OCS Study 

BOEM 2014-040 

U.S. Department of the Interior 

Bureau of Ocean Energy Management 

Gulf of Mexico OCS Region

Cooperative Agreement 

Coastal Marine Institute 

Louisiana State University

Coastal Marine Institute

Analysis of Ocean Current Data 

from Gulf of Mexico Oil and Gas Platforms
OCS Study 

BOEM 2014-040 

Published by 

U.S. Department of the Interior 

Bureau of Ocean Energy Management 

Gulf of Mexico OCS Region

Cooperative Agreement 

Coastal Marine Institute 

Louisiana State University

Coastal Marine Institute

Analysis of Ocean Current Data from 

Gulf of Mexico Oil and Gas Platforms 

Authors 

Chunyan Li 

Lawrence J. Rouse, Jr. 

April 2014 

Prepared under BOEM Cooperative Agreement 

M08AX12686 

By 

Louisiana State University

Coastal Marine Institute

Baton Rouge, Louisiana 70803
iii

DISCLAIMER

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

(BOEM) and the Coastal Marine Institute at Louisiana State University. This report has been 

technically reviewed by BOEM, and it has been approved for publication. Approval does not 

necessarily signify that the contents reflect the views and policies of BOEM, nor does mention of 

trade names or commercial products constitute endorsement or recommendation for use. 

REPORT AVAILABILITY

To download a PDF file of this Gulf of Mexico OCS Region report, go to the U.S. Department of 

the Interior, Bureau of Ocean Energy Management, Environmental Studies Program Information 

System website and search on OCS Study BOEM 2014-040. 

This report can be viewed at select Federal Depository Libraries. It can also be obtained from 

the National Technical Information Service; the contact information is below. 

U.S. Department of Commerce 

National Technical Information Service

5301 Shawnee Rd. 

Springfield, Virginia 22312 

Phone: (703) 605-6000, 1(800)553-6847 

Fax: (703) 605-6900 

Website: http://www.ntis.gov/

CITATION

Li, Chunyan, Lawrence J. Rouse, Jr. 2014. Analysis of ocean current data from Gulf of Mexico 

oil and gas platforms. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, 

Gulf of Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2014-040. 141 pp. 

v 

CONTENTS

LIST OF FIGURES ...................................................................................................................................... vii

LIST OF TABLES ........................................................................................................................................ xv

1. INTRODUCTION .................................................................................................................................. 1

2. DATA COLLECTION AND DESCRIPTION ....................................................................................... 5

2.1 Geographic area of measurements .............................................................................................. 5

2.2 Data Inventory ............................................................................................................................ 9

3. BASIC STATISTICS OF CURRENTS MEASURED BY ADCPS .................................................... 11

3.1 Data Return ............................................................................................................................... 11

3.2 Overall Mean and Standard Deviation of the Velocity Magnitude ........................................... 11

3.2.1 All Data ...................................................................................................................... 11

3.2.2 The 423* Data ............................................................................................................ 14

3.2.3 The 428* and 429* Data ............................................................................................ 17

3.3 Temporal and Vertical Changes of the Mean Velocity and Standard Deviations ..................... 20

3.4 Flow Direction’s Statistics ........................................................................................................ 30

4. Vertical variations of Horizontal Velocity ............................................................................................ 57

4.1 Velocity Vectors from Station 42361 in 2005 .......................................................................... 57

4.2 Velocity Vectors from Station 42363 in 2005 .......................................................................... 61

4.3 Velocity Vectors for Station 42366 in 2005 ............................................................................. 66

4.4 Velocity Vectors for Station 42368 in 2005 ............................................................................. 66

4.5 Velocity Vectors for Station 42370 in 2005 ............................................................................. 66

4.6 Velocity Vectors from Station 42373 ....................................................................................... 67

4.7. Velocity Vectors from Station 42374 ....................................................................................... 68

5. Deep Water Oscillations under Normal and Extreme Weather ............................................................ 69

5.1 Near Inertial Oscillations under Non-severe Weather Conditions ............................................ 70

5.1.1 Vertical Structure and Spectrum Analysis ................................................................. 96

5.2 Hurricane Events and Inertial Oscillations ............................................................................. 104

5.2.1 The Rotary Function Approach Using Laplace Transform ...................................... 112

5.2.2 Rotary Functions ...................................................................................................... 115

5.3. Conclusions ............................................................................................................................. 117

6. Summary ............................................................................................................................................. 119

7. Literature Cited ................................................................................................................................... 123

vii 

LIST OF FIGURES

Figure 2.1. Locations of the oil and gas rigs equipped with ADCP and reporting data to 

NDBC. ....................................................................................................................7

Figure 2.2. Data coverage in the vertical for different ADCPs in 2006 (The x’s indicate 

the bin size as in Table 2.1). ...................................................................................8

Figure 2.3. Vertical range for different ADCPs in 2006. .........................................................8

Figure 2.4. Temporal coverage of data for fixed stations. ........................................................9

Figure 2.5. Temporal coverage of data for the fixed stations. ................................................10

Figure 3.1. Data return from all 60 ACDP operating during 2005-2007 for the 100 m 

depth. ....................................................................................................................11

Figure 3.2. Mean velocity magnitude and its standard deviation as functions of water 

depth for all 60 instruments for (a) all years, (b) 2005, (c) 2006, and (d) 

2007. .....................................................................................................................13

Figure 3.3. Number of data points used for the statistics calculations as a function of 

water depth for all the ADCPs and for all years (black), the year 2005 (red), 

the year 2006 (the blue), and the year 2007 (light blue). .....................................14

Figure 3.4. Mean velocity magnitude and its standard deviation as functions of water 

depth for all the 423* stations (on fixed platforms) for (a) all years, (b) 

2005, (c) 2006, and (d) 2007. ...............................................................................16

Figure 3.5. Number of data points used for the statistics calculations as a function of 

water depth for the 423* ADCPs (i.e. those on fixed platforms) and for all 

years (black), the year 2005 (red), the year 2006 (blue), and the year 2007 

(light blue). ...........................................................................................................17

Figure 3.6. Mean velocity magnitude and its standard deviation as functions of water 

depth for all the 428* and 429* stations (movable platforms) for (a) all 

years, (b) 2005, (c) 2006, and (d) 2007. ...............................................................18

Figure 3.7. Number of data points used for the statistics calculations as a function of 

water depth for the 428* and 429* ADCPs (i.e. those on movable 

platforms) and for all years (black), the year 2005 (red), the year 2006 

(blue), and the year 2007 (light blue). ..................................................................19

Figure 3.8. Locations and tracks of the study platforms. Red circles are fixed platforms 

and the blue diamonds are the movable platforms. ..............................................20

Figure 3.9. Division of the study area into the east, central, and west regions. ......................21

Figure 3.10. Averaged speed as a function of time and depth. .................................................22

Figure 3.11. Current direction rose plot for Station 42361 in year 2005. .................................30

Figure 3.12. Current direction rose plot for Station 42361 in year 2006. .................................31

Figure 3.13. Current direction rose plot for Station 42361 in year 2007. .................................31

Figure 3.14. Current direction rose plot for Station 42362 in year 2006. .................................32

Figure 3.15. Current direction rose plot for Station 42362 in year 2007. .................................32

Figure 3.16. Current direction rose plot for Station 42363 in year 2005. .................................33
viii

Figure 3.17. Current direction rose plot for Station 42363 in year 2006. .................................34

Figure 3.18. Current direction rose plot for Station 42363 in year 2007. .................................34

Figure 3.19. Current direction rose plot for Station 42365 in year 2005. .................................35

Figure 3.20. Current direction rose plot for Station 42365 in year 2006. .................................35

Figure 3.21. Current direction rose plot for Station 42365 in year 2007. .................................36

Figure 3.22. Current direction rose plot for Station 42366 in year 2005. .................................36

Figure 3.23. Current direction rose plot for Station 42366 in year 2006. .................................37

Figure 3.24. Current direction rose plot for Station 42366 in year 2007. .................................37

Figure 3.25. Current direction rose plot for Station 42367 in year 2005. .................................38

Figure 3.26. Current direction rose plot for Station 42367 in year 2006. .................................38

Figure 3.27. Current direction rose plot for Station 42367 in year 2007. .................................39

Figure 3.28. Current direction rose plot for Station 42368 in year 2005. .................................40

Figure 3.29. Current direction rose plot for Station 42368 in year 2006. .................................40

Figure 3.30. Current direction rose plot for Station 42368 in year 2007. .................................41

Figure 3.31. Current direction rose plot for Station 42369 in year 2005. .................................41

Figure 3.32. Current direction rose plot for Station 42369 in year 2006. .................................42

Figure 3.33. Current direction rose plot for Station 42369 in year 2007. .................................42

Figure 3.34. Current direction rose plot for Station 42370 in year 2005. .................................43

Figure 3.35. Current direction rose plot for Station 42370 in year 2006. .................................43

Figure 3.36. Current direction rose plot for Station 42370 in year 2007. .................................44

Figure 3.37. Current direction rose plot for Station 42372 in year 2005. .................................45

Figure 3.38. Current direction rose plot for Station 42372 in year 2006. .................................45

Figure 3.39. Current direction rose plot for Station 42372 in year 2007. .................................46

Figure 3.40. Current direction rose plot for Station 42373 in year 2005. .................................46

Figure 3.41. Current direction rose plot for Station 42373 in year 2006. .................................47

Figure 3.42. Current direction rose plot for Station 42373 in year 2007. .................................47

Figure 3.43. Current direction rose plot for Station 42374 in year 2005. .................................48

Figure 3.44. Current direction rose plot for Station 42374 in year 2006. .................................48

Figure 3.45. Current direction rose plot for Station 42374 in year 2007. .................................49

Figure 3.46. Current direction rose plot for Station 42375 in year 2005. .................................50

Figure 3.47. Current direction rose plot for Station 42375 in year 2006. .................................50

Figure 3.48. Current direction rose plot for Station 42375 in year 2007. .................................51

Figure 3.49. Current direction rose plot for Station 42376 in year 2005. .................................52

Figure 3.50. Current direction rose plot for Station 42376 in year 2006. .................................52

Figure 3.51. Current direction rose plot for Station 42376 in year 2007. .................................53

Figure 3.52. Current direction rose plot for Station 42377 in year 2006. .................................54

Figure 3.53. Current direction rose plot for Station 42377 in year 2007. .................................54

Figure 3.54. Current direction rose plot for Station 42379 in year 2006. .................................55
ix

Figure 3.55. Current direction rose plot for Station 42379 in year 2007. .................................55

Figure 4.1. Vertical profiles of horizontal velocity at Station 42361, May 1-10, 2005. .........58

Figure 4.2. Vertical profiles of horizontal velocity at Station 42361, May 12-19, 2005. .......59

Figure 4.3. Vertical profiles of horizontal velocity at Station 42361, June 9-19, 2005. .........60

Figure 4.4. Vertical profiles of horizontal velocity at Station 42363, May 13-23, 2005. .......61

Figure 4.5. Vertical profiles of horizontal velocity at Station 42363, May 24-June 2, 

2005. .....................................................................................................................62

Figure 4.6. Vertical profiles of horizontal velocity at Station 42363, June 3-12, 2005. .........63

Figure 4.7. Vertical profiles of horizontal velocity at Station 42363, June 13-22, 2005. .......64

Figure 4.8. Vertical profiles of horizontal velocity at Station 42363, June 23-July 2, 

2005. .....................................................................................................................65

Figure 5.1.1. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42361. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................72

Figure 5.1.2. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42361. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................72

Figure 5.1.3. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42363. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................73

Figure 5.1.4. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42363. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................73

Figure 5.1.5. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42365. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................74

Figure 5.1.6. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42365. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................74

Figure 5.1.7. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42366. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................75

Figure 5.1.8. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42366. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................75

Figure 5.1.9. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42361. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................76

Figure 5.1.10. Time series of the eastward (upper panel) and northward (lower panel) 

velocity components in 2005 at Station 42367. Horizontal axis is Julian 

time with day 1 equals January 1, 2005. ..............................................................76
x 

Figure 5.1.11. The 2005 hurricane and tropical storm tracks for (1) Tropical Storm 

Arlene, (2) Tropical Storm Cindy, (3) Hurricane Dennis, (4) Hurricane 

Emily, (5) Hurricane Katrina, and (6) Hurricane Rita. ........................................77

Figure 5.1.12. Progressive vector diagram at different depths for May 2006 at Station 

42361. ...................................................................................................................81

Figure 5.1.13. Progressive vector diagram at Station 42361 for different depths in May 

2006. .....................................................................................................................82

Figure 5.1.14. Progressive vector diagram at Station 42361 focusing in shallow depths in 

May 2006. .............................................................................................................82

Figure 5.1.15. Progressive vector diagram at different depths for May 2006 at Station 

42364. ...................................................................................................................83

Figure 5.1.16. Progressive vector diagram at Station 42364 for different depths in May 

2006. .....................................................................................................................83

Figure 5.1.17. Progressive vector diagram at different depths for May 2006 at Station 

42368. ...................................................................................................................84

Figure 5.1.18. Progressive vector diagram at selected depths for May 2006 at Station 

42368. ...................................................................................................................84

Figure 5.1.19. Progressive vector diagram at different depths for May 2006 at Station 

42375. ...................................................................................................................85

Figure 5.1.20. Progressive vector diagram at selected depths for May 2006 at Station 

42375. ...................................................................................................................85

Figure 5.1.21. Progressive vector diagram at different depths for May 2006 at Station 

42863. ...................................................................................................................86

Figure 5.1.22. Progressive vector diagram at selected depths at Station 42863 in May 

2006 zooming in to show the NIOs. .....................................................................86

Figure 5.1.23. Progressive vector diagram at different depths for May 2006 at Station 

42865. ...................................................................................................................87

Figure 5.1.24. Progressive vector diagram at selected depths for May 2006 at Station 

42865 zooming to show NIO. ..............................................................................87

Figure 5.1.25. Progressive vector diagram at different depths for May 2006 at Station 

42869. ...................................................................................................................88

Figure 5.1.26. Progressive vector diagram at selected depths for May 2006 at Station 

42869 zooming to show NIO. ..............................................................................88

Figure 5.1.27. Progressive vector diagram at different depths for May 2006 at Station 

42873. ...................................................................................................................89

Figure 5.1.28. Progressive vector diagram enlarged at different depths for May 2006 at 

Station 42873. .......................................................................................................89

Figure 5.1.29. Progressive vector diagram at selected depths for May 2006 at Station 

42873 zooming to show NIO. ..............................................................................90

Figure 5.1.30. Progressive vector diagram at different depths for May 2006 at Station 

42875. ...................................................................................................................90
xi

Figure 5.1.31. Enlarged progressive vector diagram at different depths for May 2006 at 

Station 42875. .......................................................................................................91

Figure 5.1.32. Progressive vector diagram at selected depths for May 2006 at Station 

42875, showing the NIOs. ....................................................................................91

Figure 5.1.33. Progressive vector diagram at different depths for May 2006 at Station 

42880. ...................................................................................................................92

Figure 5.1.34. Enlarged progressive vector diagram at different depths for May 2006 at 

Station 42880 to show NIO. .................................................................................92

Figure 5.1.35. Enlarged progressive vector diagram at selected depths in May 2006 at 

Station 42880, zoomed in to show the NIOs. .......................................................93

Figure 5.1.36. Progressive vector diagram at different depths for May 2006 at Station 

42881. ...................................................................................................................93

Figure 5.1.37. Enlarged progressive vector diagram at different depths for May 2006 at 

Station 42881. .......................................................................................................94

Figure 5.1.38. Enlarged progressive vector diagram at selected depths for May 2006 at 

Station 42881 to show NIO. .................................................................................94

Figure 5.1.39. Progressive vector diagram at different depths for May 2006 at Station 

42884. ...................................................................................................................95

Figure 5.1.40. Enlarged progressive vector diagram at selected depths for May 2006 at 

Station 42884, zoom in to show the NIOs. ...........................................................95

Figure 5.1.41. Hovmoller diagram for the east velocity component for Station 42361 in 

May 2006. The x-axis is time in days and y-axis is depth in meters. ...................97

Figure 5.1.42. Hovmoller diagram for the north velocity component for Station 42361 in 

May 2006. The x-axis is in days and y-axis in meters. ........................................97

Figure 5.1.43. Spectrum and vertical profile for the east velocity component for Station 

42361 in May 2006. The x-axis is for frequency (in cycle per day), y-axis 

in meters. ..............................................................................................................98

Figure 5.1.44. Spectrum and vertical profile for the north velocity component for Station 

42361 in May 2006. The x-axis is for frequency (in cycle per day), y-axis 

in meters. ..............................................................................................................98

Figure 5.1.45. Low-pass filtered east velocity component for Station 42361 in May 2006. 

The x-axis is in days; vertical axis in meters. .......................................................99

Figure 5.1.46. Low-pass filtered north velocity component for Station 42361 in May 

2006. The x-axis is in days; vertical axis in meters. .............................................99

Figure 5.1.47. East velocity component for Station 42367 in May 2006. The x-axis is in 

days; vertical axis in meters. ..............................................................................100

Figure 5.1.48. North velocity component for Station 42367 in May 2006. The x-axis is in 

days; vertical axis in meters. ..............................................................................100

Figure 5.1.49. Mean east velocity component for Station 42367 in May 2006. The x-axis 

is in days; vertical axis in meters. .......................................................................101

Figure 5.1.50. Mean north velocity component for Station 42367 in May 2006. The x-axis 

is in days; vertical axis in meters. .......................................................................101
xii

Figure 5.1.51. Spectrum for east velocity component for Station 42367 in May 2006. The 

x-axis is in cycles per day; vertical axis in meters. ............................................102

Figure 5.1.52. Spectrum for north velocity component for Station 42367 in May 2006. 

The x-axis is in cycles per day; vertical axis in meters. .....................................102

Figure 5.1.53. Spectra of velocity components for various stations in May 2006. The xaxis is in cycles per day; vertical axis in spectrum energy unit. ........................103

Figure 5.2.1. Study area and the tracks of Hurricanes Katrina, Rita, and Wilma, the oil 

and gas platforms equipped with ADCPs (crosses), and the only platform 

(station 42375) with an ADCP recording throughout all three hurricanes 

(triangle). ............................................................................................................104

Figure 5.2.2. Wind vectors from Station 42040 (29°12'19" N; 88°12'19" W), located ~ 

118 km South of Dauphin Island, AL, and ~76 km north of platform 42375 

(triangle in Figure 5.2.1). ....................................................................................105

Figure 5.2.3. Progressive vector diagram showing the NIOs during Hurricanes Katrina 

and Rita in August and September of 2005 at station 42375. ............................106

Figure 5.2.4. Time-depth plots of low-pass filtered east velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s. .............................................................107

Figure 5.2.5. Time-depth plots of high-pass filtered east velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s. .............................................................107

Figure 5.2.6. Time-depth plots of low-pass filtered north velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s. .............................................................108

Figure 5.2.7. Time-depth plots of high-pass filtered north velocity at station 42375 

during Hurricane Katrina. Speed scale in cm/s. .................................................108

Figure 5.2.8. Depth-averaged speeds (a) before Hurricane Katrina, (b) during and after 

Katrina, (c) between Katrina and Rita, (d) during and after Rita, (e) 

between Rita and Wilma, and (f) during and after Wilma. Y-axis units are 

cm/s. ...................................................................................................................110

Figure 5.2.9. Rotary spectra for the depth-averaged velocity (u, v) in log-scale (a) before 

Hurricane Katrina, (b) during and after Katrina, (c) between Katrina and 

Rita, (d) during and after Rita, (e) between Rita and Wilma, and (f) during 

and after Wilma. The thick lines represent the clockwise rotating 

component and the thin lines represent the counter-clockwise rotating 

component. .........................................................................................................111

Figure 5.2.10. Fraction of energy from rotary spectra for the depth-averaged speeds (a) 

before Hurricane Katrina, (b) during and after Katrina, (c) between Katrina 

and Rita, (d) during and after Rita, (e) between Rita and Wilma, and (f) 

during and after Wilma. The thick lines represent the clockwise rotating 

component and the thin lines the counter-clockwise rotating component. ........112

Figure 5.2.11. Theoretical response curve for clockwise rotating velocity component in 

deep (~ 1900 m) and shallow (30 m) waters. The results for counterclockwise component for both deep and shallow waters are not sensitive to 

the depth and there is no peak in those response curves. ...................................117
xiii

LIST OF TABLES

Table 2.1 The range of data coverage in the vertical by the ADCPs (negative bin size 

indicates an upward looking ADCP) ......................................................................6

Table 3.1 Flow Statistics for All ADCPS or Different Groups of ADCPs at All 

Depths and All Years or Different Years. ............................................................23

Table 3.2 Mean and standard deviation of horizontal speed (cm/s) for all years. ...............24

Table 3.3 Mean and standard deviation of horizontal speed (cm/s) for all stations in 

different years. ......................................................................................................25

Table 3.4 Mean and standard deviation of horizontal speed (cm/s) for all fixed 

stations. (423* stations) at Different Depths during Different Years ...................26

Table 3.5 Mean and standard deviation of horizontal speed in cm/s for all movable 

stations (428*/429* stations) at different depths during different years ..............27

Table 3.6 Mean and standard deviation of horizontal speed in cm/s for different 

regions for all years. .............................................................................................28

Table 3.7 Mean and standard deviation of horizontal speed in cm/s for different 

regions at different depths for All Years ..............................................................29

1 

1. INTRODUCTION

On April 21, 2005, the Minerals Management Service (MMS), now the Bureau of Ocean Energy 

Management, of the U.S. Department of Interior issued Notice to Lessees and Operators, NTL 

No. 2005-G05, in the Gulf of Mexico (GoM) Outer Continental Shelf (OCS) Region. This NTL

required that companies report ocean current data to the National Data Buoy Center (NDBC) 

Internet website for two years effective April 30, 2005. These ocean current data were measured 

by acoustic Doppler current profilers (ADCPs) installed on oil and gas platforms and all floating 

MODUs operating in locations with water depth greater than 400 meters. 

