Annual cycles of chlorophyll-a, non-algal suspended particulate matter

28 Pages·2011·10.27 MB·English

OceanSci.,7,705–732,2011
Ocean Science
www.ocean-sci.net/7/705/2011/
doi:10.5194/os-7-705-2011
©Author(s)2011. CCAttribution3.0License.
Annual cycles of chlorophyll-a, non-algal suspended particulate
matter, and turbidity observed from space and in-situ in
coastal waters
F.Gohin
DYNECO/PELAGOS,CentreIfremerdeBrest,BP70,29280Plouzane,Brittany,France
Received: 30November2010–PublishedinOceanSci.Discuss.: 3May2011
Revised: 3October2011–Accepted: 9October2011–Published: 31October2011
Abstract. Sea surface temperature, chlorophyll, and tur- 1 Introduction
bidity are three variables of the coastal environment com-
monly measured by monitoring networks. The observation Since the launch of SeaWiFS in September 1997, followed
networks are often based on coastal stations, which do not by MODIS/AQUA and MERIS in 2002, daily ocean colour
provideasufficientcoveragetovalidatethemodeloutputsor images have been made available for monitoring the open
to be used in assimilation over the continental shelf. Con- andcoastalwaters. Amongstmanyalgorithmsdevelopedto
versely, the products derived from satellite reflectance gen- provide chlorophyll-a concentration in coastal waters, Ifre-
erally show a decreasing quality shoreward, and an assess- mer’smethodisbasedonlook-uptablesappliedtothestan-
ment of the limitation of these data is required. The annual dardremote-sensingreflectancedeliveredbythespaceagen-
cycle, mean, and percentile 90 of the chlorophyll concen- cies(NASAandESA)andspecificallydefinedfortheWest-
tration derived from MERIS/ESA and MODIS/NASA data ern European continental shelf (Gohin et al., 2002). This
processedwithadedicatedalgorithmhavebeencomparedto method gives results similar to those of OC3-MODIS and
in-situ observations at twenty-six selected stations from the OC4-MERISinopenoceanbutwithlowerandmorerealistic
Mediterranean Sea to the North Sea. Keeping in mind the levelsinturbidwaters. Anothermajorvariableofthecoastal
validation, the forcing, or the assimilation in hydrological, environmentavailablefromsatelliteimageryisthenon-algal
sediment-transport,orecologicalmodels,thenon-algalSus- suspendedparticulatematter(SPM).Thatiswhyasecondal-
pended Particulate Matter (SPM) is also a parameter which gorithmhasbeendevelopedtoproposenon-algalSPMcon-
is expected from the satellite imagery. However, the moni- centrationsinthecoastalwatersoftheEnglishChanneland
toringnetworksmeasureessentiallytheturbidityandacon- theBayofBiscay(Gohinetal.,2005). Oneofthemainad-
sistency between chlorophyll, representative of the phyto- vantagesofthesededicatedproceduresistoprovideconsis-
planktonbiomass,non-algalSPM,andturbidityisrequired. tent estimations of chlorophyll and non-algal SPM concen-
In this study, we derive the satellite turbidity from chloro- trationsfromMODISorMERISspectralreflectance,allow-
phyll and non-algal SPM with a common formula applied ing the building-up of merged MERIS/MODIS products by
to in-situ or satellite observations. The distribution of the optimalinterpolation(Saulquinetal.,2010).
