Ocean Surface Current Climatology in the Northern Gulf of Mexico 

by 

Donald R. Johnson 

Center for Fisheries Research and Development 

Gulf Coast Research Laboratory 

University of Southern Mississippi 

Project funded by the 

Marine Fisheries Initiative (MARFIN) program of NMFS/NOAA 

Published by 

Gulf Coast Research Laboratory 

Ocean Springs, Mississippi 39564 

May 2008
ii

Table of Contents 

List of Figures .............................................1 

Abstract .............................................2 

I. Introduction .............................................3 

II. Data and Statistics .............................................4 

 A. Scalar .............................................6 

 B. Vector ............................................10 

III. Wind Stress Climatology ..........................................14 

IV. Surface Current Patterns ...........................................20 

 A. Methodology .............................................20 

 B. Monthly Averaged Currents .......................................21 

Acknowledgements ............................................36 

References ............................................37 
1

List of Figures: 

 Figure Page 

 1. Sea Surface Temperature in the Gulf of Mexico 3 

 2. Location of daily current vectors in data set 4 

 3. Grid distribution 5 

 4. Average Speed (Savg) 6 

 5. Standard Deviation of Speed (Sstd) 7 

 6. Maximum Speed (Smax) 8 

 7a. Scatter plot U/V(Dog Key Pass) 9 

 7b. Scatter plot U/V (South of Petit Bois Island) 9 

 8. Vector Resultant Speed (Sr) 11 

 9. Vector Resultant Direction 12 

 10. Correlation U/V (r) 13 

 11. Monthly climatological wind stress for the northern 

 Gulf of Mexico. Taken from Harrison(1989). 15-18 

 12. Climatological wind stress averages for non-summer (upper) 

 And summer (lower) months. 19 

 13. Example of observed daily currents between year-days 

 172-192 and within 50 km of a single grid point (red square). 

 The inner red circle is 20 km from the grid point and the 

 outer red circle is 50 km away. 20 

 14. Weight of current observation vs distance from each grid point. 21 

 15. Monthly vector averages of observed currents gridded 

 To 12th degree longitude/latitude and decimated by 5 for 

 better visual resolution. 22-33 

 16. Non-summer climatology of surface currents (Sep-May). 34 

 17. Summer climatology of surface currents (June-August) 35 
2

Abstract

The goal of this technical report is to present a synthesis of 23 years of current 

observations on the continental shelves of the northern Gulf of Mexico (NGOM). As a 

result of several large Minerals Management Service programs, a rich set of satellite 

tracked drifter and moored current meter observations are available. These observations 

have been previously described in the literature (e.g., Ohlmann and Niiler, 2005 ). In this 

report, we add observations from other programs and synthesize the data set into 

statistical and circulation climatology for the continental shelves of the NGOM. This 

climatology is targeted especially for fishery researchers and managers who need to 

understand the effects of ocean currents on fishery problems. 

 Both the scalar and vector (resultant) statistical synthesis of the entire set of nearsurface currents are presented. Since wind stress plays a major role in establishing 

seasonal circulation patterns, monthly wind stress climatology has been taken from the 

literature (Harrison, 1989) and included here. The circulation climatology was formed 

from the observational data set by calculating daily current vectors and putting them into 

a year-day time frame (days 1-365) regardless of year. To elucidate patterns of currents, 

the data set was smoothed temporally (21-year-day moving window) and spatially 

(gridded by optimal interpolation). The result is a 365 day data set of surface current 

vectors, gridded at 1/12th degree longitude and latitude resolution. For presentation, this 

data set is averaged monthly and the results presented as monthly climatology. Since it 

has been noted that the circulation on the NGOM shelves can be separated into summer 

(June-August) and non-summer (rest of year) patterns, this climatology is included. 
3

I. Introduction. 

 The Northern Gulf of Mexico (NGOM) has been the site of several large 

observational programs involving measurements of ocean currents. A major goal for 

much of this work has been to develop a risk assessment for the NGOM involving oil 

spill spread by currents (Ohlmann and Niiler, 2005). As a result of these programs, a rich 

set of surface and near-surface current observations are available for other projects. 

Fishery programs involving larval transport, migratory patterns, aquaculture, marine 

protected areas, and the impact of climate change also need an understanding of 

fundamental circulation patterns and statistics of currents over broad regional areas. For 

example, the synthesized observational data described herein have previously been 

applied to the transport of red snapper (Lutjanus campechanus) larvae across the entire 

NGOM (Johnson et al., 2008). The goals of this technical report are to present the 

geographical distribution of observed current statistics and to describe and present the 

synthesis of observations into a current-climatology for the continental shelves of the 

NGOM. 

