### 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 2008ii 

### 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 ............................................371 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 (S avg ) 6

5. Standard Deviation of Speed (S std ) 7

6. Maximum Speed (S

max ) 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 (S

r ) 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 poin t (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 observati on vs distance from each grid point. 21

15. Monthly vector averages of observed currents gridded

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

better visual reso lution. 22-33

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

17. Summer climatology of surface currents (June-August) 352 

### Abstract

The goal of this technical re port is to present a synthesi s of 23 years of current

observations on the continental shelves of th e 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 obser vations are available. These observations have been previously described in the literat ure (e.g., Ohlmann and Niiler, 2005 ). In this report, we add observations from other pr ograms and synthesize the data set into

statistical and circulation c limatology for the continental shelves of the NGOM. This climatology is targeted especially for fish ery researchers and managers who need to understand the effects of ocean currents on fishery problems.

Both the scalar and vector (resultant) sta tistical synthesis of th e entire set of nearsurface currents are presented. Since wind st ress plays a major role in establishing seasonal circulation patterns, monthly wind st ress 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 resu lt is a 365 day data set of surface current vectors, gridded at 1/12 th degree longitude and latitude re solution. For presentation, this data set is averaged monthly and the result s 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 imp act of climate change also need an understanding of fundamental circulation pattern s 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 th is technical report are to present the geographical distribution of observed current statistics a nd to describe and present the synthesis of observations into a current-climatology for the continental shelves of the

NGOM.

Over the continental shelf the principa l driving forces are wind stress, buoyancy driven outflows, tides, and interactions with deep-basin events. Wi nd stress is important in driving the shallow waters over the shel f 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 sh elf. In addition, the near presence of the coastline and other boundari es contributes to ra pid wind set-up and setdown. Buoyancy driven river and estuarin e outflows also contain both seasonal and storm scales although storm scales are somewhat mitigated by interior drainage time. In the Gulf of Mexico, tidal cu rrents are relatively small a nd require special handling for adequate resolution. They will not be further discussed in this report; however, they should be noted when assessing current forci ng 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 substant ial but transient impacts, part icularly on the outer shelf and upper slope. Two major deep-basin circulat ion features created by basin geography and ocean dynamics are the Loop Current and spin-o ff rings (Figure 1). The Gulf of Mexico (GOM) is a semi-enclosed sea with inflow of North Atlantic/Car ibbean 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 ba sin. 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). Sin ce they do not contribute to seasonal patterns, these features affect current statistics but cannot be adequately captured in our4 

### Spin-off ring

Loop Current

Figure 1: Sea surface temperature in Gulf

of Mexico climatology. Most of the action from the L oop Current and its rings are contained in the deep basin. However, it should be noted that they can interact w ith continental shelf waters, particularly over the outer sh elf 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 dete rmining circulation climatology. 4.) Present monthly and seas onal circulation climatology.

II. Data and Statistics.

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

Both satellite tracked drifters and moored cu rrent meters contributed to the set. Daily averaged current vectors were calculated from the drifters after interpol ation along the drifter track to daily positions . Vector components (north a nd 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 th e moored instruments and each daily current vector component tagged with date and location. In the case of fixed level current meter5 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 (redu ces the error from surface gravity waves). Each daily value in the data set contains [date i , longitude i , latitude i , U i ,V i ], where the subscript i represents an i ndividual data value, U repr esents the positive eastward component of the current vector and V repr esents its pos itive 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 lo cations of daily current values for the drifters and the red

squares represent locatio ns of moored current meters where daily values were extracted. Since observational data was sparse south of 26 o 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 di stribution is shown for the NGOM. Grid points are spaced at 1/12 th degree separation in latitude and l ongitude. 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 presen tation although it should be no ted that the independent geographic resolution of statistics is 40 km.6 Statistics of observed current s falls into two general cate gories: scalar and vector. Scalar values (regardless of direction) ar e more likely to be of importance where engineering parameters are needed for the e ffect of currents on structures. Vector (directional resultant) averages are more li kely to be of importance where transport information is needed, e.g., larval advection or pollution dispersion.

A. Scalar

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

S i = sqrt(U i 2 + V i 2 ).

Where the indice, i, represents an in dividual current measurement within 20 km of the grid point, U is the positive east ward component of current speed and V is the positive northward component of current speed.

Average speed: S avg = sum[S i ]/N.

Where N = number of current ob servations, i, within 20 k of the grid point.

Standard deviation: S std = sqrt[sum(S i -S avg ) 2 /(N-1)]

Max S i : S

max = maximum(S i )

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 stat istic at that grid point. Figure 4 shows the di stribution of average speed, S avg , Figure 5 shows the

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

max , at each grid point. Figure 3: Grid distribution7Figure 4: Average Speed (Savg)8Figure 5: Standard Deviation of Speed (Sstd)9Figure 6: Maximum Speed (Smax)10 Figure 7a Figure 7b B: Vector

Component speeds of each observed cu rrent value are found in the following

manner.

U i = S i * sin(direction i ) and V i = S i * cos(direction i )

Where direction i is the geographic direction of each current measurement within 20 km of grid point i.

Calculate average U and average V:

U avg = sum(U i )/N ,

V avg = sum(V i )/N.

