Improvement in background error covariances using ensemble forecasts for assimilation of high-resolution satellite data

被引：0
作者：
Seung-Woo Lee
Dong-Kyou Lee
机构：
[1] Seoul National University,School of Earth and Environmental Sciences
来源：
Advances in Atmospheric Sciences | 2011年 / 28卷
关键词：
3DVAR; background error covariances; retrieved satellite data assimilation; ensemble forecasts;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data.
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