Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction

A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assi...

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Bibliographic Details
Published in:Advances in Atmospheric Sciences
Main Authors: Liu Zhengyu, Wu Shu, Zhang Shaoqing, Liu Yun, Rong Xinyao
Other Authors: Wu, S (reprint author), Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA., Peking Univ, Lab Climate Ocean & Atmosphere Studies, Beijing 100871, Peoples R China., Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI 53706 USA., Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI 53706 USA., NOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA., China Meteorol Adm, Meteorol Res Inst, Beijing 100081, Peoples R China.
Format: Journal/Newspaper
Language:English
Published: 大气科学进展英文版 2013
Subjects:
ensemble Kalman filter
coupled model
ocean-atmosphere interaction
coupled covariance
NORTH-ATLANTIC
EL-NINO
PREDICTABILITY
CIRCULATION
PREDICTION
FORECASTS
SYSTEM
ENSO
North Atlantic
Online Access:https://hdl.handle.net/20.500.11897/220955
https://doi.org/10.1007/s00376-013-2268-z
Description
Summary:A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000323278000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 Meteorology & Atmospheric Sciences SCI(E) 中国科技核心期刊(ISTIC) 中国科学引文数据库(CSCD) 9 ARTICLE 5 1235-1248 30

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