The NTL No. 2005-G05 stipulates that for the floating MODUs, real time ADCP data should be 

collected between 30 m and 1000 m in the water column at 20 minute intervals. For the floating 

MODUs in depths greater than 1100 m, an additional ADCP should be installed at near the 

bottom (100 m from the seabed) to collect data at 20-minute intervals. These observations are not 

required when the rigs are moving from one location to another. It is also required that prior to 

the installation of any new facilities for oil and gas production, a time series data of at least one 

year needs to be collected in the water column between 30 m below the surface and 100 m above 

the bottom. For single point current meters they cannot be separated by more than 500 m. The 

data are not required if a nearby facility within 30 km range can provide similar data unless it is 

near steep topography where the range is reduced to 8 km. For any additional current data or 

other data (such as weather and wave data), the MMS requested voluntary reporting. 

These ADCP were required to be put online through the NDBC web pages starting from April – 

June 2005. These web based data files are open to the public1. Data are recorded in waters with 

a total depth greater than 400 m at 10-20 minute intervals from near surface (~ 30 m) to ~ 500 - 

1000 m. In places with depth greater than 1100 m, two ADCPs may be used. Hurricanes 

Katrina and Rita damaged some of the instruments and interrupted the data reporting on the 

NDBC web site, but many were quickly restored and the rest gradually resumed data collection.

The benefit for this collective monitoring effort is obvious. It has been known that ocean current 

velocity values in the Gulf of Mexico area might have been underestimated according to oil and 

gas industries. These velocity values are used by the industry in design, operation, and function 

of mobile offshore drilling units and floating production platforms and their ancillary equipment 

such as the drilling and production risers, tendons, and mooring systems. An overlook of large 

velocity events can impact the cost and operation. A proper estimate of the ocean current 

velocity under different conditions at different sites is thus needed for structural design, fatigue 

criteria, as well as routine operations. Additionally, a better understanding of the circulation is 

important for a proper handling of spills and pollution. Furthermore, both hindcasting and 

forecasting of the ocean current using numerical models require reliable flow field 

measurements. The long-term measurements from numerous locations in the deep ocean provide 

useful database for model validation. 

One of the major concerns of the oil and gas companies with deep water oil and gas rigs in the 

Gulf of Mexico is the energy and momentum input from the Loop Current (LC), Loop Current 

 

1 Available at this NOAA web site: http://www.ndbc.noaa.gov/maps/ADCP_WestGulf.shtml. 
2 

Eddies (LCE) (e.g. Welsh and Inoue, 2000), and associated cross slope flows. Strong deepwater 

currents or jets may occur, contrary to “intuition.” These deepwater jets have a time scale of a 

few hours to one day with a maximum subsurface velocity magnitude between 0.4 m/s and 2 m/s 

at a depth between 150 and 350 m below the surface with little or no energetic surface 

expression. The large velocity can affect the deep ocean drilling and oil and gas production in the 

northern Gulf of Mexico by the associated extreme loads, causing structural fatigues, thus 

affecting the daily operations. Extensive studies have been conducted on about a dozen of 

incidents of strong subsurface jets in the area using historic hydrographic and current meter data 

(DiMarco et al., 2004; Hamilton et al., 2001, 2003). Several plausible mechanisms are discussed 

in this study, which include the baroclinic frontal instability (e.g. Tang, 1975; Hart, 1975; Hogg, 

1985; Dimas and Triantafyllou, 1995; Robinson and McWilliams, 1974; Pedlosky, 1975; Qiu et 

al, 1988; Meacham, 1988; Tanaka and Alkitomo, 2001; Olascoaga, 2001; Meacham and 

Stephens, 2001; Lozier et al., 2002; Walker and Pedlosky, 2002, etc.), inertial wave train, 

reversed geostrophic flow, interactions between eddies (Frolov et al, 2004a,b), or between slopeshelf and eddies (Vukovich and Crissman 1986; Kirwan et al. 1988; Lewis et al. 1989; Vukovich 

and Waddel 1991; Vidal et al. 1992; Hamilton et al. 1999), wind-driven flow under the influence 

of undulating seabed, internal solitons, and other motions such as filament and meanders 

associated with Loop Current or Loop Current Eddies. Some unlikely mechanisms such as the 

internal solitary waves and bathymetric influences are also discussed. Some instrument issues 

and effects of inhomogeneous flow field are investigated. It is important to note that several 

numerical models (DiMarco et al., 2004) could reproduce the strong currents but the temporal 

duration of the subsurface jets found in the model are usually longer (2-6 days or longer) than 

those seen in observations (one-third to 2 days). In addition, the high-speed core (~ 70 cm/s) in 

the models is generally higher in the water column (150-250 m) than in observations (150-350 

m). Many unknowns are present on this subject. 

The availability of these current data in deep-water from dozens of real time, oil-rig-based 

ADCPs opens a great opportunity for the study of the three dimensional flow structures in the 

northern Gulf of Mexico, specifically waters over the outer continental shelf and slope area 

between 480 and 2400 m. For the first time in history, we are able to use dozens of ADCPs in 

deep water concurrently to “see” the inside of the ocean with a synoptic large picture 

(constructed by these current profilers) as the ocean moves under the influence of different 

mechanisms such as the LC, LCE, inertial motion, frontal instability, filaments, internal soliton, 

internal waves, geostrophic motion, and extreme weather (i.e. hurricanes and tropical storms)

induced motion, to name a few. In general, the Gulf of Mexico is strongly affected by the LC and 

LCE which are one of the key sources of energy and momentum in most part of the GoM. LC 

and LCE have a range of spatial and temporal scales and they may be related to complex flow 

features such as filaments and rings of different horizontal and vertical structures and scales [e.g. 

Berger et al., 2000a,b]. 

The main objectives of this study are to determine the three-dimensional characteristics of the 

deep-water flow in the area by a systematic analysis of the current data from the dozens of 

ADCPs based on the oil and gas platforms and discuss the mechanisms that drive the flow fields. 

More specifically, the analysis is conducted for all data available from April 2005 or earlier (if 

data files are available) to 2008. 
3 

We will discuss the basic statistics of the current velocity profiles and their vertical and 

horizontal variations. The basic statistics includes the mean and standard deviation of the vector 

flow records at different depths, in different regions, and during different times. The flow 

velocity vectors are examined in a way similar to the general analysis to wind data, such that 

predominant flow directions, if any, are identified and discussed. We also discuss the spectra of 

the flow speed as functions of time, depth, and location. Rotary spectra of the velocity fields are 

also discussed. Since 2005, several hurricanes and tropical storms impacted the northern Gulf of 

Mexico. Among them are Hurricanes Katrina and Rita of 2005, and Hurricanes Gustav and Ike 

of 2008. Near inertial oscillations induced by hurricane and non-hurricane wind events are 

discussed in a separate chapter. 

5 

2. DATA COLLECTION AND DESCRIPTION

2.1 GEOGRAPHIC AREA OF MEASUREMENTS

The rigs that are reporting velocity profile data to the National Data Buoy Center (NDBC, 

http://www.ndbc.noaa.gov/maps/ADCP_WestGulf.shtml) are located off the coast of Alabama, 

Mississippi, Louisiana, and Texas (Figure 2.1). These rigs can be permanent or mobile. The rigs

are identified by a five-digit station number associated. Identification numbers starting with 423, 

denote a fixed rig. If the number starts with either 428 or 429, the rig is mobile. Mobile rigs 

may stay at one location for a few months or longer than a year. The geographic positions of the 

mobile rigs are included in the ADCP data files. 

These rigs with ADCP data reporting to NDBC are within a relatively narrow band over the 

slope of the northern Gulf of Mexico, south of the continental shelf and mostly off the Louisiana 

and Texas coasts, between 26° N and 29.2° ̊ N, and 94.9° W and 87.8° W. The southwesternmost fixed rig with ADCP data reporting to NDBC has an NDBC station number 42390, at 

26.129° ̊ N and 94.898° W; while the northeastern-most fixed rig is station 42376 at 29.108° N 

and 87.944° W. Figure 2.1 shows the locations of the rigs in May of 2006. The ones marked 

with red are fixed and the blues are mobile ones. The mobile ones move at intervals of a few 

months and are mostly within the above region. These stations are mostly in water depth between 

200 and 2000 m.

Most of the ADCPs of these stations are setup to look downward during measurements with 

vertical bins at 8, 16, 20, and 32 m recorded every 20 minutes. The data cover between a nearsurface position to a mid-depth or near bottom up to close to 2000 m, depending on the actual 

instrument. Table 2.1 and Figure 2.2 show an example of the data coverage in the vertical for 

2006, with the minimum, maximum depths covered by the measurements and the vertical bin 

size. The negative values for bin size in Table 2.1 indicate an upward looking ADCP. There are 

only two upward looking ADCPs shown in Table 2.1, with data from 2006. Figure 2.3 shows 

the range of data (the maximum bin depth minus the minimum bin depth) which has a mean 

value of 861 m and a standard deviation of 263 m. Since the mobile platforms may move, these 

values may change with time as well. For the ADCPs on the fixed platforms the mean depth 

range is 894 m, with a standard deviation of 303 m, using the 2006 data as an example. At each 

site, measurements cover, on average, more than 800 m of the water column, yielding many

velocity time series. Thus a large amount of data is available to study the vertical structure and 

variability of horizontal velocity in the northern Gulf of Mexico. 
6 

Table 2.1

The range of data coverage in the vertical by the ADCPs (negative 

bin size indicates an upward looking ADCP)

Station Number Top Bin (m) Bottom Bin (m) Bin Size (m)

42361 51.0 0803.0 16.0

42362 79.0 1023.1 16.0

42364 51.0 0995.1 16.0

42365 60.0 1004.0 16.0

42366 114.8 0610.9 16.0

42367 94.7 1024.8 30.0

42368 66.9 1123.0 32.0

42370 61.8 1316.3 -20.0

42373 103.6 0596.8 15.9

42374 44.4 0541.2 16.0

42375 48.0 0992.1 16.0

42376 53.1 0984.0 30.0

42377 21.3 0998.9 30.0

42380 52.1 1685.2 -16.0

42381 57.5 0681.5 16.0

42861 54.6 0838.8 16.0

42862 63.0 1007.1 16.0

42863 73.3 1321.4 32.0

42864 77.5 0621.6 16.0

42865 66.9 1123.0 32.0

42867 46.0 0750.0 16.0

42868 72.9 1161.0 32.0

42869 52.9 0548.9 16.0

42870 72.9 1097.0 32.0

42871 63.0 1007.1 16.0

42872 56.7 0760.7 16.0

42873 71.9 1160.0 32.0

42874 68.8 1157.6 32.0

42875 57.0 1081.1 16.0

42876 58.0 1002.1 16.0

42877 26.8 0498.8 8.0

42878 58.6 0522.7 16.0

42879 54.6 0998.7 16.0

42880 62.5 0606.6 16.0

42881 72.9 1000.9 32.0

42882 63.6 0767.7 16.0

42883 57.2 0585.2 16.0

42884 57.0 0553.0 16.0

42886 42.7 0986.7 16.0

42887 72.9 1161.0 32.0

42889 15.2 0627.3 30.0

42892 74.3 1066.4 32.0

42894 74.3 0746.4 32.0

42896 71.9 1320.0 32.0

42897 61.9 1086.0 16.0
7 

Figure 2.1. Locations of the oil and gas rigs equipped with ADCP and reporting data to NDBC. 
8 

Figure 2.2. Data coverage in the vertical for different ADCPs in 2006 (The x’s indicate the 

bin size as in Table 2.1). 

Figure 2.3. Vertical range for different ADCPs in 2006. 

0 5 10 15 20 25 30 35 40 45

-200

0

200

400

600

800

1000

1200

1400

1600

1800

Data Coverage in the Vertical (m) by Different ADCPs

ADCP #

Vertical Position (m)

0 5 10 15 20 25 30 35 40 45

0

200

400

600

800

1000

1200

1400

1600

1800

Range Coverage in the Vertical (m) by Different ADCPs

ADCP #

Range (m)
9 

2.2 DATA INVENTORY

The temporal coverage of almost all of the ADCPs is quasi-continuous, with mostly continuous 

record lasting for a few weeks to a few months separated by gaps (sometimes significant gaps of 

more than a few months). Figure 2.4 shows the temporal coverage of data from 23 fixedplatform based ADCPs from April 2005 to Feb. 2008. Figure 2.5 shows the temporal coverage 

of data from 38 mobile-platform based ADCPs from April 2005 to Feb. 2008. 

Figure 2.4. Temporal coverage of data for fixed stations.

42360

42361

42362

42363

42364

42365

42366

42367

42368

42369

42370

42371

42372

42373

42374

42375

42376

42377

42378

42379

42380

42381

42382

42383

Feb-05

Mar-05

Apr-05

May-05

Jun-05

Jul-05

Aug-05Sep-05

Oct-05

Nov-05Dec-05

Jan-06

Feb-06

Mar-06

Apr-06

May-06

Jun-06

Jul-06

Aug-06Sep-06

Oct-06

Nov-06Dec-06

Jan-07

Feb-07

Mar-07

Apr-07

May-07

Jun-07

Jul-07

Aug-07Sep-07

Oct-07

Nov-07Dec-07

Jan-08

Feb-08

Mar-08

Apr-08

MMS, Offshore ADCP, Data Inventory

Katrina Rita Katrin Rit
10 

Figure 2.5. Temporal coverage of data for the fixed stations. 

MMS, Offshore ADCP, Data Inventory

42862

42863

42864

42865

42866

42867

42868

42869

42870

42871

42872

42873

42874

42875

42876

42877

42878

42879

42880

42881

42882

42883

42884

42885

42886

42887

42888

42889

42890

42891

42892

42893

42894

42895

42896

42897

42898

42899

42900

42901

42902

42903

42904

42905

Feb-05

Mar-05

Apr-05

May-05

Jun-05

Jul-05

Aug-05Sep-05

Oct-05

Nov-05

Dec-05

Jan-06

Feb-06

Mar-06

Apr-06

May-06

Jun-06

Jul-06

Aug-06Sep-06

Oct-06

Nov-06

Dec-06

Jan-07

Feb-07

Mar-07

Apr-07

May-07

Jun-07

Jul-07

Aug-07Sep-07

Oct-07

Nov-07

Dec-07

Jan-08

Feb-08

Mar-08

Apr-08

Katrina Rita Katrina Rita
11 

3. BASIC STATISTICS OF CURRENTS MEASURED BY ADCPS

3.1 DATA RETURN

The amount of data returned from each instrument varies quite a lot. This is shown by Figure 3.1 

which shows the percentage of time during the years 2005, 2006, and 2007 for each of the 60 

ADCPs operating in the Gulf of Mexico. The data return varies from near 0% (stations 42383 

and 42905) to over 60% with a maximum not exceeding 65% (stations 42367, 42372, 42374, 

42375, 42376, 42871, 42872, 42877, 42879, 42882, and 42890). Most of the stations reported 

data 30%-60% of the time. While Figure 3.1 is just for the depth of 100 m, it is representative of 

the dataset regarding the relative amount of data returned. The actual percentage, however, 

generally decreases with depth. 

Figure 3.1. Data return from all 60 ACDP operating during 2005-2007 for the 100 m depth. 

3.2 OVERALL MEAN AND STANDARD DEVIATION OF THE VELOCITY MAGNITUDE

3.2.1 All Data

In the ADCP data files, there is a field for “Percentage Good” of the data return. This 

“Percentage Good” is not the same as the above percentage data return in time. The “Percentage 

Good” is an indication of the data quality. We use 75% with this field as our criteria of data 

selection: we reject any data point that has a Percentage Good value lower than 75%. Usually, 

when this value is below 75%, it is generally much lower than 75%: the data either has relatively 
12 

high Percentage Good (such as 100%) or a low value (such as 40%, 50%, or 0%). According to 

our experience, choosing 75% as the cut off appears to be appropriate. 

Because of the large volume of data, it is desirable that to have a general view of what the data 

provide. The first statistics are the average and standard deviation of the velocity magnitude for 

the whole dataset, or as a function of the vertical location in the water column, or for different 

years, or for different geographic locations. The results are shown in Figures 3.2-3.7, and Tables 

3.1.-3.7. As shown in Table 3.1, the averaged velocity magnitude for all available data within 

the three year period for all locations and all depths is 12.8 cm/s. The standard deviation is 13.2 

cm/s, comparable to the mean value. This indicates that the variability of the flow is relatively 

large. The total number of data points used to obtain these values is 4,640,044, including some 

data from 2008. When we exclude the 2008 data, the results are very close. The total number of 

data points without the 2008 data is 4,354,778. 

When comparing among different years, we can see that the mean velocity magnitude and 

associated deviation are similar for different years (Table 3.1): the mean velocity for 2005, 2006, 

and 2007 are 13.5, 12.7, and 12.7 cm/s, respectively. The standard deviations for these three 

years are 15.5, 13.7, and 12.1 cm/s, respectively. The total numbers of good data points used to 

obtain these statistical values are 714,729, 1,616,232, and 2,023,817, respectively. The smaller 

number of data points for the year 2005 is because data collection started in April or later, with 

many starting much later than April, 2005. 

To examine the vertical variations, the data were vertically averaged with 50 m bins and shown 

at 50 m intervals. Table 3.2 shows the results from 50 to 2300 m every 50m. The left column is 

for all data from all stations. The central column is for the data from fixed platforms. The right 

column is for data from the movable platforms. Since some of the movable platforms (those 

station numbers starting with 428 or 429) were in deeper water, only the left and right columns 

cover results to 2300 m. The central column can only cover up to 1900 m. The general trend is 

such that (1) the mean velocity magnitude decreases with depth, (2) the standard deviation 

decreases with depth, and (3) the standard deviations are comparable in magnitude to the mean 

values. More specifically, the mean velocity magnitude at the “surface” (50 m below surface) is 

28.0 cm/s for the three–year mean with a standard deviation of 23.8 cm/s (Table 3.1). The mean 

velocity magnitude at the “surface” (50 m below surface) for the year 2005 is 33.7 cm/s with a 

standard deviation of 30.6 cm/s, which are much larger than the overall mean and standard 

deviation, respectively. The year 2005 appears to be the most energetic year. It should be noted 

again that the 2005 data have a smaller ensemble (only about half of that from 2006 and a third 

of that from 2007). The year 2006 shows the second largest mean velocity on the surface and 

throughout the water column (30.1 cm/s mean velocity and 24.3 cm/s standard deviation at 50 m 

below the surface); while 2007 shows the smallest mean velocity and standard deviation of the 

three years (25.4 cm/s mean velocity and 21.4 cm/s standard deviation). These results are shown 

in Table 3.2 and reproduced in the four panels, showing the mean velocity magnitude (the blue 

curve) and the mean plus or minus the standard deviation as functions of the vertical position in 

the water column, of Figure 3.2. The deepest point may not be the actual bottom of the water. 

As we already stated, an individual ADCP may not cover the entire water column. 
13 

Figure 3.2. Mean velocity magnitude and its standard deviation as functions of water depth 

for all 60 instruments for (a) all years, (b) 2005, (c) 2006, and (d) 2007. 

The rates of decrease of both the velocity magnitude and standard deviation with depth are pretty 

rapid. The decrease of mean values appears to be exponential and smooth above 1000 m below 

the surface. Below the 1000 m, velocity becomes weak with a mean value around 5-7 cm/s and 

variable (not smooth). Near the bottom below 2000 m, the mean velocity magnitude and 

standard deviation may show some increase. This appears to be coincident with the dramatic 

drop in the number of data points (Figure 3.3). Below 1300 m, there is only a small fraction of 

the data points compared to the top 1000 m. This is partly because most of the ADCPs are 

located at a location where the total water depth is less than 1200 m. A second reason for the 

dramatic drop in the number of data points is the fact that the ADCPs measure the velocity 

values at various depths through the backscattering of ultrasonic acoustic signal from suspended 

particles in the water column but the water at deep ocean is usually very clean with small 

velocities and high clarity such that there is fewer particles for backscattering to measure the 

velocity. The increase of the near-bottom velocity may be a result of biased samplings: for faster

flows, there is better chance that the water is stirred up more with more particles and stronger 

return signal from the ADCPs. This however is pure speculation and not verified in anyway by 

this study. The vertical distribution of the number of data points is similar for the three years but 

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Velocity Magnitude - All Years

Depth (m)

(a)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Velocity Magnitude - Year 2005

(b)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Velocity Magnitude - Year 2006

Depth (m)

Velocity Magnitude (cm/s)

(c)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Velocity Magnitude - Year 2007

Velocity Magnitude (cm/s)

(d)
14 

with a general trend of increase from 2005 to 2007 at all depth. This just reflects the fact that 

more data are reported in 2006 and 2007. 

Figure 3.3. Number of data points used for the statistics calculations as a function of water 

depth for all the ADCPs and for all years (black), the year 2005 (red), the year 

2006 (the blue), and the year 2007 (light blue). 

