A Hybrid Global Ocean Data Assimilation System at NCEP
A Hybrid Global Ocean Data Assimilation System at NCEP
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DOI：
10.1175/mwr-d-14-00376.1
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发表时间：
2014-12
影响因子：
3.2
通讯作者：
S. Penny;D. Behringer;J. Carton;E. Kalnay
中科院分区：
文献类型：
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作者：
S. Penny;D. Behringer;J. Carton;E. Kalnay
摘要 使用耦合模型进行季节预报需要准确的海洋初始条件。国家环境预测中心 (NCEP) 全球海洋数据同化系统 (GODAS) 已实施混合数据同化，作为未来操作三维变分数据同化 (3DVar) 方法的替代。这种 Hybrid-GODAS 通过使用动态和静态背景误差协方差的组合以及通过使用由大气表面条件的不同实现所强制的集合来提供模型不确定性的改进表示。 1991 年 1 月至 1999 年 1 月进行了观测系统模拟实验（OSSE），对表面强迫条件施加了偏差以模拟不完美的模型。 OSSE 使用与 NCEP 气候预报系统再分析 (CFSR) 相对应的模拟现场海洋观测，将 NCEP 气候预报系统 (CFSv2) 使用的 3DVar 与新的混合系统进行比较。T...
AbstractSeasonal forecasting with a coupled model requires accurate initial conditions for the ocean. A hybrid data assimilation has been implemented within the National Centers for Environmental Prediction (NCEP) Global Ocean Data Assimilation System (GODAS) as a future replacement of the operational three-dimensional variational data assimilation (3DVar) method. This Hybrid-GODAS provides improved representation of model uncertainties by using a combination of dynamic and static background error covariances, and by using an ensemble forced by different realizations of atmospheric surface conditions. An observing system simulation experiment (OSSE) is presented spanning January 1991 to January 1999, with a bias imposed on the surface forcing conditions to emulate an imperfect model. The OSSE compares the 3DVar used by the NCEP Climate Forecast System (CFSv2) with the new hybrid, using simulated in situ ocean observations corresponding to those used for the NCEP Climate Forecast System Reanalysis (CFSR).T...