The accurate measurement of the spatial and temporal variation of tropical rainfall around the globe remains one of the critical unsolved problems of meteorology. TRMM, during its mission and broad sampling footprint between 35°N and 35°S, is providing some of the first detailed and comprehensive dataset on the four dimensional distribution of rainfall and latent heating over vastly undersampled oceanic and tropical continental regimes. Combined with concurrent measurement of the atmosphere's radiation budget, estimates of the total diabatic heating are being realized for the first time ever on a global scale.

TRMM will fill many gaps in our understanding of rainfall properties and their variation. These includes a) frequency distributions of rainfall intensity and areal coverage; b) the partitioning of rainfall into convective and stratiform categories; c) the vertical distribution of hydrometeors (including the structure and intensity of the stratiform region bright band); and 4) variation of the timing of heaviest rainfall - particularly nocturnal intensification of large mesoscale convective systems over the oceans, and diurnal intensification of orographically and sea-breezed forced systems over land. TRMM will enable mapping of larger time and space variations of rainfall in quasi-periodic circulation anomalies, such as the Madden-Julian oscillation in the western Pacific and ENSO over the broader Pacific basin. Furthermore, the critical onset of large annual circulation regimes, such as the Asian summer monsoon, can be more thoroughly studied;

Cumulus heating is the principal driver of regional and global-scale atmospheric circulations. For example, it is known that the phase speed of the intraseasonal oscillation (ISO) is highly sensitive to the height of the condensation heating maximum. Diagnostic budgets of sensible heat source (as inferred from research networks of soundings) are incomplete in their global coverage and inadequate to describe the large day-to-day variations that occur in the tropics. Nor can these networks completely capture the significant structural variations that occur in heating and cooling profiles between convective and stratiform rainfall regions. Intensive and globally-distributed observations from TRMM, however, will be crucial for the formulation of reliable cumulus parameterization schemes contained in the latest generation of global cloud models (GCMs);

Sensitivity tests using assimilation of latent heating estimates in GCMs has revealed the potential for improving the prediction of rainfall events. For example, GCM 24-h rainfall predictions using initial conditions adjusted from simulated profiles of TRMM latent heating may be improved by as much as 30% over NMC and ECMWF models.