Broadband 75 kHz 5699 294 - 302 m 5149 u (cm/s) -23.24 82.2 16.358 17.082

Long-Ranger ADCP v (cm/s) -58.36 50.85 -4.268 17.624

RDI Broadband 75 kHz 5699 302 - 310 m 5149 u (cm/s) -23.65 83.86 16.033 16.824

Long-Ranger ADCP v (cm/s) -60.06 49.79 -4.143 17.303

RDI Broadband 75 kHz 5699 310 - 318 m 5149 u (cm/s) -19.82 81.8 15.8 16.554

Long-Ranger ADCP v (cm/s) -57.33 47.39 -4.012 17.071

RDI Broadband 75 kHz 5699 318 - 326 m 5149 u (cm/s) -20.84 80.55 15.434 16.251

Long-Ranger ADCP v (cm/s) -56.54 47.47 -3.937 16.887

RDI Broadband 75 kHz 5699 326 - 334 m 5149 u (cm/s) -19.22 78.08 15.115 15.981

Long-Ranger ADCP v (cm/s) -55.15 46.75 -3.867 16.698

RDI Broadband 75 kHz 5699 334 - 342 m 5149 u (cm/s) -20.41 75.89 14.893 15.657

Long-Ranger ADCP v (cm/s) -55.53 46.46 -3.724 16.365

RDI Broadband 75 kHz 5699 342 - 350 m 5149 u (cm/s) -22.19 74.85 14.572 15.499

Long-Ranger ADCP v (cm/s) -55.49 45.56 -3.547 16.154

RDI Broadband 75 kHz 5699 350 - 358 m 5149 u (cm/s) -22.13 73.36 14.278 15.285

Long-Ranger ADCP v (cm/s) -53.66 43.81 -3.4 15.987

RDI Broadband 75 kHz 5699 358 - 366 m 5149 u (cm/s) -23.72 76.1 14.005 15.084

Long-Ranger ADCP v (cm/s) -48.75 45.39 -3.251 15.712

RDI Broadband 75 kHz 5699 366 - 374 m 5149 u (cm/s) -21.88 72.26 13.744 14.804

Long-Ranger ADCP v (cm/s) -50.05 44.79 -3.148 15.453

RDI Broadband 75 kHz 5699 374 - 382 m 5149 u (cm/s) -24.33 68.83 13.496 14.549

Long-Ranger ADCP v (cm/s) -46.35 47.43 -2.975 15.209

RDI Broadband 75 kHz 5699 382 - 390 m 5149 u (cm/s) -22.18 69.19 13.275 14.247

Long-Ranger ADCP v (cm/s) -45.47 47.88 -2.955 14.887

RDI Broadband 75 kHz 5699 390 - 398 m 5149 u (cm/s) -22.22 63.47 12.951 13.893

Long-Ranger ADCP v (cm/s) -45.9 46.74 -2.842 14.7

RDI Broadband 75 kHz 5699 398 - 406 m 5149 u (cm/s) -20.63 64.46 12.698 13.612

Long-Ranger ADCP v (cm/s) -46.45 46.3 -2.665 14.368

RDI Broadband 75 kHz 5699 406 - 414 m 5149 u (cm/s) -21.58 61 12.469 13.417

Long-Ranger ADCP v (cm/s) -47.99 46.11 -2.551 14.035

RDI Broadband 75 kHz 5699 414 - 422 m 5149 u (cm/s) -19.41 61.68 12.151 13.191

Long-Ranger ADCP v (cm/s) -41.19 49.3 -2.424 13.777

RDI Broadband 75 kHz 5699 422 - 430 m 5149 u (cm/s) -22.38 60.91 11.867 12.978

Long-Ranger ADCP v (cm/s) -39.28 45.88 -2.338 13.556

RDI Broadband 75 kHz 5699 430 - 438 m 5149 u (cm/s) -20.47 58.54 11.585 12.665

Long-Ranger ADCP v (cm/s) -41.57 44.08 -2.342 13.301

RDI Broadband 75 kHz 5699 438 - 446 m 5149 u (cm/s) -19.79 57.9 11.304 12.388

Long-Ranger ADCP v (cm/s) -37.68 50.19 -2.249 13.088

RDI Broadband 75 kHz 5699 446 - 454 m 5149 u (cm/s) -19.17 60.67 10.99 12.148

Long-Ranger ADCP v (cm/s) -35.98 48.89 -2.158 12.78

RDI Broadband 75 kHz 5699 454 - 462 m 5149 u (cm/s) -20.26 57.38 10.627 11.931

Long-Ranger ADCP v (cm/s) -35.92 51.08 -2.078 12.469

 C-10 
Table C-6 

Statistics from Mooring 3 Deployment 1 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 2129 0750 m 5148 u (cm/s) -22.85 31.45 4.376 7.598

v (cm/s) -26.69 35.07 -0.405 8.177

Aanderaa RCM 7 12084 0998 m 5148 u (cm/s) -25.95 27.07 1.612 6.624

v (cm/s) -19.68 35.77 0.798 7.152

Aanderaa RCM 8s 10643 1245 m 5148 u (cm/s) -27.14 19.98 0.751 6.341

v (cm/s) -17.86 31.89 0.469 6.31

Aanderaa RCM 7 9480 1492 m 5148 u (cm/s) -21.86 17.49 0.029 5.859

v (cm/s) -16.27 32.01 0.841 5.585

Aanderaa RCM 8s 9809 1996 m 5148 u (cm/s) -27.96 20.91 0.913 6.701

v (cm/s) -20.28 32.16 -0.161 6.552

Aanderaa RCM 8 12808 2499 m 5148 u (cm/s) -29.02 21.31 -0.498 7.767

v (cm/s) -19.59 33 0.422 6.676

Aanderaa RCM 8 12809 2699 m 5148 u (cm/s) -28.3 19.91 -0.66 7.416

v (cm/s) -19.78 32.06 0.361 7

Table C-7 

Statistics from Mooring 4 Deployment 1 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

Aanderaa RCM 8s 10112 2530 m 5099 u (cm/s) -13.8 9.7 -2.896 4.346

v (cm/s) -12.05 14.61 -0.17 4.123

Aanderaa RCM 8 12810 2630 m 5099 u (cm/s) -14.25 10.58 -2.97 4.094

v (cm/s) -13.71 15.08 0.357 4.097

 C-11 
Table C-8 

Statistics from Mooring 1 Deployment 2 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 4844 45 - 53 m 1692 u (cm/s) -80.2 58.26 -10.158 16.831

