| Short- to medium-range precipitation forecasts over the global tropics are explored using satellite products, from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) instruments, within the context of a quasi-operational environment. As a comprehensive extension of the previous multimodel/multianalysis superensemble (SE) studies of rainfall forecasts, the benefits and prospects of the SE precipitation forecasts are reviewed and elaborated within this study.;Three different precipitation ensemble configurations are first established from a great number of numerical experiments. These configurations are multianalysis (MA), multicumulus-scheme (MC), and multimodel (MM) configurations. A set of MA ensemble comes from the use of several different satellite-derived rain rates through the physical initialization (PI) procedure within the Florida State University Global Spectral Model (FSUGSM) system. Six different state-of-the art cumulus parameterization schemes are incorporated into the FSUGSM in order to briefly evaluate their performances on precipitation forecasts and introduce the MC ensemble configuration. The MM configuration of precipitation forecasts is composed of an FSU control forecast and those provided by five operational numerical weather prediction centers.;In addition to the original technique, several possible deterministic SE enhancement techniques, such as, empirical orthogonal function (EOF)-based multiple regression and regression dynamic linear model (DLM), are then proposed and applied to the above three configurations of ensemble members as well as all of them together (called ALL configuration). Probabilistic precipitation forecasts are also introduced and applied to the above ensemble configurations. A probabilistic SE approach is examined in those ensemble structures as well. The impact of a higher resolution family of models on the performance of SE forecasts is extensively investigated by repeating the above procedure with T170 resolution precipitation forecasts.;Results show that short- to medium-range SE forecasts of precipitation are invariably superior in skill to various conventional forecasts. A notably improved quantitative precipitation forecast is exhibited by a newly proposed SE technique in the present paper. The MM configuration proved to be the most effective ensemble prediction system. Although a higher resolution SE forecast requires a large amount of computing time, it turns out that the impact is significant not only in skill scores, but also in resolving mesoscale-based convective disturbances. The advantage of the SE approach is also found to be evident in making probabilistic precipitation forecasts. |
