WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 243

INTRODUCTION

The Mediterranean is, on average, an oligotroph-ic sea. Nevertheless, it supports sizeable and veryvaluable fisheries, suggesting that the Mediter-ranean must contain patches of substantial organicproduction, at least on a fine-scale. Because low dis-solved plant nutrient concentrations are believed tobe the major reason for the overall oligotrophy, oneexpects that such patches of elevated productivityshould occur where nutrient supply to the upperphotosynthetic layers of the sea is significant.

Divergent flow of surface waters driven by thestress of the wind acting on the sea surface is wellknown to induce upwelling of nutrient-enrichedsubsurface waters, thereby enhancing nutrient sup-

ply to the upper layers of the ocean. Because of theconvoluted coastline and complex topographic reliefof the Mediterranean coastlands, strong spatial pat-terning of the sea surface wind stress is to be expect-ed. Previous descriptions of the characteristic shapesof these patterns in this region have depended oncomposite averages of synoptic analyses of distribu-tions of simultaneously observed reports or onmodel results based on such distributions (Crise andCrispe, 1998). The data-based spatial resolutionattained in this manner is limited to the rather coarsespatial distribution of reports available during anysynoptic sampling period (i.e., the reports made rel-atively simultaneously by ships or other observationplatforms in the area at any given moment). Anysmaller-scale features appearing in distributions soproduced will have had to have been generated byvarious assumptions underlying interpolation func-

SCI. MAR., 65 (3): 243-257 SCIENTIA MARINA 2001

Seasonal patterns of wind-induced upwelling/downwelling in the Mediterranean Sea*

ANDREW BAKUN1,2 and VERA NATALIE AGOSTINI1,3

1Marine Resources Service, Fisheries Department, FAO, Rome, Italy.2Lab. Halieutique et Ecosystèmes Aquatiques, Institut de Recherche pour le Développement (IRD), Montpellier, France.

E-mail: andrewbakun@hotmail.com3School of Fisheries, University of Washington, Seattle, Washington,USA.

SUMMARY: The historical file of wind observations from maritime weather reports is summarized to identify the charac-teristic seasonal distributions of wind-induced Ekman upwelling and downwelling in the Mediterranean Sea. Both coastalupwelling/downwelling and wind-stress curl-driven “open ocean” upwelling/downwelling are treated in a unified descrip-tion. Vigorous upwelling zones are found in the eastern Aegean Sea, off the west coast of Greece, and in the Gulf of Lyons.The southern coast of the Mediterranean is found to be primarily a downwelling area, although significant coastal upwellingdoes appear in the Gulf of Sidra during the spring and summer seasons, and along the Algerian coast during summer.

Key words: Mediterranean, upwelling, productivity, wind, COADS.

*Received July 28, 2000. Accepted March 9, 2001.

tions used in analysis procedures, or else created bysome dynamic forecast model, etc.

Here we take a different approach which permitsa higher spatial resolution description of the charac-teristic long-term mean seasonal cycle of sea surfacewind stress patterns (Bakun and Nelson, 1991). Themean seasonal cycle is the component of variabilitywhich tends to be of greatest interest to attempts toinfer ecosystem processes and function, and tends tobe the baseline against which all other scales of vari-ability are evaluated.

Scope and limitations

In this study, we employ the term upwelling inthe sense defined by Smith (1968) in his classicreview of the subject, i.e., “an ascending motion, ofsome minimum duration and extent, by which waterfrom subsurface layers is brought into the surfacelayer and is removed from the area of upwelling byhorizontal flow”. Thus, it is not our intention here totreat all of the potential processes (e.g., turbulentmixing, vorticity-induced upwelling, breaking ofinternal waves, etc.) by which transfers from sub-surface layers to surface layers may occur in the sea. Moreover, we are addressing in particular the effectof the wind pattern in inducing either (1) coastalupwelling resulting from the flow divergence thatoccurs when surface waters are transported offshorefrom a solid coastal boundary, the driving forcebeing the component of wind stress which is paral-lel to the coast, or (2) “open ocean upwelling” whichoccurs as a result of flow divergence induced byspatial variation in the pattern of sea surface windstress, the driving force in this case being the windstress curl (Smith 1968). Regions characterized bywind-induced upwelling are known to comprisesome of the most productive large-scale oceanicareas in the world (Cushing 1969, Bakun 1996).

According to the definition of upwelling givenabove, the wind variations of interest are thosewhich are comparable to a half-pendulum day,which corresponds to about one calendar day in thelatitude range of the Mediterranean, or longer (i.e.,the Ekman transport approximation applies). Short-er period wind oscillations may induce accelerationsof surface waters that may tend to largely cancel oneanother in their net effect on the longer time-scalesurface divergence or convergence patterns thatdetermine the patterns of actual upwelling or down-welling, although they may result in net verticaltransfers through non-linear processes such as resul-

tant turbulent mixing, generation of breaking inter-nal waves, etc. According to our above-cited defini-tion, this class of processes does not constituteupwelling as such, and is not treated in this paper.

METHODS

The procedure involves compositing togetherand vector-averaging available reports of windstress estimates within similar seasonal segmentstaken from a large number of years. This results ineffects of interyear variability (and also randommeasurement or reporting errors, etc.) being largely“averaged away”, leaving an estimate of the under-lying characteristic pattern for each seasonal seg-ment. Because of the much larger numbers of actualobservations incorporated in this manner, the spatialresolution thereby attained is far greater than couldever be defined in any simultaneous synoptic reportdistribution. Because the non-linear computationsinvolved in producing the stress estimates are per-formed on each individual observation prior to anyaveraging operations, the mean fields reflect undis-torted estimates of the long-term stress magnitudesand spatial patterns. The curl is a linear mathemati-cal operator, and so computing the curl on the aver-aged seasonal distributions likewise introduces nodistortion (mathematically, the ‘curl of the mean’ isidentically equal to the ‘mean of the curl’).