Long-Ranger ADCP v (cm/s) -95.91 66.99 4.59 15.709

RDI Broadband 75 kHz 4844 53 - 61 m 3342 u (cm/s) -86.45 38.5 -20.523 18.12

Long-Ranger ADCP v (cm/s) -73.42 58.46 10.193 16.988

RDI Broadband 75 kHz 4844 61 - 69 m 3707 u (cm/s) -68.89 32.6 -21.542 17.228

Long-Ranger ADCP v (cm/s) -40.02 60.49 10.159 16.53

RDI Broadband 75 kHz 4844 69 - 77 m 3709 u (cm/s) -65.67 30.2 -21.143 16.626

Long-Ranger ADCP v (cm/s) -34.39 61.05 10.192 15.688

RDI Broadband 75 kHz 4844 77 - 85 m 3709 u (cm/s) -63.11 34.67 -20.774 16.119

Long-Ranger ADCP v (cm/s) -29.73 60.29 10.278 15.055

RDI Broadband 75 kHz 4844 85 - 93 m 3709 u (cm/s) -60.96 33.21 -20.368 15.645

Long-Ranger ADCP v (cm/s) -24.95 65.33 10.193 14.803

RDI Broadband 75 kHz 4844 93 - 101 m 3709 u (cm/s) -59.19 31.66 -20.212 15.174

Long-Ranger ADCP v (cm/s) -22.97 71.35 9.996 14.476

RDI Broadband 75 kHz 4844 101 - 109 m 3709 u (cm/s) -57.1 33.48 -20.05 14.679

Long-Ranger ADCP v (cm/s) -24.6 61.62 9.829 13.903

RDI Broadband 75 kHz 4844 109 - 117 m 3709 u (cm/s) -55.08 30.97 -20.005 14.24

Long-Ranger ADCP v (cm/s) -23.23 48.72 9.577 13.255

RDI Broadband 75 kHz 4844 117 - 125 m 3709 u (cm/s) -53.1 27.92 -19.902 13.821

Long-Ranger ADCP v (cm/s) -23.9 47.4 9.361 12.672

RDI Broadband 75 kHz 4844 125 - 133 m 3709 u (cm/s) -54.23 25.38 -19.596 13.555

Long-Ranger ADCP v (cm/s) -23.73 50.66 9.14 12.395

RDI Broadband 75 kHz 4844 133 - 141 m 3709 u (cm/s) -56 23.99 -19.361 13.33

Long-Ranger ADCP v (cm/s) -21.95 45.15 9.004 12.002

RDI Broadband 75 kHz 4844 141 - 149 m 3709 u (cm/s) -52.17 23.66 -19.054 12.972

Long-Ranger ADCP v (cm/s) -22.85 45.83 8.838 11.749

RDI Broadband 75 kHz 4844 149 - 157 m 3709 u (cm/s) -55.61 20.2 -18.827 12.778

Long-Ranger ADCP v (cm/s) -26.88 45.24 8.718 11.543

RDI Broadband 75 kHz 4844 157 - 165 m 3709 u (cm/s) -52.65 19.32 -18.633 12.443

Long-Ranger ADCP v (cm/s) -28.1 46.33 8.602 11.312

RDI Broadband 75 kHz 4844 165 - 173 m 3709 u (cm/s) -52.82 19.22 -18.437 12.266

Long-Ranger ADCP v (cm/s) -23.17 42.66 8.386 11.16

RDI Broadband 75 kHz 4844 173 - 181 m 3709 u (cm/s) -52.28 19.08 -18.173 12.14

Long-Ranger ADCP v (cm/s) -23.48 41.67 8.296 11.022

RDI Broadband 75 kHz 4844 181 - 189 m 3709 u (cm/s) -50.28 16.66 -17.911 11.944

Long-Ranger ADCP v (cm/s) -20.9 43.27 8.067 10.914

RDI Broadband 75 kHz 4844 189 - 197 m 3709 u (cm/s) -49.56 15.07 -17.667 11.79

Long-Ranger ADCP v (cm/s) -20.41 40.14 8.032 10.787

RDI Broadband 75 kHz 4844 197 - 205 m 3709 u (cm/s) -48.28 17.75 -17.347 11.631

Long-Ranger ADCP v (cm/s) -21.27 40.22 7.855 10.578

RDI Broadband 75 kHz 4844 205 - 213 m 3709 u (cm/s) -47.01 18.31 -17.078 11.497

Long-Ranger ADCP v (cm/s) -22.53 39.81 7.726 10.43

RDI Broadband 75 kHz 4844 213 - 221 m 3709 u (cm/s) -47.8 16.88 -16.917 11.366

Long-Ranger ADCP v (cm/s) -19.97 43.14 7.649 10.305

RDI Broadband 75 kHz 4844 221 - 229 m 3709 u (cm/s) -46.39 13.82 -16.613 11.234

Long-Ranger ADCP v (cm/s) -21.56 40.71 7.449 10.15

RDI Broadband 75 kHz 4844 229 - 237 m 3709 u (cm/s) -46.78 14.63 -16.393 11.151

Long-Ranger ADCP v (cm/s) -21.55 41.9 7.396 10.059

RDI Broadband 75 kHz 4844 237 - 245 m 3709 u (cm/s) -48.89 13.25 -16.283 11.079

Long-Ranger ADCP v (cm/s) -22.56 40.5 7.248 10.048

RDI Broadband 75 kHz 4844 245 - 253 m 3709 u (cm/s) -47.18 14.31 -16.03 10.967

Long-Ranger ADCP v (cm/s) -20.96 39.35 7.12 10.017

 C-12 
Table C-8. Statistics from Mooring 1 Deployment 2 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 4844 253 - 261 m 3709 u (cm/s) -43.7 14.62 -15.844 10.792

Long-Ranger ADCP v (cm/s) -23.2 42.19 7.002 9.933

RDI Broadband 75 kHz 4844 261 - 269 m 3709 u (cm/s) -44.6 13.92 -15.468 10.453

Long-Ranger ADCP v (cm/s) -20.51 38.5 6.991 9.629

RDI Broadband 75 kHz 4844 269 - 277 m 3709 u (cm/s) -43.87 14.21 -14.882 9.935

Long-Ranger ADCP v (cm/s) -18.31 37.25 6.739 9.226

RDI Broadband 75 kHz 4844 277 - 285 m 3709 u (cm/s) -43.2 12.77 -14.914 9.89

Long-Ranger ADCP v (cm/s) -21.9 35.14 6.636 9.078

RDI Broadband 75 kHz 4844 285 - 293 m 3709 u (cm/s) -43.5 12.79 -14.988 9.959

Long-Ranger ADCP v (cm/s) -22.45 36.33 6.725 9.259

RDI Broadband 75 kHz 4844 293 - 301 m 3709 u (cm/s) -45.1 15 -14.836 10.041

Long-Ranger ADCP v (cm/s) -22.18 37.4 6.604 9.166

RDI Broadband 75 kHz 4844 301 - 309 m 3709 u (cm/s) -45.08 13.64 -14.614 9.831

Long-Ranger ADCP v (cm/s) -23.5 34.45 6.499 9.077

RDI Broadband 75 kHz 4844 309 - 317 m 3709 u (cm/s) -43.45 14.89 -14.382 9.622

Long-Ranger ADCP v (cm/s) -23.72 32.74 6.393 8.925

RDI Broadband 75 kHz 4844 317 - 325 m 3709 u (cm/s) -42.97 14.17 -14.174 9.534

Long-Ranger ADCP v (cm/s) -25.1 33.5 6.41 8.743

RDI Broadband 75 kHz 4844 325 - 333 m 3709 u (cm/s) -44.51 14.01 -14.052 9.353

Long-Ranger ADCP v (cm/s) -23.74 32.27 6.399 8.597

RDI Broadband 75 kHz 4844 333 - 341 m 3709 u (cm/s) -41.59 12.88 -14.028 9.298

Long-Ranger ADCP v (cm/s) -23.01 33.11 6.356 8.512

RDI Broadband 75 kHz 4844 341 - 349 m 3709 u (cm/s) -41.83 14.1 -13.914 9.154

Long-Ranger ADCP v (cm/s) -22.89 32.67 6.313 8.456

RDI Broadband 75 kHz 4844 349 - 357 m 3709 u (cm/s) -41.19 15.88 -13.79 9.146

Long-Ranger ADCP v (cm/s) -23.41 32.1 6.124 8.36

RDI Broadband 75 kHz 4844 357 - 365 m 3709 u (cm/s) -41.99 19.27 -13.635 9.107

Long-Ranger ADCP v (cm/s) -23.42 33.24 5.97 8.327

RDI Broadband 75 kHz 4844 365 - 373 m 3709 u (cm/s) -41.69 17.58 -13.556 9.06

Long-Ranger ADCP v (cm/s) -21.73 30.18 5.926 8.253

RDI Broadband 75 kHz 4844 373 - 381 m 3709 u (cm/s) -41.32 15.69 -13.357 8.985

Long-Ranger ADCP v (cm/s) -20.74 33.85 5.879 8.244

RDI Broadband 75 kHz 4844 381 - 389 m 3709 u (cm/s) -41.69 14.39 -13.151 8.916

Long-Ranger ADCP v (cm/s) -19.45 31.3 5.921 8.199

RDI Broadband 75 kHz 4844 389 - 397 m 3709 u (cm/s) -40.74 15.7 -12.914 8.841

Long-Ranger ADCP v (cm/s) -19.62 33.69 5.79 8.208

RDI Broadband 75 kHz 4844 397 - 405 m 3709 u (cm/s) -42.13 18.64 -12.642 8.727

Long-Ranger ADCP v (cm/s) -17.51 30.3 5.724 8.119

RDI Broadband 75 kHz 4844 405 - 413 m 3709 u (cm/s) -40.72 15.8 -12.455 8.65

Long-Ranger ADCP v (cm/s) -19.18 34 5.62 8.136

RDI Broadband 75 kHz 4844 413 - 421 m 3709 u (cm/s) -38.83 17.89 -12.324 8.608

Long-Ranger ADCP v (cm/s) -19.9 33.28 5.576 8.104

RDI Broadband 75 kHz 4844 421 - 429 m 3709 u (cm/s) -42.96 15.63 -12.206 8.573

Long-Ranger ADCP v (cm/s) -19.12 30.05 5.565 8.099

RDI Broadband 75 kHz 4844 429 - 437 m 3709 u (cm/s) -41.39 14.54 -12.055 8.486

Long-Ranger ADCP v (cm/s) -18.63 30.99 5.554 8.071

RDI Broadband 75 kHz 4844 437 - 445 m 3709 u (cm/s) -40.68 16.88 -11.85 8.474

Long-Ranger ADCP v (cm/s) -19.37 32.78 5.488 8.107

RDI Broadband 75 kHz 4844 445 - 453 m 3709 u (cm/s) -40.65 16.8 -11.663 8.41

Long-Ranger ADCP v (cm/s) -21.4 32.9 5.381 8.137

RDI Broadband 75 kHz 4844 453 - 461 m 3709 u (cm/s) -41.38 16.92 -11.471 8.304

Long-Ranger ADCP v (cm/s) -21.2 31.47 5.306 8.107

 C-13 
Table C-8. Statistics from Mooring 1 Deployment 2 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 4844 461 - 469 m 3709 u (cm/s) -41.4 17.82 -11.318 8.242

Long-Ranger ADCP v (cm/s) -18.96 31.83 5.157 8.067

RDI Broadband 75 kHz 4844 469 - 477 m 3709 u (cm/s) -37.33 17.34 -11.194 8.193

Long-Ranger ADCP v (cm/s) -22.85 33.01 4.966 7.988

RDI Broadband 75 kHz 4844 477 - 485 m 3709 u (cm/s) -38.55 17.36 -10.853 8.06

Long-Ranger ADCP v (cm/s) -18.58 32.49 4.883 7.875

RDI Broadband 75 kHz 4844 485 - 493 m 3709 u (cm/s) -36.97 20.26 -10.164 7.908

Long-Ranger ADCP v (cm/s) -17.6 29.93 4.659 7.612

Table C-9 

Statistics from Mooring 1 Deployment 2 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 78017 0749 m 3732 u (cm/s) -40.02 42.19 -6.475 7.259

v (cm/s) -33.82 41.73 3.025 7.247

Aanderaa RCM 7 12805 0997 m 3732 u (cm/s) -27.17 26.75 -3.792 6.002

v (cm/s) -24.73 29.7 2.762 5.804

Aanderaa RCM 7 7692 1244 m 1731 u (cm/s) -15.05 11.45 -0.607 4.216

v (cm/s) -10.98 16.9 1.596 4.371

Aanderaa RCM 7 9722 1492 m 3732 u (cm/s) -12.12 10.51 -0.427 2.902

v (cm/s) -11.03 12.82 0.879 2.57

Aanderaa RCM 8s 10053 1995 m 3732 u (cm/s) -9.11 10.96 0.046 2.962

v (cm/s) -12.38 11.21 0.503 2.774

Aanderaa RCM 8 12085 2499 m 3733 u (cm/s) -18.09 15.94 0.385 4.333

v (cm/s) -16.67 18.42 0.228 4.237

 C-14 
Table C-10 

Statistics from Mooring 2 Deployment 2 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5165 50 - 58 m 472 u (cm/s) -47.39 18.05 -7.909 11.596

Long-Ranger ADCP v (cm/s) -38.08 54.59 8.775 18.077

RDI Broadband 75 kHz 5165 58 - 66 m 2867 u (cm/s) -58.59 81.27 -5.148 20.853

Long-Ranger ADCP v (cm/s) -58.43 59.11 5.982 24.036

RDI Broadband 75 kHz 5165 66 - 74 m 3449 u (cm/s) -88.28 77.46 -4.475 22.391

Long-Ranger ADCP v (cm/s) -60.22 70.38 5.583 26.836

RDI Broadband 75 kHz 5165 74 - 82 m 3621 u (cm/s) -72.76 75.76 -4.441 21.899

Long-Ranger ADCP v (cm/s) -60.15 73.08 5.866 27.446

RDI Broadband 75 kHz 5165 82 - 90 m 3626 u (cm/s) -69.67 67.49 -5.011 20.98

Long-Ranger ADCP v (cm/s) -58.03 73.87 5.624 27.394

RDI Broadband 75 kHz 5165 90 - 98 m 3626 u (cm/s) -76.43 54.6 -5.367 20.038

Long-Ranger ADCP v (cm/s) -57.95 69.04 5.333 26.984

RDI Broadband 75 kHz 5165 98 - 106 m 3626 u (cm/s) -77.88 50.32 -5.527 19.084

Long-Ranger ADCP v (cm/s) -55.05 71.05 5.115 26.724

RDI Broadband 75 kHz 5165 106 - 114 m 3626 u (cm/s) -76.7 50.97 -5.739 18.217

Long-Ranger ADCP v (cm/s) -51.95 75.44 4.957 26.47

RDI Broadband 75 kHz 5165 114 - 122 m 3626 u (cm/s) -75.35 49.47 -5.994 17.343

Long-Ranger ADCP v (cm/s) -53.44 82.85 4.787 26.263

RDI Broadband 75 kHz 5165 122 - 130 m 3626 u (cm/s) -79.24 44.48 -6.189 16.451

Long-Ranger ADCP v (cm/s) -57.15 82.71 4.832 26.175

RDI Broadband 75 kHz 5165 130 - 138 m 3626 u (cm/s) -72.87 41.58 -6.561 15.56

Long-Ranger ADCP v (cm/s) -55.32 71.4 4.598 25.918

RDI Broadband 75 kHz 5165 138 - 146 m 3626 u (cm/s) -66.69 37.48 -6.787 14.916

Long-Ranger ADCP v (cm/s) -56.93 70.56 4.261 25.659

RDI Broadband 75 kHz 5165 146 - 154 m 3626 u (cm/s) -65.54 33.31 -6.872 14.6

Long-Ranger ADCP v (cm/s) -57.52 66.5 4.145 25.388

RDI Broadband 75 kHz 5165 154 - 162 m 3626 u (cm/s) -59.72 32.93 -7.01 14.32

Long-Ranger ADCP v (cm/s) -56.76 65.98 4.026 25.176

RDI Broadband 75 kHz 5165 162 - 170 m 3626 u (cm/s) -58.61 34.36 -7.135 14.021

Long-Ranger ADCP v (cm/s) -57.49 64.82 4.014 24.79

RDI Broadband 75 kHz 5165 170 - 178 m 3626 u (cm/s) -59.67 32.26 -7.228 13.61

Long-Ranger ADCP v (cm/s) -54.38 63 3.922 24.438

RDI Broadband 75 kHz 5165 178 - 186 m 3626 u (cm/s) -56.01 33.52 -7.141 13.398

Long-Ranger ADCP v (cm/s) -55.2 62.24 3.937 24.317

RDI Broadband 75 kHz 5165 186 - 194 m 3626 u (cm/s) -53.49 34.62 -7.067 13.169

Long-Ranger ADCP v (cm/s) -55.02 58.05 3.981 24.186

RDI Broadband 75 kHz 5165 194 - 202 m 3626 u (cm/s) -48.17 33.44 -7.062 12.978

Long-Ranger ADCP v (cm/s) -53.14 56.26 3.97 24.097

RDI Broadband 75 kHz 5165 202 - 210 m 3626 u (cm/s) -47.55 32.11 -7.051 12.809

Long-Ranger ADCP v (cm/s) -51.5 56.34 3.824 23.799

RDI Broadband 75 kHz 5165 210 - 218 m 3626 u (cm/s) -48.66 28.71 -7.101 12.546

Long-Ranger ADCP v (cm/s) -50.58 57.6 3.841 23.59

RDI Broadband 75 kHz 5165 218 - 226 m 3626 u (cm/s) -46.88 29.12 -7.096 12.287

Long-Ranger ADCP v (cm/s) -53.39 57.63 3.736 23.295

RDI Broadband 75 kHz 5165 226 - 234 m 3626 u (cm/s) -46.8 27.91 -7.166 12.085

Long-Ranger ADCP v (cm/s) -53.89 55.39 3.659 22.947

RDI Broadband 75 kHz 5165 234 - 242 m 3626 u (cm/s) -43.47 26.32 -7.139 11.953

Long-Ranger ADCP v (cm/s) -53.89 57.8 3.613 22.789

RDI Broadband 75 kHz 5165 242 - 250 m 3626 u (cm/s) -44.9 30.46 -7.124 11.752

Long-Ranger ADCP v (cm/s) -53.5 52.68 3.616 22.618

RDI Broadband 75 kHz 5165 250 - 258 m 3626 u (cm/s) -43.48 28.59 -7.004 11.538

Long-Ranger ADCP v (cm/s) -51.9 51.95 3.546 22.257

 C-15 
Table C-10. Statistics from Mooring 2 Deployment 2 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5165 258 - 266 m 3626 u (cm/s) -44.34 27.63 -6.982 11.292

Long-Ranger ADCP v (cm/s) -51.68 52.15 3.368 21.843

RDI Broadband 75 kHz 5165 266 - 274 m 3626 u (cm/s) -42.9 26.79 -6.894 11.195

Long-Ranger ADCP v (cm/s) -53.22 53.77 3.368 21.59

RDI Broadband 75 kHz 5165 274 - 282 m 3626 u (cm/s) -43.23 25.38 -6.916 11.018

Long-Ranger ADCP v (cm/s) -51.51 52.58 3.328 21.259

RDI Broadband 75 kHz 5165 282 - 290 m 3626 u (cm/s) -42.5 25.42 -6.823 10.85

Long-Ranger ADCP v (cm/s) -51.84 51.2 3.303 21.017

RDI Broadband 75 kHz 5165 290 - 298 m 3626 u (cm/s) -42.72 25.35 -6.724 10.779

Long-Ranger ADCP v (cm/s) -46.9 54.34 3.287 20.703

RDI Broadband 75 kHz 5165 298 - 306 m 3626 u (cm/s) -43.03 24.08 -6.638 10.615

Long-Ranger ADCP v (cm/s) -46.95 50.89 3.262 20.436

RDI Broadband 75 kHz 5165 306 - 314 m 3626 u (cm/s) -42.29 22.94 -6.559 10.451

Long-Ranger ADCP v (cm/s) -46.61 52.72 3.153 20.216

RDI Broadband 75 kHz 5165 314 - 322 m 3626 u (cm/s) -45.14 23.58 -6.573 10.381

Long-Ranger ADCP v (cm/s) -46.43 55.86 3.125 20.037

RDI Broadband 75 kHz 5165 322 - 330 m 3626 u (cm/s) -45.57 21.46 -6.574 10.365

Long-Ranger ADCP v (cm/s) -44.25 50.67 3.037 19.779

RDI Broadband 75 kHz 5165 330 - 338 m 3626 u (cm/s) -43.79 23.84 -6.497 10.214

Long-Ranger ADCP v (cm/s) -44.61 49.2 2.969 19.516

RDI Broadband 75 kHz 5165 338 - 346 m 3626 u (cm/s) -43.2 22.35 -6.434 10.154

Long-Ranger ADCP v (cm/s) -42.52 47.67 2.859 19.182

RDI Broadband 75 kHz 5165 346 - 354 m 3626 u (cm/s) -43.93 25.94 -6.383 10.1

Long-Ranger ADCP v (cm/s) -42.37 44.88 2.837 18.883

RDI Broadband 75 kHz 5165 354 - 362 m 3626 u (cm/s) -42.99 24.3 -6.274 10.068

Long-Ranger ADCP v (cm/s) -47.19 47.68 2.793 18.543

RDI Broadband 75 kHz 5165 362 - 370 m 3626 u (cm/s) -42.47 23.02 -6.219 9.885

Long-Ranger ADCP v (cm/s) -45.11 46.4 2.685 18.303

RDI Broadband 75 kHz 5165 370 - 378 m 3626 u (cm/s) -42.11 23.64 -6.105 9.791

Long-Ranger ADCP v (cm/s) -44.95 43.3 2.539 17.983

RDI Broadband 75 kHz 5165 378 - 386 m 3626 u (cm/s) -43.11 24.57 -5.973 9.68

Long-Ranger ADCP v (cm/s) -45.15 43.29 2.425 17.742

RDI Broadband 75 kHz 5165 386 - 394 m 3626 u (cm/s) -39.24 25.44 -5.827 9.613

Long-Ranger ADCP v (cm/s) -45.52 40.94 2.398 17.385

RDI Broadband 75 kHz 5165 394 - 402 m 3626 u (cm/s) -40.47 25.48 -5.787 9.444

Long-Ranger ADCP v (cm/s) -45.9 41.3 2.414 17.117

RDI Broadband 75 kHz 5165 402 - 410 m 3626 u (cm/s) -38.18 26.45 -5.641 9.207

Long-Ranger ADCP v (cm/s) -43.94 41.59 2.372 16.784

RDI Broadband 75 kHz 5165 410 - 418 m 3626 u (cm/s) -36.09 25.8 -5.569 9.073

Long-Ranger ADCP v (cm/s) -43.94 41.39 2.379 16.492

RDI Broadband 75 kHz 5165 418 - 426 m 3626 u (cm/s) -33.73 26.36 -5.47 8.987

Long-Ranger ADCP v (cm/s) -43 43.78 2.412 16.284

RDI Broadband 75 kHz 5165 426 - 434 m 3626 u (cm/s) -36.45 27.16 -5.367 8.931

Long-Ranger ADCP v (cm/s) -42.73 42.71 2.286 15.949

RDI Broadband 75 kHz 5165 434 - 442 m 3626 u (cm/s) -39.31 25.25 -5.241 8.94

Long-Ranger ADCP v (cm/s) -40.73 41.68 2.222 15.739

RDI Broadband 75 kHz 5165 442 - 450 m 3626 u (cm/s) -38.53 26.2 -5.096 8.87

Long-Ranger ADCP v (cm/s) -39.5 41.1 2.188 15.533

RDI Broadband 75 kHz 5165 450 - 458 m 3626 u (cm/s) -35.95 27.08 -5.001 8.859

Long-Ranger ADCP v (cm/s) -37.85 39.75 2.074 15.241

RDI Broadband 75 kHz 5165 458 - 466 m 3626 u (cm/s) -38.25 26.84 -4.996 8.847

Long-Ranger ADCP v (cm/s) -38.58 41.4 1.948 14.948

 C-16 
Table C-10. Statistics from Mooring 2 Deployment 2 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5165 466 - 474 m 3626 u (cm/s) -39.52 22.09 -4.862 8.822

