Seasonal variability of the oceanic upper layer and its modulation of biological cycles in the Canary Island region

biologi al y lesintheCanaryIslandregion C.Troupin

a,

∗

,P.Sangrà

b

andJ.Arístegui

b

a

UniversitédeLiège,GeoHydrodynami sandEnvironmentResear h(B5a),B4000Liège,Belgium

b

Fa ultaddeCien iasdelMar,UniversidaddeLasPalmasdeGranCanaria,35017LasPalmasdeGranCanaria,Spain

Abstra t

TheCanaryIslandregionisri hinmesos ale phenomenathatae t y lesofphysi aland biologi alpro esses.A 1Dversion

of theRegional O eani Modeling System(ROMS)is usedsouthof theGranCanaria Islandto simulateseasonal limatologies

of these y les.The modelis for ed with monthlyair-sea uxes averaged from1993 to 2002 and initialized with mean insitu

prolesoftemperature,salinity,oxygenandnitrate on entrations.TheK-ProleParameterization(KPP)mixed-layersubmodel

is ompared withother submodels usingidealized numeri al experiments.When for ed with realisti air-sea uxes, the model

orre tlyreprodu estheannual y leoftemperature(mixedlayerdepth),withminimumsurfa evaluesof18

◦

C(maximaldepth

>

105m)inFebruaryduring onve tivemixingresultingfromanegativeheatux.Maximumtemperaturesabove23

◦

C(minimal

depth

<

20m)aresimulatedfromSeptembertoO toberafterstrongsummerheatingandade reaseinTradeWindsintensity. Asimplee osystemmodelis oupledtothephysi almodel,whi hprovidessimulatedbiologi al y lesthatareinagreementwith

regional observations.Aphytoplanktonbloomdevelopsinlatewinter,drivenbytheinje tionofnewnutrientsintotheeuphoti

layer.Chlorophyllhasadeepmaximumu tuatingaround100mwith on entrationsaround1mg

Chl

a

m

−3

,whilesurfa evalues

arelow(around0.1mg

Chl

a

m

−3

)duringmostoftheyear.Thephysi alandbiologi almodelresultsarevalidatedby omparisons

withdatafromregional ampaigns, limatologi aleldsandtime-seriesfromtheESTOCstation.

Keywords: CanaryIslands,Mixedlayerdepth,ROMS1Dbio-physi almodel,biologi al y les,KPPmodel,NPZDmodel,Latitude

27.5

◦

N,longitude15.5

◦

W PACS:92.60.Aa,92.10.Lq,92.60.C ,92.05.Fg 1. Introdu tion

TheCanaryIslandAr hipelagois omposedofseven

is-landslo atedinthepassageofthe ool,southwestward

Ca-naryCurrent(CC), onsideredastheeasternboundaryof

theNorthAtlanti subtropi algyre.Thestudyofphysi al

and biologi al y les in this regionis an importanttopi

onsideringthenumerousphysi alpro essesthatinuen e

these y les.

Sin ethe1990's,manystudieswere arriedoutinthe

Ca-naryIslandareainordertoexamineintera tionsbetween

physi alandbiologi alpro esses(e.g.Arísteguietal.,1994,

1997; Arístegui and Montero, 2005; Barton et al., 2004;

Pelegrí et al., 2005a,b). Alongwith these in situ studies, time-series data were a quired throughmooring stations,

su hastheEuropeanStationforTime-SeriesintheO ean,

∗

Correspondingauthor.

Emailaddress: troupinulg.a .be (C.Troupin).

CanaryIslands(ESTOC,Fig.1),lo ated100kmnorthof

GranCanaria(Neueretal.,2007).Satelliteimageryfrom theregionwasusedto onrmtheseobservations(Barton etal.,2001;Davenportetal.,2002).

Braun(1976) arried outa survey5miles o Tenerife from1971to1972betweentheo eansurfa eand1200

me-ters.Lowlevelsofnutrientsalongwitha learseasonal

vari-ationofphytoplanktonwerereported, onrmingthe

olig-otrophi onditionsofCanaryIslandwaters(e.g.DeLeón andBraun,1973;Arísteguietal.,1997).

Summeris hara terizedbyasharpseasonalthermo line

that preventsthe inje tionof nutrientsinto the euphoti

zone,resultinginlowphytoplankton on entrations.

Maxi-malphytoplankton on entrationsappearinlatewinter

un-dertheee tof onve tivemixingandthermo lineerosion,

whi h makenutrientsavailable for phytoplankton. These

high on entrationswerealsoobservedbyHernández-León et al.(1984)insouthern Canarywaters,Hernández-León etal.(1984)onthesoutheasternshelfoftheGranCanaria

Island,andArísteguietal.(2001)in oastalwaterseastof GranCanaria.

Despite interest in understanding biologi al y les in

this area, only a few oupled physi al-biologi al models

have been developed. Zielinski et al. (2002) used a one-dimensional model in order to test dierent

parameteri-zations of the photosyntheti ally a tive radiation (PAR)

atESTOCstation.Althoughtheirmodelprodu ed

realis-ti resultsfortemperatureand hlorophyll on entration,

there wasno validation of the mixed layer depth model,

whi h isof ru ial importan e forthemodulationof

bio- hemi al y les.

Bahamón and Cruzado (2003) ompared the NW Mediterranean and NE Atlanti using a one-dimensional

model, but theirresults forthe physi al variables donot

representa uratelytheseasonal y lesinthese ond

sys-tem.Theyshowedstrati ationstartinginApril,whi his

tooearly,andtwomaximaforthephytoplankton.Therst

maximumwasinwinterandthese ondinfall,asituation

thatismoretypi alforhigherlatitudes.

Therst obje tiveof thepresent work wastosimulate

theseasonal y leoftheuppero eani layersimilartowhat

wasobserved in theCanaryIslandregion. Tothisend, a

one-dimensional physi al-biologi al oupled model for ed

withre entlydeveloped limatologiesforair-seauxes(e.g.

OAFluxesforheat,Tab.2)andinitializedwith

hara ter-isti onditionsofthisparti ularregionwasused.

ApointsouthofGranCanaria(Fig.1)wassele tedfor

modelimplementationbe ausethebiologi alpropertiesin

this area were more frequently sampled. The model

im-plementation site is lo ated in the transitional zone

be-tweentheupwellingri hwatersandtheoligotrophi

inte-rioro ean.Itmaybeae tedbymesos alevariability

in-trodu edbytheAr hipelago,buttheseee tswereltered

outinthe limatologi alobservations.Be auseofthe

re og-nition that dynami sof theo ean upperlayerare

funda-mentalforthemodulationofbio hemi aluxes,spe ial

at-tentionwaspaidtothemixedlayerseasonal y le,making

omparisons withother physi al model outputsand with

availablemeasurements.