satellite-derived turbidity exhibits the same main statistical The applications of the ocean colour method to coastal
characteristicsasthosemeasuredin-situ, whichsatisfiesthe monitoringconcernthedirectobservationaswellasvalida-
firstconditiontomonitorthelong-termchangesorthelarge- tion and assimilation in hydro-sedimentological or ecologi-
scale spatial variation over the continental shelf and along cal models. The validation and calibration of regional eco-
the shore. For the first time, climatologies of turbidity, so logical models from the southern North Sea to the Bay of
useful for mapping the environment of the benthic habitats, Biscay have been improved in recent years by the use of
areproposedfromspaceonareasasdifferentasthesouthern satellite products (Huret et al., 2007; Lacroix et al., 2007;
NorthSeaorthewesternMediterraneanSea,withvalidation Me´nesguenandGohin,2006;Me´nesguenetal.,2007;Shut-
atcoastalstations. leretal.,2011). Assimilationhasalsobeenperformedwith
success in a biological model of the Gulf of Fos and the
RhoˆneRiverplumeintheMediterraneanwaters(Fontanaet
Correspondenceto: F.Gohin al., 2010). The monitoring of the water quality (short- and
([email protected]) long-term)isanotherapplicationoftheoceancolourmethod
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
706 F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity
whichhasbeenstronglysupportedintheselastyearsbydif- 2 Methods
ferent national and European projects, like MarCoast (ESA
funded)andECOOP(E.U.funded). The“waterquality”ex- 2.1 Thein-situdataset
pressionintheseprojectsreferstotheeutrophicationriskdue
totheenrichmentinnutrientsortothefrequencyandstrength The in-situ data have been obtained from the REPHY phy-
of HAB (Harmful Algal Blooms) events. The first risk is toplanktonnetworkofIfremer,includingassociatedregional
addressed explicitly by the European Water Framework Di- ornationalnetworks,andfromtheSOMLITobservationsys-
rective(WFD)andtheMarineStrategyFrameworkDirective tem managed by INSU (Institut National des Sciences de
(MSFD),andthesecondriskisaddressedbyallthemonitor- l’Univers). Twenty-six stations along the shore have been
ingnetworksandrulesestablishedforthesurveillanceofthe selected for comparison with the satellite-derived products
seafoodquality. duringtheperiod2003–2009. Thesestations,listedinTable
HABsinthecoastalwatersaroundFranceareseldomvisi- 1,havebeenselectedfortheircapacitytorepresentdifferent
blefromspaceduetotheirlowcellconcentration,deeploca- regionalwaterconditionsencounteredintheFrenchcoastal
tion(dynophysis),oroccurrenceinnarrowestuaries(Alexan- waters. They can be considered as an extension of a previ-
drium). Thesatelliteimageryisalsopoorlyefficientforthe ous data set of seven stations selected to validate SeaWiFS
direct observation of toxic Pseudo-nitzschia, which is a di- dataforthesurveillancerequiredbytheWFD(Gohinetal.,
atom able to bloom in high concentration with very vari- 2008). These stations were also chosen because they have
able toxicity (producing domoic acid, an amnesic neuro- been frequently sampled in recent years through national
toxin). Karenia mikimotoi seems to be an exception, as it or regional networks such as the SRN (Suivi Re´gional des
maygrowinveryhighconcentrationsofcellsinthewestern Nutriments) and RHLN (Re´seau Hydrologique du Littoral
stratifiedpartoftheEnglishChannel,givingmassiveblooms Normand), which are funded by the water agencies Artois-
visible from space (Van Houtte et al., 2006, Miller et al., Picardie and Seine-Normandie and included in the Ifremer
2006). These restrictions to the observation of HABs from REPHY network. The locations of the selected stations are
space are balanced by an enhanced interest for the applica- shown on Fig. 1. Two cross-shore transects off Dunkerque
tionslinked tothe long termsurveillanceof theeutrophica- andBoulogne,belongingtotheSRNnetwork,arealsocon-
tionriskrequestedbytheWFDortheMSFD(Gohinetal., sideredastheyrevealthechlorophyll-a andturbiditycross-
2008). These applications require a joint use of the in-situ shoregradientsintheproductivewatersoftheeasternChan-
and satellite capacities of observations. The coastal in-situ nelandthesouthernNorthSea. Thesetransectsalsoprovide
networks in France are now well established and are more very useful information for investigating the degradation of
and more efficient (SOMLIT/CNRS and REPHY/Ifremer). the quality of the satellite-derived products near the shore
They also benefit from the development of the coastal op- wherepixelsareoftenflagged(failureintheatmosphericcor-
erational oceanography in the frame of projects like Pre- rection,highradiance,etc.).
