OCS Study 

MMS 2004-036 

 

Coastal Marine Institute 

Observational and Predictive Study 

of Inner Shelf Currents 

over the Louisiana-Texas Shelf 

Cooperative Agreement

Coastal Marine Institute 

Louisiana State University 

U.S. Department of the Interior

Minerals Management Service 

Gulf of Mexico OCS Region 
 OCS Study 

 MMS 2004-036 

Coastal Marine Institute 

Observational and Predictive Study 

of Inner Shelf Currents 

over the Louisiana-Texas Shelf 

Authors 

Lawrence J. Rouse, Jr. 

William J. Wiseman, Jr. 

Leslie C. Bender 

Norman L. Guinasso, Jr. 

F. J. Kelly 

David A. Brooks 

Yao-Tsi Lo 

J. She 

and 

A. Valle-Levinson 

December 2004 

Prepared under MMS Contract 

14-35-0001-30660-19943 

by 

Coastal Marine Institute 

Louisiana State University 

Baton Rouge, Louisiana 70803 

Published by 

U.S. Department of the Interior Cooperative Agreement 

Minerals Management Service Coastal Marine Institute 

Gulf of Mexico OCS Region Louisiana State University
iii

AUTHORS AND THEIR AFFILIATIONS 

Lawrence J. Rouse, Jr. 

William J. Wiseman, Jr. 

Department of Oceanography and Coastal Sciences 

and Coastal Studies Institute 

Louisiana State University 

Baton Rouge, Louisiana 

Leslie C. Bender 

Norman L. Guinasso, Jr. 

Geochemical and Environmental Research Group 

Texas A&M University 

College Station, Texas 

F. J. Kelly 

Conrad Blucher Institute for Surveying and Science 

Texas A&M University – Corpus Christi 

Corpus Christi, Texas 

David A. Brooks 

Yao-Tsi Lo 

Department of Oceanography 

Texas A&M University 

College Station, Texas 

J. She 

Danish Meteorological Institute 

Copenhagen, DK-2100 Denmark 

A. Valle-Levinson 

Center for Coastal Physical Oceanography 

Old Dominion University 

Norfolk, Virginia 
v

DISCLAIMER 

This report was prepared under contract between the Minerals Management Service (MMS) and 

Louisiana State University. This report has been technically reviewed by the MMS, and it has 

been approved for publication. Approval does not signify that the contents necessarily reflect the 

views and policies of the MMS, nor does mention of trade names or commercial products 

constitute endorsement or recommendation for use. It is, however, exempt from review and 

compliance with the MMS editorial standards. 

REPORT AVAILABILITY 

Extra copies of this report may be obtained from the Public Information Office (Mail Stop 5034) 

at the following address: 

 U.S. Department of the Interior 

 Minerals Management Service 

 Gulf of Mexico OCS Region 

 Public Information Office (MS 5034) 

 1201 Elmwood Park Boulevard 

 New Orleans, Louisiana 70123-2394 

 Telephone: (504) 736-2519 or 

 1-800-200-GULF 

CITATION 

Suggested citation: 

Rouse, L.J., W.J. Wiseman, Jr., L.C. Bender, N.L. Guinasso, Jr., F.J. Kelly, D.A. Brooks, Y-T. 

Lo, J. She, and A. Valle-Levinson. 2004. Observational and predictive study of inner 

shelf currents over the Louisiana-Texas shelf. U.S. Dept. of the Interior, Minerals 

Management Service, Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 

2004-036. 207 pp. 

ABOUT THE COVER 

Plan view of model derived near surface and near bottom velocity fields in the region between 

the Mississippi River Delta and the Atchafalaya Bay 90 days into the model run. 
vii

TABLE OF CONTENTS 

List of Figures...................................................................................................xi 

List of Tables........................... ......................................................................................... xxiii 

Chapter 1 

 1.0 INTRODUCTION ......................................................................................................1 

1.1 METHODOLOGY .....................................................................................................2 

1.2 RELEVANCE.............................................................................................................4 

1.3 SUMMARY................................................................................................................7

Chapter 2 

2.0 INTRODUCTION ......................................................................................................9 

2.1 TABS BUOY DEPLOYMENT AND OPERATION.................................................9 

2.2 R/V GYRE CRUISE ..................................................................................................14 

 2.2.1 CTD Measurements ......................................................................................14 

 2.2.2 Temperature Salinity (TS) Plots ...................................................................19 

 2.2.3 Sections – Contour Plots...............................................................................19 

 2.2.3.1 Temperature ............................................................................................19 

 2.2.3.2 Salinity ....................................................................................................19 

 2.2.3.3 Density ....................................................................................................19 

 2.2.3.4 Brunt-Vaisala Frequency ........................................................................25 

 2.2.3.5 Oxygen....................................................................................................25 

 2.2.3.6 Fluorescence ...........................................................................................25 

 2.2.3.7 Downwelling Irradiance..........................................................................29 

 2.2.3.8 Transmissivity.........................................................................................29 

 2.2.4 ADCP............................................................................................................29 

 2.2.4.1 Post Processing .......................................................................................32 

 2.2.4.2 Results.....................................................................................................34 

 2.2.5 Collateral Data ..............................................................................................36 

2.3 MODELING THE BUOYANCY-DRIVEN FLOW DUE TO RIVER 

 DISCHARGE ON THE TEXAS-LOUISIANA CONTINENTAL 

 SHELF OF THE GULF OF MEXICO .....................................................................36 
viii

TABLE OF CONTENTS 

(continued) 

Chapter 3 

3.0 INTRODUCTION ....................................................................................................59 

3.1 DATA .......................................................................................................................60 

3.2 SUB-TIDAL INNER-SHELF FLOW VARIABILTY.............................................64 

 3.2.1 Monthly Mean Currents................................................................................64 

 3.2.1.1 Alongshore Current.................................................................................64 

 3.2.1.2 Cross-Shore Current................................................................................64 

 3.3 WIND-CURRENT COHERENCE ANALYSIS......................................................67 

 3.3.1 Alongshore Wind-Current Correlation .........................................................67 

 3.3.1.1 Dominant Correlation Patterns ...............................................................67 

 3.3.1.2 Transient Correlation Patterns ................................................................67 

 3.3.1.3 Negative Correlation Patterns.................................................................67 

3.4 ALONGSHORE WIND – CROSS-SHORE CURRENT 

 CORRELATION ......................................................................................................69 

 3.4.1 Dominant Correlation Patterns .....................................................................69 

 3.4.2 Transition Correlation Patterns.....................................................................69 

 3.4.3 Positive Correlation Patterns.........................................................................71 

3.5 COHERENCE STUDY ............................................................................................71 

3.6 COHERENCE BETWEEN ALONGSHORE WINDS AND 

 ALONGSHORE CURRENTS..................................................................................71 

3.7 COHERENCE BETWEEN ALONGSHORE WINDS AND CROSS- 

 SHORE CURRENTS................................................................................................74 

3.8 SPATIAL COHERENCE OF CURRENTS .............................................................74 

3.9 CONCLUSIONS AND DISCUSSIONS ..................................................................76 

Chapter 4 

4.0 CONCLUSIONS.......................................................................................................79 

4.1 ACKNOWLEDGMENTS ........................................................................................80 

REFERENCES ..............................................................................................................................81 
ix

TABLE OF CONTENTS 

(continued) 

Appendix A 

Time Series Plots of Data Collected at TABS Buoy Site P...............................................83 

Appendix B 

Hydrographic Data Collected During R/V Gyre Cruise 98-G-9: 

 Temperature Salinity Plots and Vertical Section ............................................................103 

Appendix C 

Maps and Vertical Section of ADCP Data Collection During 

R/V Gyre Cruise 98-G-9...................................................................................................169 
xi

LIST OF FIGURES

 Page 

Figure 1.1 Map showing the location of Buoy P, in Louisiana waters, as 

well as the other TABS Buoy sites and real-time current 

vectors. ....................................................................................................................3 

Figure 1.2 Currents measured by the TABS buoy array during Tropical 

Storm Dean. ...........................................................................................................5 

Figure 1.3 Currents measured by the TABS buoy array following the 

Buffalo Marine oil spill............................................................................................6 

Figure 2.1 Summary page for Buoy P current velocity data collected 

between 22 July 98 and 19 February 2000. ..........................................................11 

Figure 2.2 Time series plot of current velocity and water temperature 

from Buoy P during August 1998. ........................................................................12 

Figure 2.3 Probability distribution function of the current directions 

collected from July 1998 to 19 February 2000. .....................................................13 

Figure 2.4 Probability distribution function of the current speed data 

collected from July 1998 to 19 February 2000. ...................................................15 

Figure 2.5 Time series plot of Buoy P water temperature collected from 

July 1998 to 19 February 2000. ...........................................................................16 

Figure 2.6 Cruise track of R/V Gyre cruise 98-G-9. ..............................................................17 

Figure 2.7 Temperature Salinity relationship for all CTD stations 

sampled during R/V Gyre cruise 98-G-9. ..............................................................20 

Figure 2.8 Temperature Salinity relationship for CTD stations along 

Transect 3 (Figure 2.6, Stations 14 – 22) sampled during R/V

Gyre cruise 98-G-9. ..............................................................................................21 

Figure 2.9 Vertical profile of temperature for Transect 3 (Figure 2.6, 

Stations 14 – 22). ...................................................................................................22 

Figure 2.10 Vertical profile of salinity for Transect 3 (Figure 2.6, Stations 

14 – 22). ................................................................................................................23 

Figure 2.11 Vertical profile of density for Transect 3 (Figure 2.6, Stations 14-22) ................24 
xii

LIST OF FIGURES 

(continued) 

Figure 2.12 Vertical profile of Brunt-Vaisala frequency for Transect 3 

(Figure 2.6, Station 14-22).....................................................................................26 

Figure 2.13 Vertical profile of dissolved oxygen for Transect 3. .............................................27 

Figure 2.14 Vertical profile of fluorescence for Transect 3......................................................28 

Figure 2.15 Vertical profile of radiance for Transect 3.............................................................30 

Figure 2.16 Vertical profile of transmissivity for Transect 3....................................................31 

Figure 2.17 ADCP lines used to show vertical profiles. ...........................................................35 

Figure 2.18 Stick vector plot of ADCP currents measured at the 4-m bin 

centered at approximately the 14 m depth. ............................................................37 

Figure 2.19 Vertical section of ADCP velocities (cm s-1) normal to line 3 

for cruise 98-G-9....................................................................................................38 

Figure 2.20 Vertical section of ADCP velocities (cm s-1) parallel to line 3 

for cruise 98-G-9....................................................................................................39 

Figure 2.21 Vertical section of ADCP speeds (cm s-1) for line 3 for cruise 

98-G-9....................................................................................................................40 

Figure 2.22 TOPEX/ERS-2 composite for 15 July 1998 shows an upcoast 

flow across the outer shelf on the order of 25-30 cm s-1........................................41 

Figure 2.23 TOPEX/ERS-2 composite for 1 August 1998 shows an 

upcoast flow across the outer shelf on the order of 25 cm s-1................................42 

Figure 2.24 AVHRR 3-day composite of the Gulf of Mexico for 21 July 

1998 shows that the Atchafalaya River plume is turned 

towards the east, due to upcoast winds. .................................................................43 

Figure 2.25 Median wind speed and maximum likelihood direction wind 

vectors for the month of July 1998 for 10 NDBC 

meteorological stations. .........................................................................................44 

Figure 2.26 The 172 x 66 curvilinear orthogonal model grid of the TexasLouisiana shelf.......................................................................................................46 
xiii

LIST OF FIGURES 

(continued) 

Figure 2.27 Plan views of the near-surface velocity fields with constant 

river discharge........................................................................................................48 

Figure 2.28 Plan view of detailed information of (a) the near surface and 

(b) the near bottom velocity fields in the region between the 

Mississippi Canyon and the Atchafalaya Bay at 90 days. .....................................49 

Figure 2.29 Plan views of the near-surface velocity and salinity fields with 

constant river discharge and winds........................................................................51 

Figure 2.30 Smoothed bottom topography................................................................................52 

Figure 2.31 Vertical distributions of salinity, along-shelf, cross-shelf, and 

vertical velocities at section 1 at time t=30 days after 

downcoast and upcoast wind forcings. ..................................................................53 

Figure 2.32 Vertical distributions of salinity, along-shelf, cross-shelf, and 

vertical velocities at section 2 at time t=30 days after 

downcoast and upcoast wind forcings. ..................................................................54 

Figure 2.33 Plan views of the near-surface velocity fields with spatially 

uniform winds at (a) time t=40 days, of (b) the first 30-day 

mean (0-30 days) and (c) the second 30-day mean (30-60 

days).......................................................................................................................55 

Figure 2.34 Plan view of the surface wind field at time t=40 days...........................................56 

Figure 2.35 Plan views of the near-surface velocity fields with gridded 

winds at (a) time t=40 days and of (b) the first 30-day mean................................57 

Figure 3.1 TABS current-meter mooring and NDBC/CMAN buoy sites 

over the Texas-Louisiana inner shelf.....................................................................61 

Figure 3.2a Time series of low-passed daily alongshore currents ............................................62 

Figure 3.2b Time series of low-passed daily wind speeds........................................................63 

Figure 3. 3 31-day running-average of the alongshore currents and 

alongshore winds. ..................................................................................................65 

Figure 3.4 31-day running-average of the cross-shore currents and 

alongshore winds. ..................................................................................................66 
xiv

LIST OF FIGURES 

(continued) 

Figure 3.5 Bimonthly correlation coefficients between alongshore winds 

and alongshore currents for five current meter stations.........................................68 

Figure 3.6 Same as in Figure 3.5 but for alongshore winds and crossshore currents.........................................................................................................70 

Figure 3.7 Block-averaged coherence-squared between alongshore flow 

and alongshore winds in different seasons at B and D. .........................................72 

Figure 3.8 Same as in Figure 3.7 except for alongshore winds and crossshore currents.........................................................................................................73 

Figure 3.9 Coherence-squared and phase relationship of alongshore flow 

between B and D during the winter, summer and transition 

seasons, positive phase means B leads D...............................................................75 

Figure A.1 Time series plot of Buoy P current velocity and water temperature 

 collected during July 1998. ...................................................................................85 

Figure A.2 Time series plot of Buoy P current velocity and water temperature 

 collected during August 1998. ...............................................................................86 

Figure A.3 Time series plot of Buoy P current velocity and water temperature 

 collected during September 1998...........................................................................87 

Figure A.4 Time series plot of Buoy P current velocity and water temperature 

 collected during October 1998...............................................................................88 

Figure A.5 Time series plot of Buoy P current velocity and water temperature 

 collected during November 1998...........................................................................89 

Figure A.6 Time series plot of Buoy P current velocity and water temperature 

 collected during March 1999. ................................................................................90 

Figure A.7 Time series plot of Buoy P current velocity and water temperature 

 collected during April 1999. ..................................................................................91 

Figure A.8 Time series plot of Buoy P current velocity and water temperature 

 collected during May 1999. ...................................................................................92 

Figure A.9 Time series plot of Buoy P current velocity and water temperature 

 collected during June 1999. ...................................................................................93 
xv

LIST OF FIGURES 

(continued) 

Figure A.10 Time series plot of Buoy P current velocity and water temperature 

 collected during July 1999.....................................................................................94 

Figure A.11 Time series plot of Buoy P current velocity and water temperature 

 collected during August 1999. ...............................................................................95 

Figure A.12 Time series plot of Buoy P current velocity and water temperature 

 collected during September 1999...........................................................................96 

Figure A.13 Time series plot of Buoy P current velocity and water temperature 

 collected during October 1999...............................................................................97 

Figure A.14 Time series plot of Buoy P current velocity and water temperature 

 collected during November 1999...........................................................................98 

Figure A.15 Time series plot of Buoy P current velocity and water temperature 

 collected during December 1999. .........................................................................99 

Figure A.16 Time series plot of Buoy P current velocity and water temperature 

 collected during January 2000. ...........................................................................100 

Figure A.17. Time series plot of Buoy P current velocity and water temperature 

 collected during February 2000. .........................................................................101 

