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Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction
作者姓名:刘征宇  武术  张绍晴  刘赟  容新尧
作者单位:Laboratory for Climate, Ocean and Atmosphere Studies, Peking University;Nelson Institute Center for Climatic Research and the Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison;Geophysical Fluid Dynamics Laboratory;Meteorological Research Institute, China Meteorological Administration
基金项目:supported by the National Natural Science Foundation of China (Grant Nos. 2012CB955201 and 41130105);supported by the NOAA
摘    要: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.

关 键 词:ensemble  Kalman  filter  coupled  model  ocean–atmosphere  interaction  coupled  covariance

Ensemble data assimilation in a simple coupled climate model: The role of ocean-atmosphere interaction
LIU Zhengyu , WU Shu , ZHANG Shaoqing , LIU Yun , RONG Xinyao.Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction[J].Advances in Atmospheric Sciences,2013,30(5):1235-1248.
Authors:LIU Zhengyu  WU Shu  ZHANG Shaoqing  LIU Yun  RONG Xinyao
Institution:1. Laboratory for Climate, Ocean and Atmosphere Studies, Peking University, Beijing 100871; Nelson Institute Center for Climatic Research and the Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, USA, 53706
2. Nelson Institute Center for Climatic Research and the Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, USA, 53706
3. Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, USA, 08540
4. Meteorological Research Institute, China Meteorological Administration, Beijing 100081
Abstract: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.
Keywords:ensemble Kalman filter  coupled model  ocean-atmosphere interaction  coupled covariance
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