气候变化领域集成服务门户(CCPortal): Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations

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DOI	10.1016/j.atmosres.2020.104925
	Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations
	Hazra V.; Pattnaik S.; Sisodiya A.; Baisya H.; Turner A.G.; Bhat G.S.
发表日期	2020
ISSN	0169-8095
卷号	239
英文摘要	This study validates the performance of four different cloud microphysics parameterization (CMP) with the INCOMPASS aircraft observations during monsoon 2016 and assesses its impact on simulations of two monsoon depressions (MDs) using the Weather Research and Forecasting (WRF) model. The simulations are carried out with a lead time up to 96 h. It is found that the Aerosol Aware Thompson (AAT) scheme showed better result in terms of wind and the WRF Double Moment Six Class microphysical scheme (WDM6) showed better correlations for temperature and dew point temperature compared to aircraft measurements. It is noted that the choice of CMP significantly impacts the key characteristics of the MDs such as rainfall, wind, temperature, hydrometeors and associated convective processes (e.g. moist static energy, moisture convergence). In general, CMPs have overestimated the rainfall compared to satellite estimates Tropical Rainfall Measuring Mission (TRMM), with WDM6 producing the least errors. Therefore, inter-comparisons of simulations of CMPs are carried out using WDM6 as the benchmark. Inter-comparison results suggest that there is a substantial reduction in rainfall for the Morrison due to drier lower and middle troposphere leading to subdued convective activity compared to others. Further, WDM6 has produced the least errors in the distribution of frozen hydrometer compared to ERA5. By examining the water budget, it is found that moisture convergence is the major driver for the rainfall, and the magnitude of moisture convergence is strongly affected by the choice of CMPs. Additionally, the local and advection terms of the moisture budget equation provide minimal contributions towards rainfall generation. © 2020
英文关键词	Cloud Microphysics Parameterization; INCOMPASS; Monsoon Depression; WRF
学科领域	Aircraft; Atmospheric thermodynamics; Budget control; Moisture; Parameterization; Rain; Weather forecasting; Aircraft observations; Cloud microphysics; INCOMPASS; Microphysical parameterization; Monsoon depressions; Substantial reduction; Tropical rainfall measuring missions; Weather research and forecasting models; Rain gages
语种	英语
scopus关键词	Aircraft; Atmospheric thermodynamics; Budget control; Moisture; Parameterization; Rain; Weather forecasting; Aircraft observations; Cloud microphysics; INCOMPASS; Microphysical parameterization; Monsoon depressions; Substantial reduction; Tropical rainfall measuring missions; Weather research and forecasting models; Rain gages
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/120408
作者单位	School of Earth Ocean and Climate Sciences, Indian Institute of Technology Bhubaneswar, India; Department of Meteorology, University of Reading, Reading, United Kingdom; National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom; Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India
推荐引用方式 GB/T 7714	Hazra V.,Pattnaik S.,Sisodiya A.,et al. Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations[J],2020,239.
APA	Hazra V.,Pattnaik S.,Sisodiya A.,Baisya H.,Turner A.G.,&Bhat G.S..(2020).Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations.Atmospheric Research,239.
MLA	Hazra V.,et al."Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations".Atmospheric Research 239(2020).