Monitoring of Phytoplankton Functional Types in surface waters using ocean color imagery C. Moulin 1 , S. Alvain 1,2 , Y. Dandonneau 3 , L. Bopp 1 , H. Loisel 2 • LSCE/IPSL, Gif-sur-Yvette, France • ELICO, Wimereux, France • LOCEAN/IPSL, Paris, France [email protected]
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Monitoring of Phytoplankton Functional Types in surface waters using ocean color imagery C. Moulin 1, S. Alvain 1,2, Y. Dandonneau 3, L. Bopp 1, H. Loisel.
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Monitoring of Phytoplankton Functional Typesin surface waters using ocean color imagery
C. Moulin1, S. Alvain1,2, Y. Dandonneau3, L. Bopp1, H. Loisel2
• LSCE/IPSL, Gif-sur-Yvette, France• ELICO, Wimereux, France • LOCEAN/IPSL, Paris, France
Annual mean Chl Annual mean frequency of diatom blooms
Recent global biogeochemical models account for more than one PFT to quantify the marine « biological pump » of CO2
Validation ?
SE
AW
IFS
?
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
1,8
2
2,2
2,4
2,6
2,8
3
400 420 440 460 480 500 520 540 560
0.04
0.07
0.1
0.2
0.3
4.0
Wavelenghts(nm)Norm
alize
d w
ate
r-le
avin
g r
ad
ian
ce
Chl a (mg.m-3)
nLwref(,Chl a)
Chl a, the main ocean color product
0.040.070.10.2
0.3
4.0
Our goal is to identify the Phytoplankton Functional Type (PFT)associated with Chl a
? ?? ??
Natural variability of nLw
Is it related to PFT (at least partly) ?
NOMAD
SEAWIFS nLw spectra and PFT
We looked for a correlation between anomalies of the SEAWIFS nLw spectrum and the dominant phytoplankton group.
Two steps:
1.Develop a normalization technique to remove the 1st order Chl a effect on the nLw spectrum and to evidence a 2nd order spectral variability.
2.Compare nLw* spectra with coincident in situ pigment inventories from the GeP&CO dataset (Dandonneau et al., 2004) to find relationships between nLw* and phytoplankton groups.
PHYSAT (Alvain et al., DSRI, 2005)
nLw*() = nLw()/nLwref(, Chl a)
The specific normalized water-leaving radiance, nLw*