3.2.2 The 423* Data

In this section, we discuss the basic statistics results for data measured from fixed platforms 

(ADCPs numbered with 423 as their first three digits). We present similar calculations as 

discussed in Section 3.2.1. These stations will potentially provide longer time series than those 

that move from place to place (428 or 429 as their first three digits in their station identification 

numbers). It is therefore reasonable and useful to separate data from these fixed ADCPs from 

those in moving platforms in the discussion of the results. 

Similar to the results for all the data, when comparing among different years, we can see that the 

mean velocity magnitude and associated deviation from the fixed ADCPs (from 423-stations) are 

also similar for different years (top of Table 3.1): the mean velocity for 2005, 2006, and 2007 are 

9.6, 10.1, and 11.5 cm/s, respectively. The standard deviations for these three years are 10.9, 9.0, 

0 0.5 1 1.5 2 2.5 3

x 105

-2500

-2000

-1500

-1000

-500

0

Data Points - All Data

Depth (m)

Number of Data Points

All years

2005

2006

2007
15 

and 9.8 cm/s, respectively. The total numbers of good data points used to obtain these statistical 

values are 189,361, 585,696, and 650,420, respectively. The total is 1,425,477 points. Again, the 

smaller number of data points for the year 2005 is because the data started in April or later, with 

many starting much later than April of 2005. For all the three years, the mean speed for all 

depths is 10.7 cm/s with a standard deviation of 9.6 cm/s. 

Again, to examine the variation with vertical location, the data were vertically averaged with 50 

m bins and shown at 50 m intervals. Table 3.2 shows the results from 50 to 1900 m every 50 m. 

The deepest measurements from these ADCPs were around 1900, which is shallower than the 

deepest of those installed on movable drilling units. The general trend is again (1) the mean 

velocity magnitude decreases with depth, (2) the standard deviation decreases with depth, and (3) 

the standard deviations are comparable in magnitude to the mean values. More specifically, the 

mean velocity magnitude at the “surface” (50 m below surface) is 18.8 cm/s for all the three 

years with a standard deviation of 13.1 cm/s (Table 3.2). The mean velocity magnitude at the 

“surface” (50 m below surface) for the fixed stations in year 2005 is 14.2 cm/s with a standard 

deviation of 9.6 cm/s, which are smaller compared to the overall mean and standard deviation, 

respectively (Table 3.3, Table 3.4). Data from the fixed platforms show that the year 2005 is the 

least energetic period. The apparent contradiction may be due to the fact that the movable 

drilling units occupied deeper waters where the influence of Loop Current and Loop Current 

Eddies are much stronger. The year 2006 shows the largest mean velocity on the surface and 

throughout the water column (19.6 cm/s mean velocity and 12.8 cm/s standard deviation at 50 m 

below the surface); while 2007 shows intermediate mean velocity and standard deviation of for 

these fixed ADCPs (18.8 cm/s mean velocity and 13.8 cm/s standard deviation). These results 

are shown in Table 3.4 and reproduced visually in Figure 3.3. The number of data points for the 

fixed platforms are shown in Figure 3.4. 

Not surprisingly, the rates of decrease of both the velocity magnitude and standard deviation 

with depth from the fixed ADCPs are also rapid and smooth above 1000 m below the surface. 

Below the 1000 m, velocity becomes weak with a mean value around 5-7 cm/s and variable (not 

smooth). Near the bottom below 2000 m, the mean velocity magnitude and standard deviation 

start to increase. This is coincident with the dramatic drop in the number of data points (Figure 

3.4). Below 1300 m, there is only a small fraction of the data points. Unlike the results for all the 

data or movable ADCPs (see next section), the fixed ADCP data do not show an increase at near 

the bottom. One of the reasons for this is that the ADCPs are not as deep as some of those 

mounted on movable platforms. 
16 

Figure 3.4. Mean velocity magnitude and its standard deviation as functions of water depth 

for all the 423* stations (on fixed platforms) for (a) all years, (b) 2005, (c) 2006, 

and (d) 2007. 

0 20 40 60

-1500

-1000

-500

0

Mean Vel Mag - 423 All Years

Depth (m)

(a)

0 20 40 60

-1500

-1000

-500

0

Mean Vel Mag - 423 Year 2005

(b)

0 20 40 60

-1500

-1000

-500

0

Mean Vel Mag - Year 2006

Depth (m)

Velocity Magnitude (cm/s)

(c)

0 20 40 60

-1500

-1000

-500

0

Mean Vel Mag - 423

Velocity Magnitude (cm/s)

(d)
17 

Figure 3.5. Number of data points used for the statistics calculations as a function of water 

depth for the 423* ADCPs (i.e. those on fixed platforms) and for all years (black), 

the year 2005 (red), the year 2006 (blue), and the year 2007 (light blue). 

3.2.3 The 428* and 429* Data

The movable platform stations with ADCPs are numbered with 428 or 429 as their first three 

digits. We performed similar calculations to those discussed in Sections 3.2.1 and 3.2.2 for these 

ADCPs. These have shorter time series at each location than those that are fixed. These moving 

platforms can also occupy deeper water. Therefore, stronger influence from the Loop Current 

and associated Loop Current eddies, is expected. These movable platforms usually stay at one 

place for months if not the entire year. They may move in shorter intervals nevertheless. 

Similar to the results for all the data, when comparing among different years, we can see that the

mean velocity magnitude and associated deviation from the movable ADCPs are also similar for 

different years (top of Table 3.1): the mean velocity for 2005, 2006, and 2007 are 14.8, 14.2, and 

13.3 cm/s, respectively. The standard deviations for these three years are 16.6, 15.5, and 13.0 

cm/s, respectively. The total numbers of good data points used to obtain these statistical values 

are 525,368, 1,030,536, and 1,373,397, respectively. The total is 2,929,301 points. Again, the 

smaller number of data points for the year 2005 is because the data started in April or later, with 

0 1 2 3 4 5 6 7 8 9 10

x 104

-2000

-1800

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

Data Points - 423 Only

Depth (m)

Number of Data Points

All years

2005

2006

2007
18 

many starting much later than April of 2005. For all the three years, the mean velocity 

magnitude for all depths is 13.8 cm/s with a standard deviation of 14.5 cm/s. 

Figure 3.6. Mean velocity magnitude and its standard deviation as functions of water depth 

for all the 428* and 429* stations (movable platforms) for (a) all years, (b) 2005, 

(c) 2006, and (d) 2007. 

Again, to examine the vertical variation, the data were vertically averaged with 50 m bins and 

shown at 50 m intervals. The right column of Table 3.2 shows the results from 50 to 2300 m 

every 50 m. The deepest measurements from these ADCPs were around 2500, which is deeper 

than the deepest of those installed on fixed platforms. The general trend is again (1) the mean 

velocity magnitude decreases with depth, (2) the standard deviation decreases with depth, and (3) 

the standard deviations are comparable in magnitude to the mean values. More specifically, the 

mean velocity magnitude at the “surface” (50 m below surface) is 31.5 cm/s for all the three 

years with a standard deviation of 25.8 cm/s (Table 3.2). These values are significantly larger 

than those from the fixed platforms (> 50% of increase). The mean velocity magnitude at the 

“surface” (50 m below surface) for the year 2005 is 36.7 cm/s with a standard deviation of 31.6 

cm/s, which are the largest compared to the other two years (Table 3.5). The data from the 

movable platforms show that 2005 had the most energetic currents and more influenced by the 

Loop Current. Interestingly, 2005 was a year of unusually high hurricane activity. There may be 

some linkage between stronger and warmer Loop Current and more frequent hurricanes and 

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Vel Mag - 428/429 All Years

Depth (m)

(a)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Vel Mag - 428/429 Year 2005

(b)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Vel Mag - Year 2006

Depth (m)

Velocity Magnitude (cm/s)

(c)

0 20 40 60

-2500

-2000

-1500

-1000

-500

0

Mean Velocity Magnitude - Year 2007

Velocity Magnitude (cm/s)

(d)
19 

tropical storms. The year 2006 shows intermediate mean velocity on the surface and throughout 

the water column (34.1 cm/s mean velocity and 26.3 cm/s standard deviation at 50 m below the 

surface); while 2007 shows the smallest mean velocity and standard deviation of the three years 

for these fixed ADCPs (28.2 cm/s mean velocity and 23.4 cm/s standard deviation). These 

results are shown in Table 3.5 and reproduced visually in Figure 3.5. The vertical structures 

(Figure 3.5) are very similar to the overall results (Figure 3.2). The number of data points drop 

dramatically below 1300 m (Figure 3.7).

Figure 3.7. Number of data points used for the statistics calculations as a function of water 

depth for the 428* and 429* ADCPs (i.e. those on movable platforms) and for all 

years (black), the year 2005 (red), the year 2006 (blue), and the year 2007 (light 

blue). 

To demonstrate how much movements the 428*/429* movable drilling units may have, we 

plotted the stations and their tracks in Figure 3.8. The red color positions are the fixed platforms, 

while the blue ones are movable (although some of them did not move during the time of data 

coverage).

0 0.5 1 1.5 2 2.5

x 105

-2500

-2000

-1500

-1000

-500

0

Data Points - 428/429

Depth (m)

Number of Data Points

All years

2005

2006

2007
20 

Figure 3.8. Locations and tracks of the study platforms. Red circles are fixed platforms and

the blue diamonds are the movable platforms. 

3.3 TEMPORAL AND VERTICAL CHANGES OF THE MEAN VELOCITY AND 

STANDARD DEVIATIONS

The above statistical characteristics of the flow field provide a very crude picture which does not 

have much information of spatial variations (except the vertical structure) and temporal 

variations (except the comparison among the three years). In this section, we examine the spatial 

and temporal variations in more detail by the spatially averaging speed as a function of time for 

all stations, and by the spatially averaging speed as a function of time for stations from three 

regions – the western, central, and eastern regions. 

These three regions are defined rather arbitrarily for convenience and with consideration of the 

cluster of ADCPs. As can be seen on Figure 3.9, the West region contains about 12 ADCPs, 

while the Central and East regions have 24 and 20 ADCPs, respectively. In the following, we 

will present the results for all the ADCPs, as well as for the ADCPs from the three different 

regions. 
21 

By examining the data, it can be seen that the magnitude of the horizontal velocity as a function 

of vertical position has a long term variation. This variation does not seem to have a clear 

periodicity. As shown in Figure 3.10, the large velocity values occur mostly in the top layer 

above 200 m. When a large velocity occurs, it may last for a few months (note these are 

averaged and low-pass filtered data and exclude inertial oscillations). The central area seems to 

have the most energetic speeds, with mean speeds of 15.0, 15.8, 12.4, and 13.3 cm/s for 2005, 

2006, 2007, and 2008, respectively; the total number of data points are 150,000 (the year 2008, 

with partial data) to 819,000 (2007, with full year of coverage). The eastern area has less 

energetic speeds but stronger flows than the western region, with mean speeds of 13.6, 10.6, 

15.3, and 10.5 cm/s for 2005, 2006, 2007, and 2008, respectively; the total number of data points 

are 84,000 (the year 2008, with partial data) to 782,000 (2007, with full year of coverage). The 

western area has the least energetic speeds with means of 10.3, 11.1, 8.6, and 12.6 cm/s for 2005, 

2006, 2007, and 2008, respectively;, the total number of data points are 43,000 (the year 2008, 

with partial data) to 422,000 (2007, with full year of coverage, Figure 3.10, Table 3.6). 

Figure 3.9. Division of the study area into the east, central, and west regions. 

The west area and central area can have similarities sometimes but may still be quite 

different. The maximum flow is mostly on the surface but can extend downward. The depth at 

which the maximum velocity magnitude reaches also varies, which suggests a result of eddies 

coming through the area. The central area velocity seems to lead that of the western area most of 

the time. This is consistent with a westward propagation of eddies. In contrast, the eastern region 

however has much less similarity to the central and western regions. This suggests that the 

eastern region is not the “upstream” region of the central and western regions. 
22 

Figure 3.10. Averaged speed as a function of time and depth.
23 

Table 3.1

 

Flow Statistics for All ADCPS or Different Groups of ADCPs at All Depths and All Years or 

Different Years.

All ADCPs

Mean (cm/s) STD n Year Mean (cm/s) STD n

12.8 13.2 4354778 2005 13.5 15.5 714729

2006 12.7 13.7 1616232

2007 12.7 12.1 2023817

423* ADCPs Only

Mean (cm/s) STD n Year Mean (cm/s) STD n

10.7 9.6 1425477 2005 9.6 10.9 189361

2006 10.1 9.0 585696

2007 11.5 9.8 650420

428*/429* ADCPs Only

Mean (cm/s) STD n Year Mean (cm/s) STD n

13.8 14.5 2929301 2005 14.8 16.6 525368

2006 14.2 15.5 1030536

2007 13.3 13.0 1373397
24 

Table 3.2

 

Mean and standard deviation of horizontal speed (cm/s) for all years. 

All Stations 423* Stations Only 428*/429* Stations Only

Depth Mean STD n Depth Mean STD n Depth Mean STD n

50 28.0 23.8 238728 50 18.8 13.1 64684 50 31.5 25.8 174044

100 22.8 19.9 290892 100 17.7 14.1 86475 100 24.9 21.6 204417

150 19.3 16.7 293514 150 16.3 13.6 91089 150 20.7 17.8 202425

200 17.3 14.2 295724 200 15.2 12.0 90327 200 18.2 15.0 205397

250 15.9 13.1 293657 250 13.9 10.8 90303 250 16.7 13.8 203354

300 14.9 14.1 291193 300 12.8 9.7 90965 300 15.8 15.6 200228

350 13.1 10.1 285379 350 11.8 8.4 91693 350 13.8 10.7 193686

400 11.9 8.8 280992 400 10.9 7.5 87648 400 12.4 9.2 193344

450 11.0 8.1 274978 450 10.0 6.8 83439 450 11.5 8.5 191539

500 10.3 7.3 266133 500 9.5 6.3 83029 500 10.7 7.7 183104

550 9.6 6.9 234301 550 9.2 6.0 68841 550 9.7 7.3 165460

600 9.1 6.4 207986 600 8.7 5.9 58760 600 9.3 6.6 149226

650 8.5 6.4 182986 650 7.9 5.3 49432 650 8.7 6.7 133554

700 7.8 5.5 158267 700 7.1 4.9 41170 700 8.1 5.6 117097

750 7.1 5.6 142863 750 6.7 6.5 38808 750 7.2 5.2 104055

800 6.7 4.5 132516 800 6.1 4.0 49551 800 7.0 4.7 82965

850 6.3 4.4 121813 850 6.2 4.1 42705 850 6.4 4.5 79108

900 6.1 4.3 115054 900 6.0 3.7 42096 900 6.1 4.6 72958

950 6.0 4.3 105199 950 6.1 3.9 37314 950 5.9 4.4 67885

1000 5.8 4.4 89314 1000 6.1 3.7 34510 1000 5.7 4.8 54804

1050 5.8 5.0 59901 1050 6.0 3.9 22575 1050 5.7 5.5 37326

1100 6.0 6.1 45429 1100 5.9 4.5 22797 1100 6.1 7.3 22632

1150 5.7 4.7 29572 1150 6.4 5.0 14898 1150 5.1 4.4 14674

1200 6.3 4.9 21939 1200 6.4 5.2 15933 1200 5.9 3.9 6006

1250 6.6 5.3 24891 1250 6.7 5.6 17015 1250 6.3 4.6 7876

1300 7.6 6.8 21693 1300 8.0 7.1 15234 1300 6.6 6.2 6459

1350 5.1 3.4 10410 1350 4.9 3.6 6964 1350 5.3 3.0 3446

1400 5.1 3.9 10056 1400 5.0 4.2 6604 1400 5.4 3.0 3452

1450 5.2 3.8 10403 1450 4.9 4.0 6965 1450 5.8 3.1 3438

1500 6.2 6.6 11560 1500 6.5 7.5 8157 1500 5.5 3.3 3403

1550 5.0 3.4 10105 1550 4.6 3.3 6729 1550 5.7 3.4 3376

1600 5.2 3.7 11559 1600 4.7 3.5 8013 1600 6.4 3.8 3546

1650 6.3 4.3 12233 1650 5.4 3.3 8396 1650 8.1 5.4 3837

1700 7.3 5.6 9162 1700 5.4 4.4 5116 1700 9.6 6.1 4046

1750 5.4 4.3 6257 1750 5.1 3.7 4548 1750 6.4 5.5 1709

1800 6.9 5.4 6618 1800 6.0 4.6 4545 1800 8.8 6.3 2073

1850 6.5 4.9 5869 1850 6.6 5.1 4541 1850 6.1 4.3 1328

1900 5.8 4.3 6533 1900 6.3 4.5 4537 1900 4.9 3.6 1996

1950 5.6 3.3 2478 1950 5.6 3.3 2478

2000 5.2 3.1 2162 2000 5.2 3.1 2162

2050 8.3 8.1 2882 2050 8.3 8.1 2882

2100 7.6 5.3 1772 2100 7.6 5.3 1772

2150 8.5 5.7 2045 2150 8.5 5.7 2045

2200 9.0 6.0 2441 2200 9.0 6.0 2441

2250 8.1 6.3 2949 2250 8.1 6.3 2949

2300 9.1 7.7 2298 2300 9.1 7.7 2298
25 

Table 3.3

 

Mean and standard deviation of horizontal speed (cm/s) for all stations in different years. 

2005 2006 2007

Depth Mean STD n Depth Mean STD n Depth Mean STD n

50 33.7 30.6 31622 50 30.1 24.3 81390 50 25.4 21.4 107737

100 26.9 25.9 38959 100 24.6 20.8 95282 100 20.8 17.6 135244

150 23.0 22.1 39168 150 20.3 17.6 96816 150 18.1 14.6 136091

200 20.1 18.3 39355 200 17.9 15.2 95194 200 16.6 12.6 139245

250 18.1 16.0 38598 250 16.3 13.8 94873 250 15.5 11.8 138516

300 15.8 13.8 38298 300 15.0 14.3 94356 300 14.8 13.8 137184

350 14.3 11.9 38151 350 13.1 10.0 93252 350 12.9 9.1 133489

400 13.1 10.4 38124 400 11.9 9.2 90449 400 11.8 8.1 132438

450 12.1 9.4 38126 450 11.0 8.5 89735 450 10.9 7.6 127878

500 11.3 8.5 37235 500 10.2 7.4 87952 500 10.2 7.0 122622

550 10.4 7.9 33565 550 9.3 7.1 80287 550 9.5 6.6 105780

600 9.6 7.1 30717 600 8.8 6.5 68986 600 9.2 6.2 95448

650 9.2 6.6 27490 650 8.2 7.0 62149 650 8.6 5.9 82117

700 8.8 6.4 25138 700 7.6 5.2 56194 700 7.7 5.3 68447

750 8.3 7.1 22349 750 6.9 5.0 51179 750 6.9 5.0 62337

800 7.7 5.2 20436 800 6.6 4.5 48440 800 6.5 4.2 57219

850 7.2 4.8 18499 850 6.3 4.5 45829 850 6.2 4.0 52618

900 7.0 5.0 17775 900 6.0 4.4 45114 900 5.9 3.8 48251

950 6.5 4.5 17526 950 5.7 4.5 42486 950 6.0 3.8 41566

1000 6.0 4.5 15611 1000 5.8 5.0 36423 1000 5.8 3.7 34151

1050 5.7 4.7 11762 1050 5.9 6.0 28129 1050 5.7 3.4 18622

1100 5.7 4.6 9755 1100 6.5 8.0 19661 1100 5.4 3.5 15038

1150 5.1 4.0 6560 1150 6.1 5.4 12397 1150 5.6 4.2 9441

1200 5.2 3.9 4868 1200 6.3 5.2 10307 1200 6.8 4.7 6182

1250 5.6 3.7 6294 1250 6.3 5.7 12014 1250 7.7 5.4 6001

1300 5.6 3.6 6618 1300 7.3 7.3 10071 1300 10.0 7.8 4422

1350 5.4 3.5 3284 1350 4.8 3.5 6346 1350 5.5 2.5 780

1400 5.1 3.4 3396 1400 5.1 4.2 5921 1400 5.3 2.3 739

1450 4.8 3.2 3581 1450 5.3 4.2 6079 1450 5.9 2.3 743

1500 4.6 3.1 4019 1500 7.3 8.1 6802 1500 5.3 2.5 739

1550 4.5 3.0 4514 1550 5.4 3.7 4979 1550 5.3 2.3 612

1600 4.4 2.9 4796 1600 5.7 4.2 6018 1600 6.3 2.5 745

1650 5.5 3.2 4900 1650 6.8 4.9 6631 1650 6.8 2.7 702

1700 5.0 4.4 3219 1700 8.3 6.0 5331 1700 10.4 3.2 612

1750 4.9 4.0 3114 1750 6.0 4.5 3129 1750 2.7 0.8 14

1800 7.2 5.6 3094 1800 6.7 5.2 3510 1800 2.9 1.5 14

1850 5.4 3.7 2124 1850 7.1 5.4 3731 1850 3.5 3.0 14

1900 4.8 2.9 2606 1900 6.5 4.9 3915 1900 8.1 1.9 12

1950 5.6 2.7 920 1950 5.6 3.6 1558

2000 5.4 3.9 691 2000 5.0 2.7 1471

2050 6.9 4.9 1181 2050 9.2 9.7 1701

2100 7.6 5.3 1772

2150 8.5 5.7 2045

2200 9.0 6.0 2441

2250 8.1 6.3 2949

2300 9.1 7.7 2298

2350 12.1 9.4 1089

2400 10.5 11.3 1579

2450 11.5 12.4 1585

2500 20.4 14.7 930
26 

Table 3.4

 

