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Assimilation
of chlorophyll and nutrients into a 3-D marine carbon cycle model
(NASA-Carbon cycle)
11 section parameter optimizations
In these experiments,
ecosystem parameters are varied seasonally and regionally to fit the
SeaWiFS chlorophyll data. For this purpose the ocean model domain
is divided into eleven sections.
Figure 1 Plot of global ocean regions based in ocean
basin distribution
The regional variation of ecosystem
parameters resulted in a better
performance of the carbon cycle model with a significantly
reduced misfit between the simulated and the observed chlorophyll
concentration. The a posteriori model-data misfit in the Southern
Ocean remains relatively high in the Spring season assimilation (Figure
2c).
The optimization also improves the chlorophyll simulation in the
equatorial Atlantic and Indian Ocean, as well as in the southern
Indian Ocean. A distinguishable improvement also occurred in the North
Pacific region where the a posteriori chlorophyll concentration
increased significantly. The optimized ecosystem parameters are
listed in Table 1. Almost all of the assimilation experiments yielded
lower zooplankton grazing rates.
|
Pi
|
|
NOPA
|
NOAT
|
MIPA
|
MIAT
|
EQIN
|
EQPA
|
EQAT
|
SOIN
|
SOPA
|
SOAT
|
SOOC
|
NOPA
|
NOAT
|
Mean
|
Var
|
|
P1
|
Spring
|
1.05
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
1.01
|
1.00
|
1.01
|
1.00
|
1.00
|
1.05
|
1.00
|
1.01
|
0.00
|
|
P2
|
2.15
|
1.00
|
1.07
|
1.04
|
1.10
|
1.02
|
1.64
|
1.11
|
1.11
|
1.11
|
1.03
|
2.15
|
1.00
|
1.22
|
0.13
|
|
P3
|
0.00
|
0.99
|
0.99
|
0.97
|
1.00
|
1.00
|
1.07
|
0.99
|
1.00
|
1.00
|
1.00
|
0.00
|
0.99
|
0.91
|
0.09
|
|
P4
|
0.00
|
0.78
|
0.71
|
0.69
|
0.97
|
0.99
|
0.95
|
0.88
|
0.90
|
0.90
|
0.91
|
0.00
|
0.78
|
0.79
|
0.08
|
|
P5
|
0.00
|
0.99
|
0.83
|
0.90
|
0.94
|
0.98
|
0.09
|
0.93
|
0.92
|
0.86
|
1.05
|
0.00
|
0.99
|
0.77
|
0.13
|
|
P6
|
0.00
|
0.99
|
0.87
|
0.91
|
0.92
|
0.99
|
0.48
|
0.87
|
0.91
|
0.88
|
0.95
|
0.00
|
0.99
|
0.80
|
0.09
|
|
P7
|
0.00
|
0.99
|
0.86
|
0.91
|
0.85
|
0.99
|
0.00
|
0.94
|
0.89
|
0.89
|
1.04
|
0.00
|
0.99
|
0.76
|
0.14
|
|
P8
|
1.23
|
1.00
|
1.01
|
1.01
|
1.02
|
1.00
|
1.13
|
1.02
|
1.02
|
1.02
|
1.00
|
1.23
|
1.00
|
1.04
|
0.01
|
|
P9
|
1.03
|
1.00
|
1.00
|
1.00
|
1.01
|
1.00
|
1.02
|
1.00
|
1.00
|
1.00
|
1.00
|
1.03
|
1.00
|
1.01
|
0.00
|
|
P10
|
2.45
|
1.02
|
1.06
|
1.05
|
1.04
|
1.01
|
1.21
|
1.03
|
1.08
|
1.02
|
1.00
|
2.45
|
1.02
|
1.18
|
0.18
|
|
P11
|
3.56
|
1.12
|
1.01
|
1.04
|
0.90
|
1.00
|
0.81
|
1.13
|
1.01
|
1.05
|
1.12
|
3.56
|
1.12
|
1.25
|
0.60
|
|
P12
|
0.00
|
0.99
|
1.00
|
0.79
|
1.03
|
0.92
|
0.82
|
0.02
|
0.66
|
0.74
|
0.00
|
0.00
|
0.99
|
0.63
|
0.18
|
|
P1
|
Fall
|
1.00
|
1.00
|
1.01
|
1.00
|
1.00
|
0.99
|
1.01
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
0.00
|
|
P2
|
2.30
|
1.07
|
2.13
|
1.15
|
1.08
|
1.19
|
1.30
|
1.05
|
1.00
|
1.11
|
0.98
|
2.30
|
1.07
|
1.31
|
0.21
|
|
P3
|
0.72
|
0.11
|
0.83
|
0.99
|
1.00
|
1.00
|
1.02
|
1.02
|
1.00
|
1.05
|
1.01
|
0.72
|
0.11
|
0.89
|
0.08
|
|
P4
|
0.00
|
0.78
|
0.63
|
0.78
|
0.97
|
0.95
|
0.99
|
1.12
|
1.01
|
1.31
|
1.11
|
0.00
|
0.78
|
0.88
|
0.12
|
|
P5
|
0.57
|
0.94
|
1.15
|
0.91
|
0.90
|
0.96
|
0.76
|
0.92
|
1.00
|
0.83
|
1.06
|
0.57
|
0.94
|
0.91
|
0.02
|
|
P6
|
0.00
|
0.83
|
0.43
|
0.77
|
0.94
|
0.88
|
0.77
|
0.94
|
1.00
|
0.70
|
1.05
|
0.00
|
0.83
|
0.76
|
0.09
|
|
P7
|
0.01
|
0.96
|
1.11
|
0.93
|
0.91
|
1.01
|
0.61
|
0.94
|
1.00
|
0.88
|
1.05
|
0.01
|
0.96
|
0.86
|
0.09
|
|
P8
|
1.25
|
1.01
|
1.20
|
1.03
|
1.02
|
1.03
|
1.07
|
1.01
|
1.00
|
1.02
|
1.00
|
1.25
|
1.01
|
1.06
|
0.01
|
|
P9
|
1.10
|
1.00
|
1.17
|
1.00
|
1.00
|
0.96
|
1.02
|
1.00
|
1.00
|
1.00
|
1.00
|
1.10
|
1.00
|
1.02
|
0.00
|
|
P10
|
1.02
|
1.00
|
1.11
|
1.01
|
1.01
|
0.94
|
1.10
|
0.99
|
1.00
|
0.92
|
0.98
|
1.02
|
1.00
|
1.01
|
0.00
|
|
P11
|
2.02
|
1.23
|
0.40
|
1.31
|
0.96
|
1.30
|
0.84
|
0.98
|
1.00
|
0.97
|
0.96
|
2.02
|
1.23
|
1.09
|
0.16
|
|
P12
|
0.00
|
0.00
|
2.82
|
0.00
|
1.07
|
0.00
|
0.90
|
1.22
|
1.00
|
1.10
|
0.00
|
0.00
|
0.00
|
0.74
|
0.76
|
Table 1. A posteriori ecosystem
parameter values with mean and variance resulting from the
assimilation with regionally varying control variables for Spring
and Fall season integrations.
a) b) 
c) d) 

Figure 2. SeaWiFS chlorophyll-a data for Spring (A) and Fall (B)
seasons in comparison to the respective model a posteriori simulation
of surface chlorophyll concentration for Spring (C) and Fall (D).
Ecosystem parameters are varied by the optimization in different ocean
sections.
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