Long-Ranger ADCP v (cm/s) -37.49 42.03 1.786 14.547

RDI Broadband 75 kHz 5165 474 - 482 m 3626 u (cm/s) -37.1 23.5 -4.693 8.733

Long-Ranger ADCP v (cm/s) -36.6 42.99 1.651 14.138

RDI Broadband 75 kHz 5165 482 - 490 m 3626 u (cm/s) -35.43 23.43 -4.48 8.517

Long-Ranger ADCP v (cm/s) -35.5 38.65 1.476 13.611

RDI Broadband 75 kHz 5165 490 - 498 m 3626 u (cm/s) -34.77 20.94 -4.158 8.057

Long-Ranger ADCP v (cm/s) -34.41 40.25 1.275 12.836

Table C-11 

Statistics from Mooring 2 Deployment 2 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 81617 0749 m 3626 u (cm/s) -22.69 22.46 -2.137 5.749

v (cm/s) -24.71 23.93 0.239 7.433

Aanderaa RCM 7 7507 0997 m 3626 u (cm/s) -17.56 18.19 -0.18 5.635

v (cm/s) -17.16 16.47 0.165 5.092

Aanderaa RCM 8s 7771 1244 m 3626 u (cm/s) -18 20.29 0.575 5.628

v (cm/s) -12.68 13.5 0.045 3.884

Aanderaa RCM 8 12803 1492 m 3626 u (cm/s) -20.44 27.19 1.254 6.659

v (cm/s) -12.89 16.7 0.226 4.2

Aanderaa RCM 8s 9807 1995 m 3626 u (cm/s) -19.84 30.19 1.735 7.457

v (cm/s) -16.26 14.47 -0.529 4.172

Aanderaa RCM 8 12807 2499 m 1308 u (cm/s) -23.13 18.84 2.164 7.852

v (cm/s) -16.2 11.94 -1.092 4.893

 C-17 
Table C-12 

Statistics from Mooring 3 Deployment 2 ADCP for the u and v components of the currents 

measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5699 30 - 38 m 0 u (cm/s) ********** ********** ********** ********

Long-Ranger ADCP v (cm/s) ********** ********** ********** ********

RDI Broadband 75 kHz 5699 38 - 46 m 553 u (cm/s) -42.34 50.6 -1.641 18.334

Long-Ranger ADCP v (cm/s) -15.54 46.56 16.196 11.756

RDI Broadband 75 kHz 5699 46 - 54 m 1309 u (cm/s) -44.01 74.5 6.679 22.472

Long-Ranger ADCP v (cm/s) -38.09 61.1 10.61 17.875

RDI Broadband 75 kHz 5699 54 - 62 m 3022 u (cm/s) -46.46 100.36 26.049 28.589

Long-Ranger ADCP v (cm/s) -83.64 83.8 5.182 25.276

RDI Broadband 75 kHz 5699 62 - 70 m 3438 u (cm/s) -46.32 99.89 28.92 29.353

Long-Ranger ADCP v (cm/s) -79.98 88.51 3.06 26.419

RDI Broadband 75 kHz 5699 70 - 78 m 3587 u (cm/s) -46.17 107.91 29.979 30.111

Long-Ranger ADCP v (cm/s) -79.6 87.71 2.632 26.529

RDI Broadband 75 kHz 5699 78 - 86 m 3665 u (cm/s) -48.86 104.36 30.252 30.513

Long-Ranger ADCP v (cm/s) -78.16 90.76 2.609 26.377

RDI Broadband 75 kHz 5699 86 - 94 m 3689 u (cm/s) -47.23 109 29.398 30.098

Long-Ranger ADCP v (cm/s) -80.17 98.92 2.511 26.336

RDI Broadband 75 kHz 5699 94 - 102 m 3698 u (cm/s) -51.82 103.86 28.538 29.561

Long-Ranger ADCP v (cm/s) -74.97 105.08 2.574 26.326

RDI Broadband 75 kHz 5699 102 - 110 m 3698 u (cm/s) -59.1 105.41 27.566 28.934

Long-Ranger ADCP v (cm/s) -71.52 100.75 2.724 26.124

RDI Broadband 75 kHz 5699 110 - 118 m 3698 u (cm/s) -62.63 105.01 26.575 28.304

Long-Ranger ADCP v (cm/s) -68.67 96 2.864 25.813

RDI Broadband 75 kHz 5699 118 - 126 m 3698 u (cm/s) -60.91 107.68 25.662 27.563

Long-Ranger ADCP v (cm/s) -74.43 96.11 2.853 25.368

RDI Broadband 75 kHz 5699 126 - 134 m 3698 u (cm/s) -56.07 107.74 24.723 26.691

Long-Ranger ADCP v (cm/s) -73.04 92.36 2.86 24.976

RDI Broadband 75 kHz 5699 134 - 142 m 3698 u (cm/s) -48.16 103.88 23.911 25.99

Long-Ranger ADCP v (cm/s) -75.31 90.9 2.956 24.52

RDI Broadband 75 kHz 5699 142 - 150 m 3698 u (cm/s) -47.51 101.38 23.226 25.207

Long-Ranger ADCP v (cm/s) -72.39 86.14 3.173 24.079

RDI Broadband 75 kHz 5699 150 - 158 m 3698 u (cm/s) -42.3 98.42 22.575 24.461

Long-Ranger ADCP v (cm/s) -69.69 81.52 3.288 23.774

RDI Broadband 75 kHz 5699 158 - 166 m 3698 u (cm/s) -38.54 98.89 22.11 23.848

Long-Ranger ADCP v (cm/s) -67.08 79.29 3.31 23.382

RDI Broadband 75 kHz 5699 166 - 174 m 3698 u (cm/s) -39.7 94.35 21.531 23.284

Long-Ranger ADCP v (cm/s) -64.77 75.57 3.334 23.012

RDI Broadband 75 kHz 5699 174 - 182 m 3698 u (cm/s) -38.71 93.75 20.988 22.738

Long-Ranger ADCP v (cm/s) -64.63 73.9 3.28 22.558

RDI Broadband 75 kHz 5699 182 - 190 m 3698 u (cm/s) -40.72 90.7 20.365 22.157

Long-Ranger ADCP v (cm/s) -64.18 74.5 3.243 22.249

RDI Broadband 75 kHz 5699 190 - 198 m 3698 u (cm/s) -37.47 90.35 19.891 21.783

Long-Ranger ADCP v (cm/s) -62.6 73.17 3.239 21.987

RDI Broadband 75 kHz 5699 198 - 206 m 3698 u (cm/s) -39.85 86.29 19.43 21.328

Long-Ranger ADCP v (cm/s) -61.18 74.04 3.311 21.665

RDI Broadband 75 kHz 5699 206 - 214 m 3698 u (cm/s) -36.33 83.08 18.988 20.972

Long-Ranger ADCP v (cm/s) -59.99 73.6 3.269 21.46

RDI Broadband 75 kHz 5699 214 - 222 m 3698 u (cm/s) -33.99 79.74 18.576 20.653

Long-Ranger ADCP v (cm/s) -58.06 75.23 3.197 21.113

RDI Broadband 75 kHz 5699 222 - 230 m 3698 u (cm/s) -33.94 77.28 18.111 20.264

Long-Ranger ADCP v (cm/s) -57.64 71.7 3.082 20.893

RDI Broadband 75 kHz 5699 230 - 238 m 3698 u (cm/s) -34.93 75.89 17.784 19.942

Long-Ranger ADCP v (cm/s) -56.95 71.05 3.056 20.607

 C-18 
Table C-12. Statistics from Mooring 3 Deployment 2 ADCP for the u and v components of the 

currents measured (continued). 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5699 238 - 246 m 3698 u (cm/s) -33.35 74.93 17.375 19.631

Long-Ranger ADCP v (cm/s) -57.6 68.09 3.069 20.434

RDI Broadband 75 kHz 5699 246 - 254 m 3698 u (cm/s) -33.36 72.8 16.895 19.263

Long-Ranger ADCP v (cm/s) -58.17 65.48 3.02 20.086

RDI Broadband 75 kHz 5699 254 - 262 m 3698 u (cm/s) -33.93 70.59 16.319 18.88

Long-Ranger ADCP v (cm/s) -54.9 66.88 3.123 19.642

RDI Broadband 75 kHz 5699 262 - 270 m 3698 u (cm/s) -36.16 72.69 16.247 18.75

Long-Ranger ADCP v (cm/s) -54.93 65.88 3.189 19.54

RDI Broadband 75 kHz 5699 270 - 278 m 3698 u (cm/s) -34.36 69.05 15.941 18.496

Long-Ranger ADCP v (cm/s) -54.08 69.99 3.209 19.349

RDI Broadband 75 kHz 5699 278 - 286 m 3698 u (cm/s) -33.5 70.59 15.59 18.379

Long-Ranger ADCP v (cm/s) -53.02 65.5 3.118 19.22

RDI Broadband 75 kHz 5699 286 - 294 m 3698 u (cm/s) -36.46 69.19 15.265 18.208

Long-Ranger ADCP v (cm/s) -52.59 64.92 3.072 19.036

RDI Broadband 75 kHz 5699 294 - 302 m 3698 u (cm/s) -36.17 69.69 14.968 17.983

Long-Ranger ADCP v (cm/s) -51.9 62.6 3.006 18.782

RDI Broadband 75 kHz 5699 302 - 310 m 3698 u (cm/s) -33.75 69.55 14.666 17.772

Long-Ranger ADCP v (cm/s) -51.57 61.97 2.961 18.572

RDI Broadband 75 kHz 5699 310 - 318 m 3698 u (cm/s) -34.1 70.95 14.407 17.565

Long-Ranger ADCP v (cm/s) -52.19 61.83 2.968 18.358

RDI Broadband 75 kHz 5699 318 - 326 m 3698 u (cm/s) -32.35 71.1 14.055 17.37

Long-Ranger ADCP v (cm/s) -52.08 65.27 2.884 18.147

RDI Broadband 75 kHz 5699 326 - 334 m 3698 u (cm/s) -31.19 65.42 13.766 17.074

Long-Ranger ADCP v (cm/s) -51.1 68.05 2.944 17.901

RDI Broadband 75 kHz 5699 334 - 342 m 3698 u (cm/s) -31.86 70.75 13.503 16.957

Long-Ranger ADCP v (cm/s) -50.03 63.1 2.943 17.697

RDI Broadband 75 kHz 5699 342 - 350 m 3698 u (cm/s) -28.14 68.25 13.218 16.717

Long-Ranger ADCP v (cm/s) -49.89 61.8 2.94 17.432

RDI Broadband 75 kHz 5699 350 - 358 m 3698 u (cm/s) -27.88 67.22 12.976 16.486

Long-Ranger ADCP v (cm/s) -49.4 62.14 2.861 17.251

RDI Broadband 75 kHz 5699 358 - 366 m 3698 u (cm/s) -30.95 66.48 12.71 16.236

Long-Ranger ADCP v (cm/s) -46.75 62.47 2.827 17.025

RDI Broadband 75 kHz 5699 366 - 374 m 3698 u (cm/s) -28.26 63.53 12.483 16.029

Long-Ranger ADCP v (cm/s) -46.26 61.3 2.77 16.716

RDI Broadband 75 kHz 5699 374 - 382 m 3698 u (cm/s) -27.28 63.8 12.263 15.794

Long-Ranger ADCP v (cm/s) -46.48 61.75 2.781 16.446

RDI Broadband 75 kHz 5699 382 - 390 m 3698 u (cm/s) -28.92 61.38 11.977 15.631

Long-Ranger ADCP v (cm/s) -45.76 59.55 2.81 16.237

RDI Broadband 75 kHz 5699 390 - 398 m 3698 u (cm/s) -29.33 60.21 11.717 15.253

Long-Ranger ADCP v (cm/s) -45.52 55.99 2.742 15.908

RDI Broadband 75 kHz 5699 398 - 406 m 3698 u (cm/s) -28.65 60.75 11.384 15.063

Long-Ranger ADCP v (cm/s) -46.04 55.16 2.766 15.668

RDI Broadband 75 kHz 5699 406 - 414 m 3698 u (cm/s) -27.61 59.68 11.095 14.933

Long-Ranger ADCP v (cm/s) -44.3 54.35 2.799 15.403

RDI Broadband 75 kHz 5699 414 - 422 m 3698 u (cm/s) -26.52 59.86 10.836 14.763

Long-Ranger ADCP v (cm/s) -43.9 52.58 2.765 15.105

RDI Broadband 75 kHz 5699 422 - 430 m 3698 u (cm/s) -27.18 59.66 10.727 14.527

Long-Ranger ADCP v (cm/s) -44.58 53.03 2.704 14.93

RDI Broadband 75 kHz 5699 430 - 438 m 3698 u (cm/s) -26.48 59.86 10.529 14.285

Long-Ranger ADCP v (cm/s) -41.31 51.39 2.708 14.645

RDI Broadband 75 kHz 5699 438 - 446 m 3698 u (cm/s) -27.87 57.91 10.294 14.003

Long-Ranger ADCP v (cm/s) -42.76 49.16 2.644 14.35

 C-19 
 C-20 

Table C-12. Statistics from Mooring 3 Deployment 2 ADCP for the u and v components of the 

currents measured. 

Instrument 

Serial 

Number Bin Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

RDI Broadband 75 kHz 5699 446 - 454 m 3698 u (cm/s) -26.58 57.13 10.095 13.734

Long-Ranger ADCP v (cm/s) -39.9 46.43 2.521 14.061

RDI Broadband 75 kHz 5699 454 - 462 m 3698 u (cm/s) -28.54 57.66 9.847 13.435

Long-Ranger ADCP v (cm/s) -40.08 48.68 2.495 13.833

RDI Broadband 75 kHz 5699 462 - 470 m 3698 u (cm/s) -25.78 57.28 9.452 12.978

Long-Ranger ADCP v (cm/s) -39.34 48.68 2.394 13.439

Table C-13 

Statistics from Mooring 3 Deployment 2 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

S4 8111 0750 m 3697 u (cm/s) -24.79 35.02 3.411 9.003

v (cm/s) -34.32 35.4 0.689 9.546

Aanderaa RCM 7 12084 0997 m 3697 u (cm/s) -18.24 20.63 -0.252 5.659

v (cm/s) -24.93 19.42 -0.107 6.629

Aanderaa RCM 8s 10643 1245 m 3697 u (cm/s) -15.93 19.31 -1.461 5.182

v (cm/s) -23.07 20.75 -0.764 6.07

Aanderaa RCM 7 9480 1492 m 3697 u (cm/s) -19.13 16.21 -1.7 4.955

v (cm/s) -18.49 22.07 -0.092 5.722

Aanderaa RCM 8s 9809 1996 m 3697 u (cm/s) -21.85 14.29 -2.381 5.591

v (cm/s) -20.4 21.42 0.503 6.061

Aanderaa RCM 8 12808 2499 m 3697 u (cm/s) -23.23 16.81 -2.225 6.367

v (cm/s) -20.31 21.9 -0.666 6.586

Aanderaa RCM 8 12809 2699 m 3697 u (cm/s) -23.42 17.6 -2.206 6.253

v (cm/s) -21.38 22.53 -0.761 6.807

Table C-14 

Statistics from Mooring 4 Deployment 2 single point current meters for the u and v components 

of the currents measured. 

Instrument 

Serial 

Number Depth N Parameter Minimum Maximum Mean 

Standard 

Deviation

Aanderaa RCM 8s 10112 2530 m 3762 u (cm/s) -17.14 13.51 -0.464 5.487

v (cm/s) -11.44 16.09 -0.724 3.806

Aanderaa RCM 8 12810 2630 m 3762 u (cm/s) -17.77 12.93 -0.526 5.636

v (cm/s) -13.26 15.33 -0.818 3.973
APPENDIX D 

Barotropic Tides 

 D-1 
 D-2 

Tidal response analysis (Munk and Cartwright, 1966) determined the amplitude and phase for 

eight major tidal constituents (O1, K1, Q1, P1, M2, K2, N2, S2) from the six recovered bottom 

pressure records (PIES 1 through 6) within the array (Figures D-1, D-2, and Table D-1). 

Estimated phase and amplitude vary smoothly across the array as expected. Tidal amplitudes are 

generally small. The largest tidal amplitudes are near 14 cm for O1 and K1, near 5 cm for P1, 

and less than 5 cm for the remaining five constituents. Amplitudes have been converted to meters 

by dividing pressure by density times gravity, ρg = 1.02. 
Figure D-1. Amplitude (left column) and phase (right column) of the O1, K1, Q1, and P1 

constituents determined with the tidal response method (Munk and Cartwright, 

1966) from the six bottom pressure records. PIES locations denoted by open 

diamonds. Note that PIES7 shown but did not contribute to the calculation 

because the telemetered data are daily averages. 

 D-3 
Figure D-2. Amplitude (left panels) and phase (right panels) of the M2, K2, N2, and S2 

constituents determined with the tidal response method (Munk and Cartwright, 

1966) from the six bottom pressure records. PIES locations denoted by open 

diamonds. Note that PIES7 shown but did not contribute to the calculation 

because the telemetered data are daily averages. 

 D-4 
 D-5 

Table D-1 

Amplitude in cm and phase in degrees for the eight major tidal constituents (O1, K1, Q1, P1, 

M2, K2, N2, S2) constituents determined with the tidal response method (Munk and Cartwright, 

1966). 

O1 K1 Q1 P1 

Amplitude Phase Amplitude Phase Amplitude Phase Amplitude Phase 

Site (cm) (degrees) (cm) (degrees) (cm) (degrees) (cm) (degrees) 

P1 13.96 12.17 13.97 18.37 3.23 354.94 4.62 19.75 

P2 13.93 11.98 13.96 18.09 3.22 354.81 4.61 19.47 

P3 13.84 11.79 13.86 17.9 3.2 354.74 4.58 19.26 

P41 13.87 12.08 13.88 18.17 3.23 354.9 4.57 19.56 

P42 13.87 12.08 13.88 18.17 3.23 354.9 4.57 19.56 

P5 13.85 12.42 13.85 18.46 3.22 355.25 4.57 19.83 

P61 13.85 11.98 13.85 18.02 3.22 354.99 4.57 19.4 

P62 13.85 11.98 13.85 18.02 3.22 354.99 4.57 19.4 

M2 K2 N2 S2 

Amplitude Phase Amplitude Phase Amplitude Phase Amplitude Phase 

Site (cm) (degrees) (cm) (degrees) (cm) (degrees) (cm) (degrees) 

P1 2.31 102.78 0.5 101.8 0.45 117.85 2.08 103.12 

P2 2.49 100.57 0.51 100.54 0.49 113.11 2.15 101.97 

P3 2.79 97.81 0.54 99.36 0.52 108.06 2.26 100.92 

P41 2.58 98.94 0.52 100.38 0.49 110.68 2.2 101.75 

P42 2.58 98.94 0.52 100.38 0.49 110.68 2.2 101.75 

P5 2.4 100.25 0.51 101.44 0.46 114.84 2.13 102.71 

P61 2.8 97.2 0.55 99.67 0.52 107.37 2.27 100.84 

P62 2.8 97.2 0.55 99.67 0.52 107.37 2.27 100.84 
APPENDIX E 

Elliptical Fit Parameters 

 E-1 
Elliptical fits to a kinematic feature model (Glenn et al., 1990) were found for Eddy Ulysses, 

Eddy Vortex, Eddy Walker, four small cyclonic eddies, and a brief period of closed circulation in 

the Loop Current. This appendix contains plots of the time series of fit parameters for each eddy 

or closed circulation as determined from the available Horizon Marine drifting buoy deployed in 

2005. In some cases, more than one buoy orbited a feature. Independent solutions in those cases 

give an indication of the usefulness of the elliptical fits. 

Figures E-1 – E-5 show the parameters of the fits in Eddy Ulysses. At the beginning of 2005, this 

was an old eddy in the far southwestern Gulf. The fits to the longitude of the center show that it 

was still translating steadily to the west. The fits to the latitude of the center do not agree as well, 

but the eddy appears to have moved slowly southward. The orbital periods were around 15 days. 

This period is in the range expected in old eddies. The eccentricity and orientation show that 

Eddy Ulysses was nearly circular, with the long axis trending near north-south. 