Mean and standard deviation of horizontal speed (cm/s) for all fixed stations. (423* 

stations) at Different Depths during Different Years

2005 2006 2007

Depth Mean STD n Depth Mean STD n Depth Mean STD n

50 14.2 9.6 4232 50 19.6 12.8 22299 50 18.8 13.8 32758

100 19.1 19.6 8399 100 18.4 13.0 29462 100 17.1 14.0 42801

150 20.0 21.1 8396 150 16.0 12.5 31430 150 15.9 13.0 45336

200 18.0 17.7 8369 200 14.6 11.1 30742 200 15.4 11.7 45295

250 16.1 16.1 8441 250 13.5 10.2 30727 250 14.2 10.3 45214

300 13.7 13.4 8427 300 12.7 9.5 31517 300 13.0 9.4 45128

350 11.9 10.6 8358 350 11.6 8.3 31806 350 12.0 8.4 45475

400 11.1 8.7 7885 400 10.8 7.3 29290 400 11.1 7.6 44435

450 10.1 7.6 7847 450 10.1 6.7 29263 450 10.1 6.8 40944

500 9.3 6.7 7747 500 9.5 6.2 29388 500 9.6 6.4 40560

550 8.9 5.6 5869 550 8.9 5.8 27379 550 9.3 6.2 31865

600 7.5 4.0 4364 600 8.2 5.4 22572 600 9.0 6.4 28789

650 7.1 4.0 4011 650 7.4 4.9 18450 650 8.2 5.7 24161

700 7.7 5.8 4257 700 7.1 4.5 18710 700 6.9 4.6 16691

750 8.3 10.1 4115 750 6.4 4.3 17473 750 6.4 5.6 15741

800 6.7 4.1 7126 800 6.1 4.1 20319 800 6.0 3.9 20010

850 6.8 3.8 5857 850 5.9 4.1 18321 850 6.3 4.1 17128

900 6.6 3.8 5553 900 5.9 3.9 18158 900 5.9 3.6 17005

950 6.7 4.0 5625 950 6.0 4.2 16625 950 6.0 3.5 13825

1000 6.7 4.1 5652 1000 5.9 3.9 14680 1000 6.0 3.2 12975

1050 6.5 4.3 4617 1050 5.6 4.1 10808 1050 6.3 3.3 6568

1100 6.1 4.2 4450 1100 5.7 5.2 11003 1100 5.8 3.4 6744

1150 5.7 4.1 3966 1150 6.0 5.2 7724 1150 8.2 5.0 2625

1200 5.3 3.9 4575 1200 6.0 5.4 8169 1200 8.8 5.6 2607

1250 5.4 3.5 5044 1250 6.2 5.8 8807 1250 9.9 6.5 2582

1300 5.6 3.4 5254 1300 7.6 7.3 6825 1300 12.0 8.8 2573

1350 5.0 3.1 2200 1350 4.9 3.8 4581 1350 4.3 1.9 183

1400 4.6 3.2 2273 1400 5.3 4.8 4197 1400 4.3 1.6 134

1450 4.4 2.9 2452 1450 5.2 4.5 4379 1450 5.3 2.3 134

1500 4.3 2.9 2906 1500 7.9 9.0 5117 1500 5.8 3.4 134

1550 4.4 3.0 3436 1550 4.9 3.6 3293

1600 4.3 2.9 3708 1600 5.0 3.8 4305

1650 5.4 2.9 3767 1650 5.4 3.6 4629

1700 4.6 3.5 2028 1700 6.0 4.8 3088

1750 4.8 3.6 2040 1750 5.3 3.7 2508

1800 5.2 3.8 2039 1800 6.7 5.1 2506

1850 5.5 3.8 2036 1850 7.6 5.8 2505

1900 5.1 2.8 2038 1900 7.2 5.3 2499
27 

Table 3.5

 

Mean and standard deviation of horizontal speed in cm/s for all movable stations 

(428*/429* stations) at different depths during different years 

2005 2006 2007

Depth Mean STD n Depth Mean STD n Depth Mean STD n

50 36.7 31.6 27390 50 34.1 26.3 59091 50 28.2 23.4 74979

100 29.0 27.0 30560 100 27.4 23.0 65820 100 22.5 18.8 92443

150 23.9 22.3 30772 150 22.3 19.3 65386 150 19.1 15.2 90755

200 20.7 18.4 30986 200 19.5 16.6 64452 200 17.2 12.9 93950

250 18.6 16.0 30157 250 17.6 15.1 64146 250 16.1 12.4 93302

300 16.4 13.8 29871 300 16.2 16.1 62839 300 15.6 15.4 92056

350 15.0 12.1 29793 350 13.8 10.8 61446 350 13.4 9.4 88014

400 13.7 10.7 30239 400 12.4 9.9 61159 400 12.2 8.3 88003

450 12.7 9.7 30279 450 11.4 9.2 60472 450 11.3 7.8 86934

500 11.8 8.9 29488 500 10.6 7.9 58564 500 10.6 7.3 82062

550 10.7 8.3 27696 550 9.6 7.6 52908 550 9.6 6.7 73915

600 9.9 7.5 26353 600 9.1 6.9 46414 600 9.3 6.1 66659

650 9.6 6.9 23479 650 8.6 7.7 43699 650 8.7 6.0 57956

700 9.0 6.5 20881 700 7.9 5.5 37484 700 7.9 5.5 51756

750 8.3 6.1 18234 750 7.2 5.3 33706 750 7.0 4.8 46596

800 8.3 5.7 13310 800 6.9 4.8 28121 800 6.8 4.3 37209

850 7.4 5.2 12642 850 6.5 4.8 27508 850 6.1 4.0 35490

900 7.2 5.4 12222 900 6.1 4.7 26956 900 5.8 3.9 31246

950 6.4 4.8 11901 950 5.6 4.7 25861 950 5.9 4.0 27741

1000 5.6 4.7 9959 1000 5.6 5.7 21743 1000 5.7 3.9 21176

1050 5.2 4.9 7145 1050 6.0 6.9 17321 1050 5.4 3.4 12054

1100 5.4 4.9 5305 1100 7.5 10.4 8658 1100 5.1 3.5 8294

1150 4.3 3.6 2594 1150 6.3 5.7 4673 1150 4.6 3.4 6816

1200 3.3 3.1 293 1200 7.2 4.6 2138 1200 5.4 3.2 3575

1250 6.5 4.2 1250 1250 6.6 5.5 3207 1250 6.0 3.7 3419

1300 5.4 4.2 1364 1300 6.9 7.3 3246 1300 7.2 4.9 1849

1350 6.2 3.9 1084 1350 4.6 2.4 1765 1350 5.9 2.5 597

1400 6.0 3.7 1123 1400 4.9 2.6 1724 1400 5.5 2.3 605

1450 5.8 3.6 1129 1450 5.8 3.0 1700 1450 6.0 2.3 609

1500 5.4 3.2 1113 1500 5.7 3.6 1685 1500 5.2 2.2 605

1550 4.9 2.7 1078 1550 6.3 3.9 1686 1550 5.3 2.3 612

1600 4.9 2.6 1088 1600 7.4 4.6 1713 1600 6.3 2.5 745

1650 5.5 4.0 1133 1650 10.1 5.9 2002 1650 6.8 2.7 702

1700 5.8 5.4 1191 1700 11.4 6.1 2243 1700 10.4 3.2 612

1750 5.0 4.5 1074 1750 9.0 6.2 621 1750 2.7 0.8 14

1800 11.1 6.3 1055 1800 6.5 5.4 1004 1800 2.9 1.5 14

1850 4.1 2.5 88 1850 6.3 4.4 1226 1850 3.5 3.0 14

1900 3.8 2.7 568 1900 5.3 3.8 1416 1900 8.1 1.9 12

1950 5.6 2.7 920 1950 5.6 3.6 1558

2000 5.4 3.9 691 2000 5.0 2.7 1471

2050 6.9 4.9 1181 2050 9.2 9.7 1701

2100 7.6 5.3 1772

2150 8.5 5.7 2045

2200 9.0 6.0 2441

2250 8.1 6.3 2949

2300 9.1 7.7 2298
28 

Table 3.6

 

Mean and standard deviation of horizontal speed in cm/s for different regions for all years. 

West Central East

Mean STD n Mean STD n Mean STD n

9.966 8.561 999114 14.02 14.8 1900064 13.18 13.26 1740866

Mean STD n Year Mean STD n Year Mean STD n Year

10.30 9.88 160172 2005 15.04 17.75 296187 2005 13.59 15.29 258370 2005

11.06 9.69 373322 2006 15.78 17.44 627507 2006 10.65 10.38 615403 2006

8.60 6.52 422137 2007 12.44 11.32 819389 2007 15.31 14.31 782291 2007

12.56 8.42 43483 2008 13.28 11.95 156981 2008 10.52 11.43 84802 2008
29 

Table 3.7

 

Mean and standard deviation of horizontal speed in cm/s for different regions at different 

depths for All Years 

West Central East

Depth Mean STD n Depth Mean STD n Depth Mean STD n

50 19.2 14.3 44195 50 31.7 26.0 102964 50 28.3 23.6 91569

100 15.7 11.6 66749 100 26.8 22.4 115747 100 22.9 19.9 108396

150 13.9 10.2 71106 150 22.1 18.9 116088 150 19.9 16.7 106320

200 12.7 9.3 71128 200 19.1 15.6 119672 200 18.4 14.7 104924

250 11.5 8.3 70917 250 17.8 14.6 118226 250 16.7 13.2 104514

300 10.7 7.5 69877 300 16.9 16.8 117575 300 15.4 13.4 103741

350 9.8 6.8 68360 350 14.2 10.3 113717 350 14.1 11.1 103302

400 9.0 6.2 68011 400 12.9 9.3 114231 400 12.8 9.2 98750

450 8.4 5.7 67358 450 11.9 8.6 112595 450 11.9 8.4 95025

500 8.2 5.7 64012 500 10.8 7.5 109910 500 11.1 7.9 92211

550 7.8 6.4 54653 550 10.1 6.6 91230 550 10.1 7.4 88418

600 7.9 6.3 48441 600 9.4 5.9 76176 600 9.5 6.9 83369

650 7.8 8.0 38816 650 8.5 5.4 69248 650 8.8 6.2 74922

700 6.9 5.4 37282 700 7.7 5.4 63445 700 8.5 5.6 57540

750 5.7 5.1 33489 750 7.1 6.1 57077 750 8.0 5.2 52297

800 5.2 3.8 29726 800 7.0 4.4 54083 800 7.3 4.8 48707

850 6.0 4.2 21399 850 6.3 4.2 53133 850 6.6 4.6 47281

900 5.6 3.6 17006 900 5.8 4.0 52069 900 6.6 4.7 45979

950 5.4 3.6 16311 950 5.6 3.8 46866 950 6.6 4.9 42022

1000 5.2 3.7 14892 1000 5.5 3.8 40427 1000 6.5 5.2 33995

1050 5.4 3.6 11741 1050 5.4 3.9 28954 1050 6.6 6.7 19206

1100 5.2 4.6 11538 1100 5.5 4.1 20104 1100 7.4 8.7 13787

1150 3.9 3.0 1766 1150 6.3 4.9 16680 1150 5.2 4.6 11126

1200 3.3 4.4 120 1200 6.7 5.1 16659 1200 5.1 3.9 5160

1250 3.8 5.1 90 1250 7.4 5.9 16435 1250 5.2 3.6 8366

1300 4.0 5.1 84 1300 9.5 7.8 13041 1300 4.7 3.3 8568

1350 12.3 2.7 13 1350 5.4 4.3 2667 1350 4.9 3.0 7730

1400 13.2 5.2 11 1400 6.1 5.5 2630 1400 4.8 3.0 7415

1450 15.3 8.6 11 1450 6.3 5.3 2551 1450 4.8 3.0 7841

1500 15.8 8.2 11 1500 10.4 10.6 3108 1500 4.7 3.0 8441

1550 7.2 4.7 637 1550 4.8 3.2 9468

1600 8.8 5.8 703 1600 5.0 3.4 10856

1650 9.9 7.0 1009 1650 5.9 3.8 11224

1700 11.1 7.5 1144 1700 6.7 5.0 8018

1750 8.6 6.1 683 1750 5.0 3.8 5574

1800 6.3 5.3 1067 1800 7.0 5.4 5551

1850 6.1 4.3 1314 1850 6.6 5.1 4555

1900 4.9 3.6 1984 1900 6.3 4.5 4549

1950 5.6 3.3 2478

2000 5.2 3.1 2162

2050 8.3 8.1 2882

2100 7.6 5.3 1772

2150 8.5 5.7 2045

2200 9.0 6.0 2441

2250 8.1 6.3 2949

2300 9.1 7.7 2298

2350 12.1 9.4 1089

2400 10.5 11.3 1579

2450 11.5 12.4 1585

2500 20.4 14.7 930
30 

3.4 FLOW DIRECTION STATISTICS

This section presents the statistics of the flow directions using current roses. Flow direction 

represents as to where the water flows and the number of data points for a given direction is 

represented by the length of the rose radii. To better illustrate the spatial and temporal variability 

of the flows, we constructed a map with a current rose for each fixed platforms and each year 

(2005, 2006, and 2007). Data from movable units are more difficult to characterize and were not 

displayed. At a given station, different years may exhibit different flow directions. Some of 

them are “unidirectional” meaning that the most of the flow is in the same direction. Others are 

“bidirectional” with the majority of the flows alternating in two different directions, either 

opposite directions or at angles different than 180 degrees. Still others are “omnidirectional” 

with no apparent preferred direction. 

Station 42361 (Auger - Garden Banks 426), Figures 3.11-3.13, is operated by Shell International 

E&P. It is on a fixed platform at 27.550 N 92.490 W with a water depth of 872 m, covering 

between 51 and 803 m below the surface. At Station 42361, the flow direction is quite consistent 

during 2005 to 2007. The flow is mostly westward with a secondary direction of eastward for 

2005. For 2006, the flow is mainly westward with perhaps secondary directions of southwest and 

northwest. For 2007, the results are similar to 2006. 

Figure 3.11. Current direction rose plot for Station 42361 in year 2005.
31 

Figure 3.12. Current direction rose plot for Station 42361 in year 2006.

Figure 3.13. Current direction rose plot for Station 42361 in year 2007. 
32 

Station 42362 (Brutus – Green Canyon 158), Figures 3.14-3.15, is operated by Shell 

International E&P and located at 27.8 N, 90.67 W at 910 m water depth, covering between 79 m 

and near bottom. The site only has data from 2006 and 2007. It is almost two degrees in 

longitude (or 197 km) due east of Station 42361. The flow is quite different from Station 42361: 

it is mostly toward the northeast and north in 2006, and northwest in 2007. 

Figure 3.14. Current direction rose plot for Station 42362 in year 2006.

Figure 3.15. Current direction rose plot for Station 42362 in year 2007. 
33 

Station 42363 (Mars - Mississippi Canyon 807), Figures 3.16- 3.18, is 150 km east of Station 

42362 and is operated by Shell International E&P. This fixed platform is located at 28.160 N 

89.220 W. The water depth there is 894 m and the data expands almost the entire water column 

from 61 m below the surface. Again this site there is large variability of the flow directions from 

2005 to 2007. The predominant flow direction in 2005 is eastward with some variability (from 

northeast to southwest), and a secondary northwest flow direction. This is changed in 2006, 

which shows mostly southward flows and secondary direction of northwest. The 2007 flow is 

changed again to be mostly toward the northeast. This suggests that a large component of the 

flow in within the low frequency band with a strong inter-annual variability. The main 

dynamical systems there are the Loop Current and associated eddies. Apparently, the 

predominant flow directions change as eddies and Loop Current sweep through the area. The 

Loop Current and eddies have their typical time scales of a few months and thus are lowfrequency motions. 

Figure 3.16. Current direction rose plot for Station 42363 in year 2005.
34 

Figure 3.17. Current direction rose plot for Station 42363 in year 2006.

Figure 3.18. Current direction rose plot for Station 42363 in year 2007.

Operated by Shell International E&P, Station 42365 (Ursa - Mississippi Canyon 809), Figures 

3.19-3.21 is located at 28.200 N 89.120 W, northeast of and very close to Station 42363, in 1158 

m water depth. Figure 3.18 is very similar to Figure 3.21; showing that the predominant flow 
35 

direction in 2005 and 2007 is eastward with some variability (from northeast to southwest). In 

2006 the flow directionality changed, and the flow is going mostly. 

Figure 3.19. Current direction rose plot for Station 42365 in year 2005. 

Figure 3.20. Current direction rose plot for Station 42365 in year 2006. 
36 

Figure 3.21. Current direction rose plot for Station 42365 in year 2007.

Station 42366 (Red Hawk - Garden Banks 877), Figures 3.22 – 3.24, is operated by Kerr-McGee 

Oil and Gas Corporation and located at 27.122 N 91.959 W, southeast of Station 42361 for more 

than 50 km. The water depth at this station is 872 m. The flow at this site is very different, even 

though it is close to the Station 42361. The year-to-year variability is very little, in contrast to 

other stations and the predominant flow direction is northward. 

Figure 3.22. Current direction rose plot for Station 42366 in year 2005.
37 

Figure 3.23. Current direction rose plot for Station 42366 in year 2006. 

Figure 3.24. Current direction rose plot for Station 42366 in year 2007.

Station 42367 (Matterhorn - Mississippi Canyon 243), Figures 3.25-3.27, is operated by Total

USA, Inc. and located at 28.743 N 88.826 W in water depths of 860 m. The data cover between 

95 and 1025 m. It is located southeast of the Birdfoot’s Delta. The flow at this site appears to be 
38 

quite consistent from 2005 to 2007. The predominant flow direction is toward the southwest, 

with some secondary flows in the northwest (2005) direction and northeast directions (2006 and 

2007). Although Stations 42363 and 42365 are similar in flow directions, Station 42367 appears 

to be quite different. This could be due to the fact that the former two stations are closer to the 

Loop Current and associated eddies. 

Figure 3.25. Current direction rose plot for Station 42367 in year 2005.

Figure 3.26. Current direction rose plot for Station 42367 in year 2006.
39 

Figure 3.27. Current direction rose plot for Station 42367 in year 2007.

Station 42368 (Magnolia - Garden Banks 783), Figures 3.28- 3.30, is operated by ConocoPhillips

and located at 27.204 N 92.203 W in water depths of 1424 m. It is very close to Station 42366 

(about 20 km west-northwest of Station 42366). The flow however is very different from that 

nearby station. At this station, the flow is mostly toward the southern quadrants (southwesterly 

directed but with secondary directions such as south and northwest. The difference between 

Stations 42366 and 42368 is partly due to the difference in data coverage in the vertical. Station 

42366 covers the vertical from 115 to 610 m, while Station 42368 covers between 67 and 

1123 m.
40 

Figure 3.28. Current direction rose plot for Station 42368 in year 2005. 

Figure 3.29. Current direction rose plot for Station 42368 in year 2006.
41 

Figure 3.30. Current direction rose plot for Station 42368 in year 2007.

Station 42369 (Mad Dog - Green Canyon 782), Figures 3.31-3.33 is operated by BP, Inc.,

located at 27.189 N 90.269 W in water depths of 1372 m. The data cover 124 to 868 m. The 

flow direction exhibits large variation from time to time. The 2005 data shows a predominant 

direction of northeast, while the 2006 data added a southeast direction. The 2007 data shows a 

direction of south and southwest, with secondary directions of northwest and southeast. 

Figure 3.31. Current direction rose plot for Station 42369 in year 2005. 
42 

Figure 3.32. Current direction rose plot for Station 42369 in year 2006. 

Figure 3.33. Current direction rose plot for Station 42369 in year 2007.

Station 42370 (Holstein - Green Canyon 645), Figures 3.34-3.36, is operated by BP, Inc., and

located at 27.321 N 90.536 W in water depths of 1311 m. The data cover 62 to 992 m. The flow 

direction exhibits large variation from time to time. The 2005 data shows bi-directional with 
43 

northeast and southwest as the main directions and large variability, while the 2006 data is also 

bi-directional with southeast and northeast directions. The 2007 data is almost omnidirectional 

with more emphasis on the southwest directions. This station is very close to 42369 but the 

results seem to be quite different. The depths covered are similar. It is not known what caused 

the difference in flow directions. 

Figure 3.34. Current direction rose plot for Station 42370 in year 2005. 

Figure 3.35. Current direction rose plot for Station 42370 in year 2006. 
44 

Figure 3.36. Current direction rose plot for Station 42370 in year 2007.

Station 42372 (Genesis - Green Canyon 205), Figures 3.37- 3.39, is operated by Chevron and 

located at 27.779 N 90.519 W in water depths of 789 m. The data cover 28 to 660 m. It is very 

close to Station 42362. The flow directions however are quite different. The 2005 data for 

Station 42372 is mostly eastward and northeastward, with a weak secondary northwestward flow 

direction. The Station 42362 does not have 2005 data. The 2006 flow at Station 42372 is 

predominantly eastward; while the Station 42362 shows mainly northeast preference. The 2007 

data for Station 42372 is bimodal with southwest and northeast preference, while the Station 

42362 shows north and northwest preference. This variation between two adjacent stations may 

be caused by the gradient between the two stations: this may happen when they are at the edge of 

certain features (such as Loop Current or an eddy). 
45 

Figure 3.37. Current direction rose plot for Station 42372 in year 2005.

Figure 3.38. Current direction rose plot for Station 42372 in year 2006.
46 

Figure 3.39. Current direction rose plot for Station 42372 in year 2007.