 Over the continental shelf the principal driving forces are wind stress, buoyancy 

driven outflows, tides, and interactions with deep-basin events. Wind stress is important 

in driving the shallow waters over the shelf on both seasonal and storm scales (2-6 days 

in mid-latitudes). The Ekman Depth, or depth of wind stress momentum mixing, can 

represent a significant portion of the water column over the shelf. In addition, the near 

presence of the coastline and other boundaries contributes to rapid wind set-up and setdown. Buoyancy driven river and estuarine outflows also contain both seasonal and 

storm scales although storm scales are somewhat mitigated by interior drainage time. In 

the Gulf of Mexico, tidal currents are relatively small and require special handling for 

adequate resolution. They will not be further discussed in this report; however, they 

should be noted when assessing current forcing on structures and for short time scale 

(sub-diurnal) advection. 

 Deep basin events and their effects on the continental shelf are difficult to 

predict, and can have substantial but transient impacts, particularly on the outer shelf and 

upper slope. Two major deep-basin circulation features created by basin geography and 

ocean dynamics are the Loop Current and spin-off rings (Figure 1). The Gulf of Mexico 

(GOM) is a semi-enclosed sea with inflow of North Atlantic/Caribbean Water through 

the Yucatan Channel. The Loop Current is formed when this inflow penetrates 

northward in the GOM before turning in an anti-cyclonic (clockwise) motion and exiting 

through the Straits of Florida. The loop at times turns back on itself and forms a ring, 

which eventually breaks off from the main flow. Under the influence of the earth’s 

rotation the separated ring migrates to the western basin. The rings are large and 

relatively deep; they spread warm, salty water through the central and western GOM, 

significantly affecting the oceanic and atmospheric climatology of the entire Gulf. 

Northward penetration of the loop and break-off of a ring, however, is a dynamically 

unstable process (Hurlbert and Thompson, 1980) with an unpredictable time scale of 

roughly 9-13 months (Vukovich, 1995). Since they do not contribute to seasonal 

patterns, these features affect current statistics but cannot be adequately captured in our 
4

Spin-off ring 

Loop Current 

Figure 1: Sea surface 

temperature in Gulf 

of Mexico 

climatology. Most of the action from the Loop Current and its rings are contained in the 

deep basin. However, it should be noted that they can interact with continental shelf 

waters, particularly over the outer shelf and upper slope region (Oey, 1995). 

 In this report, we 

1.) Introduce the data set and derive current statistics. 

2.) Present wind stress climatology. 

3.) Present the methodology for determining circulation climatology. 

4.) Present monthly and seasonal circulation climatology. 

II. Data and Statistics. 

 The data set is derived from a variety of sources covering the period 1980-2002. 

Both satellite tracked drifters and moored current meters contributed to the set. Daily 

averaged current vectors were calculated from the drifters after interpolation along the 

drifter track to daily positions. Vector components (north and east positive) were formed 

from the daily positions and tagged with date and location. Moored current meters were 

both fixed level and Acoustic Doppler Current Profilers (ADCPs). Daily averages of 

near-surface currents were calculated for the moored instruments and each daily current 

vector component tagged with date and location. In the case of fixed level current meter 
5

Figure 2 

strings, the uppermost current meter was used; for acoustic profilers, the bin nearest to a 

depth of 15% of water depth was used (reduces the error from surface gravity waves). 

Each daily value in the data set contains [datei, longitudei, latitudei, Ui,Vi], where the 

subscript i represents an individual data value, U represents the positive eastward 

component of the current vector and V represents its positive northward component. 

There are 77,667 daily data values in the set. 

 Figure 2 shows the location of all daily vectors and demonstrates the relatively 

high density of currents available to the data set, particularly in the northeastern Gulf. 

The black plus signs represent locations of daily current values for the drifters and the red 

squares represent locations of moored current meters where daily values were extracted. 

Since observational data was sparse south of 26o N latitude, the study area was confined 

to the GOM north of that latitude. 

 Statistics of the observed currents were derived on a homogeneous grid across the 

entire NGOM. In Figure 3 the grid distribution is shown for the NGOM. Grid points 

are spaced at 1/12th degree separation in latitude and longitude. Currents within a radius 

of 20 km from each grid point were taken as a statistical set for that point. The 20 km 

scale was chosen to fit the estimated (10-30km) internal Rossby Radius of Deformation 

scale for continental shelves (Gill, 1982). This distance, while dynamically consistent, 

represents a compromise between geographical resolution and statistical error. Since we 

are primarily interested in continental shelf and upper slope information, and we cannot 

adequately capture the important deep-basin events, we confine this study to depths 

between 5 m and 1000 m. The grid distance represents an approximate 8-9 km resolution 

and provides good visual presentation although it should be noted that the independent 

geographic resolution of statistics is 40 km. 
6

 Statistics of observed currents falls into two general categories: scalar and vector. 

