Column Cloud Liquid Water Amounts for Nonprecipitating Clouds versus an “Effective Cloud Fraction” Derived from Microwave Data: A Simulation Study

George R. Diak Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center, University of Wisconsin-Madison, Madison, Wisconsin

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Abstract

The effective cloud fraction evaluated using a minimum residual method and microwave data synthesized for the Advanced Microwave Sounding Unit (AMSU) has been extended by a simple statistical procedure to make estimates of the column cloud water amount for nonprecipitating clouds. In this simulation study of the channel pairs investigated, the highest overall skill in the estimation of column cloud water amounts is shown by the 52–54-GHz oxygen channel pair 3 and 4 of the AMSU over a water surface, where the low surface emissivity produces a very strong cloud water signature (warming of the clear scene). As the surface emissivity rises to representative values for land surfaces, the skill of estimation of cloud water amounts is reduced. At a surface emissivity value representative of a dry land surface, estimation of cloud liquid water from the oxygen channels and these techniques is not possible. In contrast to the oxygen channels, the quality of cloud water estimates made using the 183-GHz water vapor channel pair 19 and 20 of the AMSU is poorest for a water surface and higher for land surfaces with higher emissivity. The quality of the estimates made using thew water vapor channels is shown to strongly depend on the quality of the atmospheric guess used in the procedures.

Abstract

The effective cloud fraction evaluated using a minimum residual method and microwave data synthesized for the Advanced Microwave Sounding Unit (AMSU) has been extended by a simple statistical procedure to make estimates of the column cloud water amount for nonprecipitating clouds. In this simulation study of the channel pairs investigated, the highest overall skill in the estimation of column cloud water amounts is shown by the 52–54-GHz oxygen channel pair 3 and 4 of the AMSU over a water surface, where the low surface emissivity produces a very strong cloud water signature (warming of the clear scene). As the surface emissivity rises to representative values for land surfaces, the skill of estimation of cloud water amounts is reduced. At a surface emissivity value representative of a dry land surface, estimation of cloud liquid water from the oxygen channels and these techniques is not possible. In contrast to the oxygen channels, the quality of cloud water estimates made using the 183-GHz water vapor channel pair 19 and 20 of the AMSU is poorest for a water surface and higher for land surfaces with higher emissivity. The quality of the estimates made using thew water vapor channels is shown to strongly depend on the quality of the atmospheric guess used in the procedures.

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