Station 42373 (Boomvang - East Breaks 643), Figures 3.40 - 3.42, is operated by Kerr-McGee 

Oil and Gas Corporation and located at 27.354 N 94.625 W in water depths of 1,113 m. The 

data only cover 104 to 597 m. The station is at the far west of the area. The flow direction is 

very persistent between 2005 and 2007: mostly northward, with much weaker secondary flow 

directions of various degrees. 

Figure 3.40. Current direction rose plot for Station 42373 in year 2005.
47 

Figure 3.41. Current direction rose plot for Station 42373 in year 2006. 

Figure 3.42. Current direction rose plot for Station 42373 in year 2007.

Station 42374 (Horn Mountain - Mississippi Canyon 126 and 127), Figures 3.43 – 3.45, is 

operated by BP, Inc. and located at 28.866 N 88.056 W, in water depths of 1646 m. The data 

only cover 45 to 541 m. The station is at the far east of the area. The flow direction varies a lot: 

although the 2005 data has northeast and northwest directions for the most part, the variation 
48 

covers the northern quadrants. The 2006 data is almost omnidirectional with slight preference to 

the northeast and southwest directions; whereas the 2007 data is more like bimodal with 

eastward and westward or southwestward preferences. There is a deeper ADCP at this site 

looking upward covering 1646 to 1150 m. The flow direction in 2005 is mostly southwestward, 

very different from the upper level condition (Figure 3.84 compared with Figure 3.81). 

Figure 3.43. Current direction rose plot for Station 42374 in year 2005.

Figure 3.44. Current direction rose plot for Station 42374 in year 2006.
49 

Figure 3.45. Current direction rose plot for Station 42374 in year 2007.

Station 42375 (Na Kika - Mississippi Canyon 474), Figures 3.46 – 3.48, is operated by BP, Inc. 

and located at 28.521 N 88.289 W in water depths of 1920 m. There are two ADCPs at this 

station. The data from the first ADCP cover 1912 to 1416 m (with the instrument looking 

upward). Data from the second ADCP cover depth from 48 to 992 m. These data display strong 

near-inertial oscillations and thus the flow direction is mostly omnidirectional with some 

preference perhaps as a result of superposition of larger-scale motions caused by the influence of 

Loop Current and eddies. The 2005 data is omnidirectional plus a southwestward emphasis. The 

2006 data is omnidirectional with westward, northwestward, and southwestward preferences. 

The 2007 data show more emphasis on the northeast, south, and west directions. Even though 

this station is close to Station 42374, their directionalities are somewhat different.
50 

Figure 3.46. Current direction rose plot for Station 42375 in year 2005.

Figure 3.47. Current direction rose plot for Station 42375 in year 2006.
51 

Figure 3.48. Current direction rose plot for Station 42375 in year 2007.

Station 42376 (Marlin - Viosca Knoll 915), Figures 3.49- 3.51, is operated by BP, Inc. and 

located at 29.108 N 87.944 W, in water depths of 986 m. The data from the ADCP cover 54 to 

984 m. This station is close to Station 42364 but covers deeper water and has different 

directional preferences. The majority of the data in 2005 shows a predominant direction of south 

and southwest. This is in contrast to the directionality of Station 42374 in 2005 (Figure 3.81). 

The other two years (2006 and 2007) show some similarity between data from Station 42374 and 

Station 42376. Station 42376 in 2006 shows almost omnidirectional except it lacks the southeast 

flow. The bimodal flow in 2007 at Station 42376 is much more similar to that at Station 42374. 
52 

Figure 3.49. Current direction rose plot for Station 42376 in year 2005.

Figure 3.50. Current direction rose plot for Station 42376 in year 2006.
53 

Figure 3.51. Current direction rose plot for Station 42376 in year 2007.

Station 42377 (Constitution - Green Canyon 680), Figures 3.52- 3.53, is operated by KerrMcGee Oil and Gas Corporation and located at 27.293 N 90.968 W, in water depths of 1524 m. 

The data cover 2006 and 2007 and between 69 and 999 m. The 2006 data shows bimodal 

directions – northeast and southwest. This is different from two nearby stations (42369 and 

42370, which are similar for 2006). The 2007 data also shows bimodal directions but with east 

and west preferences. This is also very different from the two nearby stations (42369 and 42370, 

which are different themselves for 2007). 
54 

Figure 3.52. Current direction rose plot for Station 42377 in year 2006.

Figure 3.53. Current direction rose plot for Station 42377 in year 2007.

Station 42379 (Marco Polo - Green Canyon 608), Figures 3.54 – 3.55, is operated by Anadarko 

Petroleum Corporation and located at 27.362 N 90.181 W, in water depths of 1286 m. The data 

cover 2006 and 2007 and between 1259 and 683 m (upward looking). This station is very close 

to Station 42369. The 2006 data shows an eastward–northeastward and some southeastward 
55 

preferences. Although this is somewhat different from 42369 and 42370, which are similar for 

2006, but these two other stations also have northeast and southeast preferences for 2006, the 

three stations have some similarities. The 2007 data shows directions from southwest to 

northwest. This covers some of the predominant directions of Station 42370. 

Figure 3.54. Current direction rose plot for Station 42379 in year 2006.

Figure 3.55. Current direction rose plot for Station 42379 in year 2007. 

57 

4. VERTICAL VARIATIONS OF HORIZONTAL VELOCITY

The previous chapter describes basic statistics of the flow velocity. Here we will examine the 

velocity time series as function of time and vertical position. Below we provide discussions of 

selected data, emphasizing their variability and other characteristics. Due to the large volume of 

data, these discussions are necessarily based on a few representative examples.

4.1 VELOCITY VECTORS FROM STATION 42361 IN 2005

As discussed in Chapter 3, Station 42361 (Auger - Garden Banks 426) is operated by Shell 

International E&P, located at 27.550 N 92.490 W in water depths of 872 m, covering between 51 

and 803 m below the surface. Note that the first data bins shown in the following figures are not

necessarily consistent with the actual first bin of the data. This is because of the QA/QC may 

take out some of the nearsurface data if the “percentage good” field is less than 75% value. The 

near-surface values are often times contaminated by the surface reflection of sidelobes of the 

ADCP signal, sidelobe effect, and are often excluded. The time series of the vertical profiles of 

the velocity vectors show quite large variations. For instance, the near-surface flow on May 1, 

2005 was southwestward. The flow appears to have a thickness of 350-400 m below the surface, 

although the flow magnitude decreases with depth (Figure 4.1). This appears to be quite 

consistent with what the satellite images reveal. Here we only mention a few variations related 

to the movement of the Loop Current that can be verified by the satellite images. We will not 

discuss changes of smaller magnitude.

From May 1, 2005, the near-surface flow decreases and on May 6 the thick layer of flow has 

decrease substantially (Figure 4.1). This is agrees with what satellite images suggest, although 

the satellite images do not show much of the details and there is not enough resolution to 

quantitatively compare with the in situ data. 

The vertical structure of the flow appears to suggest a few layers, each with its own 

characteristics. These layers however are changing with time and related features of flows can 

propagate upward and downward. The layered flows suggest that there are strong vertical shears 

of horizontal velocity at some levels during certain time periods. Strong velocity can also occur 

between layers: local maximum can be in the middle of a water column. 

After May 9, the near-surface flow started to increase again in the southwest direction. It then 

increased in a layer of up to 450 to 500 m below the surface. It is obvious that the daily 

oscillations are strong for most of the data. This appears to be near-inertial oscillation. On May 

11 and 12 there was a relatively strong deep water strong flow between 500 m and 770 m below 

the surface. The magnitude can be larger than 20 cm/s. The direction of the flow is mainly 

southward (Figure 4.2). During this time period, the Loop Current is quite strong. Its tip reached 

to relatively north and west, almost to 29N and 91W. On May 19, 2005, the Loop Current was 

still quite strong. 

The speed of the flow significantly decreased before June 9 (due to data gap we do not have flow 

data between May 21 and June 8. This speed reduction is apparently a result of the southward 

retreat of the tip of the Loop Current. The near-inertial oscillations are however still obvious. 
58 

Sometimes such oscillations (of roughly 24 hour period) are in a layer of the water column for 

some time. The thickness of the layer does not appear to be regular. Between June 9 and 13, 

there was a 5 day persistent daily oscillation between 500 and 600 meters. This oscillation 

appears to be propagating downward. From the way it varies over time, it is obvious that it has a 

clockwise rotation with time of the flow vector, although there was a mean flow going toward 

the north (Figure 4.3). During the last three days of this period, the flow below 625 m shows a 

southward flow, opposite of the upper layer flows. Between 500 and 700 m, the flow of June 18 

and 19 shows a relatively strong northward spike. It then gradually decreased even though the 

oscillation lasted for a few days. Between 250 and 450 m, there was a relatively strong and clear 

daily oscillation clearly propagated downward at a speed of about 200 m per day. 

Figure 4.1. Vertical profiles of horizontal velocity at Station 42361, May 1-10, 2005. 
59 

Figure 4.2. Vertical profiles of horizontal velocity at Station 42361, May 12-19, 2005.
60 

Figure 4.3. Vertical profiles of horizontal velocity at Station 42361, June 9-19, 2005.
61 

4.2 VELOCITY VECTORS FROM STATION 42363 IN 2005

Station 42363 (Mars - Mississippi Canyon 807) is 150 km east of Station 42362. This station is 

operated by Shell International E&P and located at 28.160 N 89.220 W, in water depths of 894 

m. The data cover almost the entire water column from 61 m below the surface. This is a place 

where the Loop Current sweeps through quite often. When this station is within the Loop 

Current, the flow velocity is very strong. Between May 13 and 23, 2005, there was first a strong 

southeastward or eastward before May 20, Figure 4.4. After May 20, the flow switched to 

northeastward until about June 29 when it decreased, Figure 4.5. It then increased again and 

changed to northward. It then decreased as the direction changed to northwestward. On June 10, 

the flow velocity magnitude had decreased to its minimum followed by a change of flow 

direction to southward on June 11 and June 12, Figure 4.6. Before June 13, the flow changed to 

northeast again followed by another change in flow direction for many days starting from June

16, Figure 4.7. This persistent southward flow started to increase its magnitude and another 

swing of flow direction on July 2, Figure 4.8, when the flow started to become southeastward. 

This strong flow lasted until August 10 when it decreased significantly.

Figure 4.4. Vertical profiles of horizontal velocity at Station 42363, May 13-23, 2005.
62 

Figure 4.5. Vertical profiles of horizontal velocity at Station 42363, May 24-June 2, 2005.
63 

Figure 4.6. Vertical profiles of horizontal velocity at Station 42363, June 3-12, 2005.
64 

Figure 4.7. Vertical profiles of horizontal velocity at Station 42363, June 13-22, 2005.
65 

Figure 4.8. Vertical profiles of horizontal velocity at Station 42363, June 23-July 2, 2005.
66 

4.3 VELOCITY VECTORS FOR STATION 42366 IN 2005

Station 42366 (Red Hawk - Garden Banks 877) is operated by Kerr-McGee Oil and Gas 

Corporation at 27.122 N 91.959 W, southeast of Station 42361 by more than 50 km. The water 

depth at this station is 1615 m. 

The May 2005 data showed oscillations between northward and southward flows until early 

September, when the flow magnitude started to increase in the southeast direction for about a 

month. This is the time when the Loop Current was deforming, extending to the west, and 

developing an eddy that eventually separated from the Loop Current. The separated anti-cyclonic 

eddy subsequently moved to the west. 

4.4 VELOCITY VECTORS FOR STATION 42368 IN 2005

Station 42368 (Magnolia - Garden Banks 783) is operated by ConocoPhillips at 27.204 N 92.203 

W in water depths of 1424 m. It is about 20 km west-northwest of Station 42366. The flow 

however is very different from that nearby station. At this station, the flow is mostly toward the 

southern quadrants (southwesterly directed but with secondary directions such as south and 

northwest. The difference between Stations 42366 and 42368 is partly due to the difference in 

data coverage in the vertical. Station 42366 covers the vertical from 115 to 610 m, while Station 

42368 covers between 67 and 1123 m. 

At this station, there was a persistent southerly flow from mid-May until mid-June of 2005, 

during which the velocity profile was quite consistent throughout the lower 1000 m of the water 

column. Daily variations are very obvious, suggesting strong near inertial oscillations. The NIO, 

however, are smaller than the mean southerly flow such that the overall flow was in the same 

direction. For a few days in mid-June (June 14 – 18), the near-surface flow reversed direction. A 

few days before this time period, the vertical profiles started to show some variations and vertical 

propagation of the NIO. While the wave form propagates upward, the energy propagates 

downward. During this time period, the near-bottom flow also appeared to have reversed its 

direction from mid-June to late June (June 12-26). Mid-depth reversal of flow also occurred 

during June 26 and July 2 between 650 and 1000 m, with apparent upward propagation of the 

NIO at a rate of about 300 m/day. Throughout much of July, the flow becomes southern again all 

the way to the bottom, with a decrease in magnitude downward. The data has a long gap until 

Dec. 9, 2005. From Dec. 9 (when measurements resumed) to Dec. 23, 2005 (when measurements 

stopped) the flow was southerly with some more randomness (noisier than the summer data). 

4.5 VELOCITY VECTORS FOR STATION 42370 IN 2005

Station 42370 (Holstein - Green Canyon 645) is operated by BP, Inc., at 27.321 N 90.536 W in

water depths of 1311 m. The data covered 62 to 992 m. This station had two ADCPs in 2005. 

The data from 2005 covered from May 5 to August 3 for the upper level ADCP. From August 4 

to Sept. 20, the top level ADCP only covered down to 250 m. The lower level ADCP covered 

most of 2005 with some minor gaps. Because of the proximity of this station to station 42369, 

the flow patterns and variations at both stations are more or less similar. 
67 

The flow started with roughly a northerly direction (similar to Station 42369) and an increasing

trend that peaked in May 13, instead of May 12. This change coincided with a westward bulging 

of the Loop Current over this station. 

Obviously, Station 42370 had about a one-day time lag compared to Station 42369. The flow 

then became southerly gradually. At this location, it appears to be from the mid-depth upward, 

i.e. there was an upward vertical propagation of the southerly flow as early as May 7 at 1300 m 

depth. By May 14, the southerly flow was at about 1000 m. By May 20th, the southerly flow had 

risen to 650 m, and by May 23, the southerly flow reached the surface. Daily oscillations are 

again imbedded in the predominant flow signal. This southerly flow lasted until June 4 when the 

flow started to reverse again to northward. This flow lasted pretty much unchanged (only minor 

changes) until June 25 when the flow speed increased rapidly. When this happened, there was a 

downward propagation of the speed increase. It was then followed by an upward propagation of 

the speed reduction, which was mostly flowing toward the northern quadrants. In the lower 

layer, there was a downward propagation of the near inertial oscillation. From June 28 to 30, 

there appears to be a strong reversed flow at the deep lower layer. The near-surface flow wax and 

wane but remained significantly high (> 50 cm/s) for much of the time until the end of August 

and early September. Again, this dramatic and lasting speed increase resulted from the large 

bulge of the Loop Current attempting to separate and becoming an eddy. The strong flow was 

mostly northeastward. A big anti-cyclonic eddy finally detached from the Loop Current on 

September 29. The lower layer ADCP continued to show near inertial oscillations with vertical 

propagation of the daily variations. 

4.6 VELOCITY VECTORS FROM STATION 42373

Station 42373 (Boomvang - East Breaks 643) is operated by Kerr-McGee Oil and Gas 

Corporation at 27.354 N 94.625 W, in water depths of 1113 m. The station is at the far west end 

of the study area. Two ADCPs operated at this station; the first ADCP cover 104 to 597 m and 

the second unit cover from about 550 to near bottom. Data from the upper ADCP spanned from 

August 20 to December 10 with a few short gaps lasting a few days each. Data from the second 

ADCP covered from October 28 until the year’s end. 

Between August 20 and 29 of 2005 the flow was strong and southerly from 100 to 250 m. 

Between 250 and 400 m vertical propagation of near inertial oscillation was observed. The 

upward propagation was about 200 m per day. Below 400 m, the near-inertial oscillations 

seemed to be vertically uniform. After August 29, the strong southerly flow was replaced by 

northward flow throughout the entire water column. There may be a downward phase 

propagation of near-inertial oscillation between 300 and 400 m and between Sept. 2 and 3. 

Measurements stopped on September 6 and resumed October 28, 2005. The flow velocity varied 

in direction and magnitude along the vertical such that the flow direction reversed along the 

water column. For example, between October 28 and November 7, the velocity between 100 and 

350 m had a persistent strong southerly flow. This flow either decreased in speed or even 

reversed direction below 400 to 450 m. The northerly flow in the deep water then increased its

speed between 600 m and near the bottom. Vertical propagation of phase occurred but the most 

obvious one was between 600 and 900 m during November3 and 6, and between 250 to 450 m 

during November 1 and 4. The upper layer flow reversed its direction again on November 6 

when some of the deep water velocity reversed direction for 3 days (600 – 800 m on Nov. 6-9) or 
68 

4 days (750 m, on November 10-14). The near-surface northerly flow peaked before November

18 followed by a sudden reversal of the flow on November 20 throughout the entire water 

column vertical phase propagation can be seen at places. Upward propagation can be seen 

between 700 and 1050 m to be at about 700 m in 12 hours. This southerly flow started to reverse 

from the bottom. This near-bottom reversal kept below 600 m till December 12 after which the 

water column was once again occupied by southerly flows throughout the bottom layer for 2-3 

days before we see once again some near-bottom reversal (northerly flow) during which 

(December 15-16) the lower layer southerly flow is strengthened for a few days, until December

18 when a strong northeasterly developed which subsequently decreased in magnitude. 

4.7. VELOCITY VECTORS FROM STATION 42374

Station 42374 (Horn Mountain - Mississippi Canyon 126 and 127) is operated by BP, Inc., at 

28.866 N 88.056 W, in water depths of 1646 m. There were two ADCPs at this site; the first 

ADCP covered 45 to 541 m. The deeper ADCP was looking upward covering 1646 to 1150 m. 

This station is at the far east of the area.

The 2005 data covered from June 29 until the year’s end for the lower level, while the upper 

ADCP data ended after August 28. Before June 29 and July 10, 2005, the upper layer (0 – 350 

m) was dominated by a northerly flow. The bottom layer velocity was weak from June 29 to

July 7. While the surface flow started to change from northward to westward with strong vertical 

shear on July 12, the lower layer flow reversed direction and increased its speed. A strong lower 

layer flow reversal occurred again on July 14. The strong flows were all quite uniform from 

1150 to 1600 m. The lower layer flow then turned to southwestward. A northward flow 

developed from the bottom on July 19 which expanded from 1600 m to 1250 m, two or three 

days later. A near-inertial oscillation was seen on July 23, 2005, near the bottom and 

propagating upward in about 5 days, with strong southerly flows. This oscillation lasted until 

August 1. 
69 

5. DEEP WATER OSCILLATIONS UNDER NORMAL AND EXTREME 

WEATHER

Near-Inertial Oscillations (NIOs) in the deep ocean are motions initiated by external forcing such 

as winds and under the influence of earth rotation (e.g. Gill, 1982; Apel, 1988). The NIOs can be 

viewed as Poincare waves regardless of whether they are internal (baroclinic) or external 

(barotropic) (Gill, 1982). A major feature of this kind of motion is that the two velocity 

components, u and v are close in magnitude and the particles’ trajectories are almost circular, 

rotating clockwise (counter-clockwise) in the northern (southern) hemisphere. Under ideal 

conditions, inertial oscillations propagate vertically without a horizontal wave number 

component (Gill, 1982; Alpel 1988). In the northern Gulf of Mexico, the NIOs are particularly 

strong because the inertial frequencies are close to those of the diurnal tides, and thus resonance 

tends to occur (e.g. Chen et al., 1996; Hamilton, 1990; Nowlin et al., 2004). Tides in the deep 

ocean are usually very small, but they are amplified in shallow waters. In the northern Gulf, 

separating diurnal tides from NIOs may require a relatively long time series because of the 

proximity of the frequencies which depend on the latitude. 

The study of NIOs has a long history. Pollard (1970) proposed a modified model of Veronis 

(1956) for the ocean response to a transient wind stress, in which a continuous stratification is 

added. The wind-generated NIOs appear to decrease with depth rapidly. However, the amount of 

energy transferred to NIOs does not really depend on the stratification and the horizontal scale of 

the wind but rather on the transient nature or the temporal variation of wind forcing, which is 

found to be responsible for both generating and destroying the NIOs. The model of Pollard 

(1970) cannot explain the deeper water NIOs because the force applied to the model is rather 

peculiar: the wind stress is applied as a body force that is non-zero only within the mixed layer. 