vimer (French national project). The harmonious develop- Allthesestationsallowadirectcomparisonofsatelliteand
mentofobservingsystemsfromsatelliteandin-situorigins, in-situ observations, except at Cabourg where the REPHY
together with modelling, is also one of the major goals of station is too close to the coast to be observed correctly by
ECOOP.Threeparametersusefulforthecoastalsurveillance satellite. Asthislocation,inthevicinityoftheplumeofthe
arecurrentlyobservedfromspace:theseasurfacetempera- riverSeine,issubjecttoeutrophicationandhighchlorophyll
ture(SST),thechlorophyll-a,andthesuspendedparticulate levels, it seemed useful to try to incorporate it into our se-
matterconcentration. TheSSTandthechlorophyllconcen- lected stations despite the proximity of the coast. To that
trationarealsomonitoredin-situandarebasicmeasurements purpose, we consider a shift of three pixels (about 3.5km)
oftheFrenchcoastalnetworks. However,thewaterclarityis furthernorthoffshoretoobtainasufficientnumberofsatel-
muchmoreoften,andinaneasierway,obtainedfrommea- lite samples for the comparisons (match-ups) and the mon-
surements of turbidity than from the concentration of sus- itoring. We have tested, through several short cruises ded-
pendedparticulatematter. Thatiswhywe’llalsopresentin icated to the study of the local pattern of chlorophyll, that
this study the validation of the satellite-derived turbidity in therewasnosignificantgradientattheCabourglocationand
complement to chlorophyll (Chl) and SPM concentrations. thatthisshiftmaybeappliedtothesatellitedatawithoutcre-
To ensure consistency between the products, turbidity will atinganybias. Thispeculiarfeatureinchlorophyll-acanbe
beexpressedfromacombinationofChlandnon-algalSPM. explainedbythecomplexsituationatthatlocationwithwa-
Considering that the light attenuation coefficient K can terssubmittedtotheinfluenceoftheplumeoftheriverSeine,
PAR
also be derived from Chl and non-algal SPM (Gohin et al., addingasignificanteast-westcomponenttotheusualcross-
2005), this will contribute to build up a consistent set of shore(heresouth-north)prevailinggradientofnutrientsand
satellite-derivedclimatologiesonourarea. turbidity.
The concentration in chlorophyll-a was obtained by fluo-
rometry or spectrophotometry. For spectrophotometric pig-
mentanalysis(Lorenzen,1967;AminotandKerouel,2004),
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F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity 707
Fig.1.The26stationsselectedforcalibration:
The stations have the following codes, from north to south, in the networks: “Point 1 SRN Dunkerque”, “Point 3 SRN Dunkerque”,
“Point 4 SRN Dunkerque”, “Point 1 SRN Boulogne”, “Point 2 SRN Boulogne”, “Point 3 SRN Boulogne”, “Cabourg Shifted”,
“Luc 1 mille”, “Ouistreham 1 mille”, “St Aubin les Essarts”, “Donville”, “Chausey”, “Saint Quay”, “ROSCOFF ASTAN”,
“Men er Roue”, “Ouest Loscolo”, “Pointe St Gildas large”, “Filiere w”, “La Carrelere”, “Le Cornard”, “Boyard”, “BANYULS SOLA”,
“Sete mer”,“MARSEILLE FRIOUL”,“22B Toulon gde rade”,“Sud Bastia”.
samplesoftwolitresofsurfacewatersareprefilteredthrough 2100N,HACH2100NIS,HACH2100A).Theseturbidime-
200µmmeshnylongauzeandthenfilteredonto47µmGF/C ters comply with ISO 7027 (FNU) or U.S.E.P.A. method
fibre filters under low-pressure vacuum. The filters were 180.1(NTU).
ground into acetone-water solution (90/10, v/v) for pig- WhenthedataareinNTU(NephelometricTurbidityUnit,
mentextractionandanalysedbyspectrophotometricmethod. U.S.E.P.A180.1),theyhavebeenobtainedfromthemeasure-
The seawater volume filtered for the fluorimetric method ment of a broad spectrum incident light in the wavelength
(Neveux, 1976; Aminot and Kerouel, 2004) is lower than range400–680nm,asoneofatungstenlamp,scatteredatan
thatusedforthespectrophotometricmethod. angle of 90+/–30◦. NTU is the unit of most of the REPHY
The concentration in SPM was only measured at the datacollectedbetween2003and2007,whereasthemostre-
SRN (Dunkerque and Boulogne transects) and SOM- centobservationsareexpressedinFNU(FormazinNephelo-
LIT stations (ROSCOFF ASTAN, Marseille FRIOUL, and metricUnit,ISO7027). Inthatcase,theyareobtainedwith
BANYULS SOLA).SPMisobtainedthroughfiltrationonto anincidentlightintherange860±60nm(LED)scatteredat
47µm Whatman GF/F filters following the procedure de- 90±2.5◦.
