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Precipitation efficiency is an important physical parameter in convective systems and has been applied to determine the rainfall intensity in operational precipitation forecasts (e.g., Doswell et al. 1996). Since Braham (1952) calculated precipitation efficiency with the inflow of water vapor into the storm through cloud base as the rainfall source more than half century ago, precipitation efficiency has been defined as the ratio of the precipitation rate to the sum of all precipitation sources. This definition of large-scale precipitation efficiency (LSPE) has been modified and widely applied in modeling studies and operational forecasts (e.g., Auer and Marwitz 1968; Heymsfield and Schotz 1985; Chong and Hauser 1989; Doswell et al. 1996; Ferrier et al. 1996; Li et al. 2002; Tao et al. 2004; Sui et al. 2005). Due to the fact that prognostic cloud microphysical parameterization schemes are used in cloud-resolving modeling of convective processes, precipitation efficiency is also defined through cloud microphysical budgets as cloud microphysics precipitation efficiency (CMPE; e.g., Weisman and Klemp 1982; Lipps and Hemler 1986; Ferrier et al. 1996; Li et al. 2002; Sui et al. 2005). The inclusion of water vapor divergence leads to a negative LSPE. The exclusion of local atmospheric drying associated with nocturnal IR cooling as a precipitation source yields more than 100% of LSPE. The exclusion of the decrease of hydrometeor concentration as a precipitation source causes more than 100% of LSPE and CMPE. These precipitation efficiencies fall within the normal range of 0–100% through the inclusion of all rainfall sources and the exclusion of all rainfall sinks from the water-vapor-related surface rainfall budget (Gao et al. 2005) for LSPE and the cloud microphysical budget for CMPE (Sui et al. 2007).
KeywordsPrecipitation Efficiency Cloud Microphysical Budget (CMPE) Rainfall Source Hydrometeor Concentration Cloud-resolving Model
- Gao S, Cui X, Zhou Y, Li X (2005) Surface rainfall processes as simulated in a cloud resolving model. J Geophys Res. doi:10.1029/2004JD005467Google Scholar