In a study with observations (Schott, 1970), data from instruments on four moorings are 

analyzed: three of the moorings form an equilateral triangle with 4.5 km on each side, around the 

fourth mooring. Temperature and currents are measured for about 13 days at depths between 18 

and 70 m. The NIO is out of phase between upper and lower layers. The inertial temperature 

variations are in phase throughout the thermocline. Perkins (1972) shows that, with 

measurements at five depths between 200 and 2200 m at 500 m intervals, the NIO frequency is 

3% higher than the local inertial frequency. The velocity magnitudes are 2-12 cm/s at 200 m, less 

than 5 cm/s at 700 m, less than 3 cm/s at 1200 m, and 2-3 cm/s at 2200 m. The model of Kroll 

(1975) uses an arbitrarily stratified β-plane model with a viscous boundary layer at the surface 

and an inviscid interior to determine the NIOs in deep water. The wind produces Ekman suction 

in the surface boundary layer and NIO propagates into the interior. Perkins (1976) tries to 

explain the observation of two peaks around the local inertial frequency by the existence of an 

anticyclonic eddy which can cause the shift in the frequency peaks from the local inertial 

frequency. A simple expression of the new frequency is 

fe = �f(f + ζ)

where ζ is the vertical component of the relative vorticity due to advection, and is non-zero for 

an eddy. This can be verified by the dispersion relationship when the nonlinear advection is 
70 

included for a mean flow. Some studies use a slightly different expression for fe, e.g. (Kunze, 

1985) 

fe = f + ζ/2

which is a commonly used form and essentially the same as the first equation above when

relative vorticity is “small”. However fe = �f(f + ζ) is more general and does not require that 

that vorticity be small. An even more general form is fe = �f(f + ζ) + δ in which δ is a 

“higher order” term consisting of velocity gradients. This can be readily shown by the dispersion 

relationship when the advective acceleration is included by only considering the importance of 

the mean flow: the nonlinear terms due to perturbation of the mean flow are all considered 

negligible. The formula by Mooers (1975) is very similar, i.e. fe = �f(f + vx) , here the cross 

stream flow shear for a long straight jet is used in place of the more general vorticity term.

Weller (1982) also confirms that vorticity in quasi-geostrophic flow shifts the frequency to either 

larger or smaller values than the local inertial frequency. In a simple barotropic model, Pollard 

and Millard (1970) show realistic-looking NIOs in the surface layer with large depth. Similar 

models are used to produce results that match observations reasonably well (e.g. Chen et al., 

1996). Though many studies have found that the NIOs are surface- or sub-surface intensified 

(e.g. Chen, 1996; Qi et al., 1995; D’Asaro et al., 1995; D’Asaro, 1995; Tintore et al., 1995), or 

with a 180-degree phase shift in surface and lower layers, some studies also show highly 

coherent oscillations throughout the water column, e.g. Brooks (1983) show such characteristics 

in a depth of 732 m using sensors deployed 200 m below the surface and 32 m above the bottom. 

Numerous numerical model studies of NIOs have also been conducted throughout the last decade 

(e.g. Chen et al., 1996; Xing and Davies, 2004a,b, 2005). 

Gill (1984) provides a frictionless, baroclinic model showing the vertical propagation of internal 

waves caused by storms. The barotropic flow was found weak. However, this conclusion was 

based on an assumption that the surface slope was too small compared to the interface 

displacements such that the rigid lid approximation would hold. This, however, can be

problematic because the rigid lid approximation effectively filters out all surface gravity 

(barotropic shallow water) waves that have an immediate response at the bottom. The baroclinic 

motion shows a very long time scale (several days to 150 days) for the propagation of the storminduced inertial waves to transfer to the bottom of the ocean. Observations show that the deep 

water inertial oscillations are almost instantaneous, right after the passage of the storm. This is 

quite contradictory and also indicates that the use of a rigid lid approximation may not be 

appropriate for the problems. In this chapter, we will examine the NIOs in the GoM under 

normal and extreme weather conditions especially immediately following three major hurricanes 

of 2005. In the analysis, we will present an analytic barotropic model and a Laplace Transform 

method to demonstrate the response of the ocean to surface atmospheric forcing and the 

dependence on water depth.

5.1 NEAR INERTIAL OSCILLATIONS UNDER NON-SEVERE WEATHER CONDITIONS

As we have seen in previous chapters that near-inertial oscillations are very common in the 

ADCP record. The difference between NIOs and ocean tide is that the former depends on local 
71 

inertial frequency (function of latitude) and external forcing which is much less predictable than

tides. As a result, NIOs happen randomly with largely variable magnitude that is also not 

predictable. This can be seen clearly from our data. It should be noted that most NIOs exist with 

background flows varying mostly at much lower frequencies.

Figures 5.1.1 through 5.1.10 are examples of time series plots of the north and east components 

of velocity at the very first bin of the velocity profile, usually a point closet to the surface of the 

ocean. These are randomly selected and they are representative of the variations of velocity 

components of the entire dataset. Despite the wide range of variability, there are some common 

features that are worth mentioning. The first of which is the variation at roughly daily period. 

This daily period variation appears to be quite irregular in terms of the magnitude. This appears 

to be mainly due to a larger irregular magnitude low-frequency variation which can be a result of 

eddies, Loop Current, and other background low frequency circulation. Another feature is that 

the north and east components have similar magnitudes. Clearly, this indicates that these daily 

oscillations are inertial oscillations. This can be verified by rotary spectrum analysis (which is 

presented later). It should also be noted that the NIOs are always excited by an external forcing, 

whether wind stress, atmospheric pressure gradient, or a water pressure gradient due to waves or 

other distances. The data suggests that the disturbances may be quite frequent; otherwise, the 

oscillations wouldn’t be so common. It is not the objective of this project to identify each of 

these external forcing for all the NIOs in this dataset. Nor is it realistic to do that. However, we 

can verify and examine NIOs after major hurricanes, which is the subject of the next sub-section. 

In 2005, there were several tropical storms and hurricanes, see Figure 5.1.11 They are (1) 

Tropical Storm Arlene, which landed on Jun 11 at 5:00PM, at 30.7 N, 87.4 W, (2) Tropical 

Storm Cindy which made landfall on July 5 2005 at 11:00PM, at 29.0 N, 90.1 W, 60; (3) 

Hurricane Dennis which made landfall at 5 PM on July 10 at 30.8 N, 87.2 W; (4) Hurricane 

Emily, which made landfall at 5 PM on July 20 at 24.7 N, 97.2 W; (5) Hurricane Katrina, which 

made landfall at 5 AM on Aug 29 at 28.8 N, 89.6 W, and (6) Hurricane Rita which made landfall 

at 5 AM on Sep 24 at 29.9 N, 93.9 W. These landfall times correspond to Julian days of 2005 

(Jan. 1 is Day 1) of 162, 186, 191, 202, 241, and 267, respectively. When the tropical storms 

come close to a station, the record may show increased NIOs. For example, Figure 5.1.3 shows 

that when Tropical Storm Cindy passed, before Day 186, NIO started to increase. Figure 5.1.8 

shows that when Hurricane Rita passed, before Day 267, NIO started to increase as well. These 

NIOs appear to be mixed with the normal condition NIOs and did not seem to show much 

difference except some increase in oscillation magnitude. More detailed examination for stations 

with stronger response will be given later. 
72 

Figure 5.1.1. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42361. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

Figure 5.1.2. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42361. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

120 122 124 126 128 130 132 134 136 138 140

-50

-40

-30

-20

-10

0

Station 42361, 2005

Time (days) in 2005

East Velocity

120 122 124 126 128 130 132 134 136 138 140

-20

-10

0

10

20

30

Station 42361, 2005

Time (days) in 2005

North Velocity

160 165 170 175 180 185 190

-20

-10

0

10

20

Station 42361, 2005

Time (days) in 2005

East Velocity

160 165 170 175 180 185 190

-20

-10

0

10

20

Station 42361, 2005

Time (days) in 2005

North Velocity
73 

Figure 5.1.3. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42363. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

Figure 5.1.4. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42363. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

130 140 150 160 170 180

-50

0

50

100

Station 42363, 2005

Time (days) in 2005

East Velocity

130 140 150 160 170 180

-100

-50

0

50

Station 42363, 2005

Time (days) in 2005

North Velocity

205 210 215 220 225 230 235

0

50

100

Station 42363, 2005

Time (days) in 2005

East Velocity

205 210 215 220 225 230 235

-100

-50

0

Station 42363, 2005

Time (days) in 2005

North Velocity
74 

Figure 5.1.5. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42365. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

Figure 5.1.6. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42365. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

120 130 140 150 160 170 180

-50

0

50

100

150

Station 42365, 2005

Time (days) in 2005

East Velocity

120 130 140 150 160 170 180

-50

0

50

100

150

Station 42365, 2005

Time (days) in 2005

North Velocity

180 190 200 210 220 230 240

-50

0

50

100

150

Station 42365, 2005

Time (days) in 2005

East Velocity

180 190 200 210 220 230 240

-60

-40

-20

0

20

Station 42365, 2005

Time (days) in 2005

North Velocity
75 

Figure 5.1.7. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42366. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

Figure 5.1.8. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42366. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

135 140 145 150 155 160 165 170 175 180

-40

-20

0

20

40

Station 42366, 2005

Time (days) in 2005

East Velocity

135 140 145 150 155 160 165 170 175 180

-40

-20

0

20

40

Station 42366, 2005

Time (days) in 2005

North Velocity

180 185 190 195 200 205 210 215

-20

-10

0

10

20

Station 42366, 2005

Time (days) in 2005

East Velocity

180 185 190 195 200 205 210 215

-20

-10

0

10

20

Station 42366, 2005

Time (days) in 2005

North Velocity
76 

Figure 5.1.9. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42361. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

Figure 5.1.10. Time series of the eastward (upper panel) and northward (lower panel) velocity 

components in 2005 at Station 42367. Horizontal axis is Julian time with day 1 

equals January 1, 2005. 

260 262 264 266 268 270 272 274 276 278 280 282

0

20

40

60

Station 42366, 2005

Time (days) in 2005

East Velocity

260 262 264 266 268 270 272 274 276 278 280 282

-80

-60

-40

-20

0

20

Station 42366, 2005

Time (days) in 2005

North Velocity

5 10 15 20 25 30

-20

0

20

Station 42367, June 2005

Time (days) in June

East Velocity

5 10 15 20 25 30

-40

-20

0

20

40

Station 42367, June 2005

Time (days) in June

North Velocity
77 

Figure 5.1.11. The 2005 hurricane and tropical storm tracks for (1) Tropical Storm Arlene, (2) 

Tropical Storm Cindy, (3) Hurricane Dennis, (4) Hurricane Emily, (5) Hurricane 

Katrina, and (6) Hurricane Rita.

Figures 5.1.12-5.1.40 show some examples of progressive vector diagrams for May 2006. These 

plots provide a different view point for the NIOs, their temporal (from time to time) and 

horizontal spatial variability (from station to station), and vertical variations. 

Figure 5.1.12 shows progressive vector diagram plot for Station 42361 at various vertical 

locations in May of 2006. It should be noted that all the “trajectories” start from the origin of the 

coordinate, i.e. (0, 0) – this makes it easy to identify where the “trajectory” starts and where it is 

moving. It is clear that the flows at different levels appear to be similar but with some variations 

such that over time, the “trajectories” are separated. This indicates strong vertical shears and 

perhaps also layered flows in which different layers behave differently. To better view this, we 

zoom in and plotted the progressive vector diagram at a few depths for improved resolution 

(Figure 5.1.13). The top bin was at 51 m below the surface. The next selected bin was at 195 m 

below the surface, which showed quite similar flow 144 m above but with a reduced magnitude – 

the flows at the two levels appear to have same directions but with a reduced magnitude 

downward such that the progressive vectors appear to be rough parallel to each other. The next 

selected vertical location for the plot was at 355 m below the surface and it shows much different 
78 

“trajectory”, suggestion that we are looking at a different layer. The last selected vertical location 

is at 515 m below the surface and had opposite flow directions at times. To further examine how 

the water particles moved in the top layer, we further zoom in and selected 6 vertical locations 

about 131 m (Figure 5.1.14). The selected vertical levels are 51, 67, 83, 99, 115, and 131 m, 

respectively. This gives an amazing picture of vertical variation of flow condition that is roughly 

consistent with the surface boundary layer Ekman spiral. On top of the long term “trajectories”, 

it is also equally striking to see the NIOs (in a clockwise direction). 

Figure 5.1.15 shows progressive vector diagram plot for Station 42364 at various vertical 

locations in May of 2006. Again, the flows at different levels appear to be similar for some 

vertical positions but with some variations such that over time, the “trajectories” are separated. 

This indicates strong vertical shears and perhaps also layered flows in which different layers 

behave differently. To better view this, we zoom in and plotted the progressive vector diagram at 

a few depths to improved resolution (Figure 5.1.16). The top bin was at 51 m below the surface. 

The next selected bin was at 195 m below the surface. Differences are obvious between the 144 

m levels in addition to being with a reduced magnitude downward although the progressive

vectors appear to be roughly parallel to each other. The next selected vertical location for the plot 

was at 355 m below the surface and it shows a similar “trajectory” in direction. The last selected 

depth was 515 m below the surface and had very different trajectory. 

Figure 5.1.17 shows progressive vector diagram plot for Station 42368 at various vertical 

locations in May of 2006. It is clear that the flows at different levels appear to be similar but 

with some variations such that over time, the “trajectories” are separated. This again indicates 

some vertical shears and perhaps also layered flows in which different layers behave differently. 

To better view this, we zoom in and plotted the progressive vector at a few depths to improved 

resolution (Figure 5.1.18). The top bin was at 51 m below the surface. The next selected bin was 

at 67 m below the surface, which showed quite similar flow. The next levels are 83, 99, 115, and 

131 m below the surface, respectively. This again gives an amazing picture of vertical variation 

of flow condition that is roughly consistent with the surface boundary layer Ekman spiral. On top 

of the long term “trajectories”, it is also equally striking to see the NIOs (in a clockwise 

direction). These features are remarkably similar to those shown earlier in Figures 5.1.12 and 

5.1.13 for Station 42361. By consulting the locations of these stations, we know that they are 

very close geographically (about 50 km apart), so is no surprise that the vertical structure of the 

flow is similar. 

Figure 5.1.19 shows progressive vector diagram plot for Station 42375 at various vertical 

locations in May of 2006. It is clear that the flows at different levels appear to be very similar 

but with a decrease of flow magnitude with depth such that over time, the “trajectories” are 

separated. This indicates strong vertical shears and but no apparent layered flows such that 

different layers behave differently (e.g. with opposite flow directions, which does not appear 

here). To better view this, we zoom in and plotted the progressive vector at a few depths to

improved resolution (Figure 5.1.20). The top bin was at 48.1 m below the surface. The next 

selected bin was at 192.1 m below the surface, which showed similar flow more than 140 m 

above but with a reduced magnitude – the flows at the two levels appear to have same directions 

but with a reduced magnitude downward such that the progressive vectors appear to be rough 

parallel to each other. The next selected vertical location for the plot was at 352.1 m below the 
79 

surface and it still shows similar “trajectory”, suggesting that we are still looking at the same 

layer. The last selected vertical location is at 512.1 m below the surface and still has the same 

flow directions for the entire time period. The overall flow is toward northeast first and then turn 

southeast, with the entire top water column (surface to 500 m). It is interesting to note that the 

flow at different levels was first quite uniform and then strong shear showed during the latter 

portion of the data. 

Figure 5.1.21 shows progressive vector diagram plot for Station 42863 at various vertical 

locations in May of 2006. Again, the flows at different levels appear to be very similar with 

some indication of a decrease of flow magnitude with depth. Over time, the “trajectories” are 

separated. The overall flow seemed to be mostly eastward first and then turned to the northwest. 

To better show this, we zoom in and plotted the progressive vectors at selected depths to 

improved resolution (Figure 5.1.22). The top bin was at 73.3 m below the surface. The next 

selected bin was at 361.3 m below the surface. The next selected vertical location for the plot 

was at 681.3 m below the surface. The last selected vertical location is at 1001.3 m below the 

surface. Again, and indeed, this is amazing to have the entire water column to move together. 

This suggests that the motion is probably not local wind-driven. It may have been a result of 

much larger scale atmospheric forcing or large scale oceanic process (Loop Current and eddies) 

or the oscillation within the Gulf of Mexico. These are speculations not even hypothesis but 

more analysis is needed for a holistic picture of the underlining dynamics. 

Figure 5.1.23 shows progressive vector diagram plot for Station 42865 at various vertical 

locations in May of 2006. It is clear that the flows at different levels appear to be very similar 

but with a decrease of flow magnitude with depth such that over time, the “trajectories” are 

separated. However, they kept being parallel to each other. This indicates vertical shears but with 

no apparent layered of flows going in different directions. To better view this, we zoomed in and 

plotted the progressive vectors at a few selected depths to improved resolution (Figure 5.1.24). 

The top bin was at 67 m below the surface. The next selected bin was at 355 m below the 

surface. The last selected vertical location is at 675 m below the surface and still has the same 

flow directions for the entire time period. No NIOs are obvious for this station during this time 

period. 

Figure 5.1.25 shows progressive vector diagram plot for Station 42869 at various vertical 

locations in May of 2006. The flows at different levels appear to be similar and with a decrease 

of flow magnitude. Again, as at the previous station, they kept being parallel to each other. This 

indicates vertical shears but with no apparent layered of flows going in different directions. The 

decrease of the flows, as in other cases, must be due to frictional effect. To better view this, we 

zoomed in and plotted the progressive vectors at a few selected depths to improved resolution 

(Figure 5.1.26). The top bin was at 52.9 m below the surface. The next selected bin was at 196.9 

m below the surface. The last two selected vertical locations are at 356.9 and 516.9 m below the 

surface, respectively. Overall, they are very consistent (perhaps the most vertically consistent 

flow example) along the same flow directions for the entire time period. The flow throughout 

the entire 500 water column was moving northeastward, and then westward, then northward, and 

final westward again. All levels exhibit this same pattern. No NIOs are obvious for the entire 

record at this station during this time period. 
80 

Figure 5.1.27 shows progressive vector diagram plot for Station 42873 at various vertical 

locations in May of 2006. The flows at different levels appear to be mostly similar and with a 

decrease of flow magnitude. In addition, there seems to be a veering of the flow direction 

toward the right as the flow decreases during the early period of the record. This is consistent 

with an upper layer surface boundary layer Ekman Spiral. To better view this plot, we zoom in 

(Figure 5.1.28). Now we can see quite a lot of NIOs, perhaps throughout the water column. We 

further selected a few depths and re-plotted the progressive vectors in Figure 5.1.29. Over the 

1000 m water column, the flow varied quite a lot – perhaps the most variable flow compared to 

the other stations discussed earlier. 

Figure 5.1.30 shows progressive vector diagram plot for Station 42875 at various vertical 

locations in May of 2006. The flows at different levels appear to be similar and with a decrease 

of flow magnitude. In addition, there seems to be a veering of the flow direction toward the right 

as the flow decreases during the early period of the record. This is consistent with an upper layer 

surface boundary layer Ekman Spiral. Overall, during the entire the record, the flow is consistent 

in direction at all levels (all going southeast). To better view this plot, we zoom in (Figure 

5.1.31). Now we can see quite a lot of NIOs. We further selected a few vertical locations and replotted the progressive vectors in Figure 5.1.32. The top bin was at 57 m below the surface. The 

next selected bin was at 201 m below the surface. The last two selected vertical locations are at 

361 and 521 m below the surface, respectively. No NIOs are obvious for these levels, indicating 

that the NIOs are all at deeper levels.

Figure 5.1.33 shows a progressive vector diagram plot for Station 42880 at various vertical 

locations in May of 2006. The flows at different levels appear to be bi-modal – one goes toward 

the east, one to the west, northwest or north. In addition, there are no observable NIOs. To better 

view this plot, we zoomed in (Figure 5.1.34). Now we can see the NIOs clearly but the mean 

flows have opposite directions. We further selected a few depths and re-plotted the progressive 

vectors in Figure 5.1.35. The top bin was at 62.5 m below the surface. The next selected bin was 

at 206.5 m below the surface, which shows consistent direction with the upper level for the early 

time but much smaller magnitude. The last two selected vertical locations are at 366.5 and 526.5 

m below the surface, respectively. Some NIOs are observable. The flow directions of the last 

two layers are about 90 degrees different from the first two levels. Down to the last level, the 

selected levels still do not show the flow opposite of the upper levels, i.e. the westward flow 

levels must be at lower levels. So in this case, we see three entirely different vertical layers: the 

upper layer, middle layer, and bottom layer, all going in different directions. 

Figure 5.1.36 shows progressive vector diagram plot for Station 42881 at various vertical 

locations in May of 2006. The flows at different levels appear to be very similar and with a 

decrease of flow magnitude. In addition, there is a veering of the flow direction toward the right 

as the flow decreases during the early period of the record. This is consistent with an upper layer 

surface boundary layer Ekman Spiral. During the latter portion of the record, the flows are 

consistent in directions such that they mostly go to the east and then southeast. To better view 

this plot, we zoom in (Figure 5.1.37). There is no obvious NIOs except at what appears to be 

lower levels (where flow magnitude reduced so the lines shorter). We further selected a few 

vertical locations and re-plotted the progressive vectors in Figure 5.1.38. The top bin was at 72.9 

m below the surface. The next selected bin was at 360.9 m below the surface. It can be seen that 
81 

the flow direction has a right veering tendency. This right veering and decrease in magnitude 

extended toward the lower layer as well at 680.9 and 1000.9 m, respectively. 

Figure 5.1.39 shows a zoomed in progressive vector diagram plot for Station 42884 at various 

vertical locations in May of 2006. The flows at different levels appear to be quite persistent, 

mostly in the east and west directions. To better view this plot, we selected a few depths and 

zoomed in (Figure 5.1.40). The top bin was at 42.7 m below the surface. The next selected bin 

was at 186.7 m below the surface. The last two selected depths were at 346.7 and 506.7 m below 

the surface. The near-surface flow was southward all the time, while the rest moved westward 

first and then eastward and then northward. 

Figure 5.1.12. Progressive vector diagram at different depths for May 2006 at Station 42361. 

-150 -100 -50 0 50 100 150 200

-60

-40

-20

0

20

40

60

Displacement-A42361.05.2006

x (km)

y (km)
82 

Figure 5.1.13. Progressive vector diagram at Station 42361 for different depths in May 2006. 

