A MODEL FOR QUANTITATIVELY ESTIMATING SHORT-RANGE PRECIPITATION BASED ON GMS DIGITALIZED CLOUD MAPS―PART I: ANALYSIS OF QUANTITATIVE CLOUD-PRECIPITATION RELATIONS AND MODEL DESIGN

摘要

Some typical samples are used to explore the quantitative correlation with their features between a convective cloud and its rainfall field, with which to develop two morphological functions for the correlation and by singling out their most suitable groups of parameters we propose a model for quantitatively estimating precipitation in the context of the in-advance recognition of meso-α convective system properties and its precipitating center. From the model fitting precision and forecasting accuracy we find that it is feasible to utilize geostationary meteorological satellite ( GMS ) digitalized imagery for estimating short-term rainfall in a quantitative manner. Also, evidence suggests that the model is supposed to be restricted in its applicability due to the fact that the employed samples are from rather typical rainfall events that are large-scale, slow-moving and have well-defined genesis and dissipative stages.