A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

Di Wu1,2, Wei-Kuo Tao1, Stephen E Lang1,3, Xiaowen Li1,4, Toshihisa Matsui1,5 and Takamichi Iguchi1,6, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)SSAI, Greenbelt, MD, United States, (3)NASA Goddard Space Flight Center, Greenbelt, United States, (4)Morgan State University, Climate Science, Baltimore, United States, (5)Earth System Science Interdisciplinary Center, COLLEGE PARK, MD, United States, (6)Earth System Science Interdisciplinary Center, College PARK, United States
Abstract:
During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamics through the release of latent heat (buoyancy, loading and pressure gradient), radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity).

Recently, several major improvements have been made to the ice microphysical schemes that have been developed for cloud-resolving (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecasting, WRF) models. These include improved single-moment bulk 3-ICE (cloud ice, snow and graupel; Lang et al. 2011) and 4-ICE (cloud ice, snow, graupel and hail; Lang et al. 2014) schemes, a spectral bin microphysics scheme and two different two-moment microphysics schemes.

The performance of these schemes has been evaluated using observational data from TRMM and other major field campaigns. In this talk, we will present high-resolution GCE, WRF and MMF model simulations and compare their results with observations (GPM GV, TRMM and CloudSat). In addition, the main issues involving microphysics schemes in high-resolution (i.e., 1-6 km grid spacing) numerical models will be discussed.

Back to: Measurements, Modeling, and Feedback of Cloud-Precipitation Microphysics II