Figure B.1 Temperature Salinity relationship for CTD stations along Transect 1 

 sampled during R/V Gyre cruise 98-G-9. ............................................................105 

Figure B.2 Temperature Salinity relationship for CTD stations along Transect 2 

 sampled during R/V Gyre cruise 98-G-9. ............................................................106 

Figure B.3 Temperature Salinity relationship for CTD stations along Transect 4 

 sampled during R/V Gyre cruise 9-8G-9. ............................................................107 

Figure B.4 Temperature Salinity relationship for CTD stations along Transect 5 

 sampled during R/V Gyre cruise 98-G-9. ............................................................108 

Figure B.5 Temperature Salinity relationship for CTD stations along Transect 6 

 sampled during R/V Gyre cruise 98-G-9. ............................................................109 

Figure B.6 Temperature Salinity relationship for CTD stations along Transect 7A 

 sampled during R/V Gyre cruise 98-G-9. ............................................................110 
xvi

LIST OF FIGURES 

(continued) 

Figure B.7 Temperature Salinity relationship for CTD stations along Transect 7B 

 sampled during R/V Gyre cruise 98-G-9. ............................................................111 

Figure B.8 Temperature Salinity relationship for offshore CTD stations sampled 

 during R/V Gyre cruise 98-G-9. ..........................................................................112 

Figure B.9 Vertical profile of temperature for Transect 1. ...................................................113 

Figure B.10 Vertical profile of temperature for Transect 2. ...................................................114 

Figure B.11 Vertical profile of temperature for Transect 4. ...................................................115 

Figure B.12 Vertical profile of temperature for Transect 5. ...................................................116 

Figure B.13 Vertical profile of temperature for Transect 6. ...................................................117 

Figure B.14 Vertical profile of temperature for Transect 7A. ................................................118 

Figure B.15 Vertical profile of temperature for Transect 7B. ................................................119 

Figure B.16 Vertical profile of salinity for Transect 1.......... ...............................................120 

Figure B.17 Vertical profile of salinity for Transect 2. ..........................................................121 

Figure B.18 Vertical profile of salinity for Transect 4. ..........................................................122 

Figure B.19 Vertical profile of salinity for Transect 5. ..........................................................123 

Figure B.20 Vertical profile of salinity for Transect 6. ..........................................................124 

Figure B.21 Vertical profile of salinity for Transect 7A. ........................................................125 

Figure B.22 Vertical profile of salinity for Transect 7B. ........................................................126 

Figure B.23 Vertical profile of density for Transect 1. ...........................................................127 

Figure B.24 Vertical profile of density for Transect 2. ...........................................................128 

Figure B.25 Vertical profile of density for Transect 4. ...........................................................129 

Figure B.26 Vertical profile of density for Transect 5. ...........................................................130 

Figure B.27 Vertical profile of density for Transect 6. ...........................................................131 
xvii

LIST OF FIGURES 

(continued) 

Figure B.28 Vertical profile of density for Transect 7A. ........................................................132 

Figure B.29 Vertical profile of density for Transect 7B. ........................................................133 

Figure B.30 Vertical profile of Brunt-Vaisala frequency for Transect 1. ...............................134 

Figure B.31 Vertical profile of Brunt-Vaisala frequency for Transect 2. ...............................135 

Figure B.32 Vertical profile of Brunt-Vaisala frequency for Transect 4. ...............................136 

Figure B.33 Vertical profile of Brunt-Vaisala frequency for Transect 5. ...............................137 

Figure B.34 Vertical profile of Brunt-Vaisala frequency for Transect 6. ...............................138 

Figure B.35 Vertical profile of Brunt-Vaisala frequency for Transect 7A. ............................139 

Figure B.36 Vertical profile of Brunt-Vaisala frequency for Transect 7B. ............................140 

Figure B.37 Vertical profile of dissolved oxygen for Transect 1. ..........................................141 

Figure B.38 Vertical profile of dissolved oxygen for Transect 2. ..........................................142 

Figure B.39 Vertical profile of dissolved oxygen for Transect 4. ..........................................143 

Figure B.40 Vertical profile of dissolved oxygen for Transect 5. ..........................................144 

Figure B.41 Vertical profile of dissolved oxygen for Transect 6. ..........................................145 

Figure B.42 Vertical profile of dissolved oxygen for Transect 7A. .......................................146 

Figure B.43 Vertical profile of dissolved oxygen for Transect 7B. ........................................147 

Figure B.44 Vertical profile of fluorescence for Transect 1. ..................................................148 

Figure B.45 Vertical profile of fluorescence for Transect 2. ..................................................149 

Figure B.46 Vertical profile of fluorescence for Transect 4..................................................150 

Figure B.47 Vertical profile of fluorescence for Transect 5. ..................................................151 

Figure B.48 Vertical profile of fluorescence for Transect 6....................................................152 
xviii

LIST OF FIGURES 

(continued) 

Figure B.49 Vertical profile of fluorescence for Transect 7A .................................................153 

Figure B.50 Vertical profile of fluorescence for Transect 7B .................................................154 

Figure B.51 Vertical profile of radiance for Transect 1...........................................................155 

Figure B.52 Vertical profile of radiance for Transect 4...........................................................156 

Figure B.53 Vertical profile of radiance for Transect 5...........................................................157 

Figure B.54 Vertical profile of radiance for Transect 6...........................................................158 

Figure B.55 Vertical profile of radiance for Transect 7A........................................................159 

Figure B.56 Vertical profile of radiance for Transect 7B........................................................160 

Figure B.57 Vertical profile of transmissivity for Transect 1..................................................161 

Figure B.58 Vertical profile of transmissivity for Transect 2..................................................162 

Figure B.59 Vertical profile of transmissivity for Transect 4..................................................163 

Figure B.60 Vertical profile of transmissivity for Transect 5..................................................164 

Figure B.61 Vertical profile of transmissivity for Transect 6..................................................165 

Figure B.62 Vertical profile of transmissivity for Transect 7A...............................................166 

Figure B.63 Vertical profile of transmissivity for Transect 7B ...............................................167 

Figure C.1 Stick vector plot of ADCP currents measured at the 4-m bin 

 centered at approximately the 26 m depth ...........................................................171 

Figure C.2 Stick vector plot of ADCP currents measured at the 4-m bin 

 centered at approximately the 50 m depth ...........................................................172 

Figure C.3 Stick vector plot of ADCP currents measured at the 4-m bin 

 centered at approximately the 102 m depth .........................................................173 

Figure C.4 ADCP lines used to show vertical profiles ..........................................................174 

Figure C.5 Vertical section of ADCP velocities (cm s-1) normal to Line 1 for 

 cruise 98-G-9 .......................................................................................................175 
xix

LIST OF FIGURES 

(continued) 

Figure C.6 Vertical section of ADCP velocities (cm s-1) parallel to Line 1 for 

 cruise 98-G-9 .......................................................................................................176 

Figure C.7 Vertical section of ADCP speeds (cm s-1) for Line 1 for cruise 

98-G-9..................................................................................................................177 

Figure C.8 Vertical section of ADCP velocities (cm s-1) normal to Line 2 for 

 cruise 98-G-9 .......................................................................................................178 

Figure C.9 Vertical section of ADCP velocities (cm s-1) parallel to Line 2 for 

 cruise 98-G-9 .......................................................................................................179 

Figure C.10 Vertical section of ADCP speeds (cm s-1) for Line 2 for cruise 98-G-9..............180 

Figure C.11 Vertical section of ADCP velocities (cm s-1) normal to Line 4 for 

 cruise 98-G-9 .......................................................................................................181 

Figure C.12 Vertical section of ADCP velocities (cm s-1) parallel to Line 4 for 

 cruise 98-G-9 .......................................................................................................182 

Figure C.13 Vertical section of ADCP speeds (cm s-1) for Line 4 for cruise 

98-G-9..................................................................................................................183 

Figure C.14 Vertical section of ADCP velocities (cm s-1) normal to Line 5 for 

 cruise 98-G-9 .......................................................................................................184 

Figure C.15 Vertical section of ADCP velocities (cm s-1) parallel to Line 5 for 

 cruise 98-G-9 .......................................................................................................185 

Figure C.16 Vertical section of ADCP speeds (cm s-1) for Line 5 for cruise 98-G-9..............186 

Figure C.17 Vertical section of ADCP velocities (cm s-1) normal to Line 6 for 

 cruise 98-G-9 .......................................................................................................187 

Figure C.18 Vertical section of ADCP velocities (cm s-1) parallel to Line 6 for 

 cruise 98-G-9 .......................................................................................................188 

Figure C.19 Vertical section of ADCP speeds (cm s-1) for Line 6 for cruise 98-G-9..............189 

Figure C.20 Vertical section of ADCP velocities (cm s-1) normal to Line 7 for 

 cruise 98-G-9 .......................................................................................................190 
xx

LIST OF FIGURES 

(continued) 

Figure C.21 Vertical section of ADCP velocities (cm s-1) parallel to Line 7 for 

 cruise 98-G-9 .......................................................................................................191 

Figure C.22 Vertical section of ADCP speeds (cm s-1) for Line 7 for cruise 98-G-9..............192 

Figure C.23 Vertical section of ADCP velocities (cm s-1) normal to Line 8 for 

 cruise 98-G-9 .......................................................................................................193 

Figure C.24 Vertical section of ADCP velocities (cm s-1) parallel to Line 8 for 

 cruise 98-G-9 .......................................................................................................194 

Figure C.25 Vertical section of ADCP speeds (cm s-1) for Line 8 for cruise 98-G-9..............195 

Figure C.26 Vertical section of ADCP velocities (cm s-1) normal to Line 9A for 

 cruise 98-G-9 .......................................................................................................196 

Figure C.27 Vertical section of ADCP velocities (cm s-1) parallel to Line 9A for 

 cruise 98-G-9 .......................................................................................................197 

Figure C.28 Vertical section of ADCP speeds (cm s-1) for Line 9A for 

 cruise 98-G-9 .......................................................................................................198 

Figure C.29 Vertical section of ADCP velocities (cm s-1) normal to Line 9B for 

 cruise 98-G-9 .......................................................................................................199 

Figure C.30 Vertical section of ADCP velocities (cm s-1) parallel to Line 9B for 

 cruise 98-G-9 .......................................................................................................200 

Figure C.31 Vertical section of ADCP speeds (cm s-1) for Line 9B for 

cruise 98-G-9 .......................................................................................................201 

Figure C.32 Vertical section of ADCP velocities (cm s-1) normal to Line 9C for 

 cruise 98-G-9 .......................................................................................................202 

Figure C.33 Vertical section of ADCP velocities (cm s-1) parallel to Line 9C for 

 cruise 98-G-9 .......................................................................................................203 

Figure C.34 Vertical section of ADCP speeds (cm s-1) for Line 9C for cruise 98-G-9...........204 

Figure C.35 Vertical section of ADCP velocities (cm s-1) normal to Line 10 for 

 cruise 98-G-9 .......................................................................................................205 
xxi

LIST OF FIGURES 

(continued) 

Figure C.36 Vertical section of ADCP velocities (cm s-1) parallel to Line 10 for 

 cruise 98-G-9 .......................................................................................................206 

Figure C.37 Vertical section of ADCP speeds (cm s-1) for Line 10 for cruise 98-G-9............207 
xxiii

LIST OF TABLES

 Page 

Table 2.1 List of CTD Station Identifiers and Location ........................................................18 

Table 2.2 ADCP Configuration Summary.............................................................................32 

Table 2.3 Complex Regression Analysis ...............................................................................33
1

Chapter 1 

1.0 INTRODUCTION 

Upon exiting the Mississippi and Atchafalaya River Deltas, the relatively fresh river waters flow 

westward along the coast to form the Louisiana Coastal Current (Wiseman and Kelly, 1994). 

The waters of this current system move downcoast (in the sense of phase propagation of Kelvin 

waves) most of the year and are readily identifiable along the Mexican coast of the Gulf of 

Mexico during the late fall, winter, and early spring. The flow is highly responsive to wind 

forcing, the most important synoptic wind pattern being cold air outbreaks (Huh et al., 1984), 

which occur on time scales of 3 to 10 days during the winter season (DiMego et al., 1976; 

Fernandez-Partagas and Mooers, 1975). Driven by such events, the current may reverse 

direction for a brief period of time and flow upcoast. During summer, when winds are weaker, 

the coastal waters of Louisiana are highly stratified and the surface flow may be incoherent with 

the near-bottom currents on sub-tidal time scales. Along the south Texas coast, the winds 

become upwelling favorable in late spring and the mean flow reverses direction and moves 

upcoast. For periods of a month or longer the direction of the mean current over the western 

Louisiana inner shelf may be eastward (Cochrane and Kelly, 1986). 

An understanding of the currents within this coastal system is important to a number of 

environmentally important processes. Not the least of these is oil spills, since any spill in 

nearshore waters is immediately transported by the waters of this current system and any spill in 

Outer Continental Shelf waters must transit this current system before impacting the highly 

productive marshes and estuaries of coastal Louisiana and Texas. Much of this country’s 

imported oil is lightered from super tankers offshore Louisiana and Texas. Offshore production 

contributes an important but significantly smaller amount than lightering. The volume of oil 

lightered last year from Southwest pass to Corpus Christi was about 275 million barrels; 

equivalent to almost 200 EXXON VALDEZ loads (Larry Smith, Calero Refining; personal 

communication). The volume continues to increase. 

LATEX, the Louisiana-Texas Shelf Physical Oceanography Program funded by the MMS, has 

produced fascinating science about the economically important shelf region west of the 

Mississippi Delta. The analysis and synthesis effort now in progress will both answer many 

questions and generate new ones. One way to build on the LATEX results is to implement a 

core field program that provides real-time observations accessible to all. New investigations can 

then efficiently pursue the ideas and questions generated by recent studies about ocean processes. 

In some cases the data from the core program will suffice; in others, small temporary additions to 

the cores program would augment the standard observations. The results would allow us to 

understand the dynamics of near-surface coastal flow on scales not measured by LATEX. 

Shortly after the end of the field portion of LATEX, the Texas General Land Office (TGLO) 

directed Texas A&M University to implement a program that provides real-time surface currents 

and water temperature at selected locations along the Texas coast. The Texas Automated Buoy 

System (TABS) is now in operation (Chaplin and Kelly, 1995), feeding the TGLO’s oil spill 

trajectory model with the input necessary for rapid effective response (Martin et al., 1997). 

TABS is a long term operational system. While the primary purpose of TABS is to provide the 
2

TGLO with information critical to early oil spill response operations, it also has tremendous 

research potential, particularly if the number of sites and the spatial extent are increased. TABS 

data are obviously useful to a myriad of other studies and applications ranging from vessel 

operations and fishing to transport of larvae and the distribution of sea-turtle strandings. 

We added buoys to the TABS system and extended it into the shelf region off Louisiana with the 

following objectives: 

To provide the scientific community with a core observational program upon 

which numerous individual research projects can be built. 

To produce a framework for the assimilation of real-time observations of currents, 

wind and sea level into a “nowcast” of Louisiana-Texas circulation. This work 

would use the time-space correlation results derived from LATEX. 

To investigate the applicability of simple shelf-wave propagation models, such as 

those valid on the west Florida shelf, for the Louisiana-Texas shelf. 

To extend a long-term database that will advance our understanding of physical 

processes responsible for inner shelf circulation in the LATEX region. 

Strategic and tactical oil spill response planning require knowledge of the expected inner shelf 

current field. Historical information on the coastal current field and its relationship to the 

climatology of regional wind forcing are important information used in risk analysis and to 

determine the optimal placement of clean up resources, e.g. booms and skimmers. Near-real 

time data on near surface flows and simple models of the wind-driven response of the coastal 

waters, which can assimilate real data to update nowcasts and short period forecasts of the flow 

field, will assist in the tactical deployment of resources, both human and material, during a spill 

response. 

