Toward an Objective Analysis of Rainfall Rate Combining Observations and Short-Term Forecast Model Estimates

Abstract

This study explores the feasibility of performing an objective analysis of instantaneous rain rate combining satellite estimates (and eventually other types of observations) with those from a numerical prediction model using the method of statistical interpolation. Results demonstrate that the quality of the short-term precipitation forecasts serving as background field has reached a level that makes such an objective analysis possible. The two main requirements to obtain an accurate analysis from available information are a realistic estimate of background field and observation errors and knowledge of the horizontal correlation of these errors with distance. The importance of specifying the errors for joint model-observation situations is emphasized; it is especially important in situations where model and observations are in conflict. These aspects of the problem are studied using collocated 6-h forecast with satellite estimates derived from visible and infrared imagery, and ground-truth rainfall data available over Japanese territory from the Global Precipitation Climatology Project. Over 90 000 truth-model-satellite collocations are available at the common scale of 130 km ? 130 km. An alternative means of establishing the model error correlation with distance and azimuth direction from 6- and 18-h forecast differences valid at the same time yield results that are similar to those derived from collocations with truth rainfall over large domains, but not locally, this result suggests a means of relaxing the assumption of homogeneity and isotropy of model errors. The sensitivity of the rain rate analysis to different specifications of the satellite to model error ratios is shown with an example.