The graphs for Eddy Vortex are broken into two sections. Figures E-6 – E-10 describe the eddy 

from the end of February through the middle of April. Figures E-11 – E-15 show its evolution 

from June through November. From April through June, the eddy re-attached to the Loop 

Current and there were no closed buoy orbits. During March, Eddy Vortex moved to the 

northwest. In the process, it got unusually close to the Mississippi Delta. At the end of April, the 

center of circulation moved back to the southeast as the eddy re-attached to the Loop Current. 

The orbital period when the eddy was definitely detached from the Loop Current in March was 

rather low, only about 7 days. During that period, it was fairly elongated with an eccentricity of 

about 0.6. The long axis of the ellipse rotated clockwise at about 4° per day. The sense and speed 

of the rotation are as predicted for an isolated eddy by Cushman-Roisin et al. (1985). 

Figures E-11 – E-15 show the evolution of Eddy Vortex after it separated again in June. There 

are some gaps in the record because the eddy re-attached to the Loop Current several times, but 

the center of circulation moved steadily to the southwest. The various buoys gave very similar 

center positions. From June through August (Yeardays 160 – 240) the orbital period was long for 

a fresh eddy, but during this time the eddy was rather large. The orientation of the ellipse 

changed rapidly during June and the early part of July (Yeardays 160 – 200) but after that the 

regular clockwise rotation set in. 

Eddy Walker first formed a closed circulation at the end of September, but did not completely 

separate from the Loop Current until 2006. There were only brief periods when buoys made 

closed orbits in it, as shown in Figures E-16 – E-20. 

Several of the buoys became trapped in small anti-cyclonic (cold) eddies. Figures E-21 – E-25 

show the fits to the first of these in February 2005. Cold Eddy 1 was in a meander on the eastern 

side of the Loop Current. Both buoys in this eddy showed that the center moved steadily 

southward. Buoy 1476 showed that the center longitude was steady, but buoy 1500 showed the 

center moving to the east. The reason is that buoy 1500 orbited at a larger radius, and went 

around a rather diffuse circulation to the east of the main center. This extension to the east is also 

seen in the eccentricity of the orbit of buoy 1500 and its longer rotational period. 

 E-2 
 E-3 

Cold Eddy 2 was in a Loop Current meander far to the south near Cuba at about the same time as 

Cold Eddy 1 existed. Its parameters are shown in Figures E-26 – E-30. It moved to the southeast 

as the meander progressed into the Straits of Florida. This was a small feature, and its orbital 

period was low at 4 – 6 days. 

Cold Eddy 3 was a persistent feature from the first of August through the middle of September. It 

was located on the northeast edge of Eddy Vortex as it was making its final separation. As Eddy 

Vortex moved to the west, Cold Eddy 3 moved with it. There is a gap in the solution from 

Yeardays 238 – 248, but the resumed circulation is apparently the same feature. The feature is 

small and its orbital period low until late in the record when the buoy moved out to a larger orbit. 

Cold Eddy 4 was the final cold eddy that had closed buoy orbits. It was directly north of Eddy 

Walker as it began to separate from the Loop Current in December 2005. This feature moved 

north as the Loop Current extended and east as its meander propagated clockwise around the 

northern edge of what would become Eddy Walker. It was a small feature with an orbital period 

of only 4 days. 

Finally, buoy 1669 made a closed orbit in the middle of the Loop Current during the last half of 

September 2005 after Eddy Vortex separated. At first the center of circulation moved to the 

northwest, but then it moved to the northeast as the Loop Current leaned to the east. The change 

of the orientation of the ellipse from north-northwest to north is consistent with this lean. The 

period of rotation lowers as the orbit becomes more circular. 

Latitude of Center

21.9

22.0

22.1

22.2

22.3

22.4

22.5

22.6

22.7

22.8

22.9

0 10 20 30 40 50 6

YearDay 2005

Latitude

0

1462 1483 1487

Figure E-1. Latitude of the center of Eddy Ulysses. 

Longitude of Center

94.6

94.8

95.0

95.2

95.4

95.6

95.8

96.0

0 10 20 30 40 50 6

YearDay 2005

Longitude

0

1462 1483 1487

Figure E-2. Longitude of the center of Eddy Ulysses. 

 E-5 
Period

0

5

10

15

20

0 10 20 30 40 50 6

YearDay 2005

Period (Days)

0

1462 1483 1487

e

Figure E-3. Orbital period in Eddy Ulysses. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 10 20 30 40 50 6

YearDay 2005

Eccentricity

0

1462 1483 1487

Figure E-4. Eccentricity of Eddy Ulysses. 

 E-6 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

0 10 20 30 40 50 6

YearDay 2005

Theta

0

1462 1483 1487

Figure E-5. Orientation of the major axis of Eddy Ulysses. 

 E-7 
Latitude of Center

26.4

26.5

26.6

26.7

26.8

26.9

27.0

27.1

27.2

27.3

27.4

27.5

45 55 65 75 85 95 105 115

YearDay 2005

Latitude

1516 1550 1551 1574

Figure E-6. Latitude of the center of Eddy Vortex early in 2005. 

Longitude of Center

87.6

87.8

88.0

88.2

88.4

88.6

88.8

89.0

89.2

45 55 65 75 85 95 105 115

YearDay 2005

Longitude

1516 1550 1551 1574

Figure E-7. Longitude of the center of Eddy Vortex early in 2005. 

 E-8 
Period

0

5

10

15

20

45 55 65 75 85 95 105 115

YearDay 2005

Period (Days)

1516 1550 1551 1574

Figure E-8. Orbital period of Eddy Vortex early in 2005. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

45 55 65 75 85 95 105 115

YearDay 2005

Eccentricity

1516 1550 1551 1574

Figure E-9. Eccentricity of Eddy Vortex early in 2005. 

 E-9 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

45 55 65 75 85 95 105 115

YearDay 2005

Theta

1516 1550 1551 1574

Figure E-10. Orientation of the major axis of Eddy Vortex early in 2005. 

 E-10 
Latitude of Center

25.4

25.6

25.8

26.0

26.2

26.4

26.6

26.8

27.0

27.2

27.4

160 180 200 220 240 260 280 300

YearDay 2005

Latitude

1605 1583 1639 1646 1658 1677 1679

Figure E-11. Latitude of the center of Eddy Vortex late in 2005. 

Longitude of Center

87.0

88.0

89.0

90.0

91.0

92.0

93.0

94.0

95.0

160 180 200 220 240 260 280 300

YearDay 2005

Longitude

1605 1583 1639 1646 1658 1677 1679

Figure E-12. Longitude of the center of Eddy Vortex late in 2005. 

 E-11 
Period

0.00

5.00

10.00

15.00

20.00

160 180 200 220 240 260 280 300

YearDay 2005

Period (Days)

1605 1583 1639 1646 1658 1677 1679

Figure E-13. Orbital period of Eddy Vortex late in 2005. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

160 180 200 220 240 260 280 300

YearDay 2005

Eccentricity

1605 1583 1639 1646 1658 1677 1679

Figure E-14. Eccentricity of Eddy Vortex late in 2005. 

 E-12 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

160 180 200 220 240 260 280 300

YearDay 2005

Theta

1605 1583 1639 1646 1658 1677 1679

Figure E-15. Orientation of the major axis of Eddy Vortex late in 2005. 

 E-13 
Latitude of Center

25.0

25.2

25.4

25.6

25.8

26.0

26.2

26.4

250 260 270 280 290 300 310 320 330 340

YearDay 2005

Latitude

1646 1701

Figure E-16. Latitude of the center of Eddy Walker. 

Longitude of Center

86.8

87.0

87.2

87.4

87.6

87.8

88.0

250 260 270 280 290 300 310 320 330 340

YearDay 2005

Longitude

1646 1701

Figure E-17. Longitude of the center of Eddy Walker. 

 E-14 
Period

0

5

10

15

20

250 260 270 280 290 300 310 320 330 340

YearDay 2005

Period (Days)

1646 1701

Figure E-18. Orbital period of Eddy Walker. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

250 260 270 280 290 300 310 320 330 340

YearDay 2005

Eccentricity

1646 1701

Figure E-19. Eccentricity of Eddy Walker. 

 E-15 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

250 260 270 280 290 300 310 320 330 340

YearDay 2005

Theta

1646 1701

Figure E-20. Orientation of the major axis of Eddy Walker. 

 E-16 
Latitude of Center

26.0

26.1

26.2

26.3

26.4

26.5

26.6

26.7

26.8

26.9

27.0

30 35 40 45 50 55

YearDay 2005

Latitude

1476 1500

Figure E-21. Latitude of the center of Cold Eddy 1. 

Longitude of Center

85.2

85.3

85.4

85.5

85.6

85.7

85.8

85.9

86.0

30 35 40 45 50 55

YearDay 2005

Longitude

1476 1500

Figure E-22. Longitude of the center of Cold Eddy 1. 

 E-17 
Period

0

5

10

15

20

30 35 40 45 50 55

YearDay 2005

Period (Days)

1476 1500

Figure E-23. Orbital period of Cold Eddy 1. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

30 35 40 45 50 55

YearDay 2005

Eccentricity

1476 1500

Figure E-24. Eccentricity of Cold Eddy 1. 

 E-18 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

30 35 40 45 50 55

YearDay 2005

Theta

1476 1500

Figure E-25. Orientation of the major axis of Cold Eddy 1. 

 E-19 
Latitude of Center

23.6

23.7

23.8

23.9

24.0

24.1

24.2

30 35 40 45 50 55 60

YearDay 2005

Latitude

1522

Figure E-26. Latitude of the center of Cold Eddy 2. 

Longitude of Center

83.4

83.6

83.8

84.0

84.2

84.4

84.6

30 35 40 45 50 55 60

YearDay 2005

Longitude

1522

Figure E-27. Longitude of the center of Cold Eddy 2. 

 E-20 
Period

0

5

10

15

20

30 35 40 45 50 55 60

YearDay 2005

Period (Days)

1522

Figure E-28. Orbital period of Cold Eddy 2. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

30 35 40 45 50 55 60

YearDay 2005

Eccentricity

1522

Figure E-29. Eccentricity of Cold Eddy 2. 

 E-21 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

30 35 40 45 50 55 60

YearDay 2005

Theta

1522

Figure E-30. Orientation of the major axis of Cold Eddy 2. 

 E-22 
Latitude of Center

27.6

27.7

27.8

27.9

28.0

28.1

28.2

220 225 230 235 240 245 250 255 260 265

YearDay 2005

Latitude

1652 1656

Figure E-31. Latitude of the center of Cold Eddy 3. 