Figure 5.1.14. Progressive vector diagram at Station 42361 focusing in shallow depths in May 

2006. 

-100 -50 0 50 100 150 200

-50

-40

-30

-20

-10

0

10

20

30

40

Displacement-A42361.05.2006

x (km)

y (km)

51

195

355

515

0 10 20 30 40 50 60

-50

-40

-30

-20

-10

0

10

Displacement-A42361.05.2006

x (km)

y (km)

51

67

83

99

115

131
83 

Figure 5.1.15. Progressive vector diagram at different depths for May 2006 at Station 42364. 

Figure 5.1.16. Progressive vector diagram at Station 42364 for different depths in May 2006.

-40 -30 -20 -10 0 10 20 30

-25

-20

-15

-10

-5

0

5

10

15

20

Displacement-A42364.05.2006

x (km)

y (km)

-5 0 5 10 15 20 25

-8

-6

-4

-2

0

2

4

6

8

10

Displacement-A42364.05.2006

x (km)

y (km)

51.1

195.1

355.1

515.1
84 

Figure 5.1.17. Progressive vector diagram at different depths for May 2006 at Station 42368.

Figure 5.1.18. Progressive vector diagram at selected depths for May 2006 at Station 42368. 

-150 -100 -50 0 50 100 150 200

-60

-40

-20

0

20

40

60

Displacement-A42368.05.2006

x (km)

y (km)

-5 0 5 10 15 20 25 30 35 40 45 50

-40

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

Displacement-A42368.05.2006

x (km)

y (km)

51

67

83

99

115

131
85 

Figure 5.1.19. Progressive vector diagram at different depths for May 2006 at Station 42375.

Figure 5.1.20. Progressive vector diagram at selected depths for May 2006 at Station 42375. 

-100 0 100 200 300 400 500 600 700 800 900

-50

0

50

100

150

200

250

Displacement-A42375.05.2006

x (km)

y (km)

-100 0 100 200 300 400 500 600 700 800 900

0

50

100

150

200

250

Displacement-A42375.05.2006

x (km)

y (km)

48.1

192.1

352.1

512.1
86 

Figure 5.1.21. Progressive vector diagram at different depths for May 2006 at Station 42863.

Figure 5.1.22. Progressive vector diagram at selected depths at Station 42863 in May 2006 

zooming in to show the NIOs. 

-100 -80 -60 -40 -20 0 20 40 60 80

-100

0

100

200

300

400

500

600

700

800

Displacement-A42863.05.2006

x (km)

y (km)

-80 -60 -40 -20 0 20 40 60 80

-100

0

100

200

300

400

500

600

700

800

Displacement-A42863.05.2006

x (km)

y (km)

73.3

361.3

681.3

1001.3
87 

Figure 5.1.23. Progressive vector diagram at different depths for May 2006 at Station 42865.

Figure 5.1.24. Progressive vector diagram at selected depths for May 2006 at Station 42865 

zooming to show NIO. 

-1000 -800 -600 -400 -200 0 200

-400

-300

-200

-100

0

100

200

300

400

500

600

Displacement-A42865.05.2006

x (km)

y (km)

-1000 -800 -600 -400 -200 0 200

-300

-200

-100

0

100

200

300

400

500

600

Displacement-A42865.05.2006

x (km)

y (km)

67

355

675

995
88 

Figure 5.1.25. Progressive vector diagram at different depths for May 2006 at Station 42869.

Figure 5.1.26. Progressive vector diagram at selected depths for May 2006 at Station 42869 

zooming to show NIO. 

-700 -600 -500 -400 -300 -200 -100 0 100

0

200

400

600

800

1000

1200

1400

Displacement-A42869.05.2006

x (km)

y (km)

-600 -500 -400 -300 -200 -100 0 100

0

200

400

600

800

1000

1200

1400

Displacement-A42869.05.2006

x (km)

y (km)

52.9

196.9

356.9

516.9
89 

Figure 5.1.27. Progressive vector diagram at different depths for May 2006 at Station 42873.

Figure 5.1.28. Progressive vector diagram enlarged at different depths for May 2006 at Station 

42873. 

-100 0 100 200 300 400 500

-60

-40

-20

0

20

40

60

80

100

120

Displacement-A42873.05.2006

x (km)

y (km)

-30 -20 -10 0 10 20 30

-30

-20

-10

0

10

20

30

Displacement-A42873.05.2006

x (km)

y (km)
90 

Figure 5.1.29. Progressive vector diagram at selected depths for May 2006 at Station 42873 

zooming to show NIO.

Figure 5.1.30. Progressive vector diagram at different depths for May 2006 at Station 42875.

-100 0 100 200 300 400 500

-40

-20

0

20

40

60

80

100

120

Displacement-A42873.05.2006

x (km)

y (km)

72

360

680

1000

-200 0 200 400 600 800 1000 1200 1400 1600

-800

-700

-600

-500

-400

-300

-200

-100

0

100

Displacement-A42875.05.2006

x (km)

y (km)
91 

Figure 5.1.31. Enlarged progressive vector diagram at different depths for May 2006 at Station 

42875. 

Figure 5.1.32. Progressive vector diagram at selected depths for May 2006 at Station 42875, 

showing the NIOs.

-30 -20 -10 0 10 20 30

-30

-20

-10

0

10

20

30

Displacement-A42875.05.2006

x (km)

y (km)

0 500 1000 1500

-800

-700

-600

-500

-400

-300

-200

-100

0

100

Displacement-A42875.05.2006

x (km)

y (km)

57

201

361

521
92 

Figure 5.1.33. Progressive vector diagram at different depths for May 2006 at Station 42880.

Figure 5.1.34. Enlarged progressive vector diagram at different depths for May 2006 at Station 

42880 to show NIO. 

-200 -100 0 100 200 300 400 500

-150

-100

-50

0

50

100

150

200

Displacement-A42880.05.2006

x (km)

y (km)

-30 -20 -10 0 10 20 30

-30

-20

-10

0

10

20

30

Displacement-A42880.05.2006

x (km)

y (km)
93 

Figure 5.1.35. Enlarged progressive vector diagram at selected depths in May 2006 at Station 

42880, zoomed in to show the NIOs. 

Figure 5.1.36. Progressive vector diagram at different depths for May 2006 at Station 42881.

-100 0 100 200 300 400 500

-50

0

50

100

150

200

Displacement-A42880.05.2006

x (km)

y (km)

62.5

206.5

366.5

526.5

-200 0 200 400 600 800 1000 1200 1400

-250

-200

-150

-100

-50

0

50

100

150

Displacement-A42881.05.2006

x (km)

y (km)
94 

Figure 5.1.37. Enlarged progressive vector diagram at different depths for May 2006 at Station 

42881. 

Figure 5.1.38. Enlarged progressive vector diagram at selected depths for May 2006 at Station 

42881 to show NIO. 

-30 -20 -10 0 10 20 30

-30

-20

-10

0

10

20

30

Displacement-A42881.05.2006

x (km)

y (km)

0 200 400 600 800 1000 1200 1400

-250

-200

-150

-100

-50

0

50

100

150

Displacement-A42881.05.2006

x (km)

y (km)

72.9

360.9

680.9

1000.9
95 

Figure 5.1.39. Progressive vector diagram at different depths for May 2006 at Station 42884.

Figure 5.1.40. Enlarged progressive vector diagram at selected depths for May 2006 at Station 

42884, zoom in to show the NIOs. 

-30 -20 -10 0 10 20 30

-30

-20

-10

0

10

20

30

Displacement-A42884.05.2006

x (km)

y (km)

-200 0 200 400 600 800 1000 1200

-50

0

50

100

150

200

250

300

Displacement-A42884.05.2006

x (km)

y (km)

57

201

361

521
96 

5.1.1 Vertical Structure and Spectrum Analysis

Vertical structures of the flow components often show signs of phase lags and vertical

propagation of velocity magnitude. For example, Figures 5.1.39 and 5.1.40 are the east and north 

velocity component time series as functions of the vertical coordinate for Station 42361 in May 

2006. In the top 300-400 m, there is an obvious upward propagation of velocity phase associated 

with a downward propagation of the maximum which indicate an internal wave excited from the 

surface.

Corresponding to the time series, the Fourier analysis of the velocity time series provides 

information of the major frequency band of the motion. For example, Figures 5.1.41 and 5.1.42 

are the vertical profiles of the spectrum for data shown in Figures 5.1.39 and 5.1.40. There are a 

few features we can identify from them. First of all, it is obvious that there are a couple of bands 

of maximum energy around the diurnal and semi-diurnal tidal frequencies. Tides in this deep 

area are rather weak and the inertial oscillation frequency is very close to that of diurnal tides. 

The maximum at one cycle per day is mainly from the NIOs, not diurnal tides. Note that it is 

relatively broad in range because of the modification of the relative vorticity. It is also obvious 

that the maximum occurs at a depth around 200 m. There is also an indication of slight increase 

of frequency toward deeper water.

The lowpass filtered data allows us to identify flow components excluding the tides and NIOs. 

Figures 5.1.43 and 5.1.44 suggest some episodic events that produce either a surface maximum 

above 200 m or subsurface maximum (400-700 m in these examples) for a duration of 3-7 days. 

The magnitude of such motion reached ~ 25 cm/s in these examples. 

Figures 5.1.45 and 5.1.46 are the 800 m vertical profiles of the east and north velocity 

components for Station 42367 in May 2006. The data had some large gaps and the vertical 

propagation of the velocity phase is not obvious. There may be a downward transfer of energy 

but the flow maximum is almost always on the surface. The lowpass filtered or mean velocity 

(Figures 5.1.47 and 5.1.48) also show some surface and subsurface maximum with a reduced 

magnitude (compared to the earlier example). There is also an indication of observation errors 

and the effect of data gaps. The velocity spectrum is similar to Station 42361 but with a lack of 

obvious semi-diurnal tidal component (Figures 5.1.49 and 5.1.50). 

Figures 5.1.51 shows more spectra of subsurface velocity components (top most bin in the 

vertical) at 15 stations. It can be seen that there is a large range of variability. Generally, there is 

a maximum at the diurnal frequency which can be a single peak or 2 or more peaks. That is a 

mixture of diurnal tides and NIOs. The semi-diurnal tidal components are much weaker if it can 

be identified. 
97 

Figure 5.1.41. Hovmoller diagram for the east velocity component for Station 42361 in May 

2006. The x-axis is time in days and y-axis is depth in meters.

Figure 5.1.42. Hovmoller diagram for the north velocity component for Station 42361 in May 

2006. The x-axis is in days and y-axis in meters.
98 

Figure 5.1.43. Spectrum and vertical profile for the east velocity component for Station 42361 

in May 2006. The x-axis is for frequency (in cycle per day), y-axis in meters.

Figure 5.1.44. Spectrum and vertical profile for the north velocity component for Station 42361 

in May 2006. The x-axis is for frequency (in cycle per day), y-axis in meters.
99 

Figure 5.1.45. Low-pass filtered east velocity component for Station 42361 in May 2006. The 

x-axis is in days; vertical axis in meters.

Figure 5.1.46. Low-pass filtered north velocity component for Station 42361 in May 2006. The 

x-axis is in days; vertical axis in meters.
100 

Figure 5.1.47. East velocity component for Station 42367 in May 2006. The x-axis is in days; 

vertical axis in meters.

Figure 5.1.48. North velocity component for Station 42367 in May 2006. The x-axis is in days; 

vertical axis in meters.
101 

Figure 5.1.49. Mean east velocity component for Station 42367 in May 2006. The x-axis is in 

days; vertical axis in meters.

Figure 5.1.50. Mean north velocity component for Station 42367 in May 2006. The x-axis is in 

days; vertical axis in meters.
102 

Figure 5.1.51. Spectrum for east velocity component for Station 42367 in May 2006. The xaxis is in cycles per day; vertical axis in meters.

Figure 5.1.52. Spectrum for north velocity component for Station 42367 in May 2006. The xaxis is in cycles per day; vertical axis in meters.
103 

Figure 5.1.53. Spectra of velocity components for various stations in May 2006. The x-axis is in 

cycles per day; vertical axis in spectrum energy unit.
104 

5.2 HURRICANE EVENTS AND INERTIAL OSCILLATIONS

Severe weather such as typhoons and hurricanes can produce strong near inertial oscillations 

(e.g. Lai and Sanford, 1986; Maeda et al., 1996; Zheng et al., 2006). According to the National 

Hurricane Center, the year 2005 was most active for Atlantic hurricanes in recorded history. At 

least three of the seven strong hurricanes that made landfall along the U.S. Gulf of Mexico coast 

caused serious damages (Knabb et al., 2005): Hurricanes Katrina, Rita, and Wilma. Hurricanes 

Dennis and Emily also caused significant destructions but here we will only focus on the study of 

the NIOs caused by Katrina (e.g. Pardue et al., 2005; Fritz, 2007; Suedel et al., 2007), Rita (Rego 

and Li, 2009a,b,c), and Wilma, as they present rather continuous records within about a twomonth period. The tracks of these three hurricanes are shown in Figure 5.2.1. They made landfall 

at three distinctly different places: Katrina on the central coast of the northern Gulf of Mexico, 

west of the Birdfoot Delta; Rita more than 400 km to the west of Katrina’s landing point; and 

Wilma about 900 km to the southeast of the Birdfoot Delta on southwest Florida near Cape 

Romano (Figure 5.2.1). 

Figure 5.2.1. Study area and the tracks of Hurricanes Katrina, Rita, and Wilma, the oil and gas 

platforms equipped with ADCPs (crosses), and the only platform (station 42375) 

with an ADCP recording throughout all three hurricanes (triangle).

Figure 5.2.2 shows the wind vector time series recorded at weather station 42040 (29°12'19" N 

88°12'19" W), a station closest to the platform station 42375 (Figure 5.2.1), which recorded the 

ADCP data discussed. Since the center of Hurricane Katrina came very close to this weather 

station, while the centers of Hurricanes Rita and Wilma were far from it, the wind vector plots 

show a strong clockwise rotating vector time series during Hurricane Katrina, a much weaker 
105 

clockwise rotating vector time series during Rita, and a counter-clockwise rotating vector time 

series during Wilma. The wind before and after Katrina appeared to be relatively weak; while it 

remained relatively strong after Rita and Wilma (Figure 5.2.2).

Figure 5.2.2. Wind vectors from Station 42040 (29°12'19" N; 88°12'19" W), located ~ 118 km 

South of Dauphin Island, AL, and ~76 km north of platform 42375 (triangle in 

Figure 5.2.1). 

The velocity data from station 42375 show strong clockwise oscillations immediately after each 

of the three hurricanes as shown by the progressive velocity vector plot (Figure 5.2.3). These 

clockwise oscillations are excited as soon as the hurricane influenced the area and during each 

hurricane event, the oscillation lasted for about 10 days. It is obvious that they are NIOs caused 

by the weather events. To better visualize the vertical structure of the NIOs caused by the 

hurricanes, a 6th order Butterworth filter is implemented with a cutoff frequency of 0.6 cycle/day 

or 40-hour filter. The high-pass and low-pass vertical profiles of the east and north components 

of the velocity during Hurricane Katrina are shown in Figures 5.2.4 – 5.2.7. The vertical profiles 

for Hurricanes Rita and Wilma are similar and are omitted here. A few points follow 

immediately by an examination of Figures 5.2.4-5.2.7: 1) There is a significant NIO throughout 

the entire water column between 1450 m and 1920 m; 2) the NIO occurred immediately after the 

passage of Hurricane Katrina (same for Rita and Wilma); 3) the NIO lasted for more than 10-

days after the passage of the hurricane and decreased slowly over the 10-day period; 4) there 

were apparently oscillations at lower frequencies – roughly 2-4 day periods. 
106 

Figure 5.2.3. Progressive vector diagram showing the NIOs during Hurricanes Katrina and Rita 

in August and September of 2005 at station 42375. 
107 

Figure 5.2.4. Time-depth plots of low-pass filtered east velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s.

Figure 5.2.5. Time-depth plots of high-pass filtered east velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s.
108 

Figure 5.2.6. Time-depth plots of low-pass filtered north velocity at station 42375 during 

Hurricane Katrina. Speed scale in cm/s.

Figure 5.2.7. Time-depth plots of high-pass filtered north velocity at station 42375 during

Hurricane Katrina. Speed scale in cm/s.
109 

To further analyze the oscillations caused by the three hurricanes, we separated the records into 

six segments and calculated the depth averaged velocity (Figure 5.2.8). Flow speed is employed 

to analyze the kinetic energy changes caused by hurricanes. Segment 1, Figure 5.2.8a, covers day 

225 to day 240, before Hurricane Katrina. This period has the lowest speed (max speed less than 

5 cm/s), with some oscillations similar to NIOs. Since the NIOs frequencies in this area are close 

to those of diurnal tides, these measured oscillations may contain some background tidal 

currents. The data also indicate that tidal currents in this deep water area should not exceed 5 

cm/s. This is very important to note as these small tidal current will not significantly interfere 

with the much stronger NIOs caused by the hurricanes. Segment 2, Figure 5.2.8b, shows the 

averaged speed from day 242 to day 252, 10-days after Katrina. This period shows the strongest 

speed of the record discussed, with the maximum flow reaching 25 cm/s and clear NIOs caused 

by the atmospheric forcing. It first ramped up within three days and then decreased almost 

linearly within 8-9 days. Segment 3, Figure 5.2.8c, shows the average speed from day 253 to 

263, a period after the impact of Katrina and before Rita. This is a period of low speed (max ~ 6 

cm/s) and less defined NIO. Segment 4, Figure 5.2.8d, shows the average speed which includes 

Rita and two weeks afterwards. The NIO is seen to have ramped up again, within 4-5 days, 

followed by a steady decrease within 10 days. The maximum speed is 15 cm/s. Segment 5, 

Figure 5.2.8e, shows the average speed after the impact of Rita and before Wilma. Again, this is 

similar to segment 3, with a small speed (up to 5 cm/s) and less defined NIO. Segment 6, Figure 

5.2.8f, shows the average speed for two weeks with Wilma’s influence, which shows once more 

increased depth averaged speed of up to 11 cm/s. The ramp-up period was about 2-3 days, 

followed by a 5-day drop. From these observations, we see that Hurricane Katrina caused the 

NIOs to be at least a factor of 5.6 times larger than before the hurricane when wind was very 

weak. Among this increase in the magnitude of NIO, the high-pass velocity (with a 6th order 40-

hr Butterworth filter) increased by a factor of 4. This implies an increase of total kinetic energy 

by about a factor of 30, and high-pass kinetic energy by a factor of 16. The effects of Hurricanes 

Rita and Wilma on the NIOs are an increase of velocity amplitudes by about a factor of 3.3 and 

2.4, respectively, than before the hurricanes. 
110 

Figure 5.2.8. Depth-averaged speeds (a) before Hurricane Katrina, (b) during and after Katrina, 

(c) between Katrina and Rita, (d) during and after Rita, (e) between Rita and 

Wilma, and (f) during and after Wilma. Y-axis units are cm/s.

The increased depth-averaged flow speeds during segments 2, 4, and 6 apparently are caused by

Hurricanes Katrina, Rita, and Wilma, respectively. The increased kinetic energy contains both 

clockwise (CW) and counter-clockwise (CC) motions. To examine how much of the motion is 

CW or CC, we conducted a rotary spectra analysis (e.g., O’Brien and Pillsbury, 1974). Figure 

5.2.9 shows the rotary spectra for the CW rotating component (thick lines) and CC rotating 

component (thin lines) for the six different time periods as in Figure 5.2.8. Because the vertical 

axis of Figure 5.2.9 is a logarithmic scale, the differences between peak values are much larger 

than what they appear. Figure 5.2.9 shows that 1) the CW component is generally much larger 

than the CC component; 2) the peak of the CW component is centered around the local inertial 

period (about 24 hours); 3) there is a spread of NIO periods, mostly between 22 and 26 hours; 4) 

Hurricane Katrina caused the strongest NIO, followed by Rita, and then Wilma; 5) the NIO 

around the local inertial period seemed to have a broader peak during and after the hurricanes 

than during non-hurricane periods. 
111 

Figure 5.2.9. Rotary spectra for the depth-averaged velocity (u, v) in log-scale (a) before 

Hurricane Katrina, (b) during and after Katrina, (c) between Katrina and Rita, (d) 

during and after Rita, (e) between Rita and Wilma, and (f) during and after 

Wilma. The thick lines represent the clockwise rotating component and the thin 

lines represent the counter-clockwise rotating component. 

Figure 5.2.10 plots the relative fraction of CW and CC components. It reiterates that most of the 

kinetic energy is in the CW component, whether with or without the influence of hurricanes. The 

frequency band with the least CC component is around the local inertial period, where the CW 

and CC components are almost 100% and 0%, respectively. This means that the east and north 

velocity components are almost equal in magnitude and the clockwise particle trajectories are 

almost circular as shown in Figure 5.2.3. As we noted earlier, the baroclinic process cannot be 

used to explain an almost instantaneous NIO at deep-ocean after the passage of a hurricane and a 

rigid-lid approximation will suppress barotropic oscillations. In this chapter, one of the points 

that we emphasize is that there is often an almost instantaneous barotropic NIO response in deepocean after a hurricane and using a Laplace Transform, we can solve the barotropic problem to 

quantify such a barotropic response. To that purpose, in the next section, the atmospheric 

forcing-induced inertial motion is examined with the depth-averaged momentum equations using 

a rotary function approach and the Laplace Transform. 
112 

Figure 5.2.10. Fraction of energy from rotary spectra for the depth-averaged speeds (a) before 

Hurricane Katrina, (b) during and after Katrina, (c) between Katrina and Rita, (d) 

during and after Rita, (e) between Rita and Wilma, and (f) during and after 

Wilma. The thick lines represent the clockwise rotating component and the thin 

lines the counter-clockwise rotating component. 