A se ondobje tivewastheestablishmentofaseasonal

limatology of biogeo hemi al properties of the o eani

upper layer, whi h will help in implementing a

three-dimensional physi al-biogeo hemi almodel urrently

un-der development(Mason et al., 2008b,a), asis a oupled larvaemodel fo usedonthe sameregion (Bro hieret al.,

2008).

To a hieve these goals, the work is divided into ve

parts: the rst is the des ription of the dierent

ompo-nents(physi s,biology,mixedlayer)ofthemodel,aswell

astheassumptionsbehindthem(Se tion2). Nextdetails

ofthemodelsetuparedes ribedbyoutliningfor ingand

initialization onditions(Se tion3),asthesearekeyto

gen-eratingrealisti solutions.Themodelbehavioristestedin

idealizedexperiments(Se tion4)andtheresultingannual

eldsarepresented(Se tion5)andvalidated(Se tion6).

18

o

W

17

o

W

16

o

W

15

o

W

14

o

W

13

o

W

26

o

N

27

o

N

28

o

N

29

o

N

30

o

N

T

P

H

G

GC

F

L

Fig.1.TheCanaryAr hipelago:P=LaPalma,H=ElHierro,G=

LaGomera,T=Tenerife,GC=GranCanaria,F=Fuerteventura,

L = Lanzarote. The region of interest is lo ated south to Gran

Canaria(square).Cir le denotes ESTOCstation and trianglesare

thelo ationsoftheprolesusedintheinitialization.

2. Modeldes ription

Simulations were arried outwith the one-dimensional

version of ROMS (Regional O ean Modeling System,

Sh hepetkin and M Williams, 2005); the mixing losure sub-model,treatmentsof verti aladve tionand diusion

are ompatible between the 3D and the 1D model. A

stret hedverti al oordinatesystemprovidesanin reased

resolutionnearthesurfa eboundarylayer(Penven,2006).

2.1. Hydrodynami smodel

The hydrodynami s model omputes velo ity

ompo-nents(

u

and

v

),temperature(

T

)andsalinity(

S

).Density isderivedfromthestateequationofJa kettandM Dougall

(1995).Hydrostati and

f

-planeapproximationsaremade. Twoimportant onsequen es arise from theuse of a1-D

model:

(i) theverti alvelo ityisnulleverywhere:

w = 0

, (ii) adve tionisnotmodeled

(u · ∇)X = 0

,with

u

, the

velo ityve tor,and

X

,anys alarvariable.

Temperatureandsalinityarebothrelaxedtowardtheir

ini-tialvaluewitharelaxationtime

τ

dependingofthedepth:

τ = 2+23 exp(z/100)

.Thisformulagivesavalueof

τ

about 5yearsbelow200mandupto25yearsatthesurfa e.

2.2. Mixedlayermodel

Small-s ale pro esses are parametrized with the

K-Prole Parametrization (KPP, Large et al., 1994). With this s heme, the mixed-layerdepth (MLD hereinafter) is

denedasthedepth

d

atwhi hthebulkRi hardson num-ber, whi h measures the ratio between strati ation and

Ri

b

(d) =

[B

r

− B(d)]d

|V

r

− V(d)|

2

+ V

2

t

(d)

= Ri

cr

= 0.3,

(1) where

B

r

and

V

_r

are estimatesof the averagebuoyan y

andvelo ity,respe tively,and

V

t

/h

istheturbulentvelo ity shear.

When buoyan y for ing is stable, the boundary layer

depthistakenastheminimumofthevalue omputed

a - ordingtoEq.(1),theMonin-Obukovlengthandthe

Ek-mandepth.

The KPP model enables to take into a ount mixing

throughsaltngering(warmsaltywaterover oolfresh

wa-ter),atypi alpro essinregionswithlowpre ipitationand

intensesolarradiation.

2.3. E osystemmodel

Theboxmodel(Fig. 2) from Fashamet al.(1990)was designed to simulate annual y lesof plankton dynami s

and nitrogen y lingin theuppero eani layer.Nitrogen

isgenerally onsidered asthelimitingnutrientofprimary

produ tion,hen eits hoi eas entralelementofthe

bio-logi almodel.TheFashametal.(1990)modelhasbeen ap-pliedtonumerousareasoftheo ean(e.g.Sarmientoetal.,

1993;Drange,1996).TheversionimplementedinROMSis anevolutionofthismodel(Gruberetal.,2006),whi hhas alsobeenappliedtoanothertransitionzone(California).

It was hosenforits simpli ity, a ordingtothe

obje -tiveofgettingmeanseasonal y les.Moreover,themodelis

ompartmental,sothatitpermitsthedistin tionbetween

newprodu tion(drivenbynewnutrients,primarilynitrate,

thatoriginatesfromoutsidetheeuphoti zone)and

regen-eratedprodu tion(drivenbynitrogenre y ledwithinthe

euphoti zone,mainlyammonium)(DugdaleandGoering,

1967). Ba teriawere eliminated asan expli itlymodeled statevariable,andrepla edwithimpli itparametrizations

ofremineralizationpro esses(Gruberetal.,2006). Biologi al variables are oupled to physi s by an

adve tion-diusion-rea tion equation and through

tem-perature. The latter inuen es various produ tion terms

of the e osystemmodel. This again emphasizesthe need

ofa orre trepresentationoftemperatureseasonal y le.

Themodelisalsofor edbythephotosyntheti ally

avail-ableradiation(PAR),derivedfromtheshortwavesolar

ra-diation(Fig.3)a ordingtothefollowingsteps(Frentzel,

2006):

(i) A linearly interpolated value is al ulated for ea h

timestep.

(ii) Adiurnal y leforinsulationissuperimposedonthe

solar shortwave radiation. If the al ulated surfa e

radiationisnegative,zeroisusedinstead.

(iii) Startingfromthetop,the

P AR

is al ulatedforea h gridboxa ordingto

P AR



=

P AR

+1

exp {(−0.5 (k

w

+ k

Chla

[Chla]



) ∆z



}

(2)

with

k

w

and

k

Chla

, the attenuation oe ients for waterand hlorophyll(Tab.1),

[Chla]

the hlorophyll on entration,

∆z

,theheightoftheverti algridlayer and



the ellindex,from1atthebottomtoNatthe top.

Aslightabundan eisanessentialfa torforprimary

pro-du tioninpelagi systems,ana urateparametrizationof

itsvariationwithdepth isrequired.Zielinskietal.(2002) testedseveral

P AR

parametrizationsandshowedthatthe lightmodelhassigni antee tsonthesimulated

distri-butionof hlorophyll,bothinspa eandtime.They

re om-mendusingamodelwithanin reasedvalueofthe

attenua-tion oe ientnearthesurfa e,duetoabsorptionatlarger

wavelengths,andwithaspe i hlorophyllattenuation.

