A simple method for integrating a complex model into an ensemble data assimilation system using MPI
A simple method for integrating a complex model into an ensemble data assimilation system using MPI
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DOI：
10.1016/j.envsoft.2015.02.003
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
P. Browne;Simon Wilson
中科院分区：
文献类型：
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作者：
P. Browne;Simon Wilson
本文详细介绍了修改复杂模型源代码以使该模型可以在数据同化环境中使用的策略，并给出了实现数据同化代码以使用此类模型的标准。该策略依赖于将模型与任何数据同化代码分开，并通过使用消息传递接口（MPI）功能将两者耦合起来。该策略限制了模型所需的更改，因此可以快速编程，但会牺牲最终性能。该实现技术应用于状态维度高达 0.2.7 × 108 的不同模型。在海洋-大气耦合气候模型中使用该实现策略所增加的开销比某些非线性数据同化技术所需的相关随机误差的添加要小一个数量级。
This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, and gives the standards for implementing a data assimilation code to use such a model. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) functionality. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to .2.7 × 108The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques.