Evaluating Goddard Multi-Scale Modeling Framework at Different fv-GCM Grid Spacing

The Goddard Multi-scale Modeling Framework (MMF) is based on the coupling of the two-dimensional Goddard Cumulus Ensemble (GCE) model and the finite-volume GCM (fv-GCM). Thus MMF enables explicit resolution of stochastic moist convection process by embedded GCE simulations, unlike traditional GCMs that rely on convection parameterization. At each fv-GCM column, the fv-GCM provides mean atmospheric conditions and large-scale temperature and moisture advection to drive the 2D GCE models, which feedback the tendencies of thermodynamic parameter and cloud statistics to the fv-GCM. Earlier investigations show that the Goddard MMF simulates better cloudiness (high and low), single ITCZ and a more realistic diurnal variation of rainfall than traditional GCMs. Another advantages of using the Goddard MMF is that the resolution of GCE-simulated clouds is compatible to satellite observations, while traditional GCM requires disaggregation of grid-volume feature to compare with high-resolution satellite observations. Thus, satellite instrumental simulator can be directly applied to translate MMF simulations into the satellite instrumental signals in straightforward way. In this year, we examine the sensitivity of the Goddard MMF simulation at different fv-GCM grid spacing, and evaluated performances against the TRMM satellite. Previously, fv-GCM was run at 2x2.5 degree horizontal lat-lon grid spacing, and we are currently running fv-GCM at 1x1.25 degree. We examine the performance of the Goddard MMF at different fv-GCM grid spacing with respect to rainfall frequency, rain structure, and microphysics using multi-sensor radiance-based evaluation method, known as the TRMM Triple-Sensor Three-step Evaluation Framework (T3EF). T3EF utilizes multi-sensor satellite simulators, Goddard Satellite Data Simulation Unit, and novel statistics of multi-sensor radiance and backscattering signals observed from the TRMM satellite. Specifically, T3EF compares GCE and satellite observations in the form of combined probability distributions of precipitation radar (PR) reflectivity, polarization-corrected microwave brightness temperature (Tb), and infrared Tb to evaluate the candidate CRM.