Modelparametersfortheuxesbetween ompartments

(Tab.1)areeitherbasedonmeasuredvaluesintheregion,

orarestandardvalues.Whennoinformationwasavailable

fortheregionofinterest,modelpres ribedvalues,originally

adaptedtoCaliforniaregion,wereused.

Fig.2. Compartments and nitrogenuxes ofthe biologi al model

(reprodu edfromFrentzel(2006)).

3. Simulationssettings

3.1. For ing

TheROMS1Disfor edbyheatuxes,windstressand

freshwaterux.Theseelds wereextra tedfromdierent

databases (Tab.2) andmonthly averagedvaluesfor the

1993-2002 period were omputed at a lo ation south of

GranCanaria(

27.5

◦

N,

15.5

◦

W).The hoi eofthe10-year

averagedfor ingeldswasmotivatedbythedesireto

ob-tainameanseasonal y le.Shortertimes alepro essesare

Parameters ofthe biologi almodel:(1)Fasham etal.(1990), (2)Gruber et al.(2006), (3) Redeld(1934), (4) Zielinskiet al.(2002), (5)

Sarmientoetal.(1993),(6)Dadouetal.(2001);(

⋆

)modeldefaultvalues.

Parameter Symbol Values Unit Sour e

Lightattenuationduetoseawater

k

w

0.04

m

−1

(1,2)

Lightattenuationby hlorophylla

k

Chla

0.025

m

2

_{(mg Chla)}

−1

(2)

Initialslopeofthe

P − I

urve

α

5.00

mg C(mg Chla W m

−2

_d)

−1

(

⋆

)

C : N

ratioforphytoplankton

r

C:N ;phyto

6.625

mM ol C(mM olN )

−1

(3)

Maximum ellular hlorophyllto

C

Ratio

θ

m

0.053

mg Chla : mg C

(2) Inversehalf-saturationforphytoplankton

N O

3

uptake

K

N O

3

1/0.5

1/(mM olN m

3

₎

(4)

Inversehalf-saturationforphytoplankton

N H

4

uptake

K

N H

4

1/0.1

1/(mM olN m

3

₎

(

⋆

)

Phytoplanktonmortalitytosmalldetritusrate

t

P mort

0.07

d

−1

(5)

Zooplankton-spe i maximumgrazingrate

t

Zgraze

0.75

d

−1

(

⋆

)

Zooplanktonassimilatione ien y

AE

0.75

−−

(2,4,6)

Zooplanktongrossgrowthe ien y

GGE

0.65

−−

(

⋆

)

Zooplanktonhalf-saturation onstantforingestion

Z

P

1.00

mM ol N m

3

(2)

Zooplanktonspe i ex retionrate

t

Zbmet

0.10

d

−1

(

⋆

)

Zooplanktonquadrati mortalitytodetritus

t

Zmort

0.10

d

−1

_{(mM ol N m}

3

₎

−1

(2)

Smalldetritalbreakdownto

N H

4

rate

t

SDremin

0.1

d

−1

(

⋆

)

Spe i (Per unit

P hyto

+

SDet

)aggregationrate

t

coag

0.005

(mM ol N m

3

₎

−1

_d

−1

(2)

Spe i rateoflargedetritusre y lingto

N H

4

t

LDremin

0.1

d

−1

(

⋆

)

Sinkingvelo ityforsmalldetritus

w

SD

0.1

m d

−1

(

⋆

)

Sinkingvelo ityforlargedetritus

w

LD

10.0

m d

−1

(2,5)

Sinkingvelo ityforphytoplankton

w

P hyto

0.1

m d

−1

(

⋆

)

Sinkingvelo ityfor hlorophylla

w

Chla

0.1

m d

−1

(

⋆

)

Oxidationof

N H

4

to

N O

3

(nitri ation)

t

nitri

0.1

d

−1

(

⋆

)

Figure3showsthenetheatux obtainedfrom OAux

data base. Maximal values (around 150

W/m

2

) o ur

in July-August and minimal negative values o ur from

November to February, leadingto winter onve tion, the

mainfa torprodu ingmixedlayerdeepening.

Figure4illustratestheannual y leofwindstressfrom

NCEP reanalysis. Maximum intensities about 0.1

N/m

2

wererea hedduringsummermonthsduetoanin reasein

thestrengthoftheTradeWinds.AsexplainedinSe .5the

stabilizing ee t of amaximum positive netheat ux in

summerandthedestabilizingee t ofwind stressduring

thisperiodleadstothemaximalstrati ationinautumn.

Freshwater ux annual y le (ECMWF reanalysis) is

showninFig.5.Valuesrangefrom0.065

cm/day

in sum-merto 0.1

cm/day

in winterandare weakin omparison withtemperateregions.

Seasurfa etemperature(SST,Fig.5)isrequiredto

or-re ttheheatuxesbe auseofthesensitivityofthesurfa e

net heat ux to the

SST

(Haney, 1971; Killworth et al.,

2000). The maximum is rea hed in September, after the TradeWindsweaken.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

−150

−100

−50

0

50

100

150

200

250

300

Months

Heat fluxes (W/m

2

)

Net heat flux

Solar shortwave radiation

Fig.3.Mean y les(boldline)andindividualyearsfrom1993to2002

(thinlines)ofsurfa enetheatux(plainlines)andsolarshortwave

radiation(dashedlines)fromOAux.

3.2. Initialization

The model was initialized in Mid-August with in situ

on-Jan Feb Mar Apr May Jun

Jul

Aug Sep Oct Nov Dec

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Months

Wind stress (N/m

2

)

Fig.4.SameasFig.3,butforwindstressfromNCEPReanalysis.

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

0.04

0.06

0.08

0.1

0.12

0.14

Months

Precipitation minus evaporation (cm/day)

P−E

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

18

19

20

21

22

23

24

25

Months

Sea Surface Temperature (

°

C)

SST

Fig.5.SeaSurfa eTemperaturefromNOAAOISSTV2and

fresh-wateruxfromECMWF40YearsRe-Analysis.

Table2

Sour esofreanalyzeddatausedformodelfor ing.

Data sour e

SST NOAA optimum interpolation SST V2 (Reynolds etal.,2002)

NHFLux Obje tively Analyzed Air-Sea Fluxes (OAFlux) for

theGlobal O eans(Yuet al.,2004;Yu andWeller,

2007;Zhangetal.,2004)

FWFlux ECMWF40YearsRe-Analysis(Uppalaetal.,2005)

WStress CDC Derived NCEP Reanalysis Produ ts Surfa e

Flux(Kanamitsuetal.,2002)

entrationsfromtheFAX ruise(Bartonetal.,2004). Ver-ti al proles were averaged within the region of interest

andttedwithfourth-orderpolynomials,in ordertohave

analyti alexpressionsforinputtothemodel.Higherorder

polynomialsweretested but resulted in largeos illations

thatwerenotphysi allyrealisti .Withthisaveraging,the

spatialvariabilityinherenttothezonesurveyedduringthe

FAX ampaignisremoved.

Salinity proles (Fig. 6) show the de rease of salinity

with respe t to depth below the mixed layer.This

nega-tivesalinitygradientis hara teristi ofsubtropi alregions,

whereevaporationandsolarradiationarehighthroughout

theyear(Figs.3and5).Thissituationisfavorableto

dou-blediusionthroughsalt-ngeringandthereforeenhan es

mixing(Pérezetal.,2001).

8

10

12

14

16

18

20

22

24

−500

−450

−400

−350

−300

−250

−200

−150

−100

−50

0

Temperature

Depth (m)

T (

°

C)

35.5

36

36.5

37

37.5

38

38.5

39

−500

−450

−400

−350

−300

−250

−200

−150

−100

−50

0

Salinity

Depth (m)

S (PSU)

Fig.6.Proles oftemperature and salinityusedfor model

initial-ization.Boldlinesrepresent meanvaluesobtainedfromindividual

FAXproles(thinlines).

Oxygen surfa e on entration is slightly lower than 5

µmol/m

3

andrea hesitsmaximumaround75m.Nitrate

hasverylow on entrations(

≤ 1 µmol/m

3

)intherst100

m,thenqui klyin reasestorea hmorethan

15 µmol/m

3

at500m.

Theotherphysi alandbiologi alvariablesareassigned

with onstantvaluesoverthewater olumn:

 Theinitialvelo itiesweresettozero.

 The initial value for the verti al mixing oe ient for

momentum(

K

M

)was

0.01 m

2

_/s

.

 The verti al mixing oe ients for salinity (

K

S

) and temperature(

K

T

)weretakenequalto

0.001 m

2

_/s

.

 Theremainingbiologi alvariableswereinitializedwith

onstantvaluesrepresentativeoftheregion(Tab.3). In

the aseofzooplankton,measuredvalueswere onverted

into units ompatible with the model (

mM ol N

2

m

−3

)

using onversions fa torsof zooplankton biomass from

Harris et al. (2000). For ammonium, the mean value obtained from numeri al simulations (Bahamón and Cruzado,2003)isassignedastheinitial ondition.

Initialvaluesforthebiologi alvariables.(

⋆

)denotesdefaultvalues.Phytoplanktonwasinitializedusingthemaximal hlorophyll/phytoplankton

ratio.

Variable Unit Pres ribedvalue Sour e

Ammonium

mM ol N

2

m

−3

_0.1

BahamónandCruzado(2003)

Chlorophylla

mg Chl

a

m

−3

_0.5

Arísteguietal.(1997) Phytoplankton

mM ol N

2

m

−3

_0.1187

Redeld(1934) Zooplankton

mM ol N

2

m

−3

_0.06

Hernández-Leónetal.(2007) Smalldetritus

mM ol N

2

m

−3

_0.04

(

⋆

) Largedetritus

mM ol N

2

m

−3

_0.02

(

⋆

)

2

2.5

3

3.5

4

4.5

5

−500

−450

−400

−350

−300

−250

−200

−150

−100

−50

0

Oxygen concentration

Depth (m)

[O

2

]

10

12

14

16

18

20

22

24

26

28

−500

−450

−400

−350

−300

−250

−200

−150

−100

−50

0

Nitrate concentration

Depth (m)

[NO

₃

]

Fig.7.SameasFig.6butforoxygenandnitrates.

3.3. Modelsetup

Thesimulationparametervalueswere hosentoprodu e

anannual y leandtosatisfythenumeri al onstraintsof

stability.Numerousrunsweremadetodeterminatesuitable

values.

Themodelwasrunfor6yearstosteadystate onditions,

withatimestep

∆t = 60s

.Resultswerestoredon eaday, whi hremovesshorttimes alevariability.

The water olumn was limited to the rst 500 m and

dis retizedonastaggeredgrid.Thedepthofthe

i

th

layer isgivenby

d(i) = −h

sinh θ

N −i

N

sinh(θ)

,

i = {0, 1, . . . , N },

with

h

the totaldepth,

N

thenumberof layersand

θ

, a parameterfor the adjustment of the grid spa ing.The

numberoflayers

N

was hosentobe40.Alargernumber

oflayersin reasedthe omputationaltimewithoutgiving

signi antdieren esintheresults.

θ

wastakenequalto4 tohaveaneresolution(

≈

1.5m)nearsurfa e.

4. Modeltesting

Before performing simulations with the for ing and

initial onditionsdes ribedinse tions3.1and3.2,

respe -tively,theKPPmodelis omparedwithothermixedlayer

models using idealized experiments. These experiments

werenotdesignedtoberepresentativeofthe onditionsof

theregion of interest, but to provide ommon

ongura-tionsforevaluatingthemixingsubmodels.

4.1. Des riptionoftheexperiments

Inea h experiment,latitudewastakentobe

29.91

◦

_N

,

whi hgivesaninertialperiod loseto24hours,andallows

omparisonswith similar resultsfrom other models. The

verti alresolution isuniformoverthewater olumnwith

∆z = 2 m

.Thevelo ityisinitializedwithzerovalueinea h dire tion.Theexperimentsaredes ribedhereinafter.

(i) thedeepeningexperiment(Exp.I)wasdesignedto

ex-aminetheee tsofwindstressonthewater olumn

stability.It onsistsofawindwith onstantdire tion

andintensity(

τ = 0.4 N/m

2

)for5 days.Theinitial

temperaturewassetto

24

◦

_C

atsurfa e,witha

ther-malstrati ationof

0.05

◦

_C/m

.Thesurfa enetheat

uxwassettozero.

(ii) the oolingexperiment(Exp.II)showedmixedlayer

deepening due to onve tive mixing produ ed by a

negativeheat ux. Initial onditionswerethe same

asthepreviousexperiment;windstresswasassigned

a onstantvalue

τ = 0.1 N/m

2

andsurfa enetheat

ux wastaken to be

−96.8 W/m

2

. The experiment

wasrunfor120days.

(iii) the heating experiment (Exp.III) illustrated mixed

layershallowingwhen the o eanexperien es a

pos-itive net heat ux. The initial onditions were the

sameasthetwoprevious ases,ex eptthat

19

◦

_C

.The wind stress wasequal to

τ = 0.1 N/m

2

andthenetheatuxwas

290.4 W/m

2

.