Data

The data employed were extracted from theComprehensive Ocean-Atmosphere Data Set(COADS) which is the result of a longstandinginternational cooperative effort to assemble andcomputerize the information contained in weatherobservations made by ships at sea in all regions ofthe world’s oceans (Slutz et al., 1985; Woodruff etal., 1987). The total file contains over 100 millionobservations dating as far back as 1854.

A summary file of greatly reduced size in whichthe observations have been averaged by 2° latitude x2° longitude quadrangular areas has been madeavailable and has been widely used in ocean climatestudies. However, the Mediterranean Sea contains avery high density of maritime reports relative tomost other areas of the world’s oceans. Also, 2° x 2°summary areas represent quite a coarse resolutionrelative to the coastline and topographical featureswithin the Mediterranean. For example, effects of

244 A. BAKUN and V.N. AGOSTINI

important coastline indentations or coastal topo-graphic features may be suppressed or lost by sum-ming together with more numerous data taken fromlarge open sea areas. In fact, 2° x 2° quadrangles arelarge enough to encompass data from both the Adri-atic Sea and Tyrrannean Sea sides of the ItalianPeninsula, as well as opposite coasts of majorislands such as Crete, Sardinia, Cypress, etc. In theAlboran Sea area, the entire Mediterranean is lessthan 2° latitude in width. The widths of the Adriaticand Aegean Seas are also tend to be 2° or less, as isthe distance from the southern coast of Crete to thecoast of Libya. Moreover, curl computations involvespatial derivatives, thereby requiring not just onesummary area but rather lines of at least two (andoptimally three, in order to support central differ-ence derivative formulations) adjacent summaryareas arrayed in each coordinate direction and cen-tered about each location for which a curl computa-tion is produced. Obviously, with such an arrange-ment, data summarized by 2° x 2° quadrangles couldyield curl computations for only a minor fraction ofthe total area of the Mediterranean Sea.

For these reasons, rather than using the standard2° x 2° COADS summaries for this study, we havegone back to the original reports and re-summarizedthe data on a much finer 0.5° latitude x 0.5° longi-tude format (Fig. 1). For this we have used a versa-tile COADS data file (Roy and Mendelssohn, 1998)assembled and distributed on computer readableCD-ROM by the Climate and Eastern Oceans Sys-

tems (CEOS) project (Durand et al., 1998). Many ofthe reports in the COADS file made before the endof the Second World War contain positions notedonly to whole degrees of latitude and longitude. It isgenerally impossible to differentiate these fromreports that were actually reported to tenths of adegree and were truly within one-tenth of the near-est integral whole degree. To prevent undue loss ofresolution due to this uncertainty in actual reportedposition, we have chosen to use only data from themore recent time interval beginning in 1946. Aresulting distribution of observations for a sample 2-month seasonal segment is shown in Fig. 2.

Software produced in the CEOS Project wasused to extract and compute composite mean windstress estimates for each one-half degree latitude-longitude quadrangle for 2-month segments of thelong-term mean seasonal cycle. Based on the result-ing data fields, all the various other operationsdescribed below were performed, and the resultsdisplayed as seasonal maps, using a prototype ver-sion of the Environmental Analysis System (EASY)workstation which was made available for this studyby its developer, Systems Applications Inc ofRedondo Beach, California.

Computation scheme

Wind stress estimates are computed from indi-vidual wind reports according to the bulk aerody-namic formula

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 245

FIG. 1. – Grid of one-half degree lat-long quadrangles used for data summarization. The heavier line separates the grid cells that were select-ed as being “land” areas, where sea surface wind stress is defined to be zero, and grid cells considered as being “sea” areas where character-istic sea surface wind stress estimates are produced from maritime reports. Thus this heavier line operates as the effective coastal boundary

in the wind stress curl and vertical velocity computations.

τ∼ = ρa Cd |v~ | v~ (1)

where τ∼ is the stress vector, ρa is the density of air,Cd is a dimensionless drag coefficient, v~ is the windvelocity, and |v~ | is the wind speed.

We make reasonable choices for constant valuesof ρ (0.00122 g cm-3) and Cd (0.0013). These are thesame values that have been used in a number ofother regional upwelling studies that have similarlyemployed constant drag coefficient formulationsBakun, 1978, 1990; Bakun and Parrish, 1990, 1991;Bakun et al., 1974, 1998; Nelson, 1977; Parrish etal., 1983; Wooster et al., 1976). Since all the subse-quent computations represented by Equations 2 to 5are entirely linear, the results can be simply adjustedby applying appropriate ratios of constant scale fac-tors to make them directly comparable to any otherstudies based on pseudostress (e.g. Goldenberg andO’Brien, 1981; Servain and Legler, 1986; Breiden-bach, 1990) or other constant drag law formulations.

The vertical component of the curl of the windstress on the sea surface, k~ · ∇ × τ~ at grid location(x,y) is calculated in finite (central) difference form as

(2)

where τy(x+1) and τy(x-1) represent the northward stresscomponents one grid location to the east and one gridlocation to the west respectively, τx(y+1) and τy(x-1) rep-resent the eastward stress components one grid loca-tion to the north and one grid location to the south

respectively, and ∆x and ∆y are the respective gridmesh lengths in the zonal and meridional coordinatedirections (linear distances corresponding to 0.5° latand long respectively).