Longitude of Center

87.4

87.6

87.8

88.0

88.2

88.4

88.6

88.8

220 225 230 235 240 245 250 255 260 265

YearDay 2005

Longitude

1652 1656

Figure E-32. Longitude of the center of Cold Eddy 3. 

 E-23 
Period

0

5

10

15

20

220 225 230 235 240 245 250 255 260 265

YearDay 2005

Period (Days)

1652 1656

Figure E-33. Orbital period of Cold Eddy 3. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

220 225 230 235 240 245 250 255 260 265

YearDay 2005

Eccentricity

1652 1656

Figure E-34. Eccentricity of Cold Eddy 3. 

 E-24 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

220 225 230 235 240 245 250 255 260 265

YearDay 2005

Theta

1652 1656

Figure E-35. Orientation of the major axis of Cold Eddy 3. 

 E-25 
Latitude of Center

27.3

27.4

27.5

27.6

27.7

27.8

27.9

28.0

28.1

28.2

330 335 340 345 350 355 360 365

YearDay 2005

Latitude

1718

Figure E-36. Latitude of the center of Cold Eddy 4. 

Longitude of Center

87.0

87.5

88.0

88.5

89.0

89.5

90.0

330 335 340 345 350 355 360 365

YearDay 2005

Longitude

1718

Figure E-37. Longitude of the center of Cold Eddy 4. 

 E-26 
Period

0

5

10

15

20

330 335 340 345 350 355 360 365

YearDay 2005

Period (Days)

1718

Figure E-38. Orbital period of Cold Eddy 4. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

330 335 340 345 350 355 360 365

YearDay 2005

Eccentricity

1718

Figure E-39. Eccentricity of Cold Eddy 4. 

 E-27 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

330 335 340 345 350 355 360 365

YearDay 2005

Theta

1718

Figure E-40. Orientation of the major axis of Cold Eddy 4. 

 E-28 
Latitude of Center

25.0

25.2

25.4

25.6

25.8

26.0

26.2

26.4

26.6

26.8

256 258 260 262 264 266 268 270 272

YearDay 2005

Latitude

1669

Figure E-41. Latitude of the center of the Loop Current. 

Longitude of Center

86.9

87.0

87.1

87.2

87.3

87.4

87.5

87.6

87.7

87.8

256 258 260 262 264 266 268 270 272

YearDay 2005

Longitude

1669

Figure E-42. Longitude of the center of the Loop Current. 

 E-29 
Period

0

5

10

15

20

256 258 260 262 264 266 268 270 272

YearDay 2005

Period (Days)

1669

Figure E-43. Orbital period in the Loop Current. 

Eccentricity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

256 258 260 262 264 266 268 270 272

YearDay 2005

Eccentricity

1669

Figure E-44. Eccentricity of the Loop Current. 

 E-30 
Orientation of Major Axis

-90.0

-60.0

-30.0

0.0

30.0

60.0

90.0

256 258 260 262 264 266 268 270 272

YearDay 2005

Theta

1669

Figure E-45. Orientation of the major axis of the Loop Current. 

 E-31 
APPENDIX F 

Ocean Response to Hurricane Katrina in Presence of a Cyclone. 

Report by Accurate Environmental Forecasting, Inc. 

 F-1 
 F-2 

The following report was written by Accurate Environmental Forecasting, Inc. (AEF), and is 

enclosed as provided to Evans-Hamilton, Inc. This report was developed in support of the 

Climatology and Simulation of Eddies (CASE) Joint Industry Project (JIP). It was provided to 

the BOEMRE study team as part of an agreement in which AEF was provided measurement 

results from the present BOEMRE study, in return for AEF’s analysis results and report to the 

JIP. 
Ocean response to hurricane Katrina in presence of a cyclone 

Ocean model validation study 

Final report 

Accurate Environmental Forecasting, Inc. 

Narragansett, RI 02882 

Tel: (401) 788-9031, Fax (401) 788-9034 

www.accufore.com

August 25, 2007 

 F-3 

Introduction 

Presented in this report are the results of a validation study intended to assess the ability of the 

AEF version of the MIT GCM ocean model to simulate the ocean response to a hurricane in the 

presence of strong mesoscale features. The observational basis for the validation is provided by 

current measurements collected by a fixed instrument array during hurricane Katrina (2005). 

Preliminary data analysis indicates large spatial variability of the ocean response in the vicinity 

of the instrument array. A strong cyclonic mesoscale feature observed by the array just prior to 

the Katrina passage is presumed to be responsible for the observed variability. 

Observations 

The observational basis for this study is provided by the BOEMRE-funded ocean measurements 

program in the Eastern GOM. The measurements program covered the area located south of 

Mobile Bay in water depths ranging from 2000 to 2800 m (Figure F-1). Three tall (M1, M2, & 

M3) and one short (M4) moorings, along with seven PIES, were deployed from January 2006 to 

January 2007, with servicing of the moorings occurring in August 2006 just a few days prior to 

the arrival of hurricane Katrina. The tall moorings contained upward-looking 75 kHz ADCPs at 

500 m depth, with single point current meters spaced at intervals from 750 m to near bottom. The 

tall moorings also contained combinations of temperature, or temperature-conductivity-pressure 

sensors at various depths. The short mooring contained two single point current meters near 

bottom. 

The Eastern GOM array moorings have captured the ocean response to hurricane Katrina as it 

passed ~150 kilometers west of the array (Figure F-2). At the time of Katrina passage the 

mooring array was affected by a cold cyclonic eddy on the periphery of a Loop Current eddy. 

The approximate position of the cyclone is indicated by a surface drifter captured within its 

circulation (Figure F-2). Near-surface currents associated with the cyclone were on the order of 

1.5 kts as indicated by the drifter speed and by ADCP measurements. As expected, the ocean 

response to Katrina primarily consisted of near-inertial oscillations. Preliminary analysis of nearinertial response was conducted by Forristall (2007) who applied a diurnal bandpass filter to the 

ADCP current time series. Results of this analysis at moorings 1 and 3 are shown in Figure F-3 

and Figure F-4 respectively. 

As expected, the oscillations have an upward phase propagation and downward energy 

propagation. The near-surface response at the Mooring 3 is about the same as at the Mooring 1, 

but at depth the oscillations are much stronger at Mooring 3 than at Mooring 1. Hurricane 

Katrina passed about the same distance from the two moorings, but they were in a different 

situation with respect to the cyclone shown in Figure F-2. Mooring 3 was in the middle of the 

cyclone and close to Loop Current Eddy Vortex. The enhanced inertial oscillations there are 

likely due to non-linear interaction between the cyclone and the hurricane. These measurements 

provide a good test case for validating the ability of three dimensional numerical models to 

adequately simulate non-linear ocean response to hurricanes in presence of background 

mesoscale ocean features. 

 F-5 
Ocean Model 

The ocean model is the Massachusetts Institute of Technology General Circulation Model (MIT 

GCM). The numerical formulation of the model is described in detail in Marshall et al. (1997); 

here we present a brief description. The model solves the incompressible Navier-Stokes 

equations using hydrostatic, quasi-hydrostatic, or non-hydrostatic approximations with rigid-lid 

or free-surface options. The equations are solved in a spherical geometry and with arbitrary 

complex coastlines, islands, and bathymetry using height as a vertical coordinate (z-coordinate 

system). For time integration the model uses a finite volume, predictor-corrector numerical 

procedure. The numerical scheme ensures that the evolving velocities are divergence free by 

solving the Poisson equation for the pressure with Neumann boundary conditions and then using 

this pressure to update the velocities. The pressure field is inverted using preconditioned 

conjugate-gradient methods. The equations are discretized using finite-volume methods with 

regular volumes based upon a uniform discretization of longitude, latitude, and depth. These 

volumes may take on irregular shapes and be “sculptured” to fit the boundary, improving the 

representation of both coastlines and topography. The model is also designed for parallel 

computation. Most of the parallelism is a so-called “fine-grained” data parallelism, available on 

the order of the total number of grid cells in the computational domain. In this approach the 

physical domain is partitioned by allocating equally sized vertical columns of the ocean to each 

processing unit. The model is well-tested; it has been employed to study numerous phenomena 

whose scales range from centimeters up to many thousands of kilometers (see Adcroft et al., 

1997 and references therein). 

For this study the model was configured for the Gulf of Mexico domain with uniform horizontal 

resolution of 4 km. The high horizontal resolution is necessary to adequately resolve a sharp 

baroclinic front associated with LC/LCEs. The uniformity of the numerical grid eliminates 

potential numerical artifacts associated with wave trapping in non-uniform grids. The model 

domain has open inflow/outflow boundaries in the Yucatan and Florida straights. The open 

boundary conditions allow a realistic simulation of the LC. The numerical grid has 50 vertical 

levels distributed uniformly with 10 m resolution in the upper 100 meters. The vertical resolution 

gradually transitions to a nearly uniform 15 meter resolution throughout most of the thermocline. 

Vertical resolution below the thermocline decreases gradually, reaching approximately 700 

meters at the very bottom. Realistic bottom topography from ETOPO-2 1/30 degree resolution 

data base was prescribed throughout the entire domain except for regions shallower than 50 

meters. Shallow regions are notorious for producing numerical instabilities under strong forcing 

conditions. Since this study is only concerned with deep ocean response, regions shallower than 

50 meters were marked as land to simplify the model configuration and reduce the study cost. 

 F-6 
Model Initialization 

The model was initialized using the methodology described in Frolov et al. (2004). Similar 

methodology is used by the AEF-HMI eddy forecast system (Coholan et al., 2005) for 

operational forecasts of the GOM currents. In brief, the methodology utilizes a feature-oriented 

approach based on describing mesoscale ocean features with their Potential Vorticity (PV) field. 

This feature-oriented approach utilizes historical observations of the GOM features, i.e. the Loop 

Current (LC), Loop Current Eddies (LCEs), and cyclones, as well as our understanding of 

physical mechanisms controlling their evolution to reconstruct the initial 3-dimensional PV field 

on the basis of a few real-time observations. Using PV instead of density and/or velocity allows 

for clean separation between closely located features. The initial density and velocity are inferred 

from the constructed 3-d PV field by solving the system of intermediate equations. Since 

intermediate equations closely approximate the full set of primitive equations for the majority of 

slow-evolving solutions (Allen, 1997; McWilliams et al., 1986), the resulting initial density and 

velocity fields can be used to initialize a primitive equation model without any significant 

adjustments. 