scribedinAminotandChaussepied(1983). Attheothersta- Thesereportingunitsareequivalentwhenmeasuringacal-
tions(REPHY),theturbidityhasbeenmeasuredasanindi- ibrationsolution(forexample,Formazinorpolymerbeads),
catorofthewaterclarity. buttheycandifferforenvironmentalsamples.Therearefour
The turbidity has been measured in-situ using multipa- optical components in coastal waters: pure sea water, col-
rameterportablefieldinstrumentsorsondes(HydrolabDS5, ored dissolved organic matter (or yellow substances), phy-
YSI 600 QS, YSI 6600, NKE MPx), or from water sam- toplankton pigments, and particles in suspension. The yel-
ples in laboratory using a laboratory turbidimeter (HACH low substances are characterized by their absorption at low
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708 F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity
Table1. The26selectedstationsandtheirmeancharacteristics. PositionsofthestationsareindicatedinFig.1. Waterissampledbetween
thesurfaceandonemetredepth.FrequencyistwiceamonthfortheREPHYandRHLNduringtheproductiveseason(MarchtoSeptember).
Station Observedvariables
andmethodsfor Network Mainlocalcharacteristics
fromnorth chl-aand
southwards turbidity
Dunkerque Spectrophotometry SRN/REPHY These stations are the only ones where the three
Point1 NTU Onceamonth parameters (chl-a, SPM, turbidity) are observed
Point3 SPM simultaneously.Theyarelocatedalongtwocross-
Point4 shoretransects.
Boulogne An instrumented buoy, MAREL, is in operation
Point1 in the harbour of Boulogne and comparisons be-
2 tween Marel fluorescence and satellite chl-a are
3 madedaily(notshowninthisarticle)
Cabourg Spectrophotometry RHLN/REPHY Cabourgisahighspotinthevicinityoftheriver
NTU,thenFNU Seine. Atthisstation,ashift(3.3kmnorthwards)
since2008 isappliedformatching-upwiththesatellitedata.
Ouistreham, idemCabourg RHLN/REPHY HigherdensityofsurveillancebyRHLNpartially
Luc 1 mille,and funded by the water Agency “Agence de l’Eau
Saint-Aubin-les- Seine-Normandie”
Essarts
Donville idemCabourg RHLN/REPHY
Chausey idemCabourg RHLN/REPHY The station is located in the vicinity of the
ChauseyIslandsandcouldbeaffectedbyland
Saint-Quay Spectrophotometry REPHY Anewpoint,dataavailablesince2007,could,as
NTU,thenFNU Chausey,beaffectedbylandcontaminationwhen
since2008 remote-sensing
Roscoff Astan Fluorometry SOMLIT Clearandturbulentwaters
SPM Long time series available at the biological sta-
tionbutthein-situseasonalcycleofSPMdoesnot
seemtoberealistic
MenerRoue Fluorometry REPHY Shellfishfarming
NTU,thenFNU
since2008
Ouest-Loscolo Fluorometry REPHY Shellfish farming in the vicinity of the river Vi-
NTU,thenFNU laine,thesecondhighspotofchl-awithCabourg
since2008
Pointe-Saint-Gildas Fluorometry REPHY InthevicinityoftheplumeoftheLoireRiver
NTU,thenFNU
since2008
Filieres West, Fluorometry REPHY Shellfish farming in the Marennes-Oleron Basin,
La Carrelere, NTU,thenFNU inthevicinityoftheriverCharentes
Le CornardBoyard sinceJuly2007 Turbidandshallowwatersataplaceofintensive
shellfishfarming
Banyuls Sola, Spectrophotometry SOMLIT Mediterraneanrelativelyclearwaters
Marseille-Frioul SPM
Sete Mer Fluorometry REPHY “”
22b Toulon-gde- NTU,FNU
rade,Bastia since2008
wavelengths. A high level of yellow substances will re- measurementsinNTUwillnotbevisibleinthedatainFNU
sult in more absorption in the 400–680nm radiation and, madeatalongerwavelength. Therefore,inpresenceofyel-
therefore, in less light exiting the turbidimeter and a lower lowsubstances,themeasurementsinFNUareexpectedtobe
value in NTU. This effect of the yellow substances on the morerelatedtoSPMthanthoseinNTU.
