Stochastic estimation of biogeochemical parameters from Globcolour ocean colour satellite data in a North Atlantic 3D ocean coupled physical-biogeochemical model

被引:31
|
作者
Doron, Maeva [1 ]
Brasseur, Pierre [1 ]
Brankart, Jean-Michel [1 ]
Losa, Svetlana N. [2 ]
Melet, Angelique [3 ]
机构
[1] UJF Grenoble I, CNRS, LGGE, UMR5183, F-38041 Grenoble, France
[2] Alfred Wegener Inst Polar & Marine Res, D-27515 Bremerhaven, Germany
[3] Princeton Univ, Geophys Fluid Dynam Lab, Princeton, NJ 08544 USA
关键词
Coupled physical-biogeochemical ocean model; North Atlantic; Parameter estimation; Stochastic method; Kalman filter; Anamorphosis; Satellite ocean colour data; Globcolour; SeaWiFS; DATA ASSIMILATION; ECOSYSTEM MODEL; SEAWIFS DATA; BIOLOGICAL MODEL; BIOCHEMICAL-MODEL; CHLOROPHYLL DATA; TIME-SERIES; DYNAMICS; NUTRIENT;
D O I
10.1016/j.jmarsys.2013.02.007
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Biogeochemical parameters remain a major source of uncertainty in coupled physical-biogeochemical models of the ocean. In a previous study (Doron et al., 2011), a stochastic estimation method was developed to estimate a subset of biogeochemical model parameters from surface phytoplankton observations. The concept was tested in the context of idealised twin experiments performed with a 1/4 resolution model of the North Atlantic ocean. The method was based on ensemble simulations describing the model response to parameter uncertainty. The statistical estimation process relies on nonlinear transformations of the estimated space to cope with the non-Gaussian behaviour of the resulting joint probability distribution of the model state variables and parameters. In the present study, the same method is applied to real ocean colour observations, as delivered by the sensors SeaWiFS, MERIS and MODIS embarked on the satellites OrbView-2, Envisat and Aqua respectively. The main outcome of the present experiments is a set of regionalised biogeochemical parameters. The benefit is quantitatively assessed with an objective norm of the misfits, which automatically adapts to the different ecological regions. The chlorophyll concentration simulated by the model with this set of optimally derived parameters is closer to the observations than the reference simulation using uniform values of the parameters. In addition, the interannual and seasonal robustness of the estimated parameters is tested by repeating the same analysis using ocean colour observations from several months and several years. The results show the overall consistency of the ensemble of estimated parameters, which are also compared to the results of an independent study. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:81 / 95
页数:15
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