The principle of conservation of mass in a rela-tively incompressible fluid such as sea water isexpressed in the equation of continuity. Since we areinterested in the directly wind-driven component offlow we integrate the continuity equation from adepth, z = – δ, where this component becomes verysmall in a relative sense (we refer to this depth as thebottom of the Ekman layer) to that at the sea surface.Applying the boundary condition of no flow throughthe sea surface yields (in finite difference form anal-ogous to Eq. 2)

(3)

Since we are addressing time scales of variationwhich are long compared to the Ekman responsetime (which is a half-pendulum day or roughly onecalendar day in the latitude band of the Mediter-ranean Sea), we may make use of the Ekmanapproximation (Ekman, 1905)

(4)

for computing the actual water transport respondingto the applied wind stress (the symbol ƒ representingthe Coriolis parameter and ρ signifying the densityof water). Substituting expressions (4) into Eq. 3yields the basic equation

V U= − = −τρ

τ

ρx y

f f;

wU U U U

−( ) =−

−−+ − + −δ ( ) ( ) ( ) ( )x x y y

x y1 1 1 1

2 2∆ ∆

kx y

y x y x x y x y

˜ ˜

( ) ( ) ( ) ( )⋅∇ × =−

−−+ − + −τ

τ τ τ τ1 1 1 1

2 2∆ ∆

246 A. BAKUN and V.N. AGOSTINI

<50�

<50�

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FIG. 2. – Distribution of observations available for one example of the six 2-month long-term composite seasonal samples (Jun-Jul is shown; data from 1946 to latest data in the file).

(5)

by which we calculate the vertical velocities at thebase of the Ekman layer from a central-difference“curl” calculation based on the composite seasonalwind stress estimates arranged on the grid systemdisplayed in Figure1.

The coastal boundary condition

The coastal boundary condition requires thatthere be no flow through the solid coastal boundary.Comparing Equations 3 and 5 term by term makes itclear that the coastal boundary condition of no oceanflow into or out of continental landmass areas isappropriately imposed if one simply ensures that thesea surface wind stress estimates at all grid pointslocated on solid land are set equal to zero (i.e., nosea surface wind stress where there is no sea sur-face). With the data gridded in this manner one cansimply apply Equation 5 at all grid locations locatedover the sea itself, as definable by the 0.5° grid res-olution (Fig. 1), to yield the composite effect of boththe alongshore stress-driven coastal upwelling andwind stress curl-driven open ocean upwelling with-in the same consistent computation scheme.

This offshore scale is large compared to theexpected width of the actual coastal upwellingresponse, which has a scale width given by theRossby radius of deformation (Yoshida, 1967; Moo-ers and Allen, 1971). Computed estimates of Ross-by radius values for temperate latitudes generally donot exceed several tens of km, although the conti-nental shelf width may provide an additional off-shore scale for coastal upwelling. The pertinent con-sideration for the results reported here is that thevertical velocity values at the near-coastal gridpoints do not reflect the real maximum values, butrather an estimate of those values averaged over anoffshore scale of about 100 km. This is consideredentirely appropriate due to the fact that the 0.5-degree mesh-length of the grid system used to sum-marize the observed data certainly does not resolvecoastal features well enough to support any finerdegree of definition. In any case, it represents a largeadvance in spatial detail over what has been previ-ously definable in terms of a consistent basin-widepicture of the seasonal wind-induced upwelling anddownwelling structure of the Mediterranean Sea.

In summary, if one imposes the condition that thestress at grid locations which are located over land

be always equal to zero, one can simply apply eq.(5) at all grid locations located over the sea to yieldthe composite vertical velocity resulting from boththe alongshore stress-driven coastal upwelling (ordownwelling) and wind stress curl-driven openocean upwelling (or downwelling, on a spatial scaleof the order of two grid mesh lengths. Thus the com-puted vertical velocities within about 100 km of thecoast will validly represent the net effect of bothprocesses averaged over this spatial scale.

Choices made in defining effective coastalboundaries

Pooling the observational data over half-degreelatitude-longitude areas results in a limitation of theeffective resolution of coastline features to the samehalf-degree latitude-longitude scale (i.e., one has tomake a choice whether any particular half-degreequadrangle should represent an area of sea or an areaof land). These choices inevitably determine someaspects of the smallest scale spatial details revealedby the analysis. Clearly, one wishes neither to over-ly exaggerate nor to unduly mask effects of coastlinefeatures that are not precisely definable by bound-aries of half-degree grid “squares”. The choicesmade for coastline definition for this study are indi-cated in Figure 1.

Islands represent an interesting problem. Theclassic Ekman coastal upwelling conceptual model(Sverdrup, 1938) assumes a very long straight coast-line such that most of the water that feeds the off-shore transport must not flow into the area horizon-tally, but must come vertically from depth. Obvious-ly, for the coastline of an island to offer a goodapproximation to this situation, the island must bevery large. For a relatively small island lying in thepath of a large scale wind flow of a time scale of ahalf-pendulum day or more, there will be Ekmantransport of surface water toward the left side of theisland (looking downwind) and away from the rightside of the island. (The northern hemisphere orien-tation is described here; in the southern hemisphere,where the Ekman transport orientation to the wind isreversed, the sides of the islands as cited in this dis-cussion would be reversed). Thus there is a potentialdriving force for downwelling on the left side of theisland and for upwelling on the right side of theisland. If the island is small enough, the water accu-mulating on one side can simply flow around theisland in response to the resulting alongshore pres-sure gradient to replenish the loss of water on the

12 2

1 1 1 1

ρδ

τ τ τ τ

fw

x yy x y x x y x y−( ) =

−−

−+ − + −( ) ( ) ( ) ( )

∆ ∆

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 247

other side. For larger islands where quasi-geostroph-ic dynamics operate, coastal trapped waves (Gill andClarke, 1974; Allen, 1975) accomplish much thesame thing, propagating their entrained velocityfields around the island to create an alongshore flowfrom the side of the island where the Ekman flow isaccumulating surface water to the side where it iscarrying it away from the coast. Clearly there will bean interdependence of time scales and space scalessuch that progressively larger islands will supportprogressively longer time-scale episodes of coastalupwelling or downwelling.

