Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

Chuan GAO; Xinrong WU; Rong-Hua ZHANG

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Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

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摘要

A four-dimensional variational(4D-Var) data assimilation method is implemented in an improved intermediate coupled model(ICM) of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The "observation" of the SST anomaly, which is sampled from a "truth" model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.

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《大气科学进展：英文版》 |2016年第7期|875-888|共14页
作者
Chuan GAO; Xinrong WU; Rong-Hua ZHANG;
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作者单位

Key Laboratory of Ocean Circulation and Waves;

Institute of Oceanology;

Chinese Academy of Sciences;

Qingdao 266071;

University of Chinese Academy of Sciences;

Beijing 100029;

Key Laboratory of Marine Environmental Information Technology;

State Oceanic Administration;

National Marine Data and Information Service;

Tianjin 300000;

Laboratory for Ocean and Climate Dynamics;

Qingdao National Laboratory for Marine Science and Technology;

Qingdao 266237;

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原文格式 PDF
正文语种 chi
中图分类统计方法、整理方法;海洋气象学;
关键词
四维变分资料同化; ENSO事件; 预测分析; 耦合模式; 测试; 四维变分同化; 四维数据同化; ENSO预测;

Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

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