4.2. Des riptionofthemodels

TheKPPmodelis omparedwithveothermodels:the

Mellor-Yamada level2(MYL 2) andlevel 2.5(MYL 2.5)

losures(MellorandYamada,1974),theNiiler(Niilerand Kraus, 1977, Nii.), Garwood (Garwood, 1977,Gar.) and Pri e-Weller-Pinkel(Pri eetal.,1986,PWP)models.The rsttwomodelsbelongtothe ategoryofdierential

mod-els,i.e.governingequationsintheirprimitiveformareused,

whilethethreeothermodelsbelongtothe ategoryof

inte-gratedmodels,i.e.governingequationsareintegratedover

themixedlayerdepth.Resultsoftheexperimentsare

sum-marizedinTab.4.Forea hexperimenttheMLD omputed

withROMS1Dis ompatiblewiththevaluesobtainedwith

theothermodels.

Table4

Mixedlayerdepth(inmeters)indierentexperimentswith6models.

Models MYL2 MYL2.5Nii. Gar. PWP ROMS1D

Exp.I 39 39 54 51 54 42

Exp.II 101 103 127 117 101 110

Exp.III 14 14 4 14 8 7

5. Numeri alresults

5.1. Physi s

Annualeldsgeneratedwiththefor ingdes ribedin

se -tion 3.1 and with the parametersof se tion 3.3 are

pre-sented.

5.1.1. Temperature

Temperature(Fig.8)rea hedamaximumfromlate

Au-gustto mid-O toberwithvaluesaround

23

◦

_C

. The

tem-peraturemaximumdoesnoto urwhentheheatuxwas

maximum (July-August), but rather in September, after

the period of peak insulation. This arises be ause of the

destabilizingee tofTradeWinds,whi hrea htheir

maxi-malintensityinJuly-August(Fig.4).Alongwiththis

max-imaltemperature,astrongstrati ationtakespla eunder

theinuen eofintensesolarheating.

FromFebruaryto May, strong onve tivemixing took

pla eandgeneratedminimumtemperaturesaround

18

◦

_C

.

Thevariabilityindu edbyair-seauxesae tedonlythe

upper 125 m of the water olumn, sin e temperature is

fairly onstantbelowthisdepth.

5.1.2. Mixedlayerdepth

TheMLD istheupperpartofthewater olumn where

propertiesaredistributedquasihomogeneously.This

phys-i al property does not only a ountsfor the inuen e of

Months

Depth (m)

(

°

C)

13

14

15

16

17

18

19

19

20

22

23

21

Jan Feb Mar Apr MayJun Jul AugSep Oct NovDec

−450

−400

−350

−300

−250

−200

−150

−100

−50

14

16

18

20

22

Fig.8.AnnualtemperatureeldobtainedwithROMS1D.

ea hfor ingparameter(wind,surfa etemperature,

pre ip-itation,heatuxes),butalsostronglydetermines

bio hem-i al y les.

The annual evolution of mixed layer omputed with

ROMS 1D model (Fig. 9, plain line) follows the

temper-ature behavior: the mixed layer is deepest in February

(

> 100

m) after a period of onve tive mixing starting in November.Then shallowing startsasnet heat ux

in- reasesandrea hesavaluearound25mbetweenJulyand

September,despiteintensesummerTradeWinds(Fig.4).

Deepening startsagain after September,under the ee t

ofde reasingsurfa enetheatux.

Jan

Fev

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

−180

−160

−140

−120

−100

−80

−60

−40

−20

0

Months

Mixed Layer Depth (m)

ROMS 1D −− KPP submodel

∆

T = 0.5

°

C from 10 m

Kara criterion with ROMS1D solution

Kara criterion with WOA05

Fig.9. Mixed layer depth: ROMS 1D  KPP model (plain line),

sametemperature riterionasNeueretal.(2007)(dashedlinewith



),density riterionfromKaraet al.(2000)appliedto ROMS1D solution(dashedlinewith

∇)

and toWOD05 limatology(dashed

5.2. Biology

5.2.1. Phytoplankton

AsillustratedinFig.10,maximalphytoplankton

on en-trationsappearinFebruaryintherst100m.This

maxi-mumisexplainedbyanutrientinje tionintotheeuphoti

zoneprovokedbythethermo lineerosionindu edby

win-ter onve tivemixing.From mid-June,adeepmaximum,

alsovisibleinthe hlorophylleld(Fig.11),develops.

Beyond 150 m,phytoplankton on entrations are very

small (

O(10

−4

₎

mMol

N

2

m

−3

). From asimple point of

view,phytoplanktonneeds two ingredientsto grow:light

and nutrients. Sin e light de reases exponentially with

depth, it be omes insu ient to sustain phytoplankton

growth, even though a su ient amount of nutrients is

available.

Months

Depth (m)

(mMol N

2

m

−3

₎

0.05

0.1

0.15

0.2

0.25

0.25

_0.25

0.25

0.3

0.3

0.35

Jan Feb Mar Apr MayJun Jul AugSep Oct NovDec

−150

−100

−50

0

0.05

0.1

0.15

0.2

0.25

0.3

Fig.10.Phytoplankton on entrationobtainedwithROMS1D.

5.2.2. Chlorophyll

Among thenumerous variablesof themodel, itis

par-ti ularlyinterestingtopresent hlorophyll on entrations,

sin ethisvariablewasinitializedwitha onstantvalue,

al-lowingthemodelto showits apabilityto reprodu ereal

prolesbyitself.

Figure 11 shows a homogeneous mixed layer of low

hlorophyll above a deep hlorophyll maximum (DCM)

developedinspringandsummer,withmaximal

on entra-tionsaround1mg

Chl

a

m

−3

at100m.Surfa e

on entra-tionsrangefrom 0.4mg

Chl

a

m

−3

,whenthemixed layer

isdeepest,to1mg

Chl

a

m

−3

insummer.

5.2.3. Summary

Inorderto summarizetheannualbiologi al y le,

on- entrationsbetweensurfa eandareferen edepth(the

eu-photi depth)areintegrated.Thelight-depthrelationship

usedinthemodelgivesanestimatedeuphoti depthof72.8

m.

Time [months]

Depth [m]

(mg Chl

a

m

−3

₎

0.1

0.2

0.2

0.30.3

0.3

0.3

0.4

0.4

0.4

0.5

0.5

0.6

0.6

0.7

0.7

0.7

0.8

0.8 0.9

0.9

0.9

1

Jan Feb Mar Apr MayJun Jul AugSep Oct NovDec

−150

−100

−50

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Fig.11. Chlorophyll on entration between surfa e and 150 m as

obtainedfromROMS1D.