1.1 METHODOLOGY 

TGLO and Texas A&M University operate multiple offshore TABS buoys (Figure 1.1). TABS 

buoys take a five-minute average of current velocity, direction and water temperature two meters 

below the surface every thirty minutes. A shore-based computer automatically acquires the data 

via cellular phone four or more times per day, performs QA/QC functions, and adds the 

observations to the TABS data base, which is publicly accessible through an interactive World 

Wide Web page: http://gergu3.tamu.edu/Tglo (Lee et al., 1996). 

The TABS buoy is a modified spar design constructed of closed-cell, cross-linked, polyethylene 

foam with a polyurethane fabric-reinforced skin. It has an internal radar reflector, and a central, 

stainless steel, water tight tube that houses the current meter and communications subsystems. A 

Marsh-McBirney electro-magnetic 2-axis current sensor extends from the bottom of the buoy. 

Two solar panels provide power through rechargeable batteries to the communications 

subsystem and a marine lantern. The current meter has an independent battery pack. Reliable 
3

Figure 1.1 Map showing the location of Buoy P, in Louisiana waters, as well as the other 

TABS Buoy sites and real-time current vectors. The figure is taken from the 

TABS Website: resolute.gerg.tamu.edu/tglo. The map also shows NOAA Data 

Buoy Center (NDBC) real-time meteorological sites and wind vectors. 
4

two-way communication is accomplished with the MNP-10 data communication protocol 

(Chaplin and Kelly, 1995). 

To access the TABS data via the website, the user selects a station via an active map showing 

buoy, meteorological and sea level stations. The user may view the latest available data or select 

archived data from the TABS database. The data are available in graphic or numeric form (or 

both) and can be captured by the user. Interesting early results included observation of an 

impulse response in the coastal jet following the passage of a strong storm in April 1995, the 

currents (Figure 1.2) off Galveston during tropical storm Dean (which passed directly over two 

buoys in August 1995), inertial oscillations during the summer months and reversals in the 

coastal current during the Buffalo Marine oil spill (Figure 1.3). 

A new buoy, designated P, was deployed over the inner shelf offshore western Louisiana. The 

buoy was serviced numerous times and, while data coverage as not continuous, large volumes of 

quality controlled data were collected, thus demonstrating the feasibility of operating TABS 

buoys offshore western Louisiana with existing resources and communications networks. The 

data collected from this buoy and from the R/V Gyre during the initial deployment cruise are 

described in the next chapter. Plots of the remaining data are presented as appendices. Initial 

results of a numerical model of the Texas-Louisiana shelf are also briefly discussed in the 

chapter. 

Historical data sets collected by the TABS array prior to this effort were carefully analyzed to 

determine their statistical relationship to one another, to coastal winds, and to coastal water 

levels. This analysis isolates scales at which purely statistical nowcasts of the near surface 

currents might be reliable and isolates dynamical balances in the inner shelf water which should 

be pursued in further modeling efforts. 

Among other results, a geopotential high over the inner shelf near 93.5o W, a hypothesized, 

transient, seasonal response to wind and riverine forcing, is used to explain observed flow 

patterns. The signals of longshore propagating flows, consistent with coastally-trapped wave 

theory, are identified in the data. Cross-shore flows, consistent with upwelling theory are also 

clearly present in the data. 

1.2 RELEVANCE 

This project addressed two framework areas: (1) modeling of environmental processes and 

systems and (2) new information about the structure/function of affected systems via application 

of descriptive and experimental means. 

Current structure is an important determinant of many environmental processes including oil 

spill motion and the movement of living marine resources. While models are being developed 

for the entire Gulf of Mexico, they presently cannot be run in response to real time scenarios nor 

do they fully resolve the inner shelf circulation. Therefore, it is important to develop simple 
5
6
7

techniques, based on dynamical principles where possible, to ‘nowcast’ or predict such current 

structures. These predictors/’nowcastors’ must be initialized with real-time data. The TABS 

array project provides a system for delivering such real-time data. It provides synoptic data that 

will allow understanding of the dynamics of coastal near surface flows on scales not measured 

by LATEX. 

1.3 SUMMARY 

A coastal current of low-salinity waters originating from the Mississippi and Atchafalaya Deltas 

dominates the Louisiana-Texas inner shelf. Relatively swift wind-driven flows in excess of a 

knot (0.5 m/s) are not uncommon within this system. These waters respond quickly and 

intensively to local and far-field wind forcing. Knowledge of the flow within these waters is 

important for both strategic and tactical planning for oil spill response. From a strategic sense, it 

is important to know the characteristics of the flow in a statistical sense: the maximum expected 

flows and the expected response to climatological wind variability. This knowledge will assist in 

the stockpiling of response equipment. From a tactical standpoint, it is important to know in 

which direction the currents are flowing when a spill occurs:, a simple model of wind-driven 

currents in conjunction with a forecast of regional winds will allow anticipation of shifts in the 

transport of spilled materials. 

Texas A&M University has deployed an initial array of buoys in Texas coastal waters that 

measure near-surface currents and water temperature. The buoys of the Texas Automated Buoy 

System (TABS) report the measured data in near-real time via cellular telephone to a base 

station. Computers automatically perform quality control procedures and post the observations 

to a publicly accessible home on the Internet. We extended this array into western Louisiana 

waters. The data were processed and the meters maintained exactly as the present Texas array is 

handled. The Texas A&M buoy operated intermittently, but provided a significant volume of 

data that passed all quality control tests and demonstrated the feasibility of extending the TABS 

array into Louisiana waters using the present technology and communication networks. Data 

collected during the deployment cruise, which also surveyed regions of the shelf as far east as the 

Mississippi Delta, are discussed in the text and plots are presented in the appendices. Finally, 

initial results of a modeling exercise carried out at Texas A&M demonstrate their ability to 

model the flows over the LATEX shelf region. Results of this portion of the project are covered 

in Chapter 2. 

Analyses of historical TABS data by scientists at Old Dominion University both add credence to 

the interpretation of previously collected data from a variety of sources and suggest new patterns. 

A geopotential high over the inner shelf near 93.5o W, a hypothesized, transient, seasonal 

response to wind and riverine forcing, is used to explain observed flow patterns. The signals of 

longshore propagating flows, consistent with coastally trapped wave theory, are identified in the 

data. Cross-shore flows, consistent with upwelling theory are also clearly present in the data. 

Results of this portion of the project are covered in Chapter 3.
9

Chapter 2 

2.0 INTRODUCTION 

This chapter describes the work conducted by Texas A&M University (TAMU). This includes 

deployment and operation of a TABS buoy in the offshore waters of western Louisiana (Chapter 

2.1), coastal oceanographic observations made during the cruise that deployed the buoy (Chapter 

2.2), and the results of modeling efforts (Chapter 2.3). 

2.1 TABS BUOY DEPLOYMENT AND OPERATION 

The Geochemical and Environmental Research Group (GERG) at TAMU developed and 

continues to operate the TABS program for the Texas General Land Office (TGLO). The heart of 

(the Texas Automated Buoy System TABS) is an array of seven buoys (Figure 1.1) that report 

ocean current velocities and water temperatures in real time (Chaplin and Kelly 1995, Magnell et 

al. 1998). The primary mission of TABS is to provide critical data for spill response (Martin et 

al. 1997). The TGLO also recognizes the value of TABS to the public and scientific community 

(Kelly et al. 1998). Therefore, TABS automatically posts all observations to a Website 

(http://resolute.gerg.tamu.edu/tglo) where the data can be freely viewed and downloaded. 

The TGLO also encourages collaborative projects that build on the TABS core program. This 

project is one such example. Another, entitled “Gulf of Mexico Ocean Modeling System” 

(OMS), was one of the projects of the National Ocean Partnership Program. The Office of Naval 

Research, with Dynalysis of Princeton, Inc., serving as the lead organization, funded OMS. The 

project’s objective was to produce nowcasts and forecasts of surface and subsurface velocities 

for the entire Gulf of Mexico and distribute them publicly via an Internet Web site 

(www.dynalysis.com). Buoys L, M and N in Figure 2.1 were funded by OMS. 

Using funds donated by the Marine Industry Group (MIRG), a partnership of oil companies 

operating in the Gulf of Mexico, GERG purchased hardware needed for a new Model II buoy to 

deploy in the coastal waters of western Louisiana. The TABS II was developed in cooperation 

between GERG and Woods Hole Group/Advanced Coastal Environmental Systems (ACES), Inc. 

Magnell et al. (1998) describe the details of the new design. The four major design 

enhancements are (1) a new geostationary satellite telephone system, (2) an increased size of the 

flotation package, (3) an Argos satellite data transmission system that is automatically activated 

if the primary communications system fails, and (4) an electronic command and control system 

based on the ACES Remote System Monitor, which includes a powerful microprocessor and 

multiple analog and digital I/O ports. On January 20, 1998, GERG deployed the first TABS II 

buoy for several months of test and evaluation next to Buoy B off Galveston. After some 

refinements, three TABS II buoys were installed during April-May 1998 for the OMS project. 

The TABS II buoy for this project was installed at Site P (Figure 1.1) on 22 July 1998 during 

cruise 98-G-9 from Galveston, Texas, to Biloxi, Mississippi, aboard the TAMU Research Vessel 

Gyre. Hydrographic observations collected during 98-G-9 are described in the Chapter 3. TABS 

Buoy R was also deployed during this cruise. 
10

Buoy P was recovered on 24 November 1998 during the R/V Gyre’s return from the Northeastern 

Gulf of Mexico (NEGOM) cruise N4 funded by US Minerals Management (MMS). Initially, the 

data recorded by Buoy P were very good. The current velocity sensor on Buoy P was a MarshMcBirny, Inc. (MMI) electromagnetic 4” diameter model. Prior to deployment, all surfaces of 

the sensor, except for the four sensing electrodes and the voltage reference electrode, were 

painted with anti-fouling paint. However, beginning about 7 September 1998, an offset began to 

creep into the velocity measurements, as evidenced by sporadic spikes and excessively high 

values in the speed data. The velocity data for the remainder of the deployment are considered 

bad. Biological fouling is the suspected cause. When recovered, the sensors had large barnacles 

growing on the electrode tips. 

Buoy P was reinstalled three months later on 1 March 1999 as part of a TABS cruise on the R/V 

Glorita, operated by TDI-Brooks International. The buoy operated until it was recovered on 15 

August 1999 as part of a R/V Gyre cruise. The sensor failed a zero test performed after recovery, 

which entails placing the unit in still water and recording the sensor’s velocity measurements. A 

non-zero velocity, i.e., failure of the test, infers a velocity offset is present in the data. There are 

two specific periods in July 1999 when the velocity data is rejected. 

A replacement for Buoy P was immediately reinstalled on 15 August 1999 as part of the above 

TABS cruise on the R/V Gyre. The buoy operated until it was recovered for the final time on 19 

February 2000. Post-analysis of the data indicated that velocity sensor worked quite well until 

approximately 20 October 1999, when high speeds and the velocity spikes suggested biological 

fouling was causing problems. These sporadic spikes continued through 1 December 1999, after 

which time the spikes apparently ceased and the velocity data for December 1999 appears to be 

good. During the first five days in January 2000 all the data are missing due to transmission 

problems. Beginning on 8 January 2000, biological fouling is again suspected to cause spikes in 

the speed data and the remaining data is highly suspect. 

In spite of the loss of data noted above, there were 15,953 half-hourly records of useable velocity 

data and 21,333 half-hourly records of temperature data. Figure 2.1 shows a summary analysis 

of the useable velocity data. The page is divided into three parts. The top shows a table of the 

basic statistics for the flow. The middle shows a scatter plot and the bottom provides a table of 

the joint frequency of speed and direction. All velocities are in cm s-1. During this entire period, 

the scalar current speed averaged 19.14 cm s-1. The mean vector flow was 5.57 cm s-1 towards 

the west at 276O True. Only 1% of the time did the current exceed 60 cm s-1. A principal axis 

ellipse analysis of the velocities shows the rotation angle is aligned along the 288.8 – 108.8O

direction. The major axis of the variance ellipse was 18.74 cm s-1 and the minor axis was 13.27 

cm s-1

Individual time-series plots of all the data collected by Buoy P are shown in Appendix A. A 

typical example of the data is shown in Figure 2.2. Velocity data that did not pass QC criteria 

are not plotted and are not used in any analysis presented in this report. 

Figure 2.3 shows the probability distribution, by one-degree bins, of the current direction over 

the entire period of useable velocity data. A predominant peak at 286o true, i.e., westward flow, 
11

Figure 2.1 Summary page for Buoy P current velocity data collected between 22 July 98 

and 19 February 2000. Top: basic statistics; middle: scatter plot; bottom: joint 

frequency distribution. 
12

Figure 2.2 Time series plot of current velocity and water temperature from Buoy P during 

August 1998. 
13

Figure 2.5. Time series plot of Buoy P current velocity and water temperature collected 

during September 1998. Velocity data after 8 September 1998 are considered 

bad, though the temperature record is still reliable. 

Figure 2.3 Probability distribution function of the current directions collected from July 

1998 to 19 February 2000. The prominent direction of 286 degrees, down-shelf

flow is clearly seen and the minor peak is nearly 180 degrees in the other 

direction. 
14

is clearly seen in the record and is supported by the principal axis results noted above. A 

secondary peak at 126O true is seen as well. This bimodal distribution is a convincing indication 

of the Louisiana Coastal Current reported by Wiseman and Kelly (1994). While not shown here, 

other buoys in the TABS program show the same bimodal distribution in the direction. 

Finally, Figure 2.4 shows the probability distribution, in 0.1 cm s-1 bins, for the current speed. 

The distribution is remarkable in its notable similarity to a two-parameter gamma distribution. 

Figure 2.5 shows the record length temperature distribution, as well as a fitted curve. There were 

21,333 data points that passed quality control, the mean temperature was 25.33o

C, and the 

standard deviation was 4.78o

C. The minimum temperature of 14.36oC occurred on 12 February 

2000 at 1800 GMT and the maximum temperature of 31.01o

C occurred on 4 August 1999 at 

0130 GMT. The smooth line represents the annual signal plus two harmonics, at 6 months and 4 

months, found from a least squares fit of the sinusoidal signals to the data. 

 

2.2 R/V GYRE CRUISE 

Cruise 98-G-9 left Galveston 2200 CDT 20 July 1998 and returned to Biloxi at 0830 CDT 25 

July 1998. 

Besides the deployment of Buoy P, the cruise performed a number of other tasks and collected 

hydrographic data that supplements the database across the Louisiana-Texas shelf. 

2.2.1 CTD Measurements 

We used the opportunity of cruise 98-G-9 to occupy 55 CTD stations using a Sea-Bird 

Electronics, Inc. 911+ CTD with rosette sampler. Station locations are depicted in Figure 2.6 

and enumerated in Table 2.1. Continuous profiles with pressure were made of temperature, 

conductivity, downwelling irradiance (with a Photosynthetically Available Radiation (PAR) 

sensor), transmissivity, fluorometry, and dissolved oxygen. The Sea-Bird SBE-911+ CTD is a 

research grade CTD system that offers high quality profiles of oceanic temperature, salinity1

, and 

density at all ocean depths. The SBE-911 uses ultra-stable time-response matched sensors and 

fast, high-resolution parallel sampling for data acquisition. 

In addition to providing precise measurements of temperature and salinity with depth, the 

TAMU/GERG Sea-Bird CTD system has other sensors integrated into its data acquisition unit. 

