THE ROLE OF VISIBLE DATA IN IMPROVING SATELLITE RAIN-RATE ESTIMATES

Data from the first Algorithm Intercomparison Project (AIP/1) collecte d over Japan and surrounding waters in June, July, and August 1989 are used in this study to assess the importance of visible data in satell ite rain estimation techniques. The purpose of the project was to comp are different methods for estimating rainfall using satellite measurem ents. Radar and surface gauge data provided the validation set. RAINSA T, an estimation technique using both visible (VIS) and infrared (IR) data, achieved the highest correlation with the validation data. In th is paper rainfall estimates from RAINSAT(VIS + IR) are compared with t wo IR-only techniques to deduce the effectiveness of VIS data. Some es timates are also made using a VIS- only technique. Comparisons are mad e on both a spatial and diurnal basis. Cloud climatologies for a subse t of the AIP/1 data and the southern Ontario data on which RAINSAT was trained showed a marked similarity. It is found that the total volume of rain as a function of albedo is very similar for both Japanese and Ontario data. The VIS data generally produced higher correlations wit h the validation data than did the IR data. This was especially the ca se when rain fell from warm, orographically induced rainfall. When rai n fell from cold bright clouds, especially over the ocean, the correla tions of the two types of data with the validation data were similar. It is also shown that normalization of VIS data by the cosine of solar zenith data was inadequate to remove diurnal variations in apparent b rightness.