Zielinski et al. (2002) ompared four water light-eld modelsandfoundarangeforthe1%depthbetween81and

139minwinter,andbetween83and133minspring.The

hoi e of therangefor theintegrationmodies

quantita-tivelytheresults,butthestudiedme hanismsarestillthe

same.

Thelate-winterbloomismadeupofthreestages:

(i) ApeakinnutrientsinearlyFebruary,dueto

onve -tivemixing.

(ii) Highphytoplankton on entrationsinmid-February

around25mMol

N

2

m

−3

.

(iii) AzooplanktonbloombeginningbytheendofMar h.

A ordingtothebiologi almodel,zooplankton

on- entrationis enhan edbygrazingofphytoplankton

and isdiminished bymetabolism, death and

ex re-tion.Itisthenassumedthattheoriginofthetimelag

andthelongerdurationofzooplanktonbloom omes

from the quantityof phytoplankton made available

duringtheshortbloomperiod.

Afterthesethreestages, on entrationsde reaseas

nu-trientsbe omeslessavailablewhilethethermo linestarts

toreform.Theevolutionofdetritus on entrationis

simi-lartothatforthezooplankton,withamaximumbetween

Mar handMayandaquasisteadyde reaseuntiltheend

ofDe ember.Thissimilarityarisesbe ausethemain

pro- essesthatdrivedetritusevolutionaremortalitiesof

phy-toplankton and zooplankton along with the part of

zoo-planktonthatisnotassimilated.

6. Validation

Resultsare omparedwiththefollowingsour es:

 limatologi aleldsextra tedfromtheWorldO ean

At-las2005(Lo arninietal.,2006,WOA05herinafter)and averagedoverthe areaof interest.Using limatologi al

valuesis ompatiblewiththegeneralgoalofsimulating

Jan Fev Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

5

10

15

20

25

30

Months

Concentrations (mMol N

2

m

−2

)

NO

3

NH

4

Phyt

Zoo

SDet

Fig.12. Con entrations integrated fromeuphoti depthto surfa e

asobtainedfromROMS1D.

fortemperature,salinityfrom 0to1500mon24levels,

andforoxygenandnitratesfrom0to500mon14levels;

 in situdata extra tedfrom theWorldO eanDatabase

andfrom ampaigns arriedaroundGranCanaria.

 measurements from ESTOC station, keeping in mind

thatthe onditionsarenotexa tlythesame.

6.1. Temperatureeld

Figures8and13showthesamenear-surfa estru ture:

intense mixing and low temperatures during winter,

for-mationof thermo linein spring,strongstrati ation and

maximaltemperaturesinsummer.

Dieren es betweenthemodelresultsand WOA05

li-matology are attributed to the use of a one-dimensional

model,whi hpreventstheexisten eofverti alvelo ityand

adve tion.TheCanaryIslandsareinuen edby the ool

CanaryCurrent,whi h isnotin ludedin themodel

for -ing, whi h results in themodeled temperaturemaximum

beinghigherthanvaluesfromtheWOA05.

Thenumeri al resultsarealso in agreementwith

mea-surementsatESTOCstation:Neueretal.(2007):  asurfa etemperatureof

18

◦

_C

alongwithadeepmixing

fromJanuarytoMar h,

 astrati ationstartinginJuneandamixedlayerdepth

around40-50m,

 amaximaltemperatureduringSeptemberaround

24

◦

_C

.

6.2. Mixedlayerdepth

There are several ways to ompute the MLD, as

illus-trated onFig.9.A ompletereview isfound in deBoyer Montgutet al.(2004).TheMLD omputedbyROMS1D isbasedonKPPmodel.Inthisformulation(Largeet al.,

1994,Eq.(21)),theMLD isthesmallestdepthvaluethat makes the bulk Ri hardson number equal to its riti al

Months

Depth (m)

12

13

14

15

16

17

18

19

19

20

21

22

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

−500

−400

−300

−200

−100

0

12

14

16

18

20

22

Fig.13.AnnualtemperatureeldfromWOA05MonthlyLongTerm

Meantemperature.

value

Ri

cr

. Hen eusingthisdenition,bothstrati ation andshearingare onsidered.

Themain hara teristi softheMLDannual y le

al u-latedfromthemodel(plain urvewith ir les)are orre tly

reprodu ed:awinterdeepening ausedby onve tive

mix-ingandasummershallowingindu edbystrongheatux.

InNeueret al.(2007),awinterMLD varyingfrom 100 min1997to200min1994isshown.For omparisonswith

ESTOCstation, themodelMLDwas omputedfollowing

thesame riterion (temperature dieren e of

0.5

◦

_C

with

respe ttothevalueat10m).Doingso,themixedlayeris

deepest(around120m)fromFebruarytoMar h(Fig.9).

A more sophisti ated method from Kara et al. (2000) isbasedonadensitydieren e riterionfrom areferen e

depth,hen eitpermitsthe onsiderationofvariable

salin-ity.ThismethodwasappliedonbothROMS1Dresultsand

WOA05 limatology oftemperatureand salinity,yielding

aunique riterionfor omparison.

Resultsare very similar from June to De ember, with

amaximal dieren e being lose to 20 m. In winter and

spring,dieren eslargerthan50m areen ountered.

Pos-sibleexplanationsarethela kofresolutionofthemodelat

thesedepthsandthemathemati aldenitionofMLD.

Nevertheless,thefour urvesrepresentthesamephysi al

pro esses,regardlessofthesele tedMLDformulation.

6.3. Nitrates

InFig.14 limatologi al(WOA05,Gar iaetal.,2006b) andinsitu(Braun,1976)dataare omparedwiththe an-nual y les of nitrates obtainedwith the model. In ea h

plot,ordersofmagnitudeare lose,suggestingthatthe

ou-plede osystemmodelprodu ed oherentresults.

Howevertwomaindieren esappear:1.theshapeofthe

iso-

N O

3

: in thenumeri al results,theyare lose to hori-zontal,whilein the limatology andin situ data,verti al

displa ements o ur. On e again, the absen e of verti al

verti algradientof

N O

3

islargerinthesimulationsthanin the limatology.Thismaybea onsequen eofthestret hed

grid(lowerresolutionasthedepth in reases)orofthe

in-trinsi e ien yofthemodel.

Near surfa e on entrations areverylow(maximumof

0.45mMol

N

2

m

−3

in therst75m), in agreementwith

Neueretal.(2007),whoreportedundete tablysmall mea-surablevalues(<1mMol

N

2

m

−3

)inthemixedlayer.

6.4. Phytoplanktonandzooplankton

Validation of plankton variables is not asdire t as for

nutrientsoroxygen,sin eno limatologiesexist forthese.