Oxygen is measured with a “Beckman” polarographic type in situ oxygen sensor. Downwelling 

irradiance is measured with a Biospherical Instruments, Inc. Model QSP-200L irradiance 

profiling sensor. Particle scattering is measured with a Sea Tech light scattering sensor. In 

addition to the light scattering sensor, the CTD is equipped with a SeaTech, Inc. 25-cm 

transmissometer. Samples for discrete measurements of suspended particulate concentration and 

 

1

 Salinity as currently defined by the Practical Salinity Scale, has no units. Values are given 

simply as a number, e.g., 35.00). 
15

Figure 2.4 Probability distribution function of the current speed data collected from July 

1998 to 19 February 2000. While the average speed is 19.14 cm s-1, the median 

speed is 9.0 cm s-1. 
16

Figure 2.5 Time series plot of Buoy P water temperature collected from July 1998 to 19 

February 2000. The smooth line is a linear-fit to a yearly sinusoidal signal plus 

two harmonics, 6-months and 4-months. 
17

Figure 2.6 Cruise track of R/V Gyre cruise 98-G-9. The connected line indicates where ADCP data wa

The dots indicate station numbers where CTD profiles were collected. Buoy locations are dated by letters. 
18

Table 2.1 

List of CTD Station Identifiers and Location 

Station Longitude 

W 

Latitude 

N 

001 94.60383 29.25800 

002 94.56400 29.16233 

003 94.52683 29.08017 

004 94.49400 29.00117 

005 94.14150 28.19833 

006 94.06417 28.04100 

007 93.98567 27.89100 

008 93.73733 29.00450 

009 93.69850 29.16750 

010 93.66050 29.33383 

011 93.62300 29.50133 

012 93.60250 29.58450 

013 93.59133 29.63600 

014 92.69767 29.53317 

015 92.69717 29.46317 

016 92.70017 29.40733 

017 92.70050 29.29417 

018 92.69633 29.17500 

019 92.70100 29.04817 

020 92.70050 28.89167 

021 92.70033 28.75850 

022 92.70367 28.64250 

023 91.61617 29.00017 

024 91.61500 28.83517 

025 91.61583 28.66767 

026 91.61267 28.49967 

027 90.84717 28.83367 

028 90.84733 28.66633 

Station Longitude 

W 

Latitude 

N 

029 90.84633 28.49883 

030 90.27383 28.70200 

031 90.07733 28.98283 

032 90.07483 28.83400 

033 90.07033 28.66800 

034 90.06783 28.67100 

035 90.01617 28.64967 

036 90.07550 28.65350 

037 89.98133 28.63283 

038 89.89133 28.61850 

039 89.81917 28.56350 

040 89.78683 28.44900 

041 89.78583 28.33167 

042 88.94867 27.66683 

043 88.94950 27.83400 

044 88.94917 28.00233 

045 88.95033 28.16883 

046 88.94967 28.33800 

047 88.94783 28.50267 

048 88.94450 28.66883 

049 88.95000 28.75000 

050 88.94867 28.82967 

051 88.94517 28.91817 

052 88.94533 29.00100 

053 88.94900 29.08467 

054 88.77700 29.10483 

056 88.68733 29.21367 
19

dissolved oxygen were drawn from the 10-liter PVC Niskin bottles mounted on the General 

Oceanics Rosette sampler, which is part of the CTD profiling system. 

There were a total of seven across-shelf transects made during R/V Gyre cruise 98G9 (Figure 2.6 

and Table 2.1). In the figures that follow Transect 1 refers to stations 001 through 007. Transect 

2 refers to stations 007 through 013. Transect 3 refers to stations 014 through 022. Transect 4 

refers to stations 023 through 026. Transect 5 refers to stations 027 through 029. Transect 6 

refers to stations 031 through 041. Transect 7 refers to stations 042 through 053, but is divided 

into two parts, 7A – stations 042 through 049, and 7B – stations 049 through 053. 

2.2.2 Temperature Salinity (TS) Plots 

Figure 2.7. shows the temperature salinity relationship for all 55 CTD stations collected during 

the cruise. Figures 2.8 shows the TS relationship for transect 3 where Buoy P is moored. The TS 

relationships for the other transects, as well as the deepest stations on each transect, are shown in 

Appendix B. Evidence of a Loop Current intrusion is seen in the salinities exceeding 36.5. The 

most prominent feature in the deep water is the salinity minimum that represents the core of the 

Antarctic Intermediate Water (AAIW), which enters the Gulf of Mexico at water depths of 700 

800 m. This is most clearly seen on transect 7A. 

2.2.3 Sections – Contour Plots 

 2.2.3.1 Temperature 

Contours of temperature along transect 3 are shown in Figure 2.9 contoured temperature plots for 

other transects are in Appendix B. CTD station locations are identified across the top of the 

figure, as well as the position of each data point. The data quality is high. A strong thermocline 

at about the 30-m depth is evident. Maximum temperature in excess of 31o C is seen along this 

transect while the minimum temperature of 5o C is seen only for the deepest stations (see 

Appendix B) and not at all along transect 3. 

2.2.3.2 Salinity 

Contours of salinity along transect 3 are shown in Figures 2.10. Contoured salinity plots for 

other transects are in Appendix B. CTD station locations are identified across the top of the 

figure, as well as the position of each data point. The data quality is, again, high. There is a 

suggestion of coastal upwelling in the data. The following points can be noted in the plots of 

Appendix B. The evidence of a Loop Current intrusion is seen at stations 042 through 045 where 

the salinity exceeds 36.5. A very strong halocline between 5- and 10-m depth is seen in transects 

5 and 6. The maximum surface salinity is seen on transect 1. The minimum surface salinity is 

seen on transect 5. 

2.2.3.3 Density 

Contours of computed potential density anomaly along transect 3 are shown in Figure 2.11. 

Potential density anomaly distributions for other transects are contoured in Appendix B. CTD 
20

Figure 2.7 Temperature Salinity relationship for all CTD stations sampled during R/V 

Gyre cruise 98-G-9. 
21

Figure 2.8 Temperature Salinity relationship for CTD stations along Transect 3 (Figure 

2.6, Stations 14 – 22) sampled during R/V Gyre cruise 98-G-9. 
22

Figure 2.9 Vertical profile of temperature for Transect 3 (Figure 2.6, Stations 14 – 22). 

The contour interval is 1o

C. 
23

Figure 2.10 Vertical profile of salinity for Transect 3 (Figure 2.6, Stations 14 – 22). The 

contour interval is 1.0. 
24

Figure 2.11 Vertical profile of density for Transect 3 (Figure 2.6, Stations 14 – 22). The 

contour interval is 1.0 σθ. 
25

station locations are identified across the top of each figure, as well as the position of each data 

point. The data quality is high. The suggestion of coastal upwelling is, again, evident in this 

plot. A strong density gradient between transects 2 and 3 is quite evident. The minimum surface 

density is seen in transect 5. 

 2.2.3.4 Brunt-Vaisala Frequency 

The Brunt-Vaisala frequency, in cycles per hour (cph), was computed from the temperature and 

salinity profiles. High values are typically found near the surface, where the vertical density 

gradient is the largest. Contours of the Brunt-Vaisala frequency transect 3 are shown in Figure 

2.12. Contour plots of the Brunt-Vaisala frequency along other transects are presented in 

Appendix B. CTD stations locations are identified across the top of each figure, as well as the 

position of each data point. 

 2.2.3.5 Oxygen 

Continuous profiles of dissolved oxygen were measured with a Beckman type polarographic in 

situ oxygen sensor, manufactured by Sensor-Medics, Inc. Mounted in the Sea-Bird SBE-911+ 

CTD, the oxygen sensor was attached to a manifold that permitted active pumping of water past 

the sensor membrane. To maintain sensor stability, care was taken to ensure that the dissolved 

oxygen membrane was not fouled with hydrocarbon contaminants. Between casts, the oxygen 

sensor was flushed and filled with clean water. 

At all of the hydrography stations, with the exception of station 51, bottle titrations were 

performed to determine discrete dissolved oxygen values. This data served as an independent 

means of calibrating the oxygen sensor. Applying a non-linear least-squares regression 

technique, downcast oxygen sensor values were fit to the upcast bottle sample oxygen 

measurements. The calibration was effective for all but 15% of the stations (i.e., stations 35, 36, 

38, 40, 41, 43, 44, and 45.) In these cases, it appears that the oxygen sensor was not properly 

equilibrated before the CTD package was lowered through the water column, resulting in oxygen 

sensor values significantly less than the bottle oxygen values over the top 30 m. 

 

Contours of the calibrated dissolved oxygen concentration along transect 3 are shown in Figure 

2.13. Contour plots of dissolved oxygen concentration for the other transects appear in 

Appendix B. CTD stations locations are identified across the top of each figure, as well as the 

position of each data point. Because there was no bottle data collected for station 51, that station 

is not included. For all other stations, the bottle value and its location are plotted on each figure 

as well. 

 2.2.3.6 Fluorescence 

Continuous profiles of fluorescence were measured using a Chelsea fluorometer. Contoured data 

from transect 3 is shown in Figure 2.14, while that for the remaining transects appears in 

Appendix B. Units are μg/l of chlorophyll. 
26

Figure 2.12 Vertical profile of Brunt-Vaisala frequency for Transect 3 (Figure 2.6, 

Stations 14 – 22). The contour interval is 10 cph. 
27

Figure 2.13 Vertical profile of dissolved oxygen for Transect 3. The contour interval is 

0.5 ml l-1. 
28

Figure 2.14 Vertical profile of fluorescence for Transect 3. The contour interval is 0.20. 
29

 2.2.3.7 Downwelling Irradiance 

Continuous profiles of downwelling irradiance were measured using a Biospherical Instruments, 

Inc. Model QSP-200L irradiance profiling sensor. While the CTD package was on deck, the 

sensor was covered with an opaque cap for protection. Unfortunately, a review of the data 

reveals that the cap was probably not removed for stations 1-4, 8-13, 20-25, 31-36, 42-45, and 

52-53. Contours of downwelling irradiance along transect 3 are presented in Figure 2.15 while 

contoured data from other transects are presented in Appendix B. In each of the figures, the 

following contour levels were used: 0.75, 1.0, 5.0, 10, 50, 100, 500, and 1000, μE/(m2

•s). 

 2.2.3.8 Transmissivity 

The CTD system was equipped with a SeaTech, Inc. 25-cm path length transmissometer to 

provide continuous profiles of percent transmission. The transmissometer lenses were cleaned 

every few stations using distilled water. Contours of transmissivity as recorded by the sensor 

along transect 3 are shown in Figure 2.16. Contours from other sections are presented in 

Appendix B. 

2.2.4 ADCP 

We used the opportunity of cruise 98-G-9 to operate a RDI 150 kHz Broadband ADCP and make 

continuous underway measurements of current velocities beneath the vessel down to a depth of 

about 150 – 200 m. Murphy et al. (1992) have described the mounting of the ADCP on the R/V 

Gyre. Shown in Figure 2.6 is the track line along which the ADCP was operated, though this 

does not imply useful data was obtained everywhere along the line. 

The Broadband ADCP was a “direct reading” model with a four beam, downward looking, 30-

degree convex head arrangement. The offset for the Broadband was set by visually aligning 

beam #3 transducer head with the ship’s longitudinal axis. Any misalignment was corrected 

during post processing. The unit was operated in the bottom-tracking mode, which successfully 

tracked the bottom in depths up to 400 m. The ADCP was controlled by a personal computer 

that also processed and logged the data. Global positioning system navigation data, supplied by 

a separate system, were recorded by the RDI software in separate navigation files, but annotated 

with the ensemble number being collected. This easily allowed the navigation and raw data 

current files to be merged in post processing. The ship’s Sperry gyrocompass was connected to 

the ADCP to provide heading information that was in addition to the GPS navigation data. The 

ADCP was configured as follows in Table 2.2. 
30

Figure 2.15 Vertical profile of radiance for Transect 3. The contour interval is defined in 

the text. There is no data for stations 020, 021, and 022. 
31

Figure 2.16 Vertical profile of transmissivity for Transect 3. The contour interval is 5%. 
32

Table 2.2 

ADCP Configuration Summary 

Parameter 

Instrument Type Broadband 

Frequency (kHz) 153.6 

Transducer pattern Convex 

Depth cell length (m) 4.00 

Number of depth cells 90 

Pings per ensemble 2 water track, 2 bottom track 

Time between pings (s) 2 

First bin depth (m) 14.11 

Transmit pulse length (m) 6.15 

Blank after transmit (m) 4.00 

Navigation type GPS, gyro heading 

Data recorded Raw, averaged, navigation 

 2.2.4.1 Post Processing 

After collection, the undamaged raw data files were converted to a format suitable for post 

processing on a PC using MATLAB computer codes. All of the post processing described below 

was conducted on individual ensembles. We did not take advantage of the RDI processed 

average files. Examining each ensemble significantly increases the amount of data that can be 

used. Post processing required several levels of effort to merge navigation data, determine 

absolute ship velocity with respect to GPS positions, calibrate the offset and alignment of the 

ADCP, calculate current velocity, and remove outliers and suspicious data. The final step in this 

process is the production of ASCII data files containing the data and associated metadata, as well 

as plots of the resulting currents. 

Merging of the Navigational Data

The first step of the post processing is to associate each ADCP ensemble with a valid GPS 

position fix. The RDI software annotates the incoming GPS stream with the current ensemble 

number, which conveniently allows each ensemble to be linked to a GPS position. Occasionally 

the GPS data stream is interrupted and not every ensemble has a valid GPS fix associated with it. 

Those ensembles were subsequently discarded. Of the 32,615 ensembles recorded by the ADCP 

prior to station 42, only 396 ensembles were rejected because they had no navigational data. 

Ship’s Velocity

For a given ensemble with a valid GPS fix, the great circle distance traveled during that 

ensemble is computed from the GPS fix at the beginning of that ensemble to the GPS fix at the 

beginning of the next ensemble. This step is critical in order to calculate the ship’s velocity 

during an ensemble. The ship’s velocity must be subtracted from the raw ADCP measurements 
33

in order to obtain the current velocity. Errors in the ship velocity directly affect the variance in 

the current velocity. 

The set of navigational ship velocities were inspected for any occurrence when the ship speed 

was less than 100 cm s-1, when the ship speed was in excess of 650 cm s-1, when the ship’s 

acceleration exceeded 0.2 cm s-2, or the ship was rapidly changing direction. Over the typical 

10-second period needed to collect an ensemble, an acceleration of 0.2 cm s-2 corresponds to a 1 

cm s-1 change in the ship speed. This variability is carried directly into the determination of the 

current velocity. The rapid change in direction criteria recognizes that the ship’s gyrocompass is 

an electro-mechanical servo system with inertia and, therefore, exhibits lag. Consequently the 

gyro heading does not reflect the true ship’s heading when the ship is rapidly turning. Each of 

these four criteria contributes errors to the final computed water velocity. Data that do not pass 

these requirements were rejected and any ensemble associated with it was rejected from further 

processing. Of the 32,219 ensembles that were processed through this step, 9,859 ensembles 

were rejected for failure to meet these four QC criteria. This left 22,360 ensembles of the 

original 32,615 ensembles that could be used in the following steps. 

Offset and Alignment

The ADCP operated in bottom track mode also provides an estimate of the ship’s velocity when 

the bottom is typically less than 400 m. The subset of data having both bottom-track and 

navigation velocities are used to perform a calibration of the ADCP after the manner of Joyce 

(1989). The errors are of two types: sensitivity and offset. Sensitivity errors arise because the 

orientation of the acoustic beam is not correct due to factors such as nonzero trim of the 

transducer and ship, small errors in the beam geometry, or an overall system bias. Alignment 

errors are caused by a misalignment between the reference frame of the ADCP and the ship’s 

gyro. Joyce (1989) notes that these two errors arise from independent sources and are 

approximately orthogonal to each other. The misalignment causes errors that can be 

considerable in the velocity component perpendicular to the ship’s longitudinal axis, while the 

sensitivity error occurs in the velocity component parallel to the ship. The mean alignment error 

is typically one to two degrees for the R/V Gyre. The mean sensitivity error is usually from 1.01 

to 1.04, so the ADCP data is scaled up by this amount. 

Only those ensembles with valid bottom track velocities and velocities that were sufficiently 

close to the navigational velocities were used in this step. Of the 22,360 ensembles that were 

processed through this step, 1,845 ensembles were not used. Results of the complex regression 

analysis for the bottom-track versus GPS navigation velocities are summarized in Table 2.3. 

Table 2.3 

Complex Regression Analysis 

GPS vs. bottom-track velocity 

Ensembles utilized 20515 

Clockwise regression angle, deg 4.1936 

Sensitivity 0.99987 

Average GPS ship speed, cm s-1 433.97 
34

Calculate Current Velocity

For each ensemble that passed through the ship’s velocity step: 

1. Extract beam velocities from raw data files. 

2. Perform three-level screening: (a) Remove depth cells with bad data flags. (b) 

Remove depth cells with low correlations (< 64) and (c) cells with low percent 

good (< 25%). 

