Improved Forecasts of the Diurnal Cycle in the Tropics Using Multiple Global Models. Part I: Precipitation

Abstract

The Tropical Rainfall Measuring Mission (TRMM) satellite supplemented with the Defense Meteorological Satellites Program (DMSP) microwave dataset provides accurate rain-rate estimates. Furthermore, infrared radiances from the geostationary satellites provide the possibility for mapping the diurnal change of tropical rainfall. Modeling of the phase and amplitude of the tropical rainfall is the theme of this paper. The present study utilizes a suite of global multimodels that are identical in all respects except for their cumulus parameterization algorithms. Six different cumulus parameterizations are tested in this study. These include the Florida State University (FSU) Modified Kuo Scheme (KUO), Goddard Space Flight Center (GSFC) Relaxed Arakawa?Schubert Scheme (RAS1), Naval Research Laboratory?Navy Operational Global Atmospheric Prediction System (NRL?NOGAPS) Relaxed Arakawa?Schubert Scheme (RAS2), NCEP Simplified Arakawa?Schubert Scheme (SAS), NCAR Zhang?McFarlane Scheme (ZM), and NRL?NOGAPS Emanuel Scheme (ECS). The authors carried out nearly 600 experiments with these six versions of the T170 Florida State University global spectral model. These are 5-day NWP experiments where the diurnal change datasets were archived at 3-hourly intervals. This study includes the estimation of skills of the phase and amplitudes of the diurnal rain using these member models, their ensemble mean, a multimodel superensemble, and those from a single unified model. Test results are presented for the global tropics and for some specific regions where the member models show difficulty in predicting the diurnal change of rainfall. The main contribution is the considerable improvement of the modeling of diurnal rain by deploying a multimodel superensemble and by constructing a single unified model. The authors also present a comparison of these findings on the modeling of diurnal rain from another suite of multimodels that utilized different versions of cloud radiation algorithms (instead of different cumulus parameterization schemes) toward defining the suite of multimodels. The principal result is that the superensemble does provide a future forecast for the total daily rain and for the diurnal change of rain through day 5 that is superior to forecasts provided by the best model. The training of the superensemble with good observed estimates of rain, such as those from TRMM, is necessary for such forecasts.