Moreover,allthe phytoplanktonandzooplanktonspe ies

are representedbytwoaggregatedstatevariables(

[phyto]

and

[zoo]

)in themodel, whereasseveral groupsare usu-ally onsidered(e.g.pi o-,nano-phytoplankton,

mesozoo-plankton, ...). Forthese reasons,their evolution will be

dis ussedqualitatively.

6.4.1. Phytoplankton

Arístegui et al. (2001) measured the biomass between Mar h1988andJune1989,withthe losestsampling(one

week)duringwinterbloom:maximaofintegrated

on en-trationo urinlatewinterandare omposedoftwopeaks

(see theirFig.3a), onein mid-Februaryandthe otherin

mid-Mar h.Theseobservationsare oherentwith the

nu-meri alresults(Figs.10and15),wheretwodistin tperiod

of high phytoplankton on entrationin therst 20-25m

arepresent.

Jan Fev Mar Apr May Jun Jul Aug Sep Oct Nov Dec

8

9

10

11

12

13

14

15

16

Months

Phytoplankton concentration (mMol N

2

m

−2

)

Fig.15.Integrated phytoplankton on entrationobtainedwiththe

modelinthe40rstm.

6.4.2. Zooplankton

InFig.12thezooplanktonbloomtakespla ewithatime

lagwithrespe ttothephytoplanktonbloom,inagreement

with observationsfrom Hernández-Leónet al.(1984)and

Arísteguiet al.(2001). However,with this ex eption,the

biologi almodelwasnotabletoreprodu ethetypi al

fea-turesofthezooplankton y le.

Hernández-Leónetal.(2004)measuredtheaverageand zooplanktonbiomasses(theirFigs.3and6)andshoweda

learmaximumby theend of February, while ROMS1D

resultsshowamaximumextendingoverseveraldaysinlate

Mar h.TheyalsoreportedamaximuminJuly,mentioned

inBraun(1976),andattributedittointenseTradeWinds duringthese months.Thisfeaturewasnotreprodu edby

themodel.

Asstatedpreviously,dieren esbetweenmodeland

re-alityoriginatefromtheuseofasinglevariabletorepresent

zooplankton. TheCanaryIslandwatersare hara terized

byaprodu tionmainlydrivenbymesozooplankton.

Adve -tionof biologi alproperties, throughupwelling laments

forexample,mayalso ontributetosu hdis repan ies.

6.5. Chlorophylla

Figure11showsresultsthatareinagreementwith

mea-surementsofNeuer et al. (2007),whoshowed on entra-tionshigherthan0.5mg

Chl

a

m

−3

neartheeuphoti depth

andBartonet al.(2000)whoreportedvalueshigherthan 0.6mg

Chl

a

m

−3

intheleeregionofGranCanaria.

A ord-ingtoTett etal.(2002),thisDCMresultsfroma steady-statebalan ebetweenthelimitationofphytoplankton

pro-du tionduetolightandlossesduetoexportedprodu tion

andlo almetabolismofmi roplankton.

Simulatedsurfa e on entrationsagree with the

obser-vationsofNeueretal.(2007):highestvalues(upto0.4mg

Chl

a

m

−3

)whenthemixedlayerisdeepestandlowervalues around0.05mg

Chl

a

m

−3

(1mg

Chl

a

m

−3

insimulations)

insummer.Arísteguietal.(2001)reportedasmall hloro-phyllbloom,withvalueslargerthantheannualmean,but

lowerthanthoseen ounteredintemperateregions.

ComparisonwithinsitudatafromtheFAX ruise( Bar-tonetal.,1998)ismadeinFig.16.Variationsfromoneday toanother annotbe apturedbyone-dimensionalmodel,

astheymay omefromthe omplex ir ulationpatternof

the region. However, the model shows distributions that

agreeinstru tureandmagnitude.

ComparisonswithZielinskietal.(2002)showgood agree-ment.Thesimulatedand observedDCMappearsat

sim-ilardepths. Moreover,ROMS1Dresults ompare

quanti-tativelybettertotheESTOCobservedvaluesthandothe

simulatedresults presented in Zielinski et al. (2002)(see theirFig.10).

6.6. Oxygen

Thesimulatedoxygenannual y le(Fig.17(a))is

om-paredwith limatologi alelds(Gar iaetal.(2006a),Fig. 17(b)).Bothshowsimilarordersofmagnitudeandahigh

near-surfa e on entrationsabove5mMol

O

2

m

−3

at the

endofwinter.Anothersurfa estru turewithoxygen

on- entrationsaround5mMol

O

2

m

−3

Months

Depth (meters)

(mMol N

2

m

−3

)

1

1

2

2

3

4

5

6

7

8

9

10

11

12

12

13

13

14

14

15

15

₁₆

17

16

18

18

18

19

19

20

20

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

−500

−400

−300

−200

−100

0

2

4

6

8

10

12

14

16

18

(a)WOA2005 (b)Insitu

Months

Depth (m)

(mMol N

₂

m

−3

)

1

2

3

4

₅

6

7

8

9

10

11

12

13

14

15

Jan Feb Mar Apr MayJun Jul AugSep Oct NovDec

−450

−400

−350

−300

−250

−200

−150

−100

−50

2

4

6

8

10

12

( )ROMS1D

Fig.14. Annual eldof nitrate on entration: (a)WorldO ean Atlas 2005,(b)measurements 5mileseasto Tenerife(reprodu ed from

Braun(1976)),( )modelresults.

0

0.5

1

1.5

2

−150

−100

−50

0

(mg Chl

a

m

−3

)

Depth (m)

FAX data

Simulation

Fig.16.Modelresults(boldlines)andinsitumeasurements(Barton etal.,1998)forthe hlorophyll on entrationbetween7thand9th ofAugust.

Thedieren es seenbetweenthesimulated andobserved

nitrate valuesmodel arealso visible in theoxygen

distri-butions.

7. Dis ussion

More than 50 years ago, Sverdrup (1953) developed a modelto explain thespring bloomof phytoplankton and

the onditionsunderlyingitsformation.Histheorystates

that the phytoplankton growth season starts in early

spring, when the mixed layer depth be omes shallower

thanthe riti aldepth. Criti aldepthdepth isdenedas

the depth above whi h the depth-integrated daily gross

primaryprodu tionequalsrespiration,i.e.thedepthabove

whi hintegratednetdailyprimaryprodu tionequalszero

(Nybakken,2001).