In this study, we take a quite pragmatic, empir-ical approach to deciding how to deal with islandsin this respect. Satellite images of the largestislands in the Mediterranean –Sicily, Sardinia,Corsica, Crete and Cypress– often exhibit sea sur-face temperature signatures indicative of coastalupwelling. Thus we chose to represent these assignificant coastline features in our computations(Fig. 1). For Mallorca and smaller islands, wefound these signatures to be less evident. (In thecase of Mallorca, in particular, the island was alsoparticularly hard to portray appropriately by any

248 A. BAKUN and V.N. AGOSTINI

10� 20�0�

Dec-Jan�

10� 20�0�

Feb-Mar�

10� 20�0�

Apr-May�

b.�

c.�

a.�

FIG. 3. – Seasonal variation of Ekman transport produced from smoothed distributions of wind stress estimates. Transport magnitudes (t s-1m-1) are indicated by length of the vector symbols (reference scale appears on each panel). (a) Dec-Jan. (b) Feb-Mar. (c) Apr-May. (d)

Jun-Jul. (e) Aug-Sep. (f) Oct-Nov.

available choice of grid-cell combinations in ourhalf-degree computation grid.) Consequently,coastal boundary effects of islands the size of Mal-lorca and smaller are absent from our computeddistributions of vertical velocity (Fig. 4). Readerswishing to gauge the seasonal distributions ofEkman convergence and divergence at the coastsof these smaller islands (which could possibly bereflected to some degree in corresponding verticaltransfers) will need to make reference to thesmoothed Ekman transport vector symbols them-selves (Fig. 3).

However, it should be noted that effects on thewind stress curl pattern that may be due to shelter-ing and wind-channeling effects of islands mayinduce the “open ocean” type of upwelling. If sucheffects are of sufficiently large scale, they shouldindeed be reflected in the computed results present-ed. But as discussed in Section 1.1, other potential“island effects” which are not directly forced bywind (e.g., upwelling occurring within eddy struc-tures produced by the interaction of current flowswith obstructing islands (Aristegui et al. 1997)) arenot addressed in this study.

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 249

10� 20�0�

Jun-July�

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Aug-Sept�

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Oct-Nov�

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FIG. 3. (Cont.) – Seasonal variation of Ekman transport produced from smoothed distributions of wind stress estimates. Transport magnitudes (t s-1m-1) are indicated by length of the vector symbols (reference scale appears on each panel). (a) Dec-Jan. (b) Feb-Mar. (c) Apr-May. (d)

Jun-Jul. (e) Aug-Sep. (f) Oct-Nov.

Smoothing and filling data gaps

Although the observational data available in theCOADS data base for the Mediterranean is ratherlarge in total amount, it is quite unevenly distributed.There are large zones, e.g., along the main ship routebetween the Straits of Gibraltar and the Suez Canal,much of the Gulf of Lyons, etc., containing at leastseveral hundred observations per half-degree quad-rangle for each 2-month seasonal segment (Fig. 2).However, there are other areas, e.g., along theAfrican coast, in the upper extremes of the Adriaticand Aegean Seas, etc., where data are exceedinglysparse, and in fact occasionally entirely lacking for agiven grid cell and 2-month seasonal segment. Obvi-ously, some means of filling data gaps is needed.

Even in the cases where data exist, one needs asignificant number of observations to arrive at anadequately stable seasonal mean of vector windstress components, the computed values of whichare extremely sensitive to variations both in winddirection and in wind speed (the effects of which areamplified by the process of raising the observedmagnitude to the second power; ref. Eq. 1). Sam-pling error in the curl calculation (Eq. 5) is furtheramplified by the process of subtracting the meancomponent values for adjacent samples one fromanother. Such sampling errors in the calculated windstress curl values tend to grow rapidly as observa-tions per grid cell sample fall significantly belowabout one hundred (Bakun and Nelson, 1991), caus-ing very disordered artificial spatial pattern toappear in resulting distributions.

To help ameliorate these problems, a combina-tion of linear and nonlinear spatial smoothing wasapplied to the distributions of the two vector com-ponents of wind stress. This was performed as fol-lows. First, a 1.5° lat x 1.5° long areal smoothing fil-ter, covering a total of nine grid cells, arranged in a3 x 3 square array was centered on the half-degreegrid cell for which a smoothed value is to be con-structed. The nonlinear part of the filter process,designed to guard against potentially serious distor-tions due to highly non-characteristic values appear-ing in one or two of the nine component cells of thefilter, consisted of trimming and discarding the twohighest and two lowest values among the nine datavalues found in the array. The linear part of theprocess consisted in computing the average of thevalues in the remaining five cells. This averagedvalue is then saved as the new “smoothed” value forthe grid cell location at the center of the filter. The

filter was applied cell by cell, for each of the two(northward and eastward) wind stress components,producing a new gridded field of smoothed valuesfor each of the wind stress components.

However, when filtering cells adjacent to the coastthe 3 x 3 grid cell filter encounters cells which havebeen designated as representing land. These areas, ifin reality they contain some actual areas of sea sur-face, may contain a certain amount of reported data.However, these valid data values would be sparse inany case relative to the much better data density andconsequent much greater reliability of the estimatesin the adjacent “sea” cells. Moreover, there is a strongpossibility that such cells may contain a large per-centage of mis-reported data. (For example, an areaof high data density in another hemisphere may con-tain reports in which the hemisphere code is enteredincorrectly, causing the maritime reports to erro-neously appear over land. Thus reports from the heav-ily trafficked route through the Straits of Gibraltarwhich were erroneously coded as “east latitude”instead of “west latitude” would appear as reports onthe Algerian coast land). Consequently we have cho-sen to delete such “land” cells from the filter area inwhich they fall. Then, the trimming procedure is per-formed as before and the resulting reduced number ofremaining cells averaged. (Thus if four cells wereremoved from the filter as being “land area” cells,five cells would remain. Of these, four would betrimmed. This would leave one remaining cell. Thevalue of that cell, i.e., the median of the values in thefive “sea” cells, would become the smoothed value atthe location over which the filter was centered.) Thereare several places where a “sea” cell is largelyenclosed such that the filter area centered on it maycontain only four or even three “sea” cells. In thesecases, we reduced the nonlinear part of the filter totrim only the single highest and lowest extreme val-ues. In the case of a “four sea cell” situation, thisleaves values which are then averaged to produce therelevant smoothed value. There is only one “three seacell” situation that occurs in the grided system (Fig. 1;i.e., the grid cell in the northwestern Aegean Sea thatextends into the bay containing the harbor of Thessa-lonika). In this case the smoothed value is represent-ed by the median of the three “sea” cells underlyingthe filter when it is centered at that location.