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F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity 709
2.2 Thesatelliteimagesandtheirprocessing backscatteringcoefficientsofpureseawater,phytoplankton,
andnon-algalParticles(NaP).
2.2.1 Thesatellitedata Firstly,wemaketheclassicalapproximationinEq.(1)that
theabsorptionaandthebackscatteringcoefficientsb canbe
b
Dailystandardremote-sensingreflectancesofMODIS/Aqua
expressedfromtheconcentrationofphytoplankton,through
since January 2003, and MERIS/ENVISAT since January
Chl,andNaP(withcoefficientsfromtheliterature):
2007, have been used in this study. The MODIS Level-2
reflectance products (reprocessed in 2010, SeaDAS V6.2) a=a +a +a =a +a∗×Chl+a∗ ×NaPand
w φ NaP w φ NaP
have been downloaded from the OceanColor/GSFC (God-
dardSpaceFlightCentre)WEBserverinMay2010.MERIS b =b +b +b =b +b∗ ×Chl+b∗ ×NaP (1)
b bw bφ bNaP bw bφ NaP
datahavebeenobtainedfromtherollingarchiveoftheEN-
VISATacquisitionstationofKiruna(PDHS-K)inNearReal Secondly, in Eq. (2) we define a linear relation between
Time. R*(550), a variable linked to the reflectance, and the satel-
literemote-sensingreflectanceRrswithcoefficientsαandβ
2.2.2 Processingthesatellitereflectanceforchlorophyll obtainedbyminimizationfromin-situobservationsofchl-a
andNaP.
TheestimationofChlisobtainedbyapplicationoftwolook-
up tables (LUT) to the spectral remote-sensing reflectance R∗(550)=b /(a+b )=α+β Rrs(550) (2)
b b
(Rrs)ofMODISandMERIS.Themethod, describedinde-
tail in Gohin et al. (2002), is empirical and derived from InEq.(2),R*(550)isobtainedfromChlandNaPthrougha
the OC4/SeaWiFS algorithm of NASA (or OC3M-547 for andbb(Eq.1)
MODIS and OC4E for MERIS). This method gives results Thirdly, considering that the chlorophyll is known after
similar to OC4 in open waters but provides more realistic applicationoftheLUTtothesatellitereflectance,weinverse
values over the continental shelf. In coastal waters, min- R*(550)togetthelastunknown,whichistheconcentration
eral SPM, absorption by CDOM (Coloured Dissolved Or- ofNaP.
ganic Matter), and errors in the atmospheric correction are Initially defined at 550nm (Gohin et al., 2005) and vali-
the causes of frequent overestimations in the chlorophyll datedoncruisesonthecontinentalshelf,theoperationalap-
concentration by the standard procedures. Whereas OC4 plicationofthemethodoftenshowedlowvaluesinverytur-
makes use of the SeaWiFS and MERIS four channels rang- bid waters, leading sometimes to unrealistic features in the
ing from 442 (Blue) to 559nm (Green) and determines Chl estuaries and the river plumes. That could be explained by
fromthemaximumofthebandratiosRrs(Blue)/Rrs(Green) increasederrorsintheatmosphericcorrectionforveryturbid
calculated from the three Blue Channels ranging from 442 waters and by the saturation effect due to the fact that the
to510nmavailableforSeaWiFSandMERIS,ouralgorithm quantitative retrieval of SPM is no longer reliable beyond a
considers also the reflectances at 412nm and in the Green certain concentration for a specified wavelength (Bowers et
(547nmforMODISand559nmforMERIS).TheChlcon- al.,1998). Nechadetal.(2010)suggestchoosingaretrieval
centrationisthereforedeterminedfromthetriplet{Rrs(412), wavelengthwithsufficientlyhighpurewaterabsorption,us-
Rrs(Green), Maximum band ratio Rrs(Blue)/Rrs(Green)}. ing longer red or near infrared wavelengths for water with
Rrs(412) accounts for the absorption by CDOM and the er- higher SPM. That is why a second channel at 670nm has
rorinatmosphericcorrection, particularlysignificantatthis been added to take into account the most turbid areas. Fi-
low wavelength, and Rrs(Green) accounts for the effect of nally,SPM(hereafterusedforNaP)isdefinedfromaswitch
thebackscatteringby thesuspendedsediment not relatedto ofSPM(550)toSPM(670),dependingontheSPMlevels. If
the phytoplankton. The algorithm is a 5-channel algorithm SPM(550) and SPM(670) are both inferior to 4gm−3, then
for MERIS (and SeaWiFS, not processed in this study) and SPM(550) is conserved; otherwise, SPM (670) is chosen.