Scalar values (regardless of direction) are more likely to be of importance where 

engineering parameters are needed for the effect of currents on structures. Vector 

(directional resultant) averages are more likely to be of importance where transport 

information is needed, e.g., larval advection or pollution dispersion. 

A. Scalar

Calculate speed, S, for all measured currents within 20 km of a grid point: 

 Si = sqrt(Ui

2

 + Vi

2

). 

 Where the indice, i, represents an individual current measurement within 20 km 

 of the grid point, U is the positive eastward component of current speed and V is 

 the positive northward component of current speed. 

Average speed: Savg = sum[Si]/N. 

 Where N = number of current observations, i, within 20 k of the 

 grid point. 

Standard deviation: Sstd = sqrt[sum(Si-Savg)

2

/(N-1)] 

Max Si: Smax = maximum(Si) 

Blank spaces in the following figures where Figure 3 shows a grid point indicate that 

there was and insufficient number of data points (N<4) to obtain a statistic at that grid 

point. Figure 4 shows the distribution of average speed, Savg, Figure 5 shows the 

distribution of standard deviation of the speed, Sstd, and Figure 6 shows the maximum 

speed, Smax, at each grid point.

Figure 3: Grid distribution 
7

Figure 4: Average Speed (Savg) 
8

Figure 5: Standard Deviation of Speed (Sstd) 
9

Figure 6: Maximum Speed (Smax) 
10

Figure 7a Figure 7b 

B: Vector

 Component speeds of each observed current value are found in the following 

manner. 

 Ui = Si * sin(directioni) and Vi = Si * cos(directioni) 

 Where directioni is the geographic direction of each current measurement within 

 20 km of grid point i. 

Calculate average U and average V: 

 Uavg = sum(Ui)/N , 

 Vavg = sum(Vi)/N. 

Calculate resultant current speed and direction: 

 Sr = sqrt(Uavg

2

 +Vavg

2

) 

 

 Dirr = arctan(Uavg/Vavg) 

 Stability (directional consistency) is an issue for resultant currents. This can be 

estimated by correlating Ui and Vi and is demonstrated in scatter plots of Ui versus Vi

(Figures 7a and 7b). In Figure 7a, the current measurements were taken in a shipping 

channel where the currents were constrained by channel topography; the correlation of 

Ui and Vi is r = 0.94, a high value. In Figure 7b, the current measurements were taken on 

the continental shelf south of Petit Bois Island. The currents are clearly more scattered 

with only modest directionality. The correlation there is r = 0.47. 

 In Figure 8 the resultant speed distribution is shown and in Figure 9 the resultant 

direction by 45 degree quadrants is shown. Figure 10 shows the correlation (stability) 

distribution. 
11

Figure 8: Vector Resultant Speed (Sr) 
12

Figure 9: Vector Resultant direction 
13

Figure 10: Correlation U/V (r) 
14

III. Wind Stress climatology 

 As previously noted, wind stress is an important forcing mechanism for 

continental shelf flows. Consistent seasonal wind patterns tend to establish consistent 

seasonal scale current patterns. Because of its importance to continental shelf currents, 

monthly wind stress climatology is included here. The wind stress shown was extracted 

from Harrison (1989). Using an historical global surface marine observation data set, 

Harrison (1989) created monthly ocean wind stress climatology with 1° spatial resolution 

from the Large and Pond (1981) surface drag coefficient formulation. In figure 11, this 

monthly wind stress climatology is shown for the NGOM. The vectors are in the 

direction of wind forcing on the water surface. 
15

 
16
17

 
18

 

Figure 11: Monthly climatological wind stress for the northern Gulf of 

Mexico. Taken from Harrison (1989) 
19

 It has been noted (Cho et al., 1998) that with respect to wind stress and resulting 

surface currents, there are two seasons in the northern GOM, a summer season consisting 

of June, July and August, and a non-summer season consisting of the remainder of the 

year. In Figure 11 it is readily seen that for non-summer months, wind stress is toward 

the west/southwest, with an offshore component. For summer months the wind stress is 

toward the north, mainly onshore. In Figure 12 wind stress is shown as climatological 

averages for both the summer and non-summer seasons. The months of May and 

September are transition months between the two seasonal patterns 

 

Figure 12: Climatological wind stress averages for nonsummer (upper) and summer (lower) months. 
20

Figure 13: Example of observed daily 

currents between year-days 172-192 and 

within 50 km of a single grid point (red 

square). The inner red circle is 20 km 

from the grid point and the outer red 

circle is 50 km away.