Significance of indicated features

Obviously, the finest level of spatial detaildefinable by the 0.5° x 0.5° data summaries will

250 A. BAKUN and V.N. AGOSTINI

have been attenuated by the smoothing processwhich was deemed necessary to suppress the grosssampling error variance and associated high noiselevel in the computed upwelling/downwelling dis-tributions which would have made interpretationquite difficult and tedious. However, at distancesgreater than about one grid mesh length from thecoast, where the patterning effects of coastaltopography have become diffused, one expects thatthis relatively fine scale would exhibit a lowerlevel of real signal relative to noise introduced bysampling errors.

Directly adjacent to the coast, however, the sit-uation might be different. By smoothing the largerscale wind stress field, one loses the finest scale ofspatial variation in the wind available in the one-half degree lat-long summaries. However, theeffect of coastline variation, as well as can beresolved on the one-half degree scale (Fig. 1), isindeed reflected in the vertical velocity estimates(shown in Fig. 4).,

Recall that the central difference derivatives usedin the curl calculation (Eq. 5) span two 0.5° gridmesh lengths. Also, the smoothing filter used maycause data to be incorporated from an additional0.75° distance on each end of that span. Thus themaximum possible length scale for any spatial inter-dependence imposed by our computation, smooth-ing, and analysis procedures is 2.5°. Consequently,features that exhibit unity and coherence on scaleslarger than a 2.5° linear scale can be assigned a highdegree of confidence. In addition, the separate two-month seasonal segments displayed in each of theadjacent panels of Figure 3 and of Figure 4 are basedon entirely separate, independent data sets. Thus, itis reasonable to assign an enhanced degree of confi-dence to features that remain evident, and are stableor exhibit a regular seasonal progression, betweenadjacent seasonal segments. The discussion to fol-low focuses on features that conform to both, or atleast to the first, of these criteria.

RESULTS

The Mediterranean Sea lies on the eastern flankof the major subtropical high pressure system of theNorth Atlantic Ocean, the Bermuda-Azores High.The interaction of this high pressure system with theseasonal continental pressure systems of the greatland masses situated to the south, east, and north ofthe Mediterranean, and with the Icelandic Low

which during the winter half of the year extends itsinfluence over much of western Europe, determinesthe major large scale aspects of the air-flow over theMediterranean zone. Over the western part, the iso-bars around the Bermuda-Azores High system gen-erally trend north—south throughout the year. Nearthe earth’s surface, the imbedded meridionalgeostrophic wind flow tends to be deflected some-what to the left by frictional effects, and so the seasurface stress has a generally southeastward tenden-cy in this area.

In winter, a weak thermal low pressure zoneforms over the relatively warm waters of theMediterranean. This interacts with a slight ridge ofrelatively high pressure that forms in winter over thenorthernmost edge of the African continental landmass, resulting in generally eastward wind stress,and corresponding southward (onshore) Ekmantransport (Fig. 3a) in the central and eastern portionsof the Sea. The effect of the enormous Asian wintercontinental high pressure system is reflected in thetendency for westward wind flow (northwardEkman transport) during winter in the extremenortheastern area.

In summer, there is quite a continuous zonal gra-dient of pressure between the seasonally strength-ened Bermuda-Azores High and the intense lowpressures of the Asian summer monsoon. Thisresults in a generally southward geostropic windflow, that near the sea surface is turned by frictionand local topographic effects to range from south-ward (westward Ekman transport) to eastward(southward Ekman transport) over much of theMediterranean zone. However, in the western halfnear the African coast, low pressure related to heat-ing of the continental surface turns the coastwisewind flow toward the west, yielding northward, off-shore directed Ekman transport.

These large scale features are reflected in thegross distributions of resulting wind-inducedupwelling and downwelling in the Mediterranean(Fig. 4): (1) downwelling along the southern coastalboundary during winter, reversing to coastalupwelling off Libya in spring and off Algeria insummer and fall; (2) strong upwelling in the easternAegean Sea throughout the year, becoming remark-ably intense in the summer and fall seasons; (3)strong summer and fall upwelling in the eastern Ion-ian Sea; (4) strong upwelling in the Gulf of Lyons;and (5) a tendency for upwelling on the westernand/or southern sides of the major islands and down-welling on the northern and/or eastern sides.

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 251

The Alboran Sea and adjacent area

The predominantly westerly winds in the Albo-ran Sea tend to induce coastward surface Ekmantransport and corresponding upwelling on the Span-ish side and offshore-directed transport and down-welling on the African side of this area of theMediterranean. However, during late summer andfall, the tendency reverses in the area to the east,yielding offshore-directed wind-driven Ekman

transport (Fig. 3d,e) and resulting upwelling (Fig.4d,e) along the Algerian coast and onshore tranportand downwelling off southeastern Spain (fromCosta de la Luz to Costa Blanca). A clockwise turn-ing tendency in the wind pattern off northernMorocco in summer produces an area of anticy-clonic wind stress curl, resulting in convergent sur-face Ekman flow and corresponding open oceandownwelling over the west central portion of theAlboran Sea.

252 A. BAKUN and V.N. AGOSTINI

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FIG. 4. – Seasonal variation of computed vertical velocities at the bottom of the surface Ekman layer. Units are meters per day. Contour inter-val is 0.25. Shaded areas indicate zones of upwelling. Darker shading indicates upward velocities greater than 0.5 m/day. Unshaded areas

indicate zones of downwelling. (a) Dec-Jan. (b) Feb-Mar. (c) Apr-May. (d) Jun-Jul. (e) Aug-Sep. (f) Oct-Nov.