a 4-channel one for MODIS. The method has been applied SPMisthereforeobtainedfromthechannelat550nminrel-
withsuccesstotheSeaWiFSdataintheFrenchcoastalwa- ativelyclearwatersandfromthechannelat670nminturbid
tersandalsointheNorthSeaandotherturbidcoastalwaters waters. This method takes advantage of the relatively good
(Huretetal.,2005,Tilstoneetal.,2011)foryears. sensitivityofthechannelat550nmtothevariationofSPM
in clear waters and of the better quality of the atmospheric
2.2.3 Processingthesatellitereflectancefornon-algal correction at 670nm, as the atmospheric correction is ob-
SPM tainedbyextrapolationfromthechannelsinthenearinfrared
atabout760and860nm.
The procedure is described in Gohin et al. (2005). In
this method we consider that the absorption by yellow sub- 2.2.4 Processingthesatellitereflectanceforturbidity
stancescanbeneglectedatwavelengthslongerthan550nm
and propose a simple equation to express the reflectance AsmentionedbyNechadetal.(2009),studiesontheremote-
(or the water-leaving radiance) from the absorption and sensingofturbidityincoastalwatersarelessnumerousthan
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710 F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity
Thiscannotbeinterpretedasanindicationofalowerquality
oftheMODISproductscomparedtoSeaWiFSasthecoastal
datasetconsideredinthisstudyismuchmoreheterogeneous
thanthatusedinthe2002publication. Inthe2002publica-
tion,thedatasetwasobtainedfromcruisesonthecontinen-
tal shelf. There is also a clear alteration of the quality of
the retrievals approaching the coast due to scattering of the
photonsbylandandfailuresintheatmosphericcorrections,
whichmayaffectourcoastaldataset(Gohinetal.,2008).
Toassessthecapabilityofthesatellitemethodtoprovide
monthly climatologies of environmental variables so useful
for operational oceanography, comparisons of the seasonal
cycles of Chl have been carried out locally at the selected
stations.
Fig.2. MODIS-derivedchlorophyllversusin-situobservationsat
theselectedstati. Figure3showstheannualcyclesofChlforsomeselected
stations near the shores of the southern North Sea to north-
ern Brittany. These graphs can be separated into 3 classes
thoseonSPM.However,turbidityisanopticalproperty(vol-
corresponding to typical developments of the phytoplank-
umescatteringfunctionat90◦),whichistightlyrelatedtothe
ton during the year. The curves at Dunkerque Points 3 and
backscattering coefficient b . Nechad et al. (2009) propose
b 4 show a characteristic spring peak of chlorophyll in mid-
an estimation of turbidity using a method based on a con-
April. The Dunkerque’s curves are unique in our data set
cept equivalent to Eq. (2). Doing so, they derive turbidity
andpermitidentificationofthislocationasthenutrient-rich
from MERIS (channels at 665 and 680nm) with success in
(high level) North Sea offshore station. The stations of the
theveryturbidwatersofthesouthernNorthSea.
Boulogne transect have a similar behaviour but the spring
However, to care for consistency between our different
peaks are lower and later in the season. We can also notice
products,thoseobservedin-situorbysatelliteandthosede-
thatthespringpeakismoremarkedatBoulognePoint3(off-
finedintheecologicalmodels,wehavechosentoderivetur-
shore)thanatBoulognePoint2.Thespringpeakisrelatively
bidityfromChlandnon-algalSPM.Chlandnon-algalSPM
moreintenseforstationsoffshorewherethemainsourceof
aretwovariablesusedforvalidationorforcingoftheecolog-
nutrientscomesfromthewinter“reservoir”withoutsignifi-
icalmodel(Huretetal.,2007),whereasturbidityisaparam-
cantsupplyfromriversinspringandsummer. Thestationof
etercommonlymeasured.
