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Definition and assessment of a regional Mediterranean Sea ocean colour algorithm for surface chlorophyll
Gianluca Volpe
National Oceanography Centre, Southampton School of Ocean and Earth Science
MPhil/PhD Transfer
• Motivations & Aims
• Ocean Colour Principle
• Development of a NEW MED algorithm
• Regional vs Global datasets
• SeaWiFS data Validation
• Conclusions & Future work
Outline
Marine primary production plays an important role
regulating atmospheric CO2
Biological pumpIn principle …..We can calculate global ocean Primary Production
Earth observation data from satellites(Behrenfeld et al., 2001)
Motivation
Gregg et al. (2003)
blending CZCS & SeaWiFSdata with in situ data
primary production declined by 6% since 1980s
Antoine et al. (2005)
algorithm refinements
chlorophyll concentration increased by 22% since 1980s
Motivation
DISCREPANCIES
Different methodologies
Related assumptions
Highlight NEED
ASSESS and QUANTIFY
large UNCERTAINTIES
satellite retrieved chlorophyll
Motivation
Evaluate SENSITIVITY
Primary Productivity Calculation
with respect to:
• Quality of the input data• Primary production models• Integration length and time scales
Aim of the PhD
The main goal
ASSESS the ACCURACY
Remote-Sensed Chlorophyll
….This is of crucial importance in
determining the MAGNITUDE at which
the OCEANS ABSORB CO2
Aim of this work
Atmospheric Correction
Aerosol space-time variability
Optical properties of seawater
Phytoplankton species composition
Vertical distribution
CDOM
Factors influencing the chlorophyll retrieval
Chlorophyll a&
Fluorescence
In situ OpticalMeasurements
Satellitedata
Fls calibration&
Data quality
Compute OWP(chl seen
from surface)
Algorithms’Evaluation
AssessAtmospheric
Correction errorbudget
Run best Chlalgorithm
over satellite data
Run differentPP models
Are theysignificantlydifferent?
Assess PPchanges and
their significance
yes
no
In situ PP data Select bestalgorithmPRIMARY
PRODUCTION
CHLOROPHYLL
DATA
Done
Still to be done
PhD Conceptual Scheme
Sensitivity analysis on input parameters
Compute ERROR budget
Laboratory basin(Lacombe et al., 1981; Robinson & Golnaraghi, 1995)
Processes controlling the global ocean general
circulation in reduced temporal and spatial scales.
…
Large amount of data
Why in the Mediterranean Sea
•Spectral shape R() defines the so called “Ocean Colour”
•OC is indexed by the Blue-to-Green reflectance ratio In case 1 waters is essentially due to phytoplankton chlorophyll content
•B/G decreases with increasing pigment concentration
Rationale for a Bio-optical Algorithm
d
u
E
LR
Ocean colour algorithms relate surface chlorophyll concentration to B/G
(O'Reilly et al., 1998; O'Reilly et al., 2000; Morel and Maritorena, 2001)
GLOBAL
OCRS of the Mediterranean Sea: Three existing Algorithms
REGIONAL algorithms improve the accuracy of
satellite chlorophyll estimates
(Garcia et al., 2005; Gitelson et al., 1996)
REGIONAL
DORMA (D’Ortenzio et al., 2002 )
R is log10 (490/555) reflectance ratios.