The Balearic Sea

The Balearic Sea is characterized by a wind pat-tern favorable to convergent ocean surface transportand downwelling. However this pattern is brokenduring late fall and winter where strong downslopewinds developed in the valley of the Ebro Riverextend outward over the Sea in a strong offshore-directed wind jet. The resulting zone of strongcyclonic (positive) wind stress curl exerted on the

zone of sea surface located to the left of the jet axisproduces an area of Ekman divergence and associat-ed upwelling.

As discussed above (see the subsection oncoastal boundary condition in the Methods section),we have elected not to include the specific boundaryeffects of Mallorca or the other islands in the groupin our vertical velocity computions. However, thewind field associated with the Ebro jet extends to thevicinity of the islands where significant winter

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 253

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FIG. 4. (Cont.) – Seasonal variation of computed vertical velocities at the bottom of the surface Ekman layer. Units are meters per day. Con-tour interval is 0.25. Shaded areas indicate zones of upwelling. Darker shading indicates upward velocities greater than 0.5 m/day.

Unshaded areas indicate zones of downwelling. (a) Dec-Jan. (b) Feb-Mar. (c) Apr-May. (d) Jun-Jul. (e) Aug-Sep. (f) Oct-Nov.

wind-driven Ekman transport (Fig. 3a,b,f) is indicat-ed toward the northeastern coasts of the islands andaway from their southwestern coasts.

The Gulf of Lyons

An even stronger analog to the Ebro jet is the jetwhich exists to the north side of the Pyrénnéesmountain range, where a major topographic gapexists between the mountains of the Pyrénnées andthe French Massif Central groups. From this gap adeep valley slopes down to the Mediterranean coast,in which air cooled at higher altitudes tends to cas-cade downward displacing the warmer, less dense,surface air mass. The extension of this “Tramon-tagne” wind jet out over the Gulf of Lyons acts inconjunction with the similar “Mistral” wind jet pro-duced in the valley of the Rhone River to produceone of the most remarkable features of our comput-ed vertical velocity distributions. Strong zones ofintense Ekman divergence and convergence exist onthe respective cyclonic (left) and anticyclonic (right)sides of the jet axis. The divergent zone extends tothe northern coast of the Gulf, producing an intenseupwelling zone from Montpellier to Toulon alongthe stretch of coast which includes the Rhone Deltaand the port of Marseille. The divergent zone, inturn extends southeastward over the sea to beyondthe Balearic Islands and southwestward along theSpanish coast to Barcelona. The coupled feature isvery strong on average throughout the year butreaches maximum intensity in winter (Fig. 4a), withindicated seasonal average upward velocities at thebottom of the Ekman layer surpassing a meter perday near the coast in the northeastern part of theGulf, with downwelling velocities of even greatermagnitude being indicated near the coast in thesouthwestern part.

The Ligurian Sea

The coastal upwelling feature associated withthe Tramontagne-Mistral wind pattern actuallyextends around Cap Coisette and continues alongthe Côte d’Azur. Here it increases in intensity dur-ing the summer months (Fig. 4d) when the pre-dominently offshore-directed wind veers toward theeast to yield a larger stress component parallel tothe coastline. Offshore, the Ligurian Gulf is an areaof largely divergent wind-driven surface flowexcept for an area of convergence extending north-west from the Island of Corsica.

The Tyrrhenian Sea

Most parts of the west coast of Italy south ofthe island of Elba, except in the extreme south-west, are under the influence of winds that onaverage produce a mild net coastal upwelling ten-dency. An area of moderate wind driven surfaceflow divergence, and corresponding mild open seaupwelling, extends out from the part of this coastalupwelling zone which is north of the vicinity ofRome to intersect the southern half of the westcoast of Corsica.

South of Rome, the tendency in the offshore area isfor mild surface convergence which becomes moreintense with proximity to Sicily. The north coast ofSicily contains a zone of relatively intense down-welling which, during the spring and summer (Fig.4c,d,e), develops a moderately intense extension to thenorthwest that reaches to the west coast of Sardinia,which is a zone of coastal downwelling throughout theyear. However, between the western point of Sicilyand the southern part of Sardinia there tends to be azone of substantial wind-induced surface flow diver-gence and resulting Ekman upwelling.

The Adriatic Sea

The Adriatic Sea appears to be an area of ratherweak average net wind stress, which tends to have adegree of clockwise tendency resulting in weakcoastal upwelling on the Balkan side, weak to mod-erately strong coastal downwelling on the Italianside, and zones of moderate upward Ekman pump-ing in the interior.

The Ionian Sea

During the winter, a southwestward wind jetdevelops in the Gulf of Taranto. On the eastern(cyclonic) side of the jet an area of divergenceextends at least 200 km southward from the “heel”of the Italian “boot”. On the western (anticyclonic)side of the jet, a zone of convergence and coastaldownwelling occupies the area adjacent to thesouth coast of Calabria.

In spring, this feature fades. The interior of theIonian Sea becomes largely convergent but coastalupwelling begins to spread along the west coast ofGreece. In summer (Fig. 4d,e), a band of strongupwelling (reaching intensities greater than 0.5 mday-1 off the west coast of the Pelopinnisos) extendsalong the west coast of Greece.

254 A. BAKUN and V.N. AGOSTINI

The Aegean Sea

The Aegean sea is characterized by strongnortherly (southward) wind stress and correspond-ingly intense westward Ekman transport (Fig. 3).The resulting Ekman flow away from the coast onthe eastern side and toward the coast on the westernside produces a upwelling/downwelling couple thatis weakest in the spring (Fig. 4c). However, itstrengthens rapidly in the late spring and early sum-mer (Fig. 4d) to reach characteristic vertical veloci-ties of 0.5 to 1.5 m day-1 in a band along the easternboundary of the Aegean and beyond.

The same wind pattern produces, during thespring, summer and fall seasons, strong coastwardtransport (Figs. 3d,e) and associated downwelling(Fig. 4d,e) off the northeastern “corner” of theisland of. Crete.

