A statistical approach to rainfall estimation using satellites and conventional data
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A statistical approach to rainfall estimation using satellites and conventional data

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A statistical approach to rainfall estimation using satellites and conventional data


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    A statistical approach is employed in an attempt to estimate convective rainfall using both satellite and conventional data. The objective is to provide rainfall estimates in a form suitable as input to hydrologic models which forecast riverflow.

    A variety of variables derived from both satellite and conventional meteorological sources are included in the study. All variables are thought to be potentially related, either physically or empirically, to the rainfall process. From among these variables, a screening regression method selects those which best explain area-averaged rainfall.

    Among the cases studied, the relationship of each variable to rainfall is weak to poor, particularly as cases are combined. Although multivariate selections improve the relationships, inconsistency of selection develops from one case to another and from one time to another, even in the same meteorol gi cal situation. Regression equations are found to estimate the amount inadequately, even when using dependent data. These facts led to the conclusion that, at best, rainfall is not likely to be measured quaotitively by such an approach and, at worst, concern is raised about the validity of using the variables investigated to estimate rainfall.

    An IR threshold temperature of 0°C is found to effectively separate instances of rain from no rain. Even this result is tempered by the fact that all cases selected were over rather confined areas during select periods of active convection and rainfall. Given less vigorous convection but with cloud tops above the freezing level, an entirely different result may occur.

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