5.2.1 The Rotary Function Approach Using Laplace Transform

Since the water depth in the Gulf of Mexico is less than 4 km while the width is roughly 1000 

km by 1600 km, the aspect ratio is very small, O(10-3), the Gulf can be treated as “shallow 

water.” Therefore, the overall response of the depth-averaged velocity to wind stress and 

pressure gradient can be examined. For the barotropic component only, we can use the depthaveraged momentum and continuity equations. Although the NIO in the upper layer of the ocean 

often involves baroclinic processes, here the equation is integrated vertically and only the 

barotropic processes are examined. It should be noted that this approach is rather different from 

most recent studies in which stratification is considered. Our selection of a barotropic model is 

based on the following reasons: 1) although the upper ocean (e.g. maximum 800 m and above) is 

often stratified, the deep ocean (e.g. > 800 m) is rather uniform and barotropic in motion (e.g. 

Welsh, et al., 2009). 2) For motions forced by severe weather such as hurricanes, the barotropic 

motion is the first order quantity, rather than a secondary addition to a baroclinic motion. 3) The 

barotropic model used in past studies use the rigid lid approximations which filter out all gravity 

waves and eliminates any effect of pressure gradient, while NIOs are a special kind of Poincare 

Waves under the influence of both earth rotation and gravity. 4) We lack information about what 

is the effect of pressure gradients from both the atmosphere and the surface of the ocean in the 

generation of NIOs in different waters (shallow and deep). A barotropic model will allow us to 

examine the effect of pressure gradient, water depth, and bottom friction from a holistic point of 

view. The majority of the Gulf’s circulation consists of Loop Current and Loop Current Eddies 
113 

as well as NIOs caused or influenced by meteorological forcing factors. The linearized equations 

of motion, assuming a constant water depth for simplicity, are

∂u

∂t − fv = −g ∂ζ∂x + τax

ρh − β

h

u −

1

ρ

∂pa

∂x (1)

∂v

∂t + fu = −g ∂ζ∂y + τay

ρh − β

h

v −

1

ρ

∂pa

∂y (2)

∂ζ

∂t + h �∂u∂x + ∂v∂y� = 0, (3)

in which u, v, ζ, f, g, h, x, y, t, ρ, β, τax, τay, and pa are the east and north velocity, surface 

elevation, Coriolis parameter, gravitational acceleration, depth, east and north coordinates, time, 

water density, bottom friction coefficient, east and north wind stress components, and 

atmospheric pressure, respectively.

Applying the Laplace Transform (e.g. Riley et al., 2006) to the first two equations and assuming 

that initially all fields are zero, yields, 

�p + β

h

� u� − fv� = −g ∂ζ�

∂x + τ�ax

ρh − 1

ρ

∂p�a

∂x (4)

�p + β

h

� v� + fu� = −g ∂ζ�

∂y + τ�ay

ρh − 1

ρ

∂p�a

∂y (5)

in which p is the Laplace Transform parameter and the tildes are those after the Laplace 

Transform. The above equations can be rewritten as

u� = −f

ρ

∂p�a

∂y −�p+βh�

1

ρ

∂p�a

∂x +fτ�ay

ρh +�p+β

h�

τ�ax

ρh −fg∂ζ�∂y−g�p+βh�

∂ζ�

∂x

f2+�p+β

h�

2 (6)

v� = −�p+β

h�

1

ρ

∂p�a

∂y +fρ

∂p�a

∂x +�p+βh�

τ�ay

ρh −fτ�ax

ρh +fg∂ζ�∂x−g�p+βh�

∂ζ�

∂y

f2+�p+β

h�

2 (7)

The Inverse Laplace Transform of the equations (6) and (7) gives the following

u = F1(t) + F2(t) + F3(t) + F4(t) + F5(t) + F6(t) (8)

v = G1(t) + G2(t) + G3(t) + G4(t) + G5(t) + G6(t) (9)

where

F1(t) = f2(t)⨂ τay

ρh = ∫ f2(τ) t

0

τay(t−τ)

ρh

dτ (10) 

F2(t) = f1(t)⨂ τax

ρh = ∫ f1(τ) t

0

τax(t−τ)

ρh

dτ (11) 
114 

F3(t) = −f2(t)⨂g ∂ζ

∂y = −g ∫ f2(τ) t

0

∂ζ(t−τ)

∂y dτ (12) 

F4(t) = −f1(t)⨂g ∂ζ

∂x = −g ∫ f1(τ) t

0

∂ζ(t−τ)

∂x dτ (13) 

F5(t) = f2(t)⨂ −1

ρ

∂pa

∂y = −1

ρ ∫ f2(τ) t

0

∂pa(t−τ)

∂y dτ (14) 

F6(t) = f1(t)⨂ −1

ρ

∂pa

∂x = −1

ρ ∫ f1(τ) t

0

∂pa(t−τ)

∂x dτ (15) 

G1(t) = f1(t)⨂ τay

ρh = ∫ f1(τ) t

0

τay(t−τ)

ρh

dτ (16) 

G2(t) = −f2(t)⨂ τax

ρh = − ∫ f2(τ) t

0

τax(t−τ)

ρh

dτ (17) 

G3(t) = f2(t)⨂g ∂ζ

∂x = g ∫ f2(τ) t

0

∂ζ(t−τ)

∂x dτ (18) 

G4(t) = −f1(t)⨂g ∂ζ

∂y = −g ∫ f1(τ) t

0

∂ζ(t−τ)

∂y dτ (19) 

G5(t) = f2(t)⨂ 1

ρ

∂pa

∂x = 1

ρ ∫ f2(τ) t

0

∂pa(t−τ)

∂x dτ (20) 

G6(t) = −f1(t)⨂ 1

ρ

∂pa

∂y = −1

ρ ∫ f1(τ) t

0

∂pa(t−τ)

∂y dτ (21) 

f1(t) = e−β

ht

cos (ft) (22) 

f2(t) = e−β

ht

sin (ft) (23) 

In the above equations, the symbol ⨂ indicates convolution, which involves either (22) or (23). 

The frequency, f, which is originally the Coriolis parameter, can also be understood as the 

“effective inertial frequency”, fe, as discussed earlier in section 5.1. The functions f1(t) and f2(t) 

defined by (22) and (23) can be called the Frictional Inertial Functions (FIF) because the 

exponential term is simply the frictional decay factor. Equations (8) and (9) show that both u 

and v are given by six terms. The first two terms are contributed by wind stress, the third and 

fourth terms by the surface pressure gradient, while the last two terms by the atmospheric 

pressure gradient. Note that the continuity equation is not used here. A general procedure for

solving this kind of problem is using all three equations, and initial and boundary conditions to 

solve for u, v, and ζ, treating the pressure gradient as unknowns. Equations (8) and (9) show 

relationships between u, v, wind stress, and the pressure gradient. The general properties of the 

solution will be examined next, without seeking an accurate solution of a specific boundary 

value problem. 
115 

5.2.2 Rotary Functions

The common feature of the expression of the solution given above is that all the terms are 

convolved with the frictional inertial functions (FIFs) which have a frequency of the Coriolis 

force f (or a modified NIO frequency, fe , by a few percent of difference from the local Coriolis 

parameter f). The convolution essentially serves as a natural filter that limits the results to be in 

some frequency bands, in this case, the inertial frequency band, particularly in deep water (see 

below). To be an inertial or near inertial oscillation, the velocity vector must be rotating 

clockwise (counterclockwise) in the northern (southern) hemisphere. This can be examined by 

defining a Rotary Flow Velocity as [O’Brien and Pillsbury, 1974] 

ZR = u + iv (24) 

Likewise, for convenience, we also define the “Rotary Wind Stress”, “Rotary Pressure 

Gradient”, and “Rotary Atmospheric Pressure Gradient” to be, respectively,

τR = τax + iτay (25) 

DR = −g �∂ζ

∂x + i

∂ζ

∂y� (26) 

PR = − 1

ρ �

∂pa

∂x + i

∂pa

∂y � (27) 

The reason for the use of equations (24)-(27) is simply because these complex variables can be 

used to describe the corresponding vectors’ sense of rotation when their respective time series 

are evaluated. Using the above results, equation (24) can be expressed as, using (8) and (9)

ZR = u + iv = (f1 − if2)⨂ τR

ρh + (f1 − if2)⨂DR + (f1 − if2)⨂PR (28) 

in which the function f 1 – i f 2 is:

F(t) = f1 − if2 = e−β

ht

e−ift (29) 

It is easy to see that this is a clockwise rotating complex function of time t, affected by the 

frictional decay factor. For this reason, it will be called the “Frictional Rotary Inertial Function 

(FRIF)”. Examining the results so far, equation (28) states that the rotary water velocity (ZR) has 

three components: the first is a convolution of the FRIF and the rotary wind stress per unit mass 

(

τR

ρh), the second is the convolution of the FRIF and the rotary pressure gradient (DR), and the 

third is the convolution of the FRIF and the rotary atmospheric pressure gradient (PR). 

To further examine the effect of the convolution of Rotary Wind Stress on the Rotary Flow

Velocity, it is assumed that the Rotary Wind Stress force per unit mass can be expressed by its 

Fourier series in exponential format:
116 

τR

ρh = ∑�Aeiωt + Be−iωt� (30) 

Now look at a component of wind forcing with arbitrary frequency ω, the counterclockwise part will produce a Rotary Flow Velocity determined by 

 I = F(t) ⊗ τR

ρh = Ae−β

ht

e−ift ⊗ eiωt = A

β

h+i(f+ω)

�eiωt − e−(

β

h+if)t

� (31) 

Similarly, the clockwise part will produce a Rotary Flow Velocity determined by 

J = F(t) ⊗ τR

ρh = Be−β

ht

e−ift ⊗ e−iωt = B

β

h+i(f−ω)

�e−iωt − e−(

β

h+if)t

� (32) 

Obviously, (31) and (32) indicate that for either the clockwise or counter-clockwise rotating 

wind forcing, the flow will have the original frequency, ω, of the same sense of rotation plus an 

inertial oscillation decaying with time, rotating clockwise (in northern hemisphere). Further, 

these oscillations are multiplied by a frequency dependent factor (the gain): for the counterclockwise, and clockwise components, with the following magnitudes, respectively,

H1 = � 1

β

h+i(f+ω)

� = 1

��

β

h�

2

+(f+ω)2

 (33) 

 H2 = � 1

β

h+i(f−ω)

� = 1

��

β

h�

2

+(f−ω)2

 (34) 

Figure 5.2.11 shows the “gain” expressed in (33) and (34) in log-scale for latitude 28.52°, the 

same latitude as station 42375. The curves are for water with large depth (1900 m) and small 

depth (30 m) with various bottom drag coefficient values (varying from 0.001 to 0.002). For 

different latitudes, the results are similar, and are thus omitted. From these gain functions, it is 

found that 1) there is a sharp peak at the NIO frequencies (which is also close to the diurnal tidal 

frequencies in this case) in deep water for the clockwise rotating component; 2) this peak for 

clockwise rotating component is much reduced in shallow water; 3) the change in bottom drag 

coefficient has a more significant impact on the peak for the clockwise component in shallow 

water than in deep water (the variation in deep water are barely visible such that only one curve 

is visible – it actually is multiple curves almost all on top of each other as the differences are 

very small); 4) the much reduced peak in shallow water also has a shift toward shorter period or 

higher frequency (which corresponds to a “blue shift”); 5) the counter-clockwise component 

does not have the peak oscillation; 6) the counter-clockwise component has a much reduced 

magnitude; and 7) the counter-clockwise component does not have a strong dependency on 

depth. The parameter β is a simplified (linearized) bottom friction coefficient and it depends on 

water depth and flow condition at the bottom. 
117 

Figure 5.2.11. Theoretical response curve for clockwise rotating velocity component in deep (~ 

1900 m) and shallow (30 m) waters. The results for counter-clockwise component 

for both deep and shallow waters are not sensitive to the depth and there is no 

peak in those response curves. 

The important finding from this simple model is that the earth rotation serves as a “filter” which 

favors the inertial frequency component, such that the NIOs tend to have a higher peak in deep 

water. In shallow waters, the bottom friction significantly reduces the effectiveness of this 

“filter”. Therefore, whenever the “forcing” (wind stress or pressure gradient) contains an inertial 

frequency, this natural filter will tend to pick it out while reducing all other components at 

different frequencies.

5.3. CONCLUSIONS

Here we proposed a method using the Frictional Rotary Inertial Function and a Laplace 

Transform to the barotropic shallow water equations, aimed at obtaining the temporal evolution 

of the NIOs. We have found that the NIOs as results of the atmospheric forcing depend on water 

depth and bottom friction in a dramatic manner: the mathematical solution is a convolution of 

the frictional rotary function with the input signal (i.e. the forcing); and this is effectively a 

“band-pass filter” that passes the NIOs and damps all the rest. The model predicts no peaks for 
118 

counter-clockwise rotating components in both shallow and deep waters. This “filter” is more 

efficient in deeper waters than in shallower waters. This is in contrast to the tidal currents which 

is minimum in deep waters and amplified in coastal waters. In this chapter, we also argue that 

the atmospheric forcing contributes to pressure gradient which in turn contributes to NIOs 

through a barotropic process. This makes it appropriate to use a baotropic rather than a 

baroclinic model for a secondary quantity (the baroclinic response). With a baroclinic model, it 

would have a rigid-lid and the effect of the atmospheric pressure gradient would be suppressed. 

All baroclinic model shows that it takes a much longer time for the NIOs to propagate to the 

bottom of a deep ocean (e.g. > 1000m), while the barotropic model allows the pressure gradient 

effect to be instantaneous. 

With some unique observational data, we have also analyzed the barotropic NIOs during 

hurricane periods and non-hurricane periods. Strong NIOs initiated by Hurricanes Katrina, Rita, 

and Wilma in August, September, and October of 2005, respectively, in deep water between 

1400 and 1900 m below the surface in the Gulf of Mexico are demonstrated using an ADCP 

equipped on a platform. Apparently, the observed NIOs started immediately after the passage of 

the hurricanes, with an additional ramping period of 2-3 days and a 7-10 day decay thereafter. 

The ramping process may have been caused by the vertical propagation of the baroclinic NIOs 

(e.g. Gill, 1984) on top of the barotropic NIOs. The NIOs appeared to be vertically uniform and 

in phase, lasting for about 10 days after each hurricane. These instantaneously generated NIOs at 

depth may be explained by a barotropic forcing provided by the wind stress, atmospheric 

pressure gradient, and related surface pressure gradient. 
119 

6. SUMMARY

In summary, we have analyzed a large set of time series of acoustic Doppler current profiler data 

from the Gulf of Mexico collected from oil and gas platforms. Data are recorded in waters with a 

total depth deeper than 400 m at 10-20 minute intervals from near surface (~ 30 m) to ~ 500-

1000 m. At places where water depth was greater than 1100 m, two ADCPs may be used. These 

data are often quite continuous but contains gaps of a few weeks to a few months. Our analysis 

started by filling the small gaps using interpolation, but left the large gaps intact. This is 

particularly useful and needed for spectrum analysis because, otherwise, the frequency peaks can 

be distorted. Our analysis focused mainly on the period of 2005-2007. We included some 

analysis for 2008 data, but this time is largely ignored because of the large data volume. Also, 

we focused mainly on the fixed platform data, thus ADCP data from the movable drilling units

were not analyzed as extensively. Our data files are in MATLAB format and therefore can be 

used easily for further analysis.

We completed basic statistical analysis. In the ADCP data files, we used a field called 

“Percentage Good” to QA/QC and select the “good data” before doing the analysis. The 

“Percentage Good” is an indication of the data quality. We use 75% with this field as our criteria 

of data selection: we reject any data point that has a Percentage Good value lower than 75%. As 

we stated earlier, when this value is below 75%, it is mostly much lower than 75%. Most of the 

data either has relatively high Percentage Good (such as 100%) or a very low value. Therefore, a 

cut off at 75% separates the good and bad data very well. 

The number of data points is highly dependent on the depth of the point of interest. The data 

points dropped dramatically going into deeper water. Comparing the years with more than 4 

million data points, we found that the mean speed and standard deviation did not vary much from 

year to year and are about 12-14 cm/s and the standard deviations vary between 12 and 16 cm/s. 

Comparing the different vertical locations, it is found that the mean velocity is largest near the 

surface and decreases with depth until a depth of about 1000 m where the velocity, while 

exhibiting some variations, remains relatively constant. Some of the near-bottom velocity 

increased substantially. This near-bottom increase may be an artificial result because of a lack of 

backscatter at these depths and the flow could be biased toward large velocities. 

We examined the flow direction statistics. It is found that there are several types of variations: 

uni-modal, bi-modal, multi-modal, and omnidirectional. This result can be misleading as 

direction does not necessarily has a strong relation with the dynamics. For specific times, this 

can be true though: for example, if the Near Inertial Oscillation is particularly strong, the flow 

experiences all directions almost equally (unless there is a strong background mean flow), it will 

then be shown as omnidirectional. For the same NIO, if the background mean flow is very strong 

in one direction, then this NIO may appear as a uni-modal with background smaller counts of 

omnidirectional feature. 

The temporal variation of the velocity is as large as the vertical variation. These temporal 

variations have two major components: one with a daily oscillation – the Near-Inertial 

Oscillation, and one with a much longer time scale of a few months. 
120 

We have plotted all the velocity vectors at all depths as functions of time for all stations for the 

years 2005 to 2007. These plots provide rich information about the NIOs, Loop Current, Loop 

Current frontal eddies, and the impact of Loop Current and eddies to nearby areas. The results 

show that NIOs are ubiquitous in the Gulf of Mexico. NIOs wax and wane but their dependence 

on wind or weather is investigated only for some case studies of hurricane-induced NIOs. It is 

clearly shown that major hurricanes such as Hurricanes Katrina and Rita produced large NIOs. 

Some less intensive hurricanes did not produce large NIOs partly because of the relative position 

of the hurricane track to the locations of the stations – if they are on the left of the tracks, the 

NIOs are usually not as large and as obvious. 

In the analysis to hurricane induced NIOs, we proposed a method using the Frictional Rotary 

Inertial Function and a Laplace Transform to the barotropic shallow water equations. We have 

found that the NIOs as results of the atmospheric forcing depend on water depth and bottom 

friction in a dramatic manner: the mathematical solution is a convolution of the frictional rotary 

function with the input signal (i.e. the forcing); and this is effectively a “band-pass filter” that 

passes the NIOs and damps all the rest. The model predicts no peaks for counter-clockwise 

rotating components in both shallow and deep waters. This “filter” is more efficient in deeper 

waters than in shallower waters. This is in contrast to the tidal currents which is minimum in 

deep waters and amplified in coastal waters. We also argue that the atmospheric forcing 

contributes to pressure gradient which in turn contributes to NIOs through a barotropic process. 

This makes it appropriate to use a barotropic rather than a baroclinic model for a secondary 

quantity (the baroclinic response). With a baroclinic model, it would have a rigid-lid and the 

effect of the atmospheric pressure gradient would be suppressed. All baroclinic model shows 

that it takes a much longer time for the NIOs to propagate to the bottom of a deep ocean (e.g. > 

1000m), while the barotropic model allows the pressure gradient effect to be instantaneous. 

It should be noted that the analysis completed are of a preliminary nature and not exhaustive. 

This large dataset is a rich resource that can be used by the scientific community for years to 

come in studies of the dynamics of the Gulf of Mexico. 

In summary, the major findings of this work include the following: 

(1) Statistically, the central northern Gulf of Mexico region has larger flow velocity than that 

of the western area. A variation in flow magnitude in the central area appears to 

propagate to the west, possibly as an integrated impact from mesoscale eddies or Loop 

Current Eddies.

 

(2) NIOs are one of the dominant motions in the GoM. The other important component is 

strong low-frequency flows controlled mainly by the Loop Current and Loop Current 

Eddies, and possibly to some extent by significant large scale weather systems, which 

when added together can overwhelm the NIOs by a few times.

(3) The top 300-400 m are seen to have vertical variations of the NIOs, indicating internal 

wave effect due to vertical stratification. The NIO’s phase and energy are seen to 

propagate vertically quite frequently. The bottom layer (e.g. below 1000 m), however, 

does not demonstrate such vertical propagation. This highlights the need to examine the 
121 

NIOs with barotropic, rather than baroclinic, mode in mind (the work and finding in (5) 

below). 

(4) Hurricanes produce significant and almost instantaneous NIOs at ~1 mile below the 

surface. Our analysis of NIOs induced by the 2005 hurricanes suggested an increase of 

kinetic energy of ~30 times of the background tidal oscillations at 1450 m to 1900 m 

below the surface. The time scale of these NIOs is on the order of 10 days.

(5) Based on the above observations, we examined the dynamical response of NIOs caused 

by the barotropic surface pressure gradient and wind stress. This is in contrast to the 

baroclinic NIO responses that required stratification which mostly occur in the surface 

layer, rather than in the deep bottom layer. Our analysis gives remarkable results which 

indicate that the Coriolis force and the barotropic forcing from the pressure gradient and 

wind stress can work together to produce resonance modulated by the water depth, such 

that external forcing tends to excite NIOs at deep water. The response is less important 

for NIOs as water becomes shallower. This is in contrast to tidal oscillations which are 

small in deep-ocean but get amplified in shallow waters. This theoretical conclusion 

supported by data is the most interesting result. 

123 

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