Cabourgdoesn’tshowsuchastrongspringpeakbutthelev-
Therefore, we express turbidity as a combination of non-
elsreachedarealsoveryhigh(thehighestofourselectedsta-
algalSPMandChl:
tions). TheshapeofthephytoplanktoncurveatCabourgcan
Turbidity=α(SPM+0.234Chl0.57) (3) be described as a bell curve, characterising a station where
a regular supply in nutrient is provided by a river, here the
where the term 0.234Chl0.57 represents the phytoplankton riverSeine. ChauseyandROSCOFF ASTAN,locatedinthe
biomass linked to the chl-a concentration (Gohin et al., Channel,showlowerlevelsofchl-a andamoreregularpro-
2005). ductivity in waters strongly mixed by the turbulence due to
thetidalcurrentandwaves.
Figures 4 and 5 show the annual cycle of chlorophyll at
3 Resultsanddiscussion
our selected stations along the Atlantic and Mediterranean
coasts. The statistics during the productive season (from
3.1 ResultsfortheMODISandin-situdatasets
March to October) are also indicated in the figures. We
3.1.1 Theannualcycleofchlorophyll-aobservedfrom observe a slight overestimation of Chl from MODIS data
spaceandin-situ in winter (2µgL−1 in stead of 1µgL−1) at the stations lo-
cated in Southern Brittany (Men Er Roue, Ouest-Loscollo
Tohaveaquickoverviewoftheoverallrelationshipbetween andPointe-Saint-Gildas-large)butduringtheproductivesea-
satellite-derived and in-situ data, a scatterplot of the satel- son,thesatelliteandin-situcurvesareverysimilar.
lite versus observed Chl at the selected stations is shown Figure6presentsthesatelliteversusin-situmeanandper-
in Fig. 2. The match-up is considered for satellite and in- centile90attheselectedstations. Theseparametersarealso
situobservationsobservedatthesamepixellocationandthe essential variables mentioned in the long-term surveillance
same day. The coefficient of determination r2 obtained on ofthewaterquality.
thelog-transformedChldataisequalto0.67. Thisr2coeffi-
cientappearsalittlebitlowerthanthevalueof0.7obtained
in the processing of SeaWiFS data in Gohin et al. (2002).
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F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity 711
(a) (b)
(c) (d)
(e) (f)
(g) (h)
Fig.3.TheannualcyclesofchlorophyllatsomeselectedstationsfromtheNorthSeatoNorthernBrittany.Statisticsindicatedonthegraphs
(mean, p90, Nb samples available) concern the productive season (March to October). For the SRN transects off Dunkerque, Point 1 is
coastalandPoint4thefurthestoffshore.SameforBoulognewithPoint3thefarthestoffshore.
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712 F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity
(a) (b)
(c) (d)
(e) (f)
(g)
Fig.4.TheannualcyclesofChlattheselectedstationsoftheAtlanticcoast.
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F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity 713
(a) (b)
(c) (d)
(e)
Fig.5.TheannualcyclesofChlattheselectedstationsoftheMediterraneancoast.
3.1.2 Theannualcycleofnon-algalSPMobservedfrom phytoplanktonincasesofbloomsofcoccolithophorideswith
spaceandin-situ their characteristic calcite skeleton, our SPM satellite prod-
uctisdominatedbymineralparticles.
TheSPMvalidationwillbecarriedoutonlyonthe8SOM- The annual cycles derived from the satellite data fit well
LITandSRNstationswhereSPMhasbeenmeasured. thoseobservedin-situ,exceptatROSCOFF ASTAN(Fig.7)
Oursatellite-derivednon-algalSPMisdefinedasthedif- where the in-situ concentration of SPM stays high in sum-
ference between total SPM and the phytoplankton biomass mer. The annual average and P90 of satellite SPM appear
derivedfromchl-a. Therefore, whatwedefineasnon-algal alsologicallylowerin-situforthisstationinFig.8. Despite
SPMincorporatesmainlymineralSPMbutalsoorganicSPM the curious discrepancy at this station, with high SPM lev-
not related to the living phytoplankton (whose biomass is els measured in-situ in summertime when lower concentra-
considered proportional to Chl), as organo-mineral aggre- tions are expected following the decrease in the resuspen-
gates (flocs) or organic matter from the river plumes. Al- sion induced by the waves in the English Channel (Vele-
though it may also include particles directly related to the grakis et al., 1999), the overall adjustment is excellent and
www.ocean-sci.net/7/705/2011/ OceanSci.,7,705–732,2011
714 F.Gohin: AnnualCyclesofChlorophyll-aandTurbidity
(a) (b)
Fig. 6. Average (a) and P90 (b) of the MODIS and in-situ Chl for the productive season. The stations are represented by two or
three characters corresponding to the codes defined in Fig. 1. The lowest Chl means and P90s are obtained for Bas (“Sud Bastia”),
Tln(“22B Toulon gde rade”), Mar(“MARSEILLE FRIOUL”)locatedintheMediterraneanSea. ThehighestlevelsareobservedatOue
(“Ouest Loscolo”)andCaS(“Cabourg Shifted”)inthevicinityoftheVilaine(SouthernBrittany)andSeinerivers.
thecorrelationcoefficientishigh. However,wehaveonly8 Relation(3)and(5)cannowbecombinedandappliedto
stationsandthisenhancestheinterestforturbiditytoassess satelliteSPM(withitstwocomponents,algalandnon-algal)
the capacity of the ocean colour sensors to monitor water toderivesatelliteturbidity:
clarity.
Turbidity=0.54(SPM+0.234Chl0.57) (6)
3.1.3 Relation between turbidity, non-algal SPM, and
Chl-a
3.1.4 Theannualcycleofturbidityobservedfrom
spaceandin-situ
Relationbetweenin-situturbiditymeasurementsmade
inNTUandFNU
Theannualcyclesofsatellite-derivedandin-situturbidityare
very similar (Figs. 11 to 13). The stations where the differ-
Mostofourobservationsinturbidityhavebeenmeasuredin
ences are the highest are located in the Mediterranean Sea
NTU.Itisonlyrecently(since2008)thatthemeasurements
(likeToulonandSudBastia,seeFig.13). Intheseveryclear
aremadeinFNU.Forthatreasonwehavetoconvertdatain
waters,themeanturbidityisalsoverylow(Fig.14)andthe
FNUtoNTUtoobtainaconsistentdataset. Therelation:
decreasing gradient from inshore to offshore waters in tur-
TurbidityinFNU=1.267TurbidityinNTU (4) bidity may be the cause of the large underestimation by the
satellitedatawhichmaycovermoreoffshorewaters. Wecan
has been obtained from a regression based on 69 pairs of alsonoticethatwhenthenumberofsatellitesamplesishigh,
turbiditymeasurementsatdifferentREPHYstations(Fig.9). likeatMenerRoue(Fig.12)whereitreaches525,thesatel-
liteandin-situcurvesareveryclosetooneanother. Ahigh
numberofsamplesfromspacemeansthatthefailuresinthe
Relationbetweenin-situturbidityandSPM
atmosphericcorrectiondon’toccursignificantlyandthatthe
locationofthestationissufficientlyfarfromthecoast. Itis
The term α in Eq. (3) is obtained by regression of turbidity
a criterion of quality. At all those points where the number
on total SPM (TSPM) at the stations where both measure-
ofsatellitesamplesissuperiorto200,thedifferencebetween
ments are available (Fig. 10). These stations belong to the
thesatelliteandin-situcurvesisverylow.
SRN network (Boulogne and Dunkerque transects) and are
Figure 15 presents an example of the maps pro-
all located in the north of the studied area. The continuous
duced to define the initial state of the French coastal
lineinFig.10correspondstothelinearrelation:
environment for the MFSD. All the in-situ stations
Turbidity=0.54TSPM (5) available around Normandy are shown in the figure.
The selected stations, considered as representative, are
withturbidityinNTUandTSPMingm−3. from west, eastwards: “Cabourg Shifted”, “Luc 1 mille”,
OceanSci.,7,705–732,2011 www.ocean-sci.net/7/705/2011/