IV. Surface Current Patterns. 

A. Methodology. 

 The surface current data set consists of observations made over a time span of 23 

years with non-uniform horizontal spacing. In order to elucidate patterns of currents, the 

data set was smoothed in space and time. Each daily vector (n=77,667) was tagged with 

longitude, latitude and year-day (1-365) regardless of year, a moving window of 21-yeardays was applied (temporal smoothing) and the current vectors in that 21-year-day 

window were interpolated to a uniform grid (spatial smoothing). Both temporal and 

spatial smoothing was accomplished as the data were gridded. 

 Gridding was done at the same grid scale as in the statistical analysis (Figure 2). 

As an example of the gridding scheme, Figure 13 shows daily vector observations that 

fall within year-days 172 to 192, centered on year-day 182, and that are contained within 

50 km of a single grid point at -88.5W and 29.5N. The vectors were interpolated to the 

grid point (red square in Figure 13) using an exponential weighting scheme (Bretherton et 

al., 1976): 

 wi=exp(-di

2

/rd

2

) 

where di is the distance in km of vector i from the grid point and rd=20 km. The 

parameter rd, serves to establish how fast weighting diminishes with distance from the 

grid point. Statistically, the best choice of r would be from calculating the correlation 

length scale for currents at that 

point. However, with insufficient 

data to establish this length scale, it 

is estimated as the typical first mode 

baroclinic radius of deformation on 

continental shelves (10-30 km; Gill, 

1982). A cut-off distance of 50 km 

applied before weighting prevents 

excessive, non-contributory 

calculations. 
21

Figure 14: Weight of current 

observation vs distance from each 

grid point. 

∑

∑ ×

= n

i

i

n

i

ii

j

w

Uw

u

∑

∑ ×

= n

i

i

n

i

ii

j

w

Vw

v

 Figure 14 shows the value of weight, wi, applied to each observation versus 

distance from the grid point 

j. The individual weights 

are normalized by the sum 

of all weights applied 

at that grid point. The 

contribution of each 

observation to the 

calculated current value at 

the grid point is diminished 

rapidly with its distance 

away. 

 Current components uj and vj for grid point j, then, are formed in the following 

manner: 

 

 

 

where j is the grid point indice and i is the indices of all observations within 50 km of 

grid point j. uj and vj are the resulting current components at grid point j. 

 After currents have been computed at all grid points, the temporal 21-year-day 

window is moved over by one day, and currents are calculated for the new year-day. As 

the end of the year is reached in December, the 21-year-day window is wrapped around 

to January. 

B. Monthly Averaged Currents 

 The calculated climatology then consists of 365 current values for each grid point. 

In order to display the results, monthly vector averages were made. Due to the density of 

grid points, the resulting vector averages were spatially decimated by a factor of 5 for 

display purposes. Figure 15 shows the vector monthly averages. 
22
23
24
25
26
27
28
29
30
31
32
33

Figure 15: Monthly vector averages of observed currents gridded to 1/12th degree longitude/latitude 

and decimated by 5 for better visual resolution. 
34

Figure 16: Non-summer surface current climatology (Sep-May). 
35

Figure 17: Summer surface current climatology (June-August). 
36

Acknowledgements 

 We gratefully acknowledge funding for this study from the Marine Fisheries 

Initiative (MARFIN) program of NMFS/NOAA, Southeastern Regional Office. The 

study would not have been possible without the generous contribution of data from a 

number of research scientists. Many of the current observations are from several large 

Minerals Management Service (MMS) projects in the northern GOM. We would 

especially like to acknowledge W. Johnson (MMS) and P. Niiler (Scripps Institution of 

Oceanography). Other programs involved W. Sturges (Florida State University) and R. 

Weisberg (University of South Florida). Drifter and moored current data were provided 

by J. Blaha, C. Szczechowski and S. Dinnel (Naval Oceanographic Office). A number of 

research scientists at Texas A&M and Louisiana State University contributed to a CDROM data set available through the National Oceanographic Data Center. 
37

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 23, p. 559-582. 

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 on the Texas-Louisana shelf based on 32 months of moored current meter data. J. 

 Geophys. Res 103(C5): 10377-10390. 

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