Calculate resultant current speed and direction:

S

r = sqrt(U avg 2 +V avg 2 )

Dir

r = arctan(U avg /V avg )

Stability (directional consistency) is an issue for resultant currents. This can be estimated by correlating U i and V i and is demonstrated in scatter plots of U i versus V i (Figures 7a and 7b). In Figur e 7a, the current measurements were taken in a shipping

channel where the currents were constraine d by channel topography; the correlation of

U i 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 Isla nd. The currents are clearly more scattered with only modest directionality. The correlation there is r = 0.47.

In Figure 8 the resultant speed distributi on is shown and in Figure 9 the resultant direction by 45 degree quadrants is shown. Figure 10 shows the corr elation (stability)

distribution.11Figure 8: Vector Resultant Speed (Sr)12Figure 9: Vector Resultant direction13Figure 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 seasona l wind patterns tend to establish consistent seasonal scale current patterns. Because of its importance to continental shelf currents, monthly wind stress climatol ogy is included here. The wi nd stress shown was extracted from Harrison (1989). Using an historical global surface marine observation data set, Harrison (1989) created monthl y ocean wind stress climatology with 1° spatial resolution from the Large and Pond (1981) surface drag co efficient formulation. In figure 11, this monthly wind stress climat ology is shown for the NGOM. The vectors are in the direction of wind forcing on the water surface.15161718 Figure 11: Monthly climat ological 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 compone nt. For summer months the wind stress is toward the north, mainly onshore. In Figur e 12 wind stress is shown as climatological averages for both the summer and non-summ er 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 si ngle grid point (red square). The inner red circle is 20 km from the grid point and the outer red

circle is 50 km awa y

. 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 horizonta l spacing. In order to elucid ate patterns of currents, the data set was smoothed in space and time. E ach daily vector (n=77,667) was tagged with longitude, latitude and year-day (1-365) rega rdless of year, a movi ng 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 an alysis (Figure 2). As an example of the gridding scheme, Figur e 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 29.5 N. The vectors were interpolated to the grid point (red square in Figur e 13) using an exponential weig hting scheme (Bretherton et al., 1976):

w i =exp(-d i 2 /r d 2 )

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

parameter r d , serves to establish how fast weight ing 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, w i , 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 u j and v j 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. u j and v j are the resulting current co mponents at grid point j.

After currents have been computed at al l 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 Decemb er, 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 vect or averages were spatially de cimated by a factor of 5 for display purposes. Figure 15 show s the vector monthly averages.222324252627282930313233Figure 15: Monthly vector averages of observedcurrents gridded to 1/12thdegree longitude/latitudeand decimated by 5 for better visual resolution.34Figure 16: Non-summer surface currentclimatology (Sep-May).35Figure 17: Summer surface currentclimatology (June-August).36 

### Acknowledgements

We gratefully acknowledge funding for th is study from the Marine Fisheries Initiative (MARFIN) program of NMFS/NOA A, Southeastern Regional Office. The study would not have been possible without th e generous contribution of data from a number of research scientists. Many of th e current observations are from several large Minerals Management Service (MMS) proj ects in the northern GOM. We would especially like to acknowledge W. Johnson (M MS) and P. Niiler (Scr ipps Institution of Oceanography). Other programs involved W. St urges (Florida State University) and R. Weisberg (University of South Florida). Dr ifter and moored current data were provided by J. Blaha, C. Szczechowski and S. Dinnel (N aval Oceanographic Office). A number of

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

### References

Bretherton F.P., R.E. Davis and C.B. Fandry (1976): A Technique for Objective Analysis and Design of Oceanic Experiments a pplied to MODE-73. Deep Sea Research, 23, p. 559-582.

Cho, K., R. O. Reid, W. D. Nowlin Jr. 1998. Objectively mapped st ream function fields

on the Texas-Louisana shelf based on 32 m onths of moored current meter data. J. Geophys. Res 103(C5): 10377-10390.

Gill, A. E. 1982. Atmosphere-Ocean Dynamics. Academic Press. New York.

Harrison, D. E. 1989. On climatological mont hly mean wind stress and wind stress curl

fields over the world ocean J. Climate 2(1): 57-70.

Hurlbert, H. E. and J. D. Thompson. 1980. A numerical study of Loop Current intrusions and eddy shedding. J. Phys. Oceanogr. 10: 1611-1651.

Johnson, D. R., H. M. Perry, J. Lyczkowski-Shultz, D. Hanisko. 2008. Red snapper ( Lutjanus campechanus ) larval transport in the no rthern Gulf of Mexico.

Submitted Trans. Amer. Fish.

Large, W.G., and S. Pond, 1981: Open ocean mo mentum flux measurements in moderate to strong winds. J. Phys. Oceanogr., 11, 324-336.

Oey, I. 1995. Eddy- and wind-forced shelf circulation. J. Geophys. Res. 100: 8621-8637.

Ohlmann, J. C., P. P. Niiler. 2005. Circulati on over the continental shelf in the northern Gulf of Mexico. Prog. In Oceanogr., 64: 45-81

Vukovich, F. M. 1995. An updated evaluation of the Loop Current’s eddy-shedding frequency. J. Geophs. Res. 100(C5): 8655-8659.