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Sensitivity of ecosystem parameters to simulated satellite ocean colour data using a coupled physical-biological model of the North Atlantic

机译:利用北大西洋的物理-生物耦合模型对生态系统参数对模拟卫星海洋颜色数据的敏感性

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摘要

A means of assimilating simulated satellite ocean color data with a coupled physical-biological model of the North Atlantic Ocean is implemented, allowing the relative sensitivities of different biological parameters to those data to be investigated. The model consists of an eddy-permitting general circulation model derived from the WOCE Community Modeling Effort and a nitrogen-based, four-compartment NPZD marine ecosystem model. Many of the parameters in marine ecosystem models are poorly known and via assimilation, we hope to better constrain their values. The control parameters chosen for the variational assimilation are the model parameters involved in parameterizations of recycling as these are the most poorly known. Simulated observations are taken while following several floats seeded in varying dynamical biogeochemical provinces of the North Atlantic model domain over a six-month period. Twin experimental results show that, for the given functional forms of growth, mortality and grazing, the following parameters can be successfully recovered from simulated satellite ocean color data: nitrate and detrital recycling parameters in the trade wind domain, zooplankton parameters at higher latitudes (westerly wind and polar domains), and the phytoplankton mortality rate in all regions. By simultaneously assimilating ocean color data in different biological provinces, it becomes possible to successfully constrain all ecosystem parameters at once.
机译:实现了一种将模拟的卫星海洋颜色数据与北大西洋的耦合物理生物学模型同化的方法,从而可以研究不同生物学参数对这些数据的相对敏感性。该模型由源自WOCE社区建模工作的允许涡流的一般循环模型和基于氮的四室NPZD海洋生态系统模型组成。海洋生态系统模型中的许多参数鲜为人知,并且希望通过同化来更好地限制它们的价值。选择用于变化同化的控制参数是涉及回收参数化的模型参数,因为这些参数最为人所知。在六个月的时间里,在北大西洋模型域的不同动态生物地球化学省中播种了多个浮标之后,进行了模拟观察。孪生实验结果表明,对于给定的生长,死亡率和放牧功能形式,可以从模拟的卫星海洋颜色数据中成功恢复以下参数:贸易风域的硝酸盐和碎屑再循环参数,较高纬度的浮游动物参数(向西)风和极地域),以及所有地区的浮游植物死亡率。通过同时吸收不同生物省份中的海洋颜色数据,可以一次成功地约束所有生态系统参数。

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