期刊
GEOPHYSICAL RESEARCH LETTERS
卷 29, 期 14, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2002GL015311
关键词
-
[1] A new convective parameterization is introduced that can make use of a large variety of assumptions previously introduced in earlier formulations. The assumptions are chosen so that they will generate a large spread in the solution. We then show two methods in which ensemble and data assimilation techniques may be used to find the best value to feed back to the larger scale model. First, we can use simple statistical methods to find the most probable solution. Second, the ensemble probability density function can be considered as an appropriate prior'' (a'priori density) for Bayesian data assimilation. Using this prior'', and information about observation likelihood, measured meteorological or climatological data can be directly assimilated into model fields. Given proper observations, the application of this technique is not restricted to convective parameterizations, but may be applied to other parameterizations as well.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据