A comparison of cumulus parameterization schemes in a numerical weather prediction model for a monsoon rainfall event

摘要

In order to evaluate cumulus parameterization (CP) schemes for hydrological applications, the Pennsylvania State University-National Center for Atmospheric Research's fifth-generation mesoscale model (MM5) was used to simulate a summer monsoon in east China. The performances of five CP schemes (Anthes-Kuo, Betts-Miller, Fritsch-Chappell, Kain-Fritsch, and Grell) were evaluated in terms of their ability to simulate amount of rainfall during the heavy, moderate, and light phases of the event. The Grell scheme was found to be the most robust, performing well at all rainfall intensity and spatial scales. The Betts-Miller scheme also performed well, particularly at larger scales, but its assumptions may make it inapplicable to non-tropical environments and at smaller scales. The Kain-Fritsch scheme was the best at simulating moderate rainfall rates, and was found to be superior to the Fritsch-Chappell scheme on which it was based. The Anthes-Kuo scheme was found to underpredict precipitation consistently at the mesoscale. Simulation performance was found to improve when schemes that included downdrafts were used in conjunction with schemes that did not include downdrafts.