Development of a Scale-Aware Cumulus Parameterization – Part I: Evaluation of...

Fan, J., Y. Liu, K. Xu, K. North, S. Collis, X. Dong, G. J. Zhang, and S. Ghan (2014), Development of a Scale-Aware Cumulus Parameterization – Part I: Evaluation of Model Simulations with Spectral-Bin Microphysics and Comparisons with Bulk Microphysics, J. Geophys. Res. (submitted).

The ultimate goal of this study is to develop a scale-aware cumulus parameterization for meso-scale and climate models. As Part I of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in mid-latitude continent and tropical regions using the Weather Research and Forecasting (WRF) model with spectral-bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MO-R) and Milbrandt and Yau (MY). Compared to observations, in general, SBM gives better simulations of precipitation, vertical velocity of convective cores, and the vertically decreasing trend of radar reflectivity than MO-R and MY, and therefore will be used for analysis of scale-dependency of eddy transport in Part II. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates radar reflectivity in convective cores (SBM predicts smaller radar reflectivity but does not remove the large overestimation); and (3) the model performs better for mid-latitude convective systems than tropical system. The modeled mass fluxes of the mid-latitude systems are not sensitive to microphysics schemes, but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.

Research Program: 
Modeling Analysis and Prediction Program (MAP)