The fundamental assumption of this initialization methodology is that the PV structure of a 

mesoscale feature is conserved along the flow lines within that feature. In the case of the LC, its 

PV structure is expected to be conserved along the perimeter of the Loop. However, this 

assumption becomes invalid when the LC undergoes a process of merging with another 

anticyclonic feature, e.g. a warm-core eddy. During this process, the flow within the LC becomes 

disrupted and its PV structure undergoes a complex evolution while blending with the PV 

structure of the merging feature. In this situation a more accurate initialization approach is to use 

the primitive equations model itself to calculate the complex frontal structure resulting from the 

process of feature merging. With this approach, the primitive equations model is initialized prior 

to the merging event and is run forward to the target initialization date without any external 

forcing or data assimilation. The initial conditions prior to the merging event are adjusted 

iteratively to achieve a close agreement between the model and observations over the time period 

preceding the target initialization date. 

Surface frontal analysis on August 20 shown in Figure F-5 indicates that the LC was undergoing 

the process of reconnecting with eddy Vortex (Figure F-6). The “connection” region is located 

just south of the Eastern Gulf Array and may have a significant impact on the ocean response to 

Katrina in its vicinity. Consequently, the alternative initialization approach (described above) 

had to be applied in order to realistically initialize frontal structure in the LC/Vortex connection 

region. The ocean model was initialized on August 18 when eddy Vortex was clearly separated 

from the LC enabling the application of the PV conservation assumption along the eddy front. 

After initialization on August 18 the model was allowed to evolve freely, i.e. without any 

external forcing or data assimilation. The simulated eddy-LC evolution was compared with 

observations, i.e. drifter trajectories and frontal positions; the initial conditions were adjusted 

iteratively to ensure a good agreement. The comparison between the model simulation and 

observations prior to the Katrina passage is shown in Figure F-7 through Figure F-10. 

 F-7 
The cyclonic feature east of the eddy Vortex required special attention during the initialization 

since this feature is hypothesized to be primarily responsible for the spatial variability in the 

near-inertial response observed by the Eastern Gulf Array. Surface drifters captured within the 

feature indicate that it is not a frontal cyclone but rather an isolated cyclonic feature that is 

interacting with the LC. This conclusion is based on the fact that the location of the circulation 

center, as it is indicated by drifter trajectories, does not move any appreciable distance along the 

LC front over the time period since August 20 (compare Figure F-5 and Figure F-6). The cyclone 

was initialized using the Gaussian PV anomaly feature model previously developed by AEF for 

modeling isolated cyclones over the northern slope (Frolov et al., 2004). The position of the 

cyclone was derived from drifter trajectories and the Eastern Gulf Array current meter data. The 

latter was given a heavier weight in the analysis since the center of near-surface circulation 

derived from drifter trajectories can be significantly affected by the warm LC water being pulled 

into the cyclonic circulation. Parameters of the cyclonic feature model controlling its vertical 

structure were determined on the basis of the current observations from the Eastern Gulf Array. 

On the basis of these observations the core PV anomaly associated with the cyclone was placed 

at 200 meters, which is consistent with previous observations of isolated cyclones in the GOM 

(Hamilton et al., 2002). 

Validation Results and Discussion 

Simulated and observed currents at the mooring locations are shown in Figure F-11 through 

Figure F-13. Simulated currents are interpolated into the vertical coordinates moving with each 

mooring and truncated near the surface to make the comparison consistent. The comparison 

shows a very good agreement between the observed and simulated ocean response. The spatial 

variability in the near-inertial response observed and simulated in the vicinity of the cyclonic 

feature is consistent with the analytical work of Kunze (1985) and observational work of 

D’Asaro (1995). Near-inertial waves are being trapped and propagate downward in the zone of 

high horizontal shear within the cyclone. The southern mooring is located in the high shear zone 

within the cyclone, consequently, it experiences the strongest near-inertial response at depth. The 

northern mooring is located just outside of the cyclone, where the near-inertial response remains 

bound to the upper mixed layer with very little vertical propagation. The middle mooring is 

located within the cyclonic circulation but in the region of relatively low horizontal shear. The 

near-inertial response at this mooring penetrates below the mixed layer but at a slower rate 

relative to the southern mooring. 

References 

Adcroft, A., C. Hill, and J. Marshall. 1997. Representation of topography by shaved cells in a 

height coordinate ocean model. Mon. Weather Rev. 125:2293-2315. 

Allen, J., J. Barth, and P. Newberger. 1990. On intermediate models for baroclinic continental 

shelf and slope flow fields. Part I: Formulation and comparison of exact solutions. J. 

Phys. Oceanogr. 25:2953-2958. 

Coholan, P.D., S.P. Anderson, and S.A. Frolov. 2005. Forecasting eddy Ulysses. Proceedings of 

Dynamic Positioning Conference. September 27-28, 2005. 

 F-8 
D'Asaro, E.A. 1995. Upper-ocean inertial currents forced by a strong storm. Part III: Interaction 

of inertial currents and mesoscale eddies. J. Phys. Oceanogr. 25:2953-2958. 

Forristall, G.Z. 2007. Industry Perspective on the Northeast Gulf of Mexico Current 

Measurements. Proc. Minerals Management Service, 24th Information Transfer Meeting. 

New Orleans. Jan 2007. 

Frolov, S.A., G.D. Rowe, L.M. Rothstein, and I. Ginis. 2004. Cross-shelf exchange processes 

and the deepwater circulation of the Gulf of Mexico: Dynamical effects of submarine 

canyons and the interactions of Loop Current Eddies with topography: Final Report. U.S. 

Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, LA. 164 pp. 

Hamilton, P., T.J. Berger, and W. Johnson. 2002. On the structure and motions of cyclones in the 

northern Gulf of Mexico. J. Geophys. Res. 107(C12):3208-3219. 

Kunze, E. 1985. Near-inertial wave propagation in geostrophic shear. J. Phys. Oceanogr. 15:544-

565. 

Marshall, J., A. Adcroft, C. Hill, L. Perelman, and C. Heisey. 1997. A finite-volume, 

incompressible Navier-Stokes model for studies of the ocean on parallel computers. J. 

Geophys. Res. 102(C3):5733-5752. 

McWilliams, J.C., P.R. Gent, and N.J. Norton. 1986. The evolution of balanced, low-mode 

vortices on the beta-plane. J. Phys. Oceanogr. 16:838-855. 

 F-9 
Figure F-1. Mooring map for the Eastern GOM observational program. (Image is taken from 

the ITM report by Evans Hamilton Inc., courtesy of Jeff Cox). 

 F-10 
Figure F-2. Locations of tall moorings M1-M3 (shown with read stars) overlaid on the realtime analysis of surface fronts for August 29, 2005 (provided by Horizon Marine 

Inc.) 

 F-11 
Figure F-3. Near-inertial response to hurricane Katrina at Mooring 1 (Forristall, 2007). 

 F-12 
Figure F-4. Near-inertial response to hurricane Katrina at Mooring 3 (Forristall, 2007). 

 F-13 
Figure F-5. Surface frontal analysis provided by Horizon Marine Inc. for August 20, 2005. 

Thick black lines indicate surface front positions. Colored lines indicate drifting 

buoy trajectories; color indicates the buoy speed, i.e. local current speed. All 

drifting buoys are drogued at 50 meters depth. 

 F-14 
Figure F-6. Surface frontal analysis provided by Horizon Marine Inc. for August 27, 2005. 

Thick black lines indicate surface front positions. Colored lines indicate drifting 

buoy trajectories; color indicates the buoy speed, i.e. local current speed. All 

drifting buoys are drogued at 50 meters depth. 

 F-15 
Figure F-7. Surface currents simulated during the “spinup” initialization on August 24, 2005. 

Thick black lines indicate surface front positions as they are digitized from the 

Horizon Marine charts. Drifter trajectories are shown with colored lines. The line 

color represents the average drifter speed over the shown portion of the trajectory 

(24 hours) with the color scale consistent with the rest of the figure. Mean drifter 

position and velocity are shown with black dots and arrows. The Eastern Gulf 

Array moorings are shown with red dots. The upper level current velocity 

measured at each mooring is shown with a red arrow. All arrow scales are 

consistent throughout the figure. 

 F-16 
Figure F-8. Surface currents simulated during the “spinup” initialization on August 25, 2005. 

Thick black lines indicate surface front positions as they are digitized from the 

Horizon Marine charts. Drifter trajectories are shown with colored lines. The line 

color represents the average drifter speed over the shown portion of the trajectory 

(24 hours) with the color scale consistent with the rest of the figure. Mean drifter 

position and velocity are shown with black dots and arrows. The Eastern Gulf 

Array moorings are shown with red dots. The upper level current velocity 

measured at each mooring is shown with a red arrow. All arrow scales are 

consistent throughout the figure. 

 F-17 
Figure F-9. Surface currents simulated during the “spinup” initialization on August 26, 2005. 

Thick black lines indicate surface front positions as they are digitized from the 

Horizon Marine charts. Drifter trajectories are shown with colored lines. The line 

color represents the average drifter speed over the shown portion of the trajectory 

(24 hours) with the color scale consistent with the rest of the figure. Mean drifter 

position and velocity are shown with black dots and arrows. The Eastern Gulf 

Array moorings are shown with red dots. The upper level current velocity 

measured at each mooring is shown with a red arrow. All arrow scales are 

consistent throughout the figure. 

 F-18 
Figure F-10. Surface currents simulated during the “spinup” initialization on August 27, 2005. 

Thick black lines indicate surface front positions as they are digitized from the 

Horizon Marine charts. Drifter trajectories are shown with colored lines. The line 

color represents the average drifter speed over the shown portion of the trajectory 

(24 hours) with the color scale consistent with the rest of the figure. Mean drifter 

position and velocity are shown with black dots and arrows. The Eastern Gulf 

Array moorings are shown with red dots. The upper level current velocity 

measured at each mooring is shown with a red arrow. All arrow scales are 

consistent throughout the figure. 

 F-19 
Figure F-11. Observed (upper panel) and simulated (lower panel) current speed at 

the northern mooring. 

 F-20 
Figure F-12. Observed (upper panel) and simulated (lower panel) current speed at 

the middle mooring. 

 F-21 
Figure F-13. Observed (upper panel) and simulated (lower panel) current speed at 

the southern mooring. 

 F-22