The Levantine Sea

As these northerly winds exit the confines of theAegean, they undergo a general turning toward theeast. As a result, the strong upwelling band along theeast side of the Aegean actually curves around the“corner” of the Asia Minor peninsula to producecoastal divergence and upwelling off the southerncoast of Turkey. However, north of the island ofCypress this pattern is broken during the winter bythe effect of a lobe of the Asian winter monsoonhigh pressure system which impinges on that stretchof coast and induces an easterly (westward) windflow and corresponding surface Ekman transporttoward the coast (not shown well in Fig. 3 due tovector symbols that would extend across the coast-line being obscured) and resulting coastal down-welling (Fig. 4a).

In essentially all seasons, the channel betweenCypress and the continental coast is dominated byconvergent surface Ekman flow. Coastal divergencethat would tend to induce upwelling, occurs on thesouthern side of the island and is strongest in sum-mer (Fig. 4d).

Along the eastern boundary of the Levantine Sea,the wind stress is generally eastward, toward thecoast. Slight turnings of the vectors produce spots ofeither divergence or convergence; the coastal inden-tation formed by the coasts of Syria and Lebanon isgenerally a site of convergence.

The south coast of the Levantine Sea tends to be anarea of coastal convergence and downwelling though-out the year, but is most intense in winter (Fig. 4a).

Gulf of Sidra - Gulf of Gabes

The wide indentation of the continental coast-lines of Libya and Tunisia formed between the Gulfof Sidra (Sirte) and the Gulf of Gabes is an area ofextremely low data density. Thus the indications wecan draw are very uncertain. It seems generally to bean area of coastward Ekman transport and down-welling. However, during spring and summer thewind tendency appears to turn more northerly(southward) so that the stress becomes parallel to thecoastline tending to favor upwelling along the eastboundary of the Gulf of Sidra (Fig. 4c,d,e).

Algerian coast

The Algerian coast, like the rest of the Africancoast of the Mediterranean, is an area of coastaldownwelling during the winter season (Fig. 4a).However, during summer (Fig. 4d,e), coastalupwelling appears in response to turning of the windnear the coast toward the west, probably in responseto low barometric pressure effects related to solarheating of the adjacent land surface.

DISCUSSION

The Mediterranean Sea is not known for con-taining upwelling-dominated marine ecosystems.Nevertheless, several of the upwelling zones indi-cated in this study are substantial by world stan-dards. For example, using previously publishedestimates of characteristic Ekman transport magni-tudes (Parrish et al., 1983; Bakun and Parrish,1990), one may calculate characteristic upwardvertical velocities during the seasonal upwellingpeak, averaged over a zone extending 50 km off-shore (i.e., on a similar basis to the values pro-duced in this study) for some of the well-knownupwelling regions of the world. This would indi-cate that the values reached during late summer offsouthwestern Turkey, and during winter off thenortheastern coast of the Gulf of Lyons are equal tothose in the respective peak upwelling seasons offthe Iberian Peninsula or off Cabo Frio, Brazil. Inaddition, they are about 50% of the seasonal peakintensity in the upwelling maximum core (CapeMendicino) of the California Current, 45% that offnorth central Peru (Chimbote), 40% that off south-ern Peru (San Juan) or off Cap Blanc (in theCanary Current) and some 37% that off Lüderitz

WIND-INDUCED UPWELLING IN THE MEDITERRANEAN 255

(in the Benguela Current) which is the most intenseof the sustained eastern ocean coastal upwellingzones found on earth. (Of course, the most intenseoff large-scale ocean upwelling is that whichoccurs off northeastern Somalia during the South-west Monsoon, but that system is quite a specialcase (Bakun et al., 1998).) However, one does notsee (e.g., in satellite-sensed ocean color distribu-tions) these inferred Mediterranean upwellingzones delineated as areas of particularly high sur-face chlorophyll. There are various factors thatmight at least partially account for this. Because ofthe relatively high latitude location of the northernparts of the Mediterranean (many people are sur-prised to realize that for example Venice, Italy, isactually further north than Halifax, Canada), agiven intensity of offshore Ekman transport isaccompanied by a much higher input of turbulentmixing energy by the wind than would be the caseat lower latitude locations (Bakun, 1996). Thus,deep mixing will tend to inhibit development ofblooms near the upwelling zone itself. (The con-gruities between the shapes of the spatial patternsof surface chlorophyl pigments and of rates ofinput of turbulent energy by the wind Agostini andBakun (1999) are quite suggestive in this respect.)In both the cases of the Aegean and Gulf of Lyonsupwellings, the nutrients that are upwelled into thesurface layer are carried directly in the surfaceEkman transport field toward zones of conver-gence, which also happen to be under the influenceof fresher surface waters due to coastal runnoff,Black Sea inflow, major riverine lenses, etc. These“downstream” zones may be where a major portionof the upwelling-based production may actuallyresult (Agostini and Bakun, 1999).

Off course, the nutrient input to the surface lay-ers depends on the nutrient content of the waters atsource of the upwelling. Certainly, the thermoclinewaters of the Mediterranean have much lower con-centrations of dissolved nutrients than in easternboundary currents, which contain rich sub-polarwater masses being advected equator-ward withinthe thermoclines.

The work presented here does not attempt to pre-sent any convincing answers to such questions, butmerely to provide a basis for posing them, and there-by to contribute to the progressive process of sortingout and elaborating the various factors influencingthe biological productivity, species diversity, andresource sustainability of the Mediterranean LargeMarine Ecosystem.

ACKNOWLEDGEMENTS

Funding support for this work was provided by theMediterranean Action Plan of the United NationsEnvironment Programme (UNEP) and by theMarine Resources Service of the Food and Agricul-ture Organization of the United Nations (FAO)

REFERENCES

Agostini, V.N. and A. Bakun. – 1999. “Ocean Triads” in theMediterranean Sea: Physical mechanisms potentially structur-ing reproductive habitat suitability. FAO, Rome.

Allen, J.S. – 1975. Coastal trapped waves in a stratified ocean. J.Phys. Oceanogr., 5: 300-325.