Theassumptionsunderlyingthistheoryare:

(i) phytoplankton ellsareuniformlydistributed inthe

mixedlayer,

(ii) photosynthesisisassumedtode reaseexponentially

withdepth,asthelightdoes,

Months

Depth (m)

(mMol O

2

m

−3

₎

3.8

4

4.2

4.4

4.6

4.8

5

5

5.2

Jan Feb Mar Apr MayJun Jul AugSep Oct NovDec

−500

−400

−300

−200

−100

0

3.8

4

4.2

4.4

4.6

4.8

5

(a)ROMS1D

Months

Depth (m)

[mMol O

₂

m

−3

]

3.2

3.4

3.6

3.6

3.8

3.8

4

4.2

4.4

4.6

4.8

4.8

5

5

5.2

5.2

5.2

5.2

5.4

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

−500

−400

−300

−200

−100

0

3.5

4

4.5

5

(b)WOA2005

Fig.17.Annualeldofoxygen on entration:(a)Resultsfrom

mixedlayer.

The riti aldepthwas al ulatedusingtheaveragevalue

oflight

I

¯

D

penetratingintotheeuphoti zone. This aver-ageamountoflightisobtainedbyintegratingtherelation

betweendepthandlightintensity

I

λ

(z) = I

λ,0

exp(−k

λ

z)

(3) fromthesurfa e(

z = 0

)tothedepth

D

,whi hleadsto

¯

I

D

=

¯

I

0

kD

(1 − e

−kD

_).

(4)

The previousequation is used to getan expression for

the riti aldepth

D

cr

.Assumingthatphytoplankton ells moveupanddowninthemixedlayer,theyre eiveon

av-erage alight intensity equal to

I

¯

D

. The riti al depth is thenthedepthatwhi h

I

¯

D

equalsto

I

C

,the ompensation lightintensity, dened asthe amountof lightthat makes

produ tionandlossequal.The ompensationdepthisthe

depthatwhi hthatequalityissatised.

CombiningthepreviousdenitionwithEq.(3),the

om-pensationdepthis al ulatedby

D

c

=

ln(I

0

) − ln(I

C

)

k

,

(5)

Finally,thesubstitutionof

I

¯

D

bythe ompensationlight intensity

I

C

in(4)yields

D

cr.

=

¯

I

0

k I

C

[1 − exp(−k D

cr.

)]

(6) The ompensationdepthdependsonthe larityofwater

andthusvariesovertheworldo eans.However,a ording

toNybakken(2001),theeuphoti depthisagoodestimate. Solving Eq. (6)with this approximation, a riti aldepth

equal to 113 m wasfound. As the MLD depends on the

wayitisdened(seeFig.9),interpretationofSverdrup's

riti aldepththeoryisnotstraightforward.

TheMLD omputedfromtheROMS1Dsimulation

re-sults results in a riti al depth that is deeper than the

MLDallyearlong,whi histypi alforsubtropi alregions

(Arísteguietal.,2001).However,ifothermethodsareused to omputetheMLD,thereisaninterse tionbetween

rit-i al and mixed layer depths, taking pla e during April,

whi hdisagreeswiththeobservationofalate-winter

phy-toplanktonbloom.

Hen eitis on ludedthatthemixedlayerdepthisa

on-trolonthetimingofthebiologi al y les,evenifSverdrup's

theory ouldnotbeappliedintheregionofinterest.

8. Con lusions

8.1. Physi s

Physi alpro essessouthofGranCanariawere

su ess-fullysimulatedusingtheROMD1Dmodel.Maximal

sur-fa e temperatures and strongest strati ation were

pro-du ed in late summerearly fall, when the Trade Winds

100mo ursinFebruary,undertheee tofnegativeheat

ux,inagreementwithobservationsandwithexisting

li-matologies.The orre trepresentationofthisphysi al

fea-tureisarststepindevelopmentofamodeltounderstand

thebiogeo hemi alpro esses.

Thedieren esbetweennumeri alresultsand data(in

situor limatologi al)arebelievedtobeduetothe

follow-ing:

 Thenatureofa1-Dmodel:neitheradve tionnorverti al

velo ityexists.

 For ing is arried out with monthly valueslinearly

in-terpolatedatea htimestep,thuspro esseswithshorter

times alearelteredout.

However,evenwiththese dieren esmeanseasonal

y- lesweresimulated.

8.2. Biology

Astrong ouplingbetweenair-seauxesand biologi al

y leswasobserved:

 the phytoplankton bloom o urs in late winter, when

surfa etemperature is minimumbe ause of onve tive

mixingprodu edbynegativeheatux.

 Fromearly springto latefall, biologi al on entrations

tendtode reaseundertheee toftheshallowseasonal

thermo lineformedbyintenseheating.

This y le ontrasts with what is usually observed in

temperateregions,whereaphytoplanktonbloomo ursin

early spring,strongest mixing in winter,due to maximal

windvelo ities duringthisseason,andmaximal

tempera-turesinsummer.

Primary produ tion in the Canary Island region is

nutrient-limited, as there is a su ient amount of light

re eivedbythe water olumn allyearlong,while in

tem-perateregions,primaryprodu tionislightlimited,asthe

mixing is strong enough to feed the euphoti layer with

newnutrientsduringmostoftheyear.

Numerousbiologi almodelshavebeendes ribedin the

literatureandsomewereprimarilydesignedtoworkwithin

a pre-determinate domain of the sea. As a model is

al-waysan idealizationofreality,ithasto bea eptedthat

some pro esses may not be a urately modeled or well

parametrized.Nevertheless,thee osystemmodel oupled

withthephysi almodelyieldedresultsthat orrespondto

observedpatternsformostofthesimulatedvariables.

8.3. Perspe tives

Furtherworkshould on entrateonthe omputationof

the riti aldepthwithamoredetailed model, totest the

appli abilityofSverdup'stheorytotheCanaryIsland

wa-ters. Some of the parameters in the biologi al model

re-quiremodi ationsthatshouldbebasedonmeasurements

and/or experiments arried out in the Canary Island

sim- omponentintoseveral ompartments.

9. A knowledgments

Theauthorsareverygratefultotwoanonymous

review-ersfor their onstru tive ommentswhi h ontributesto

deeplyimprovetheoriginalmanus ript,toP.Penven(IRD)

formakingavailabletheROMS1Dmodelandforhelping

foritsuse, E.Mason(ULPGC)forhis orre tionsonthe

manus ript and S. Hernández-León for his omments on

thezooplankton y le.

NOAA-ESRLPhysi al S ien es Division,theECMWF

and the WHOI are a knowledged for providing the data

setsusedinthefor ing,andtheNODCformakingavailable

theWorldO eanAtlas.

FundingbyFondsde la Re her he S ientique- FNRS

throughaFRIA Grantandby theMECthroughRODA

Proje t(CMT2004-06842-CO3/MAR)are greatly

appre- iated. This resear h was initialized during a stay of C.

TroupinattheULPGCfa ilitatedbyanERASMUSgrant

fromtheEuropeanCommission.

ThisisMAREpubli ation172.

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