3. Transform beam velocities to earth velocities using the ship’s gyro heading. 

4. Perform three-beam solutions where needed. 

5. Correct earth velocities for alignment and sensitivity error. 

6. Subtract navigational velocities from earth velocities to yield current velocities. 

Ensemble Averaging

In order to reduce the large, but expected, variance in the individual ensemble velocities, 5-

minute averages were constructed from individual, consecutive ensembles. Five minute 

averages, or segments, were constructed for the (a) water column velocities, (b) bottom track 

velocities, (c) navigational ship velocities, (d) ship’s heading, and (e) GPS positions. Secondly 

the side lobe contamination depth for each segment was flagged and the velocities for all depth 

cells below that depth were summarily rejected. 

It was possible to construct 644 5-minute segments from the 22,360 ensembles that were 

successfully processed through the previous step. On average, there were 31 ensembles per 5-

minute segment, with a minimum of 15 and a maximum of 33. In the case of 180 segments, the 

side lobe contamination depth was less than the depth of the first good bin and the entire 

ensemble was rejected. This left 464 segments to process through final quality control. 

Final Quality Control

The final step was to perform a cruise wide quality control check of the velocities. This entailed 

the following two steps: 

1) Remove any segment if the current velocity exceeded 200 cm s-1.

2) Compute the cruise-wide averaged standard deviation for each depth cell and 

 then remove any segment if its velocity exceeded twice the cruise-wide average 

 standard deviation. 

Of the 464 segments processed through this step, 54 were rejected for failing the above two 

criteria. Consequently, of the 32,615 ensembles collected by the ADCP prior to data loss at CTD 

station 42, approximately 39% of the ensembles were acceptable. 

2.2.4.2 Results 

In order to show vertical profiles of velocity along different sections, Figure 2.17 defines 10 

ADCP lines. These are called lines in order to distinguish them from the hydrography transects. 
35

Figure 2.17 ADCP lines used to show vertical profiles. Bathymetric contours are shown for 30-, 5

1,000-m depths. 
36

Specifically, ADCP line 1 overlies hydrography transect 1, ADCP line 2 overlies hydrography 

transect 2, ADCP line 3 overlies hydrography transect 3, ADCP line 5 overlies hydrography 

transect 4, and ADCP line 9 overlies hydrography transect 6. In every case the inshore end of 

the ADCP line does not correspond to the inshore station of the hydrography transect, but 

actually occurs in deeper water. ADCP line 9 was transited three times, yielding results called 

lines 9A, 9B, and 9C. 

Figure 2.18 shows the currents at 14 m. Maps of current vectors at 26, 50, and 102 m are in 

Appendix C. The normal velocity, parallel velocity, and speed for Line 3 are shown in Figures 

2.19 to 2.21. Similar figures for the other lines are in Appendix C. 

2.2.5 Collateral Data 

Sea surface altimetry and computed geostrophic flows for the Gulf of Mexico were obtained 

from the University of Colorado’s Center for Astrodynamics Research. The Center provides 

near real-time and archived maps of the sea surface height or height anomaly with superimposed 

velocity vectors. An analysis product is produced every weekday, based on the latest ten days of 

TOPEX and 17 days of ERS-2 sampling. The analysis TOPEX/ERS-2 for 15 July 1998 (Figure 

2.22) shows an upcoast, geostrophic, flow across the outer shelf on the order of 25-50 cm s-1. 

The TOPEX/ERS-2 satellite image for 1 August 1998 (Figure 2.23) shows the flow direction is 

essentially unchanged, but the velocity is less than 25 cm s-1. 

Sea surface temperatures for the Gulf of Mexico are made available by the Ocean Remote 

Sensing Group of the Johns Hopkins University Applied Physics Laboratory. The Ocean 

Remote Sensing Group records and processes imagery from the Advanced Very High Resolution 

Radiometer (AVHRR) on the NOAA polar orbiting satellites. Multi-day composites for specific 

periods of interest are made available on their website. The AVHRR 3-day composite for 21 

July 1998 (Figure 2.24) clearly shows that the Atchafalaya River plume is turned towards the 

east. 

The National Data Buoy Center (NDBC) owns and maintains a system of buoys and coastal 

monitoring stations that provides, among many other products, wind speed and direction. In 

Figure 2.25 we show the location of 10 specific buoys and the median wind speed and maximum 

likelihood direction for the month of July 1998. It is obvious that winds are upcoast near the 

Mississippi delta and on coast from Brownsville to Galveston. 

2.3 MODELING THE BUOYANCY-DRIVEN FLOW DUE TO 

RIVER DISCHARGE ON THE TEXAS-LOUISIANA CONTINENTAL 

SHELF OF THE GULF OF MEXICO 

The principal objective of the modeling effort was to investigate the basic physical mechanisms 

responsible for the development of the Mississippi-Atchafalaya River plume associated with 

surface wind forcing on the Texas-Louisiana continental shelf. It is well known that the upper 

layer ocean current responds to wind on a short time scale. In an analysis of the coherence 

between winds and sea surface currents on the Texas-Louisiana continental shelf, Cochrane and 

Kelly (1986) and Wang (1996) concluded that the inner-shelf current is strongly coherent with 
37

Figure 2.18 Stick vector plot of ADCP currents measured at the 4-m bin centered at approximately th

Bathymetric contours are shown for 30-, 50-, 100-, and 1,000-m depths. 
38

Figure 2.19 Vertical section of ADCP velocities (cm s-1) normal to line 3 for cruise 98-G-9. 

Upcoast velocities are positive. Ensemble locations are marked with a small 

triangle. 
39

Figure 2.20 Vertical section of ADCP velocities (cm s-1) parallel to line 3 for cruise 98-G-9. 

Onshore velocities are positive. Ensemble locations are marked with a small 

triangle. 
40

Figure 2.21 Vertical section of ADCP speeds (cm s-1) for line 3 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
41

Figure 2.22 TOPEX/ERS-2 composite for 15 July 1998 shows an upcoast flow across the 

outer shelf on the order of 25-30 cm s-1. 
42

Figure 2.23 TOPEX/ERS-2 composite for 1 August 1998 shows an upcoast flow across the 

outer shelf on the order of 25 cm s-1. 
43

Figure 2.24 AVHRR 3-day composite of the Gulf of Mexico for 21 July 1998 shows 

that the Atchafalaya River plume is turned towards the east, due to 

upcoast winds. This image was produced by the Space Oceanography 

Group, Johns Hopkins University, Applied Physics Laboratory. 
44

Figure 2.25 Median wind speed and maximum likelihood direction wind vectors for the month of July 

meteorological stations. NDBC buoy 42019 was not operating during this time period. Mississippi delta region are clearly upcoast. 
45

the along-shore wind component. When the along-shore wind turns upcoast (in the direction 

from the Rio Grande to the Mississippi Delta) from late-June through mid-August, the coastal 

current on the southwestern part of the shelf also turns upcoast and an anticyclonic circulation 

forms over the mid shelf. The right-bounded coastal current near the Mississippi Delta, on 

occasion, disappears during the upcoast wind period. With regards to the data used by Cochrane 

and Kelly (1986) to make their conclusions, it should be mentioned that Dinnel and Wiseman 

(1986) pointed out that the Mississippi and Atchafalaya Rivers had relatively small discharges 

during the 1963-1965 period. It is of interest to study the variability of the summer circulation 

pattern caused by unusual river discharge events such as the summer flood of 1993. In 

particular, the following questions were addressed: 

What is the spatial and temporal structure of the Mississippi-Atchafalaya River 

plumes under different regimes? What physical mechanisms are important in the 

plume front near the river mouth and downstream? 

What is the physical mechanism by which the cross-shelf density front is 

influenced by winds over the inner shelf? 

Does the southwestward along-shore coastal current persist due to the large river 

fluxes during the upcoast wind period during flood conditions? Specifically, how 

did the summer flood of 1993 affect the model-predicted summer circulation 

pattern on the Texas-Louisiana continental shelf? 

To answer these questions, a set of model experiments was conducted to investigate the basic 

physical mechanisms responsible for formation and evolution of the Mississippi-Atchafalaya 

River plumes on the Texas-Louisiana continental shelf. The methods and results are fully 

discussed in Lo (1999); here we present a summary of the relevant findings. 

The numerical model used in this study was a modified version of the Princeton Ocean Model 

(POM), which is a three-dimensional, primitive-equation, estuarine and coastal ocean circulation 

model. The present model applies a 170 × 64 curvilinear orthogonal grid in the horizontal as 

shown in Figure 2.26 and 21 levels with irregular spacing in the vertical direction. In order to 

examine the influence of variable bathymetry on the river plume and buoyancy-driven flow in 

the shelf sea region, the present model utilizes realistic bottom topography and irregular coastline 

geometry for model simulation. 

In summary, the model results of the present study demonstrate that the buoyancy flow induced 

by the river inflow from the Mississippi and Atchafalaya Rivers has a significant impact on the 

circulation over the Texas-Louisiana continental shelf. The major findings of this study are 

given as follows: (1) Consistent with previous studies, such as Chao and Boicourt (1986) and 

Oey and Mellor (1993), freshened bulges are formed near the river mouths and a baroclinic 

boundary current, propagating as a coastal Kelvin-like wave, is developed along the coast toward 

the west. (2) The model results show that the near bottom current flows, opposite to the surface 

current, toward the east in the region near the river mouths, indicating a first baroclinic mode 

structure. (3) An anticyclonic eddy associated with upwelling is found near the head of the 

Mississippi Canyon. The generation mechanism of this eddy is in accordance with the linear 
46

Figure 2.26 The 172 x 66 curvilinear orthogonal model grid of the Texas-Louisiana shelf. The mesh re

km on the inner shelf to 19.7 km near the open boundary. 
47

theory of geostrophic adjustment. (4) The dynamics of the plume front near the river mouths are 

strongly nonlinear, but the flow in the downstream region is geostrophic. (5) The bottom 

boundary layer is an important region in the adjustment of the structure of the cross-shelf front, 

where buoyancy is transported across the shelf near the bottom. (6) The river plume is 

significantly altered by the surface wind stress, especially the along-shore component of wind 

stress. (7) The surface current is primarily dominated by the surface wind stress. The model 

predicts that the right-bounded coastal current completely vanishes during an upcoast wind 

period even where both rivers have extreme inflow such as during the summer flood of 1993. 

To better understand and characterize the basic physical mechanisms and the evolution of the 

Mississippi-Atchafalaya River plume, the first group of model experiments was performed with 

initially homogeneous conditions and the current was mainly driven by the buoyancy or potential 

energy induced by river discharge. Similar to the previous studies, without considering other 

forcing factors such as tides or winds, the model also shows that the effects of the Coriolis force 

play an important role in the river plume dynamics. As freshwater discharges from the river 

mouths onto the shelf, the surface flow turns anticyclonically within the freshened bulge due to 

the Coriolis force. A right-bounded coastal current leaking from the bulge is formed in the 

downstream region, with a width of about 60 km, or about 2~3 Rossby radii. This is shown in 

Figure 2.27. From a diagnostic analysis of the momentum balance, the river plume in the crossshelf direction can be described by linear dynamics in which the flow is a balance between the 

pressure gradient and the Coriolis force terms; i.e., a geostrophic balance. In contrast, in the 

along-shelf direction the flow becomes strongly non-linear within the frontal zone near the river 

mouths in the model. 

The model also reveals the importance of the bottom boundary layer in adjusting the vertical 

structure of the density fields in the cross-shelf direction. The cross-shelf transport near the 

bottom, generated due to bottom friction, is known to be an important mechanism in driving the 

density front across the shelf. The model results illustrate that the vertical structures of the 

density and velocity fields in the region near the river mouths and in the downstream regions are 

very different because of the different direction of the cross-shelf transport produced by bottom 

friction in the bottom boundary layer. In the downstream region, an offshore transport is 

generated in the bottom Ekman layer and causes the water column to be vertically homogeneous 

in the inner shelf. In contrast, in the region near the river mouths, onshore transport is generated 

in the model near the bottom, which is in partial compensation of the offshore transport above 

the bottom boundary layer; the onshore near-bottom flow has a tendency to tilt the density 

contours seaward from bottom to surface. 

One of the important findings of this present study is that the model illustrates a significant 

interaction between the river plume and the Mississippi Canyon. The pressure gradient is built 

up as the offshore current, propagating from the east, approaches the transverse canyon, where 

high pressure occurs in the deep region of the canyon and drives an up-canyon flow. An 

anticyclonic eddy, therefore, is formed near the head of the canyon as a result of geostrophic 

adjustment (Figure 2.28). Although there is no observation to support the model results that an 

anticyclonic circulation is trapped by the Mississippi Canyon, the dynamics of the flow around 

the canyon is generally consistent with other studies of the interaction between a current and a 

canyon (Freeland and Denman 1982; Klinck 1988; Howard 1992). Based on a diagnostic 
48

Figure 2.27 Plan views of the near-surface velocity fields with constant river discharge. 

Snapshots are taken at times (a) 30, (b) 60, and (c) 90 days. For clarity, current 

arrows are plotted at every other grid point. Contours represent bottom 

topography. The sponge layer is not shown. 
49

 

Figure 2.28 Plan view of detailed information of (a) the near surface and (b) the near 

bottom velocity fields in the region between the Mississippi Canyon and 

the Atchafalaya Bay at 90 days. Contours represent bottom topography. 

Heavy solids lines indicate the locations of Sections 3 and 4. 
50

analysis of the vertically integrated vorticity balance, we found that the vortex stretching or 

compression of the water columns mainly determines the vertical motion within the canyon. The 

model predicts that the anticyclonic eddy induces upwelling at the head of the canyon as the flow 

moves from depth onto the shelf along the canyon axis. 

The influence of spatially uniform winds on the preexisting river plume on the Texas-Louisiana 

continental shelf also has been examined. The model results suggest that the river plume is 

significantly altered by the surface wind stress. This is especially so for the along-shore 

component of wind, which generates surface Ekman transport across the shelf and induces strong 

downwelling or upwelling near the shore. For a downwelling-favorable wind, the right-bounded 

coastal current is intensified by converging surface onshore Ekman transport, and the water 

column over the inner shelf becomes vertically homogeneous. In contrast, if the wind is 

upwelling-favorable, the right-bounded coastal current completely vanishes as shown in Figure 

2.29. In addition, a large amount of the plume water is moved across the shelf by the surface 

offshore Ekman transport and a shoreward transport is generated underneath the surface Ekman 

layer to compensate the surface offshore transport. As a result, the stratification of the water 

column in the inner shelf becomes stabilized. The vertical distributions of the salinity and 

velocity fields at Sections 1 and 2 (Figure 2.30) at time t = 30 days after application of the 

downcoast and upcoast wind forcing are presented in Figures 2.31 and 2.32. The model salinity 

results for the upcoast wind (upwelling favorable wind) are consistent with the vertical sections 

of salinity measured during the late July 1998 cruise (Figure 2.10 and Figures B.16 to B.22). 

It is of interest that the model shows the interaction between the buoyancy-drive flow and the 

surface wind stress. First, in the downstream region, the surface current is in agreement with the 

typical Ekman theory, but the surface flow in the region near the river mouths becomes more 

complex because of the interaction of the pressure gradient induced by the river inflow. 

Secondly, the structure of the nearshore vertical velocity in the near field is dominated by the 

buoyancy-driven flow. The model indicates that the nearshore water moves upward in the near 

field for a downwelling-favorable wind. 