4)( 3
32
21010 cChl RcRcRcc
BRIC (Bricaud et al. 2002)
R is 443/555 Reflectance ratios for Chl < 0.4
OC4v4 is used in the other cases
10
cRcChl
OC4v4 (O’Reilly et al. 2000)
R is log10 of the maximum value between:
443/555 490/555 510/555
)( 44
33
221010 RcRcRcRccChl
Mediterranean Ocean Colour CAL-VAL dataset
Bio-optical measurements137 chl/opt measurements used to define the Mediterranean regional algorithm
10 Mediterranean cruises (1998-2003 ):Organized by GOS in the framework of Italian National Projects
In situ chlorophyll-a data 944 chl profiles used to validate satellite chlorophyll products
Fluorescence Calibration
• Calibration performed cruise by cruise
r2 = 0.98
Clearly Log-normal More Gaussian shape
• Log-transformation
Calibrated Fluorescence OWP
“an accurate representation of the pigment concentration measured by a remote sensor
viewing a stratified ocean”(Clark, 1997)
Optical Weighted Pigment Concentration (OWP)
pd
pd
z
Surf
kz
z
Surf
kz
dze
dzezChlOWP
2
2)(
• Chl = in situ chlorophyll concentration
• Zpd = 1/k
• k = attenuation coefficient of downwelling PAR irradiance
%1001
1
NOWP
OWPAlgRPD
N
i i
ii
%1001
1
NOWP
OWPAlgAPD
N
i i
ii
Statistical Parameters for Algorithms’ Evaluation
r2 = coefficient of determination
Alg = [Chl] estimated from different algorithms
covariance between in situ observations and algorithm derived chlorophyll
Error as function of the chlorophyll values
Algorithms’ Evaluation Analysis
Algorithms’ Evaluation
Algorithms’ Evaluation
Need for a NEW Mediterranean Sea OC Algorithm
The New Mediterranean Algorithm: the MedOC4
MedOC4
R is log10 of the maximum value between:
443/555 490/555 510/555
)( 44
33
221010 RaRaRaRaaChl
The good, the ugly, the bad and the MedOC4
Max Ratio choice similar for MED and Global
Regional VS Global Datasets
Mediterranean
Low Chlorophyll: Med Band Ratio < Global Band Ratio
Is the Mediterranean Greener or less Blue than the Global Ocean?
Global
Global
MED
MED
G
B
G
B
Chlorophyll
Max
imu
m B
and
Rat
io
Chlorophyll
Max
imu
m B
and
Rat
io
Global Ocean
Is the Mediterranean Greener and/or less Bluethan the Global Ocean?
Global 30% BLUER than MED
Global Regional
Global Regional
0.01 < Chl < 0.1
MED 15% GREENER than Global
0.1 < CHL < 0.3
Global 12% BLUER than MED
Global Regional
Global Regional
MED 10% GREENER than Global
Is the Mediterranean Greener and/or less Bluethan the Global Ocean?
CHL > 0.3
Global and MED tend to overlap
Global Regional
Global Regional
Is the Mediterranean Greener and/or less Bluethan the Global Ocean?
•DORMA, BRIC and the New MedOC4 into the SeaDAS Code
•A Match-up dataset between concurrent SeaWiFS passes and in situ measurements was built
SeaWiFS data validation
Matchup criteria
Clouds
944 profiles
290 data points
SeaWiFS data validation
•does not show significant changes from the one calculated using in situ data
•MedOC4 is the most stable algorithm performing better than the other in all the chlorophyll ranges
MedOC4 vs OC4v4: Oligotrophy
OC4v4 MedOC4 OC4v4 – MedOC4
0-0.1 0.20.01 50.01 5
2 July 2004
Same dynamical patterns
Significant difference between the two algorithms
Positive difference for lower values
Negative difference for higher values
MedOC4 vs OC4v4: Meso-eutrophy
0-0.80 0.30.01 5 0.01 5
21 April 2004
OC4v4 MedOC4 OC4v4 – MedOC4
Morel’s Primary Production Model
Impact on Primary Productivity
Plots by courtesy of Simone Colella
Impact on Primary Productivity
Plots by courtesy of Simone Colella
Colella’s Primary Production Model
• Mediterranean Sea DIFFERENT bio-optical properties as compared to the global ocean
• Large Errors associated with Global algorithm
• Need of a NEW Regional algorithm
• MedOC4 IMPROVES chlorophyll retrieval
(17 % error vs 110 % OC4v4)
Conclusions
• Estimate ERROR Budget for MedOC4 evaluation and implementation
– Assess the atmospheric correction impact
• Understand WHY MED bio-optical properties are so DIFFERENT as compared to the GLOBAL ocean ones
• Identify most suitable PP model for Mediterranean basin
Future Work