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A Generalized Approach To Parameterizing Convection Combining Ensemble and Data Assimilation Techniques


[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.}

Article / Publication Data
Available Metadata
Accepted On
June 12, 2002
Fiscal Year
Publication Name
Geophysical Research Letters
Published On
July 25, 2002
Publisher Name
Amer Geophysical Union
Print Volume
Print Number
Submitted On
April 11, 2002


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Authors who have authored or contributed to this publication.