An attempt at a short-term model prediction of the circulation on the Texas-Louisiana 

continental shelf during the summer of 1993 was made. The monthly mean surface circulation 

of August shows some differences between the model predictions under spatially uniform winds 

(Figure 2.33) and hourly gridded wind conditions (Figures 2.34 and 2.35). The gridded wind set 

was derived from hourly surface meteorological data taken from 16 NDBC stations during the 

period from July 31 to September 30, 1993, when upcoast winds occur. In comparison with the 

low-frequency circulation scheme given by Cochrane and Kelly (1986), the model result with 

gridded wind forcing is more consistent with past observations. Furthermore, in comparison 

with Figure 2.18, the stick vector plot of ADCP currents measured during late July 1998 at the 

14m depth, the model derived, near-surface velocity field driven by gridded winds, as shown in 

panel (b) of Figure 2.32, is surprisingly consistent. This suggests that the right-bounded coastal 

current completely vanishes during an upcoast wind period, even when both rivers have extreme 

inflow such as caused by the summer flood of 1993. 
51

Figure 2.29 Plan views of the near-surface velocity and salinity fields with constant river 

discharge and winds. Snapshots are taken at time t=30 days after adding (a) 

downcoast and (b) upcoast winds. For clarity, current arrows are plotted at every 

other grid point. Salinity contours are shown at intervals of 1.5‰. The sponge 

layer is not shown. 
52

Figure 2.30 Smoothed bottom topography. Depth contours are in meters. The circles indicate the hydro

of LATEX A cruise H06; crosses indicate the hydrographic stations of LATEX B cruise the wind observing stations. 
53

Figure 2.31 Vertical distributions of salinity (top), along-shelf (second), cross-shelf (third), 

and vertical (bottom) velocities at section 1 at time t=30 days after downcoast 

(left) and upcoast (right) wind forcings. Solid (dashed) contours represent 

upcoast (downcoast) flow in the second panels, shoreward (seaward) flow in 

the third panels, and upward (downward) flow in the bottom panels. 
54

Figure 2.32 Vertical distributions of salinity (top), along-shelf (second), cross-shelf (third), 

and vertical (bottom) velocities at section 2 at time t=30 days after downcoast 

(left) and upcoast (right) wind forcings. Solid (dashed) contours represent 

upcoast (downcoast) flow in the second panels, shoreward (seaward) flow in the 

third panels, and upward (downward) flow in the bottom panels. 
55

Figure 2.33 Plan views of the near-surface velocity fields with spatially uniform winds at (a) 

time t=40 days, of (b) the first 30-day mean (0-30 days) and (c) the second 30-

day mean (30-60 days). For clarity, current arrows are plotted at every other grid 

point. The sponge layer is not shown. 
56

Figure 2.34 Plan view of the surface wind field at time t=40 days. The gridded winds are 

interpolated by using the observed meteorological data of NBDC. For clarity, 

wind vectors are plotted at every other grid point. 
57

Figure 2.35 Plan views of the near-surface velocity fields with gridded winds at (a) time t=40 

days and of (b) the first 30-day mean. For clarity, current arrows are plotted at 

every other grid point. The sponge layer is not shown. 
58

In general, the model results of the present study are in considerable agreement with past and 

present observations and previous model studies. The model results support the hypothesis that 

the river plume structure is primarily modified by local winds. The model experiments with 

spatially and temporally uniform wind indicate that the surface wind stress has a first-order 

impact on the surface current. The river plume structure is significantly altered by the surface 

wind stress, especially the along-shore component of the wind stress. 
59

Chapter 3 

3.0 INTRODUCTION 

The Texas-Louisiana shelf is an area with a constant risk of oil spills. Therefore, knowledge of 

the surface circulation in this area is of particular value. Previous works (Cochrane and Kelly, 

1986; Oey, 1995, Li et al., 1997; Cho et al., 1998) mainly focus on the mid- and outer TexasLouisiana shelf while the Texas-Louisiana inner shelf (shallower than 20 m) has not been fully 

explored. The alongshore current is mainly wind-driven, particularly during winter, and the 

response time of the alongshore current to the alongshore wind is less than one day. Recent work 

(Nowlin et al., 1998) indicates that the variation of the inner shelf circulation is very 

complicated. The coherence between local alongshore wind and alongshore current has large 

spatial and temporal variability, though significant coherence is found in both the weather band 

(2-10 days) and the diurnal band. In general, in the cross-shore direction, the coherence 

decreases with the distance from the coast; in the alongshore direction, the coherence over the 

eastern region of study is lower than over the western region; seasonally, the coherence is higher 

in winter than in the summer stratified season. 

Despite the above findings, several issues involving the relationship of wind and inner shelf flow 

have not been elucidated. One is the structure of the inner shelf circulation: is it simply a 

downcoast (from Louisiana to Texas) branch of the offshore circulation gyre in winter and 

upcoast branch in summer (e.g., Cochrane and Kelly, 1986) or of more complicated structure? 

The second issue is that the mechanisms by which the inner-shelf flow is driven have not been 

fully studied. It is widely regarded that the inner-shelf alongshore flow is dominated by 

alongshore wind forcing. During winter the inner shelf water is well mixed and the balance 

between alongshore wind stress and bottom friction controls the volume of the alongshore flow. 

The balance mechanism was used by Cochrane and Kelly (1986) and Chuang and Wiseman 

(1983) to explain the relationship between observed alongshore wind and current or water level, 

respectively. Linear bottom friction coefficients were estimated. In addition to the local windfriction balance, there are other important mechanisms such as coastal-trapped waves and windinduced downwelling/upwelling. The former is a principle way to propagate non-local effects 

and the latter dominates the cross-shore flow and vertical transport. Current (1996) developed a 

coastal-trapped wave model to simulate the inner-shelf current variability with a scale of 2-10 

days. On average, the model could explain 46% of the total variance of observed alongshore 

current. Thus, there is a large part of the total variance that still cannot be explained by the 

barotropic wind forcing. Spring floods result in a density front, strong along-front geostrophic 

currents, and inhibition of vertical mixing. The resultant strong stratification is enhanced by solar 

heating during summer. The existence of the stratification can significantly influence the inner 

shelf circulation. Wiseman et al. (1997) studied the seasonal and interannual variation of 

stratification over the east Texas-Louisiana shelf (93.5°W-89°W). Strongest stratification is 

observed in spring and summer. In winter, the stratification is disrupted by strong mixing caused 

by storms. The stratification greatly influences the vertical shear of inner shelf currents, 

especially when alongshore wind stress is weak (in summer). This also impacts the coherence 

between wind and current in different seasons (Nowlin et al, 1998). Last, but not least, Loop 

Current rings may have an influence on the inner shelf flow as a boundary forcing. 
60

The influences of these factors are all reflected in the current observations. However, it is a great 

challenge to quantify them. Recent wind and current velocity measurements from the Texas 

Automated Buoy System (TABS) provide a new source of data to study inner-shelf current 

variability in space and time. The subsequent examination of the TABS data shall extend 

existing knowledge, provide new findings, and suggest dynamic explanations of the inner-shelf 

flow variability in this area. 

The objectives of this report are therefore to use TABS data, re-examining previous findings of 

wind-current coherence variability over the Texas-Louisiana inner shelf and exploring the spatial 

structures of the inner shelf circulation (including both mean circulation and coastal trapped 

waves) and the momentum balance. Since wind variations over the Texas-Louisiana inner shelf 

have been well documented (Wang et al., 1996; Nowlin et al., 1998), this chapter will omit 

description of the wind spectrum analyses. The rest of the chapter is organized as follows: 

Chapter 3.1 describes data sources and pre-processing; Chapter 3.2 examines the monthly mean 

inner shelf circulation variability; wind-current coherence analysis is discussed in Chapter 3.3 

and the spatial coherence of currents in Chapter 5. Conclusions and discussions are presented in 

Chapter 3.5. 

3.1 DATA 

Locations of wind and current stations are shown in Figure 3.1. Wind measurements were taken 

from stations SRST2, PTAT2 and 42035 (Figure 3.1). The first two are C-MAN stations and the 

third one is a buoy station maintained by the National Data Buoy Center (NDBC). The heights of 

the anemometers are 14.5 m, 12.5 m and 5.0 m at SRST2, PTAT2, and 42035, respectively. 

Surface current measurements (at 2m depth) were taken from five TABS sites: A, B, C, D and F 

(Figure 3.1). All current meters and wind velocity stations are located near or over the innershelf. 

Daily surface current and wind velocities from 1 April 1995 through 1 April 1998 were used in 

this study. The original data consists of hourly winds and half-hourly currents, downloaded from 

the TABS web site. A 71h low-pass filter (Thompson, 1983) has been applied to the wind and 

current data to remove the tidal and inertial currents. The daily winds and currents are then 

produced by sampling the low-passed data at the middle of each day. The results are shown in 

Figure 3.2a and Figure 3.2b. We interpolate across data gaps shorter than 3 days in the daily time 

series. Larger gaps at wind stations SRST2 and PTAT2 are filled with data from the other, since 

the spatial scale of the wind is large enough to include both stations (Nowlin et al., 1998) and the 

amount of filled data constitutes less than 5% of the total amount of data (Figures 3.2a and 3.2b). 

Minor errors introduced by this data substitution do not influence the results in this paper. After 

the preprocessing there is only one gap in wind data in the record of station 42035 but still 

several gaps in the currents. Continuous data segments shorter than 60 days are not used in this 

study. 
61

Figure 3.1 TABS current-meter mooring and NDBC/CMAN buoy sites over the 

Texas-Louisiana inner shelf. 
62

Figure 3.2a Time series of low-passed daily alongshore currents. 
63

 Figure 3.2b Time series of low-passed daily wind speeds. 
64

Local alongshore and cross-shore coordinate systems are defined as follows: the x axis is parallel 

to the local coastline or isobath and the y axis is directed offshore, thus the positive x axis is 

directed down-coast from Louisiana to Texas. This local coordinate system is applied to both the 

winds and the currents. For currents at A, B and F, winds at SRST2 are assumed to be "local 

winds" and 42035 winds for currents at C and PTAT2 winds for currents at D. 

3.2 SUB-TIDAL INNER-SHELF FLOW VARIABILTY 

3.2.1 Monthly Mean Currents 

 3.2.1.1 Alongshore Current 

The 31-day running average of the low-passed alongshore winds and currents is shown in Figure 

3.3. Substantial spatial variability is observed. Alongshore flow at D is always in phase with the 

alongshore wind. At stations A, B and C, an upcoast wind is associated with downcoast currents 

in April, May and even June in some years. Monthly mean upcoast flow commences 2-3 months 

later than the upcoast wind. This is likely caused by the downcoast pressure gradient force 

related to a suggested geopotential high at 93.5°W and the discharge from the MississippiAtchafalaya River system. The south-southeasterly wind during this season combines with the 

curvature of the coastline to cause an alongshore wind stress convergence, as pointed out by 

Cochrane and Kelly (1986). The convergence of the alongshore wind stress leads to a 

convergence of the alongshore wind driven flow and, consequently, the development of a 

geopotential high. The upcoast wind must overcome the downcoast pressure gradient force 

before upcoast flow can occur. 

Downcoast flow commences, in the records, around late August or the beginning of September, 

in phase with the downcoast wind. The downcoast wind and flow are in phase until mid-March 

or April when alongshore winds begin to change direction. For the monthly low-passed innershelf alongshore flow at A, 46% of its variance can be explained by the alongshore wind forcing; 

this value is 79% at D and 38% at F. 

There are extended periods when the alongshore flow is out of phase with the alongshore wind, 

such as autumn 1995 at C and mid-November 1996 until the end of May 1997 at B. During these 

periods, alongshore flow at other stations is still in phase with the alongshore wind. This 

suggests a local circulation around A, B, C and F during these times. It is very interesting that 

starting from mid-November 1996, alongshore flow at A, which is upstream of B, increases 

significantly. This is not due to the local wind forcing (Figure 3.3). The strong alongshore flow, 

however, can result in convergence in a coastal area with converging isobaths, such as around B 

and C, thus provoking local circulations. It is worthwhile to explore whether this alongshore flow 

at A could cause the flow at B moving in the opposite direction to the wind. 

3.2.1.2 Cross-Shore Current 

The 31-day running average of the low-passed alongshore winds and cross-shore currents are 

shown in Figure 3.4. In general the cross-shore flow is out of phase with the alongshore wind at 
65

Figure 3.3 31-day running-average of the alongshore currents (solid line) and 

alongshore winds (dotted line). 
66

Figure 3.4 31-day running-average of the cross-shore currents (solid line) and alongshore 

winds (dotted line). 
67

all stations, i.e., offshore flow from May to August and onshore flow from September to April. 

This is consistent with wind-forced upwelling and downwelling (Gill, 1982). During AprilAugust, the cross-shore flow response to the upcoast wind is less than during the downcoast 

wind periods at B and F. The reason is that there exists an onshore component of the flow in 

balance with the downcoast pressure gradient force. This will be further discussed in Chapter 

3.3. 

3.3 WIND-CURRENT COHERENCE ANALYSIS 

3.3.1 Alongshore Wind-Current Correlation 

 3.3.1.1 Dominant Correlation Patterns

Bimonthly linear correlation coefficients are estimated at each station between the low-passed 

alongshore winds and alongshore currents (Figure 3.5). The 95% significance level is also 

shown. The number of equivalent degrees of freedom is 29. The dominant feature in Figure 3.5 

is the difference between winter and summer correlation patterns. Downcoast currents driven by 

downcoast winds characterize the winter pattern. The winds and flow are positively correlated. 

While this pattern is mainly found in winter, it sometimes occurs in spring and autumn. The 

summer pattern is characterized by upcoast flow driven by an upcoast wind, again resulting in 

positive correlation. It is apparent, in Figure 3.5, that the correlation during summer is weaker 

than during the winter at most stations. This is partly due to the effects of strong stratification. 

This is consistent with previous findings (Nowlin et al., 1998). The pattern is strongest at station 

D and weakest at B. No significant correlation is found from October 1997 until April 1998 at B 

(Figure 3.5). 

3.3.1.2 Transient Correlation Patterns 

In addition to the two principle patterns some new features have been found. One is a transition 

correlation pattern, which is characterized by mean upcoast winds together with mean downcoast 

currents (Figure 3.3). The alongshore winds and currents are positively correlated, which means 

that the downcoast wind variations always strengthen the downcoast flow variations. This 

pattern, mainly found during the transient months between winter and summer, i.e., April, May 

and August, suggests a non-locally wind-driven downcoast mean flow over the inner shelf. The 

downcoast flow is consistent with a geopotential high around 93.5°W, related to the alongshore 

wind stress convergence and associated flow convergence, as suggested in Chapter 3.2. The 

transition pattern is found at A, B, C, and F, but not D. This suggests that the hypothesized nonlocally wind-driven downcoast flow does not extend to the down-stream area around station D. 

3.3.1.3 Negative Correlation Patterns 

Another feature is the occasional occurrence of negative correlations at B, C, and D. The 

alongshore winds are negatively correlated with the alongshore currents from November 1996 

thru May 1997 at B, September 1995 thru November 1995 at C, and June 1996 thru July 1996 at 
68

Figure 3.5 Bimonthly correlation coefficients between alongshore winds and alongshore 

currents for five current meter stations. 
69

D. The time scale of the negative correlation varies from 1 month at D to 6 months at B. The 

correlation coefficients are -0.57, -0.71 and -0.56 at B, C and D, respectively. The correlations 

are significant at a level of 99.9% at B and C, and at 95% at D. Negative correlation is only 

found locally; other stations still exhibit normal positive correlation. At B and C, the alongshore 

flow moves in the opposite direction to the wind, i.e., the stronger the downcoast wind, the 

stronger the upcoast flow. A local circulation around A, C, F and B is suggested during the 

negative correlation periods. A possible forcing mechanism has been discussed above. At D, the 

stronger upcoast flow is related to a weaker upcoast wind, which is contrary to a local wind 

forcing mechanism. Isolation of the cause of this response is not possible given the present 

limited data coverage. 

3.4 ALONGSHORE WIND – CROSS-SHORE CURRENT CORRELATION 

Significant correlation is found between the alongshore winds and cross-shore currents at all 

stations. This is in contrast with Nowlin et al. (1998), who found no significant coherence 

between the alongshore winds and cross-shore currents in the weather band. Figure 3.6 shows the 

bimonthly correlation coefficients for the current stations. The correlations shown in Figure 3.6 

are even greater than that between the alongshore wind and current (Figure 3.3) during some 

periods. For example, at B, the correlation between alongshore wind and cross-shore current is 

significant from October 1997 through April 1998, though the alongshore wind-current 

correlation is not. 

