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Proceedings Paper

The impact of hydrometeors on the microphysical parameterization in the WRF modelling system over southern peninsular India
Author(s): A. R. Ragi; Maithili Sharan; Z. S. Haddad
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Paper Abstract

This study examines the influence of Purdue-Lin microphysical parameterization scheme (Lin et al.,1983) on quantitative precipitation for pre-monsoon/monsoon conditions over southern peninsular India in the Weather Research and Forecasting (WRF) model. An ideal microphysical scheme has to describe the formation, growth of cloud droplets and ice crystals and fall out as precipitation. Microphysics schemes can be broadly categorized into two types: bin and bulk particle size distribution (Morrison, 2010). Bulk schemes predict one or more bulk quantities and assume some functional form for the particle size distribution. For better parameterization, proper interpretation of these hydrometeors (Cloud Droplets, Raindrops, Ice Crystals and Aggregates, Rimed Ice Particles, Graupel, Hail) and non-hydrometeors (Aerosols vs. Condensation Nuclei vs. Cloud Condensation Nuclei vs. Ice Nuclei) is very important. The Purdue-Lin scheme is a commonly used microphysics scheme in WRF model utilizing the “bulk” particle size distribution, meaning that a particle size distribution is assumed. The intercept parameter (N0) is, in fact, turns out to be independent of the density. However, in situ observations suggest (Haddad et al., 1996, 1997) that the mass weighted mean diameter is correlated with water content per unit volume (q), leading to the fact that N0 depends on it. Here, in order to analyze the correlation of droplet size distribution with the convection, we have carried out simulations by implementing a consistent methodology to enforce a correlation between N0 and q in the Purdue-Lin microphysics scheme in WRF model. The effect of particles in Indian Summer Monsoon has been examined using frequency distribution of rainfall at surface, daily rainfall over the domain and convective available potential energy and convective inhibition. The simulations are conducted by analyzing the maximum rainfall days in the pre-monsoon/monsoon seasons using Tropical Rainfall Measuring Mission (TRMM) accumulated rainfall data for 24 hours.

Paper Details

Date Published: 9 May 2016
PDF: 8 pages
Proc. SPIE 9876, Remote Sensing of the Atmosphere, Clouds, and Precipitation VI, 98762Q (9 May 2016); doi: 10.1117/12.2223669
Show Author Affiliations
A. R. Ragi, Indian Institute of Technology Delhi (India)
Maithili Sharan, Indian Institute of Technology Delhi (India)
Z. S. Haddad, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 9876:
Remote Sensing of the Atmosphere, Clouds, and Precipitation VI
Eastwood Im; Raj Kumar; Song Yang, Editor(s)

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