集合卡尔曼滤波在大气-海洋耦合模式中的应用

2006 IEEE Nonlinear Statistical Signal Processing Workshop Pub Date : 2006-09-01 DOI:10.1109/NSSPW.2006.4378835

G. Ueno, T. Higuchi, T. Kagimoto, N. Hirose

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引用次数: 3

摘要

本文报道了集合卡尔曼滤波(EnKF)在大气-海洋中间耦合模式中的首次应用[1]，该模式吸收了TOPEX/POSEIDON (T/P)测高的海面高度(SSH)异常观测数据。从1981个观测点和2048个集合成员获得了54,403维状态的平滑估计。在同化数据仅为海面异常的情况下，基于EnKF的2002/03年El Niño事件的集合实验可以提前5个月预测一致的Niño 3海温异常。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of the Ensemble Kalman Filter to Atmosphere-Ocean Coupled Model

We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates ofthe 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Niño event based on the EnKF can predict consistent Niño 3 sea surface temperature (SST) anomalies about 5 months in advance.

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2006 IEEE Nonlinear Statistical Signal Processing Workshop

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