3.4.1 Dominant Correlation Patterns 

Similar to the correlations between alongshore wind and alongshore current, winter and summer 

patterns are identified as two distinct principal correlation patterns. The former is characterized 

by downcoast winds and onshore currents and the latter by upcoast winds and offshore currents 

(Figure 3.4). The alongshore winds and cross-shore currents are negatively correlated, which 

means that the downcoast winds always strengthen the onshore currents and upcoast winds 

strengthen the offshore currents, consistent with wind-forced down/upwelling near shore (Gill, 

1982). The winter pattern prevails in non-summer months and the summer pattern prevails only 

in the summer months (June - July). 

3.4.2 Transition Correlation Patterns 

In the transition months between the winter and the summer, the correlation is still negative but 

mean cross-shore currents are onshore while mean winds are upcoast. This pattern is particularly 

clear at B during April, May, August and September. This is because the negative alongshore 

wind stress has to overcome the alongshore pressure gradient force associated with the 

hypothesized geopotential high near 93.5°W and the buoyancy-driven flow from the MississippiAtchafalaya River system before generating the offshore flow. 
70

Figure 3.6 Same as in Figure 3.5 but for alongshore winds and cross-shore currents. 
71

3.4.3 Positive Correlation Patterns 

Positive correlation between the alongshore winds and cross-shore currents is found at B during 

the same period as the negative correlation between alongshore wind and alongshore current. 

This means that downcoast winds always strengthen the offshore currents at B, in contrast to a 

local wind forcing mechanism. The possible reason for this has been discussed in Chapter 3.2. 

3.5 COHERENCE STUDY 

The wind-current relationship can also be studied in the frequency domain. Coherence squared 

estimates between alongshore wind and alongshore and cross-shelf flow are estimated for 

summer (June-August), winter (October-March) and transition seasons (April, May, August and 

September). A block-averaging method (Emery and Thompson, 1997) is used. For a given 

station, the current time-series is first divided into 3 categories, i.e., summer, winter and 

transition. Then the data in each category are divided into several blocks, with 90-day data 

blocks for the winter and the summer and 60-day blocks for the transient season. Up to 50% data 

overlap is applied to some winter and summer data. The coherence squared is estimated by using 

averaged covariance spectra and energy density spectra of the two components. A Hanning 

window is applied in the computation. The 95% significance level for the coherence-squared 

estimates is calculated as: 

γ= 1 - α[1/(EDOF - 1]

where α = 0.05 and EDOF is the equivalent degrees of freedom, determined by the number of 

blocks and the method of spectrum smoothing (Emery and Thompson, 1997). In the calculation, 

the periods of negative correlation between alongshore wind and current (Chapter 3.3.1.3) were 

not used. 

Figure 3.7 shows examples of the block-averaged coherence squared between alongshore wind 

and alongshore currents in summer, winter and the transition season at B and D. Figure 3.8 

shows the same but for alongshore wind stress and cross-shore currents. Since a 71-h low-pass 

filter has been used to produce daily time series, the coherence analysis should only focus on the 

time scale longer than 3 days. Considering that the current response time scale to alongshore 

winds is less than one day, the coherence phases are not shown here. 

3.6 COHERENCE BETWEEN ALONGSHORE WINDS 

AND ALONGSHORE CURRENTS 

During winter (Figure 3.7), significant coherence between alongshore winds and alongshore 

currents is found in all bands between 3 and 30 days for D and F. At A, B and C, however, the 

bands of significant coherence are gappy. The coherence is only significant in the 6-20 day band 

at A, the 4-7 and 13-30 day bands at B, and the 4-7 and 9-30 day bands at C. The peak coherence 

is around 5-6 days and 10 days, i.e. within the weather band. A common feature, though, is that 
72

Figure 3.7 Block-averaged coherence-squared between alongshore flow and alongshore 

winds in different seasons at B and D. The solid line is the 95% significance 

level. 
73

Figure 3.8 Same as in Figure 3.7 except for alongshore winds and cross-shore currents. 
74

the significant coherence extends outside the weather band to low frequency. In summer, the 

coherence decreases and significant coherence bands become narrow and lower at all stations 

except C. Significant coherence is found in the 4-9 day band at A, the 6-9 day band at B, the 4-5 

day and 6-13 day bands at C, the 4-5 and 8-10 day bands at D, and the 4 day and 7-9 day bands 

at F. Coherence peaks are found around 4 days and 9 days at most stations. The coherence in the 

transition season is also weaker than in the winter. In this season, station F exhibits the strongest 

coherence, which is significant in all bands longer than 3 days. Significant coherence is also 

found in the 3-10 day band at C, the 4-10 day band at D, around 5 days at A and B, and at 

periods longer than 12 days at A. 

3.7 COHERENCE BETWEEN ALONGSHORE WINDS 

AND CROSS-SHORE CURRENTS 

Significant coherence between alongshore winds and cross-shore currents in winter (Figure 3.8) 

occurs in all bands longer than 3 days at station D, in the 5-20 day band at A, the 4-9 and 13-30 

day bands at B, the 4 and 9 day bands at C, and the 3-11 day band at F. In summer, the coherence 

varies greatly with location. At D, all bands except near five-day periods exhibit significant 

coherence. At B no significant coherence is found except for a narrow band around 12 day 

periods. At C, significant coherence occurs at periods longer than 10 days, and at F at periods of 

8-14 days. Reduced gravity wave theory in a two-layer stratified ocean (Gill, 1982) predicts that 

cross-shore flow induced by alongshore winds is related to distance from the coastline and the 

stratification. The space-dependent coherence between alongshore winds and cross-shore flow 

over the Texas-Louisiana inner shelf should be related to the local stratification, which is very 

complicated (Wiseman, et al., 1997) and beyond the scope of this work. 

3.8 SPATIAL COHERENCE OF CURRENTS 

One way to isolate possible coastal trapped wave signals and other kinds of alongshore 

propagating signals is to have recourse to the spatial coherence of the alongshore flow. We chose 

to compare stations B and D. These stations have the longest time series and both are located 

along the 18m isobath. Figure 3.9 presents the coherence squared and phase estimates between 

alongshore flow at B and D. In winter, alongshore flow at B is highly coherent with the 

alongshore flow at D at periods longer than 4.5 days. The phase relationship shows that 

alongshore flow at D leads that at B. The lead is about 1.3 days at the coherence peak near 30 

days and about zero at the other peak near 7 days. The in-phase coherence at seven days is 

caused by large scale wind forcing, but an upcoast propagation with a scale of 30 days is hard to 

explain. The phase relationship is contrary to that predicted by coastal-trapped wave theory. 

There are two coherence peaks in summer. One, near 10-day periods, exhibits an in-phase 

relationship and the other, very weak, peak occurs near 4.3 days, where alongshore flow at B 

leads that at D by about 50°, i.e., 14 hours. Again, the in-phase relationship at 10 days is caused 

by the large scale wind forcing. The downcoast propagation at 4.3 day periods has a phase speed 

of 3.7 m/s. This speed is similar to that of the first mode of a wind-forced barotropic coastal 

trapped wave (Brink and Allen, 1978), which is about 4.3 m/s. 
75

 

Figure 3.9 Coherence-squared and phase relationship of alongshore flow between B and D 

during the winter, summer and transition seasons, positive phase means B leads 

D. The solid line is the 95% significance level. 
76

The coherence in the transition season also exhibits two weak peaks: one at about 8.5 days with 

D leading B by about 5.4 hours and the other at 5.5 days with B leading D by about 6.4 hours. 

The former is, again, difficult to explain as the phase propagation is opposite to long coastally 

trapped waves. The latter suggests a phase speed of 1.7 m/s, which is comparable to that of a 

second mode wind-forced barotropic coastal-trapped wave (Brink and Allen, 1978). As with the 

summer coherence peak near 4.3 day periods, the significance of these coherence peaks is small. 

Longer records will be required to establish the existence of important propagating signals in this 

highly frictional environment. It should be noted, though, that Current (1996) successfully 

modeled a significant percentage of the inner shelf low-frequency flow using a wind-driven 

coastal trapped wave model. 

3.9 CONCLUSIONS AND DISCUSSIONS 

TABS buoy data obtained from April 1995 to March 1998 have been used to verify previous 

findings and explore new features of the subtidal circulation over the Texas-Louisiana innershelf and its response to wind forcing. General winter and summer coherence/correlation patterns 

are consistent with prior conclusions. From September to March, downcoast wind and downcoast 

flow prevail. These are positively correlated. During summer, upcoast wind and flow prevail. 

They are also positively correlated. In the upstream area near the Texas-Louisiana border, about 

42% of the monthly alongshore flow variance can be explained by the alongshore wind forcing, 

but 79% at station D further south. In general, correlation between the two signals is weaker in 

summer than that in winter. 

Some additional points have been suggested. During the upcoast wind period, i.e., April-August, 

the upcoast flow starts rather late (July) near the Texas-Louisiana border. We suggest that this is 

because the upcoast wind must overcome a downcoast pressure gradient force related to riverine 

discharge in Louisiana waters and a suggested geopotential high near 93.5°W. The high is 

mainly caused by the alongshore wind-driven convergence due to the curvature of the coastline. 

Alongshore flow at station D further south, however, is in-phase with the upcoast wind. 

Significant negative correlation is observed, during some periods, between the alongshore wind 

and current, implying flow variations moving in opposition to the wind variations. These 

correlations are local. The case at station B is of particular interest because positive correlation 

is found between the alongshore wind and cross-shore current during the same period and 

because of the extended duration of the event. This suggests a local circulation near station B. 

Simultaneous, strong alongshore flow at A, interacting with converging isobaths, can cause 

convergence and enhancement of the suggested local geopotential high , which drives a local 

circulation. 

Significant negative correlation exists between alongshore wind and cross-shore flow, consistent 

with wind-induced upwelling/downwelling theory (Gill, 1982). The spatial variation of this 

correlation is large in the summer and transition seasons, suggesting the importance of local 

stratification. 
77

Alongshore spatial coherence was analyzed to investigate the alongshore propagation of the 

coastal waves. Three kinds of coherence/phase relations were found. One is an in-phase 

relationship at 7 day periods in winter and 10 day periods in summer, resulting from the 

alongshore flow response to large scale alongshore wind forcing. The second is an apparent 

upcoast propagation near 30-day periods in winter and 8.5-day periods in the transition season. 

The reason for the apparent upcoast propagation is not clear. The third is downcoast propagation 

near 4.3 day periods in summer and 5.5 day periods during the transition season. The coherence 

is barely significant at the 95% level and further analysis has not been pursued, although it is 

noted that the inferred phase speeds are consistent with barotropic coastal trapped wave theory 

(Brink and Allen, 1978). 

For the alongshore wind and alongshore flow, significant coherence occurred at most periods 

longer than 3 days in winter. The coherence peaks occurred near 5-6 days and 10 days. The 

coherence in summer and the transition seasons was lower and the bands of significant coherence 

became narrower. Coherence peaks occurred near 4 and 9 day periods in summer. The spatial 

variability of the coherence in summer was large. 

Significant coherence was also found between the alongshore wind and the cross-shore flow in 

bands from 3-30 day periods at different stations. In winter, a 4-9 day band of significant 

coherence was common. In summer, more spatial variability of the coherence was found than in 

winter. 

The results of these analyses, thus, indicate both significant spatial and temporal variability in the 

response of currents along the Texas-Louisiana inner shelf to wind forcing and the fact that a 

local, linear relationship between the two fields does not explain all the observed variability in 

the currents. The role of upstream river discharge and local flow convergence have been 

suggested as important contributors to this variability. The importance of local 

upwelling/downwelling was confirmed. Further advancement in understanding of the shelf flows 

in this complex environment awaits the acquisition of longer time-series and data from more 

focused process experiments. 
79

Chapter 4 

4.0 CONCLUSIONS 

The efforts of the scientists at Texas A&M’s Geochemical Environmental Research Group 

resulted in the deployment of a TABS buoy over the inner shelf of Louisiana and its maintenance 

from July 1998 to February 2000. Despite typical problems with biofouling and instrument 

failure, extended periods of quality controlled data recovery occurred and the data reported from 

this buoy through the TABS communication network were posted on the TABS web site in real 

time. 

These data add to the growing database of inner shelf flows that are available for the study of 

pollutant transport along this important region of U.S. coastline. Furthermore, the ancillary data 

collected during the cruise of the R/V Gyre used to deploy the buoy also add to the data set. 

Texas A&M has a long history of modeling the circulation in the Gulf of Mexico and over its 

shelves, e.g. Lewis and Reid (1985). The spectral model developed by Current (1996) clearly 

demonstrates the skill that a model of inner shelf currents might produce in forecasting flows 

when upstream boundary conditions, such as could be produced by an array of current meter 

moorings reporting in real time are provided. The excellent results produced by this model were, 

though, confined to the barotropic flows. The strong stratification present over the LATEX 

shelf region during much of the year suggests the importance of fully three-dimensional effects. 

The initial modeling results presented at the end of Chapter 2 represent the first steps towards 

development of such a model, which would then be able to assimilate the real time data provided 

by observing arrays such as TABS. 

The usefulness of such observing arrays for operational programs is already demonstrated and 

justifies the continued maintenance of the system by the Texas General Land Office. The 

usefulness of the data sets being collected and stored at Texas A&M for scientific studies is 

demonstrated by the analyses of historical TABS data presented in Chapter 3. These analyses 

have allowed: 

• Confirmation of the findings of Nowlin et al. (1998) regarding the 

seasonal coherence relationships between local winds and currents. 

• Identification of strong cross-shore flow patterns consistent with 

upwelling theory. (Previous studies had been unable to identify such 

strong signals because of the depths at which moored inner shelf current 

meters are typically deployed.) 

• Identification of marginally significant signatures of longshore 

propagating flow features consistent with coastally-trapped wave theory 

(Brink and Allen, 1978). 

• Development of the hypothesis that there exists a seasonal geopotential 

high near 93o W, forced by the convergence of wind-driven flows from the 

southwest and riverine-driven flows from the east, which is used to 

explain the very low-frequency patterns of flow. 
80

When this effort was initially proposed, it was the intention that the results would be used to 

promote continued funding of an extended TABS array into coastal Louisiana waters. Since that 

time, the WAVCIS array of anemometers, pressure cells, and bottom-mounted acoustic Doppler 

current meters (http://wavcis.csi.lsu.edu/introd.html; Stone and Zhang, 2000) has been developed 

and planned expansions include western Louisiana waters. The full water column coverage 

available from this program, as well as the ability to obtain wave characteristics (the purpose for 

which it was originally designed), have convinced us that expansion of this array should be 

pursued for Louisiana waters. The data from the two systems, both of which report in real-time, 

can be easily coupled in any coastal ocean observing network and assimilated into developing 

models. 

4.1 ACKNOWLEDGMENTS 

This work was supported by the Minerals Management Service, U.S. Department of the Interior, 

under MMS agreement No. 14-12-0001-30660, Task Order 19943. Computer facilities and 

support were provided by the Center for Coastal Physical Oceanography, Old Dominion 

University. Data were kindly made available by the Geochemical and Environmental Research 

Group at Texas A&M University, College Station, TX. 
81

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83

Appendix A 

Time Series Plots of Data Collected at TABS Buoy Site P 
85

 

Figure A.1. Time series plot of Buoy P current velocity and water temperature collected during 

July 1998. 
86

Figure A.2 Time series plot of Buoy P current velocity and water temperature collected 

during August 1998. 
87

Figure A.3 Time series plot of Buoy P current velocity and water temperature collected 

during September 1998. Velocity data after 8 September 1998 are considered 

bad, though the temperature record is still reliable. 
88

Figure A.4 Time series plot of Buoy P current velocity and water temperature collected 

during October 1998. Velocity data after 8 September 1998 are considered bad, 

though the temperature record is still reliable. 
89

Figure A.5 Time series plot of current velocity and water temperature from Buoy P during 

November 1998. Except for brief periods, velocity data after 8 September 1998 

are considered bad, though the temperature record is still reliable. 
90

Figure A.6 Time series plot of current velocity and water temperature from Buoy P during 

March 1999. 
91

Figure A.7 Time series plot of current velocity and water temperature from Buoy P during 

April 1999. 
92

Figure A.8 Time series plot of current velocity and water temperature from Buoy P during 

 May 1999. 
93

Figure A.9 Time series plot of current velocity and water temperature from Buoy P during 

June 1999. 
94

Figure A.8 Time series plot of current velocity and water temperature from Buoy P during 

May 1999. 

Figure A.10 Time series plot of current velocity and water temperature from Buoy P during 

July 1999. Gaps in the velocity record are due to bad data. 
95

Figure A.11 Time series plot of current velocity and water temperature from Buoy P during 

August 1999. 
96

Figure A.12 Time series plot of current velocity and water temperature from Buoy P during 

September 1999. 
97

Figure A.13 Time series plot of current velocity and water temperature from Buoy P during 

October 1999. 
98

Figure A.14 Time series plot of current velocity and water temperature from Buoy P during 

November 1999. Gaps in the velocity record are due to bad data. 
99

Figure A.15 Time series plot of current velocity and water temperature from Buoy P during 

December 1999. 
100

Figure A.16 Time series plot of Buoy P current velocity and water temperature collected 

during January 2000. Gaps in the velocity record are due to bad data. 
101

Figure A.17 Time series plot of Buoy P current velocity and water temperature collected 

during February 2000. Gaps in the velocity record are due to bad data. 
103

Appendix B 

Hydrographic Data Collected During R/V Gyre 

Cruise 98-G-9: Temperature-Salinity Plots and Vertical 

Sections 
105

Figure B.1 Temperature Salinity relationship for CTD stations along Transect 1 sampled 

during R/V Gyre cruise 98-G-9. 
106

Figure B.2 Temperature Salinity relationship for CTD stations along Transect 2 sampled 

during R/V Gyre cruise 98-G-9. 
107

Figure B.3 Temperature Salinity relationship for CTD stations along Transect 4 sampled 

during R/V Gyre cruise 98-G-9. 
108

Figure B.4 Temperature Salinity relationship for CTD stations along Transect 5 sampled 

during R/V Gyre cruise 98-G-9. 
109

Figure B.5 Temperature Salinity relationship for CTD stations along Transect 6 sampled 

during R/V Gyre cruise 98-G-9. 
110

Figure B.6 Temperature Salinity relationship for CTD stations along Transect 7A 

sampled during R/V Gyre cruise 98-G-9. 
111

Figure B.7 Temperature Salinity relationship for CTD stations along Transect 7B 

sampled during R/V Gyre cruise 98-G-9. 
112

Figure B.8 Temperature Salinity relationship for offshore CTD stations sampled during 

R/V Gyre cruise 98-G-9. 
113

Figure B.9 Vertical profile of temperature for Transect 1. The contour interval is 1oC. 
114

Figure B.10 Vertical profile of temperature for Transect 2. The contour interval is 1oC. 
115

Figure B.11 Vertical profile of temperature for Transect 4. The contour interval is 1oC. 
116

Figure B.12 Vertical profile of temperature for Transect 5. The contour interval is 1oC. 
117

Figure B.13 Vertical profile of temperature for Transect 6. The contour interval is 2oC. 

Note the strong thermocline between the 30 and 50m depth. 
118

Figure B.14 Vertical profile of temperature for Transect 7A. The contour interval is 4oC. 

Note the strong thermocline between the 30 and 50m depth. 
119

Figure B.15 Vertical profile of temperature for Transect 7B. The contour interval is 4oC. 
120

Figure B.16 Vertical profile of salinity for Transect 1. The contour interval is 0.25. 

Note the indication of a possible surface salinity front between stations 005 
121

Figure B.17 Vertical profile of salinity for Transect 2. The contour interval is 0.50. 
122

Figure B.18 Vertical profile of salinity for Transect 4. The contour interval is 1.0. 
123

Figure B.19 Vertical profile of salinity for Transect 5. The contour interval is 1.0. 
124

Figure B.20 Vertical profile of salinity for Transect 6. The contour interval is 1.0. 
125

Figure B.21 Vertical profile of salinity for Transect 7A. The contour interval is 1.0. Note 

the presence of a Loop Current intrusion, S > 36.5. 
126

Figure B.22 Vertical profile of salinity for Transect 7B. The contour interval is 1.0. 
127

Figure B.23 Vertical profile of density for Transect 1. The contour interval is 0.5 σθ. 
128

Figure B.24 Vertical profile of density for Transect 2. The contour interval is 1.0 σθ. 
129

Figure B.25 Vertical profile of density for Transect 4. The contour interval is 1.0 σθ. 
130

Figure B.26 Vertical profile of density for Transect 5. The contour interval is 1.0 σθ. 
131

Figure B.27 Vertical profile of density for Transect 6. The contour interval is 2.0 σθ. 
132

Figure B.28 Vertical profile of density for Transect 7A. The contour interval is 1.0 σθ. 
133

Figure B.29 Vertical profile of density for Transect 7B. The contour interval is 2.0 σθ. 
134

Figure B.30 Vertical profile of Brunt-Vaisala frequency for Transect 1. The contour 

interval is 5 cph. Evidence of a strong stability layer is seen at 10m. 
135

Figure B.31. Vertical profile of Brunt-Vaisala frequency for Transect 2. The contour 

interval is 10 cph. Evidence of a strong stability layer is seen at 15m. 
136

Figure B.32 Vertical profile of Brunt-Vaisala frequency for Transect 4. The contour 

interval is 10 cph. 
137

Figure B.33 Vertical profile of Brunt-Vaisala frequency for Transect 5. The contour 

interval is 10 cph. 
138

Figure B.34 Vertical profile of Brunt-Vaisala frequency for Trsansect 6. The contour 

interval is 10 cph. 
139

Figure B.35 Vertical profile of Brunt-Vaisala frequency for Transect 7A. The contour 

interval is 5 cph. 
140

Figure B.36 Vertical profile of Brunt-Vaisala frequency for Transect 7B. The contour 

interval is 10 cph. Evidence of a strong stability layer is seen at the surface. 
141

Figure B.37 Vertical profile of dissolved oxygen for Transect 1. The contour interval is 

0.25 ml l-1. 
142

Figure B.38 Vertical profile of dissolved oxygen for Transect 2. The contour interval is 0.5 

ml l-1. 
143

Figure B.39 Vertical profile of dissolved oxygen for Transect 4. The contour interval is 

0.25 ml l-1. 
144

Figure B.40 Vertical profile of dissolved oxygen for Transect 5. The contour interval is 

1.0 ml l-1. 
145

Figure B.41 Vertical profile of dissolved oxygen for Transect 6. The contour interval is 

0.5 ml l-1. Note the oxygen minimum seen at station 036. 
146

Figure B.42 Vertical profile of dissolved oxygen for Transect 7A. The contour interval is 

0.25 ml l-1. Note the oxygen minimum seen between 300 and 400 m depth 

that is associated with a maximum in the NO3 concentration. 
147

Figure B.43 Vertical profile of dissolved oxygen for Transect 7B. The contour interval is 

0.25 ml l-1. 
148

Figure B.44 Vertical profile of fluorescence for Transect 1. The contour interval is 0.05. 

Fluorescence 
149

Fluorescence 

Figure B.45 Vertical profile of fluorescence for Transect 2. The contour interval is 0.20. 
150

Fluorescence 

Figure B.46 Vertical profile of fluorescence for Transect 4. The contour interval is 0.10. 
151

Fluorescence 

Figure B.47 Vertical profile of fluorescence for Transect 5. The contour interval is 0.1. 
152

Fluorescence 

Figure B.48 Vertical profile of fluorescence for Transect 6. The contour interval is 0.10. 
153

Fluorescence 

Figure B.49 Vertical profile of fluorescence for Transect 7A. The contour interval is 0.05. 
154

Fluorescence 

Figure B.50 Vertical profile of fluorescence for Transect 7B. The contour interval is 1.0. 
155

Figure B.51 Vertical profile of radiance for Transect 1. The contour interval is defined in 

the text. There is no data for stations 001, 002, 003 and 004. 
156

Figure B.52 Vertical profile of radiance for Transect 4. The contour interval is defined in 

the text. There is no data for stations 023, 024, and 025. 
157

Figure B.53 Vertical profile of radiance for Transect 5. The contour interval is defined in 

the text. There is no data for stations 020, 021, and 022. 
158

Figure B.54 Vertical profile of radiance for Transect 6. The contour interval is defined in 

the text. There is no data for stations 031, 032, 033, 035, and 036. 
159

Figure B.55 Vertical profile of radiance for Transect 7A. The contour interval is defined 

in the text. There is no data for stations 042, 043, 044, and 045. 
160

Figure B.56 Vertical profile of radiance for Transect 7B. The contour interval is defined 

in the text. There is no data for stations 052 and 053. 
161

Figure B.57 Vertical profile of transmissivity for Transect 1. The contour interval is 5%. 
162

Figure B.58 Vertical profile of transmissivity for Transect 2. The contour interval is 5%. 
163

Figure B.59 Vertical profile of transmissivity for Transect 4. The contour interval is 5%. 
164

Figure B.60 Vertical profile of transmissivity for Transect 5. The contour interval is 5%. 
165

Figure B.61 Vertical profile of transmissivity for Transect 6. The contour interval is 5%. 
166

Figure B.62 Vertical profile of transmissivity for Transect 7A. The contour interval is 5%.
167

Figure B.63 Vertical profile of transmissivity for Transect 7B. The contour interval is 5%
169

Appendix C 

Maps and Vertical Sections of ADCP Data Collected During 

R/V Gyre Cruise 98-G-9 
171

Figure C.1 Stick vector plot of ADCP currents measured at the 4-m bin centered at approximately the 26-m depth. 

Bathymetric contours are shown for 30-, 50-, 100-, and 1,000-m depths. 
172

Figure C.2 Stick vector plot of ADCP currents measured at the 4-m bin centered at approximately the 50-m depth. 

Bathymetric contours are shown for 30-, 50-, 100-, and 1,000-m depths. 
173

Figure C.3 Stick vector plot of ADCP currents measured at the 4-m bin centered at approximately the 102-m depth. 

Bathymetric contours are shown for 30-, 50-, 100-, and 1,000-m depths. 
174

Figure C.4 ADCP lines used to show vertical profiles. Bathymetric contours are shown for 30-, 50-, 100-, and 1,000-m 
175

Figure C.5 Vertical section of ADCP velocities (cm s-1) normal to Line 1 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
176

Figure C.6 Vertical section of ADCP velocities (cm s-1) parallel to Line 1 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
177

Figure C.7 Vertical section of ADCP speeds (cm s-1) for Line 1 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
178

Figure C.8 Vertical section of ADCP velocities (cm s-1) normal to Line 2 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
179

Figure C.9 Vertical section of ADCP velocities (cm s-1) parallel to Line 2 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
180

Figure C.10 Vertical section of ADCP speeds (cm s-1) for Line 2 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
181

Figure C.11 Vertical section of ADCP velocities (cm s-1) normal to Line 4 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
182

Figure C.12 Vertical section of ADCP velocities (cm s-1) parallel to Line 4 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
183

Figure C.13 Vertical section of ADCP speeds (cm s-1) for Line 4 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
184

Figure C.14 Vertical section of ADCP velocities (cm s-1) normal to Line 5 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with 

a small triangle. 
185

Figure C.15 Vertical section of ADCP velocities (cm s-1) parallel to Line 5 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
186

Figure C.16 Vertical section of ADCP speeds (cm s-1) for Line 5 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
187

Figure C.17 Vertical section of ADCP velocities (cm s-1) normal to Line 6 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
188

Figure C.18 Vertical section of ADCP velocities (cm s-1) parallel to Line 6 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
189

Figure C.19 Vertical section of ADCP speeds (cm s-1) for Line 6 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
190

Figure C.20 Vertical section of ADCP velocities (cm s-1) normal to Line 7 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
191

Figure C.21 Vertical section of ADCP velocities (cm s-1) parallel to Line 7 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
192

Figure C.22 Vertical section of ADCP speeds (cm s-1) for Line 7 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
193

Figure C.23 Vertical section of ADCP velocities (cm s-1) normal to Line 8 for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
194

Figure C.24 Vertical section of ADCP velocities (cm s-1) parallel to Line 8 for cruise 98-

G-9. Onshore velocities are positive. Ensemble locations are marked with a 

small triangle. 
195

Figure C.25 Vertical section of ADCP speeds (cm s-1) for Line 8 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
196

Figure C.26 Vertical section of ADCP velocities (cm s-1) normal to Line 9A for cruise 98-

G-9. Upcoast velocities are positive. Ensemble locations are marked with a 

small triangle. 
197

Figure C.27 Vertical section of ADCP velocities (cm s-1) parallel to Line 9A for cruise 

98-G-9. Onshore velocities are positive. Ensemble locations are marked 

with a small triangle. 
198

Figure C.28 Vertical section of ADCP speeds (cm s-1) for Line 9A for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
199

Figure C.29 Vertical section of ADCP velocities (cm s-1) normal to Line 9B for cruise 

98-G-9. Upcoast velocities are positive. Ensemble locations are marked 

with a small triangle. 
200

Figure C.30 Vertical section of ADCP velocities (cm s-1) parallel to Line 9B for cruise 

98-G-9. Onshore velocities are positive. Ensemble locations are marked 

with a small triangle. 
201

Figure C.31 Vertical section of ADCP speeds (cm s-1) for Line 9B for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
202

Figure C.32 Vertical section of ADCP velocities (cm s-1) normal to Line 9C for cruise 

98-G-9. Upcoast velocities are positive. Ensemble locations are marked 

with a small triangle. 
203

Figure C.33 Vertical section of ADCP velocities (cm s-1) parallel to Line 9C for cruise 

98-G-9. Onshore velocities are positive. Ensemble locations are marked 

with a small triangle. 
204

Figure C.34 Vertical section of ADCP speeds (cm s-1) for Line 9C for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
205

Figure C.35 Vertical section of ADCP velocities (cm s-1) normal to Line 10 for cruise 

98-G-9. Upcoast velocities are positive. Ensemble locations are marked 

with a small triangle. 
206

Figure C.36 Vertical section of ADCP velocities (cm s-1) parallel to Line 10 for cruise 

98-G-9. Onshore velocities are positive. Ensemble locations are marked 

with a small triangle. 
207

Chapter 1 

1.0 INTRODUCTION 

Figure C.37 Vertical section of ADCP speeds (cm s-1) for Line 10 for cruise 98-G-9. 

Ensemble locations are marked with a small triangle. 
The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has responsibility 

for most of our nationally owned public lands and natural resources. This includes fostering 

sound use of our land and water resources; protecting our fish, wildlife, and biological diversity; 

preserving the environmental and cultural values of our national parks and historical places; 

and providing for the enjoyment of life through outdoor recreation. The Department assesses 

our energy and mineral resources and works to ensure that their development is in the best 

interests of all our people by encouraging stewardship and citizen participation in their care. 

The Department also has a major responsibility for American Indian reservation communities 

and for people who live in island territories under U.S. administration. 

The Minerals Management Service Mission 

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS) 

primary responsibilities are to manage the mineral resources located on the Nation's Outer 

Continental Shelf (OCS), collect revenue from the Federal OCS and onshore Federal and Indian 

lands, and distribute those revenues. 

Moreover, in working to meet its responsibilities, the Offshore Minerals Management Program 

administers the OCS competitive leasing program and oversees the safe and environmentally 

sound exploration and production of our Nation's offshore natural gas, oil and other mineral 

resources. The MMS Minerals Revenue Management meets its responsibilities by ensuring the 

efficient, timely and accurate collection and disbursement of revenue from mineral leasing and 

production due to Indian tribes and allottees, States and the U.S. Treasury. 

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being 

responsive to the public's concerns and interests by maintaining a dialogue with all potentially 

affected parties and (2) carrying out its programs with an emphasis on working to enhance the 

quality of life for all Americans by lending MMS assistance and expertise to economic 

development and environmental protection.