Arístegui, J., P.Tett, A. Hernández-Guerra, G. Basterretxea, M.F.Montero, K. Wild, P. Sangrá, S. Hernández-León, M. Cantón,J.A. García-Braun, M. Pacheco and E.D. Barton. – 1997. Theinfluence of island-generated eddies on chlorophyll distribu-tion: a study of mesoscale variation around Gran Canaria.Deep-Sea Res. I, 44: 71-96.

Bakun, A. – 1978. Guinea Current upwelling. Nature, 271: 147-150.Bakun, A. – 1990. Global climate change and intensification of

coastal ocean upwelling. Science, 247: 198-201.Bakun, A. – 1996. Patterns in the Ocean: Ocean Processes and

Marine Population Dynamics. University of California SeaGrant, San Diego, California, USA, in cooperation with Centrode Investigaciones Biológicas de Noroeste, La Paz, Baja Cali-fornia Sur, Mexico.

Bakun, A., and C.S. Nelson. – 1991. Wind stress curl in subtropical east-ern boundary current regions. J. Phys. Oceanogr., 21: 1815-1834.

Bakun, A., and R.H. Parrish. – 1990. Comparative studies of coastalpelagic fish reproductive habitats: the Brazilian sardine (Sar-dinella aunta). J. Cons. Explor. Mer., 46: 269-283.

Bakun, A., and R.H. Parrish. – 1991. Comparative studies of coastalpelagic fish reproductive habitats: the anchovy (Engraulisanchoita) of the southwestern Atlantic. ICES J. mar. Sci., 48:343 -361.

Bakun, A., D.R. McLain and F.V. Mayo. 1974. – The mean annualcycle of coastal upwelling off western North America asobserved from surface measurements. Fish. Bull., U.S., 72:843-844.

Bakun, A., C. Roy and S. Lluch-Cota. – 1998. Coastal upwellingand other processes regulating ecosystem productivity and fishproduction in the western Indian Ocean. In: E. Okemwa, M.Ntiba and K. Sherman, (eds.), Large Marine Ecosystems of theIndian Ocean: Assessment, Sustainability, and Management,pp. 103-141. Blackwell Science Inc. Malden, Massachusetts,

Breidenbach, J. – 1990. EOFs of pseudo-stress over the IndianOcean (1977-85). Bull. Amer. Meteorol. Soc., 71: 1448-1454.

Crise, A. and G. Crispe. – 1998. The effect of seasonal forcings onthe nutrients gradients in the Mediterranean Sea: a numericalapproach. Rapp. Comm. int. Mer. Médit., 35: 112-113.

Cushing, D.H. – 1969. Upwelling and fish production. FAO Fish.Tech. Pap., 84.

Durand, M.-H., P. Cury, R. Mendelssohn, C. Roy, A. Bakun and D.Pauly (eds.). – 1998. Global Versus Local Changes inUpwelling Systems, ORSTOM Editions, Paris.

Ekman, V.W. – 1905. On the influence of the earth’s rotation onocean currents. Ark. Mat. Astron. Fys., 2: 1-55.

Gill, A.E. and A.J. Clarke. – 1974. Wind-induced upwelling, coastalcurrents, and sea level changes. Deep-Sea Res., 21: 325-345.

Goldenberg, S.B. and J.J. O’Brien – 1981. Time and space vari-ability of tropical Pacific wind stress. Mon. Wea. Rev., 109:1190-1207.

Mooers, C. and J.S. Allen. – 1973. Final Report of the CoastalUpwelling Ecosystems Analysis Summer 1973 TheoreticalWorkshop. School of Oceanography, Oregon State University,Corvallis, Oregon.

Nelson, C.S. – 1977. Wind stress and wind stress curl over the Cal-ifornia Current. U.S. Dep. Commer. NOAA Tech. Rep., NMFSSSRF-714.

256 A. BAKUN and V.N. AGOSTINI

Parrish, R.H., A. Bakun, D.M. Husby and C.S. Nelson. – 1983.Comparative climatology of selected environmental processesin relation to eastern boundary current pelagic fish reproduc-tion. In: G.D. Sharp and J. Csirke, (eds.), Proceedings of theExpert Consultation to Examine Changes in Abundance andSpecies Composition of Neritic Fish Resources, pp. 731-778.FAO Fish. Rep., 291:.

Roy, C. and R. Mendelssohn. – 1998. The development and the useof a climatic data set for CEOS using the COADS data set. In:M.-H. Durand, P. Cury, R. Mendelssohn, C. Roy, A. Bakun andD. Pauly (Eds.), Global Versus Local Changes in UpwellingSystems, pp. 27-44. ORSTOM Editions, Paris.

Servain, J. and D.M. Legler. – 1986. Empirical orthogonal functionanalysis of tropical Atlantic sea surface temperature and windstress. J. Geophys. Res., 91: 14181-14191.

Slutz, R.J., S.J. Lubkeer, J.D Hiscox, S.D Woodruff, R.I.. Jenne,D.H. Joseph, P.M. Steurer and J.D. Elms. – 1985. Comprehen-sive Ocean-atmosphere Data Set; Release 1. NOAA Environ-

mental Research Laboratories, Climate Research Program,Boulder, USA.

Smith, R.L. – 1968. Upwelling. Oceanogr. Mar. Biol. Ann. Rev., 6:11-46.

Sverdrup, H.U. – 1938. On the process of upwelling. J. Mar. Res.,1: 155-164.

Woodruff, S.D., R.J. Slutz, R.I. Jenne and P.M.Steurer. – 1987. Acomprehensive ocean-atmosphere data set. Bull. Amer. Meteor.Soc., 68: 1239-1250.

Wooster, W.S., A. Bakun and D.R McLain. – 1976. The seasonalupwelling cycle along the eastern boundary of the NorthAtlantic, J. Mar. Res., 34: 131-141.

Yoshida, K. – 1967. Circulation in the eastern tropical oceans withspecial reference to upwelling and undercurrents. Japan. J.Geophys., 4: 1-75.

Scient. ed.: J. Font

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