Development of a regional rain retrieval algorithm for exclusive mesoscale convective systems over peninsular India

被引:1
作者
Dutta, Devajyoti [1 ]
Sharma, Sanjay [1 ]
Das, Jyotirmay [2 ]
Gairola, R. M. [3 ]
机构
[1] Kohima Sci Coll, Dept Phys, Nagaland 797002, India
[2] Indian Stat Inst, Elect & Commun Sci Unit, Kolkata 700108, India
[3] Ctr Space Applicat, Meteorol & Oceanog Grp, Ahmadabad 380015, Gujarat, India
关键词
Brightness temperature; Rain intensity; Mesoscale convective systems; Artificial neural network; Rain estimation; TROPICAL PRECIPITATION PROFILES; AIRCRAFT MICROWAVE OBSERVATIONS; PASSIVE MICROWAVE; 183; GHZ; BRIGHTNESS TEMPERATURE; RADIATIVE-TRANSFER; RADAR MEASUREMENTS; DEEP CONVECTION; ICE-SCATTERING; TRMM;
D O I
10.1016/j.asr.2012.02.028
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The present study emphasize the development of a region specific rain retrieval algorithm by taking into accounts the cloud features. Brightness temperatures (T-bs) from various TRMM Microwave Imager (TM!) channels are calibrated with near surface rain intensity as observed from the TRMM Precipitation Radar. It shows that T-b-R relations during exclusive-Mesoscale Convective System (MCS) events have greater dynamical range compared to combined events of non-MCS and MCS. Increased dynamical range of T-b-R relations for exclusive-MCS events have led to the development of an Artificial Neural Network (ANN) based regional algorithm for rain intensity estimation. By using the exclusive MCSs algorithm, reasonably good improvement in the accuracy of rain intensity estimation is observed. A case study of a comparison of rain intensity estimation by the exclusive-MCS regional algorithm and the global TRMM 2A12 rain product with a Doppler Weather Radar shows significant improvement in rain intensity estimation by the developed regional algorithm. (C) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1750 / 1762
页数:13
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