The Impact of Parameterization of Cloud Microphysical Processes on Convective Precipitation Forecasting

摘要

@@ 1. Introduction Cloud microphysical processes play critical roles in vertical distribution of atmospheric moisture and heat, and bring gr eat uncertainty to precipitation prediction, especially for severe rainfall eve nts. Due to the lim itation of computer power , p arameterized microphysical schemes are usually utilized in weather forecasting models and climate models. Dif ferent p arameterizations of cloud microphysics can lead to large discrepancies in pr ecipitation simulati ons. Li et al. (2009) sugges ted that single-moment schemes could significantly overestimate precipitation, especially with the Lin scheme, whereas precipitation amounts simulated with two-moment schemes were comp arable with the measurement s. Khain and Lynn (200 9) compared their simulation results obtained us ing the weat her research and forecast (WRF) model with spectral (bin) microphysics and compared with that obtained from the Thompson bulk-parameterization scheme. They found that the difference in vertical velocity, cloud structure and precipitatio n obtained by different schemes is much larger than the changes caused by variation of aerosol concentration within each scheme. In the present study, we perform simu lations using WRF model with different parameterization schemes for cloud microphysical processes to investigate the efects of p arameterization of cloud mi crophysics on precipit ation for a deep convective system.