Why does cloud superparameterization improve the simulated daily rainfall cycle in a multiscale climate modeling framework?

The Multiscale Modeling Framework (MMF*) approach to global climate modeling results in improved simulations of small-scale, fast (daily) rainfall variability, but understanding why is difficult. Analysis of the vertically integrated diurnal composite moisture budget provides several new clues to the physical processes involved.

Daytime entrainment humidification resolved by the embedded cloud-resolving model (CRM) in the Super-Parameterized Community Atmosphere Model v3.0 (SPCAM3) tempers the amplitude and fixes the timing of the overly vigorous CAM3 diurnal rainfall cycle over land. Diurnal water budget analysis shows that at night time, and over the ocean, substantially different representations of diurnal moisture convergence in the two models play a major role in differentiating daily tropical rainfall. In CAM3 a large-scale equatorial planetary wave of diurnal moisture convergence and storage connects the vigorous over-land rainfall cycle to the diurnal rainfall cycle over open ocean thousands of kilometers away. The absence of this wave in SPCAM3 is another, more subtle reason for its improved diurnal rainfall cycle.

*MMFs are global climate models (GCMs) that represent sub-grid cloud and boundary layer processes using nested cloud resolving models (superparameterization) in each grid column instead of conventional statistical parameterizations. The MMF (SPCAM3) and GCM (CAM3) compared in this study are identical except for their treatment of the sub-grid scale.