Strongly Coupled Data Assimilation of Ocean Observations Into an Ocean-Atmosphere Model

被引:11
|
作者
Tang, Q. [1 ,2 ]
Mu, L. [1 ,3 ]
Goessling, H. F. [1 ]
Semmler, T. [1 ]
Nerger, L. [1 ]
机构
[1] Alfred Wegener Inst, Helmholtz Ctr Polar & Marine Res, Bremerhaven, Germany
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
[3] Pilot Natl Lab Marine Sci & Technol, Qingdao, Peoples R China
关键词
coupled ocean-atmosphere model; cross-covariance; ensemble Kalman filter; sea surface temperature; strongly coupled data assimilation; FORMULATION; CLIMATE;
D O I
10.1029/2021GL094941
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
We compare strongly coupled data assimilation (SCDA) and weakly coupled data assimilation (WCDA) by analyzing the assimilation effect on the estimation of the ocean and the atmosphere variables. The AWI climate model (AWI-CM-1.1) is coupled with the parallel data assimilation framework (PDAF). Only satellite sea surface temperature data are assimilated. For WCDA, only the ocean variables are directly updated by the assimilation. For SCDA, both the ocean and the atmosphere variables are directly updated by the assimilation. Both WCDA and SCDA improve ocean state and yield similar errors. In the atmosphere, WCDA gives slightly smaller errors for the near-surface temperature and wind velocity than SCDA. In the free atmosphere, SCDA yields smaller errors for the temperature, wind velocity, and specific humidity than WCDA in the Arctic region, while in the tropical region, the errors are generally larger.
引用
收藏
页数:10
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