The colour of the Mediterranean Sea: global versus regional bio-optical algorithm evaluation

and development of regional chlorophyll dataset in the framework of MERSEA

Gianluca Volpe1, Rosalia Santoleri1, Salvatore Marullo2, Simone Colella1

1 Istituto di Scienze dell’Atmosfera e del Clima – sezione di Roma2 Ente per le Nuove tecnologie l’Energia e l’Ambiente – Centro Ricerche Frascati

r.santoleri@isac.cnr.it; http://gos.ifa.rm.cnr.it;

The aims are:

1. to identify and develop of an optimal algorithm for the Mediterranean sea to produce high quality ocean colour datasets for the region.

2. to provide an accurate and consistent stream of ocean colour data at a resolution and format compatible with operational forecasting of the Mediterranean Marine Environment.

3. To setup the Mediterranean Forecasting System (MFS) core products: satellite and model structure

NRT MODIS and the SeaWiFS reanalysis from 1997 to 2005

A new regional algorithm for Chlorophyll retrieval

Impact of OC regional product in models

In situ chlorophyll-a data: 1144 chlorophyll profiles for satellite data validation

Mediterranean Ocean Color CAL/VAL DATA SETS

28 Mediterranean cruises:from 1997 up to now were organized by ISAC in the framework of Italian National Projects

+ 2 permanent stations

Bio-optical measurements: 155 chl/opt measurements to define the Mediterranean regional algorithm(red points)

Optical measurements: 938 SIMBADA for Rrs validation(blue points)

CAL/VAL cruise in the Eastern Mediterranean

CNR-JRC joint cruise in Sep 2006

)( 44

33

221010 RbRbRbRbbC

MEDOC4 : R is log10 of either the 443/560 or the 490/555 or the 510/555 band reflectance ratios. The switch from one band ratio to another one is based on the chlorophyll concentration itself (the Maximum is Chosen)

THE NEW MEDITERRANEAN ALGORITHM (Volpe et al. RSE, 2006 in press)

a

b

AlgorithmsALL N = 155 OWP < 0.4 N = 105 OWP > 0.4 N= 50

r2 RPD APD r2 RPD APD r2 RPD APD

OC4 0.8 86.7 100 0.77 127, 129 0,62 -10,3 31.5

MedOC4 0.91 0.0 29.2 0.88 7.8 25.9 0.83 -12.3 34.5

In situ

Satellite

MED_OC4

Validation of MBRA SIMBADA-SeaWiFS RRS matchup dataset was build to test the accuracy of the satellite band ratios over the Mediterranean Sea.

SeaBAM N=1174Mediterranean N=156

Optical characteristics: Mediterranean vs Global

1. Low Chlorophyll: Med Band Ration < Global Band Ratio

2. Max Ratio choice similar for Med and Global

3. Is the Med Sea Greener or less Blue then the Global Ocean?

Is the Med Sea Greener or less Blue then the Global Ocean?

-blue (30%); +Green (15%)

-blue (35%); +Green (18%)

-blue (32%); Green similar

Med and Global tend to converge

+ blue (23%); - Green (35%)

MODIS & MERIS Algorithm Validation

MODIS MERIS

chl whole range N=156 r² RPD APD r² RPD APD

Standard Algorithm 0,78 89,3 104,6 0,76 108,1 118

Regional Algorithm 0,78 7,8 30,8 0,72 8,1 33,5

0.01<chl<0,4 N=110        

Standard Algorithm 0,78 133,7 134,8 0,79 153,3 154

Regional Algorithm 0,72 11,6 28,9 0,77 13,5 31

MODIS vs SeaWiFS

regional

global

MERIS vs SeaWiFS

regional

global

N° RMS BIAS R2 RPD APD

SeaWiFS 92 0.47 -0.03 0.82 -0.94 8.4

MODIS 78 0.54 -0.2 0.75 -4.3 9.9

MERIS 81 0.65 -0.42 0.83 -8.5 11.3

MBR validation against in situ measurements:

Examined period: 2003-2004

The SeaWiFS reanalysis from 1997 to 2005: reprocessing of the entire Mediterranean Sea L1A archive using MedOC4

Algorithm

Available at the MERSEA web site

SeaWiFS Re-PROCESSING ON ESA-CNR GRID infrastructure

UI CE

SE

WN:Node01.. ….Node16

WN:Node01.. ….Node16

Gridtest03.esrin.esa.int Grid0007.esrin.esa.int

Se0.artov.rm.cnr.it

1) Globus-job-submit

2) Globus-job-status3) Globus-job-get-output

Globus-url-copy Globus-url-copy

UI=User Interface

SE=Storage element

CE=Computer Element

WN=Worker node

N° SeaWiFS pass= 6127 Total processing time

~ 4 days

Previous algorithm NEW algorithm Difference OLD-NEW

OC4.V4 Med OC4 (OC4.V4) – (Med OC4)0-0.1 0.2

0.01 50.01 5

2 July 2004

The GRID products output

OC4.V4 Med OC4

(OC4.V4) – (Med OC4)

1999 yearly average

Impact on Primary Productivity

The use of MedOC4 chlorophyll in PP Models reduces the annual PP estimate by about 40% and 10% respect to corresponding estimate made using OC4 and BRIC02

Global Model + Chl(OC4)

Global Model + Chl(BRIC02)

Global Model + Chl(MedOC4)

Other MED Optical characteristic

Ctot Csat Ze Ctot

Antoine and Morel, 1996 (yellow)

Morel and Berthon, 1989 (red)

Uitz et al., 2006 (green)

Colella 2006 (blue)

Morel and Berthon, 1989 (red)

Morel and Maritorena, 2001 (green)

Colella 2006 (blue)

Impact on Primary Productivity: global vs regional PP model

(a) Global Model + Chl(OC4)

(b) Global Model + Chl(BRIC02)

(c) Global Model + Chl(MedOC4)

(d) Regional Model + Chl(BRIC02)

(e) Regional Model + Chl(MedOC4)

MAX PP in SPRING

Monthly chlorophyll climatology maps derived from SeaWiFS data, processed by GOS-ISAC-CNR, for the year 1997-2004.

Monthly chlorophyll concentration maps obtained from OGS/OPA transport model after 10y spin-up.

Mediterranean biogeochemical coupled Mediterranean biogeochemical coupled model for future Short term Forecasting:model for future Short term Forecasting:

Model sensitivity to a longitudinal variable extinction coefficient

Crise et al, 2006

•Overall overestimation of surface

•Chlorophyll

•underestimates spring bloom

•in NW

•Relative error is below 0.8

•relative error lower in late-Autumn Winter

• error bias constant throughout the basin (positive anomaly in the W.Med in Spring)

Chl Anomaly Map

[Chl(data)-Chl(model)]/Chl(data))

Basin averaged relative anomaly

Concluding remarks• The analysis demonstrate that OC overestimation

chlorophyll in the Med is due to its peculiar optical characteristics.

• the use of regional algorithm is mandatory to produce high quality OC products for ecosystem model assessment and assimilation

• The MFS requirement for the GlobColour Project is to give access to the L2/L3 products (single sensors collocated Rrs data) from which we can produced specific regional L4 products taking into account the model community needs.

• Regional OC products should be produced in the TAC

The Mediterranean L4 products using L2P Medspiration data

Data mergingISACISAC

Optimal Interpolation

Data delivery on theGOS-ISAC web-site

Data quality controll

Night-time SST using MF algorithm

Cloud detection

SST daily composite binning on model grid

(1/16x1/16)

MF AVHRR acquisition

Atlantic buffer zone + west Med

Night-time SST using Pathfinder algorithm

Cloud detection

SST daily composite binning on model grid

(1/16x1/16)

ISAC AVHRR acquisition

Entire Mediterranean

L2P MedspirationProducts

To save the Mediterranean Sea from environmental problemlook at the combination of

satellites and ocean forecast!!

Conclusions