Combining Satellite Infrared and Lightning Information to Estimate Warm‐Season Convective and Stratiform RainfallSource: Journal of Applied Meteorology and Climatology:;2013:;volume( 053 ):;issue: 001::page 180DOI: 10.1175/JAMC-D-13-069.1Publisher: American Meteorological Society
Abstract: his paper describes and evaluates a satellite rainfall estimation technique that combines infrared and lightning information to estimate precipitation in deep convective systems. The algorithm is developed and tested using seven years (2002?08) of TRMM measurements over the southern United States during the warm season. Lightning information is coupled with a modified IR-based convective?stratiform technique (CST) and produces a lightning-enhanced CST (CSTL). Both the CST and CSTL are then applied to the training (2002?04) and independent (2005?08) datasets. In general, this study shows significant improvement over the IR rainfall estimates (rain area, intensity, and volume) by adding lightning information. The CST and CSTL display critical skill in estimating warm?season precipitation and the performance is very stable. The CST can generally identify the heavy (convective) and light rain regions, while CSTL further identifies convective areas that are missed by CST and removes convective cores that are incorrectly defined by CST. Specifically, the CSTL improves the convective cell detection by 5% and reduces the convective false alarm rate by more than 30%. Similarly, CSTL substantially improves the CST in the overall estimate of instantaneous rainfall rates. For example, when compared with passive microwave estimates, CSTL increases the correlation coefficient by 30%, reduces the bias by 50%, and reduces RMSE by 25%. Both CST and CSTL reproduce the rain area and volume fairly accurately over a region, although both techniques show some degree of overestimation relative to radar estimates.
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contributor author | Xu, Weixin | |
contributor author | Adler, Robert F. | |
contributor author | Wang, Nai-Yu | |
date accessioned | 2017-06-09T16:50:08Z | |
date available | 2017-06-09T16:50:08Z | |
date copyright | 2014/01/01 | |
date issued | 2013 | |
identifier issn | 1558-8424 | |
identifier other | ams-75001.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4217287 | |
description abstract | his paper describes and evaluates a satellite rainfall estimation technique that combines infrared and lightning information to estimate precipitation in deep convective systems. The algorithm is developed and tested using seven years (2002?08) of TRMM measurements over the southern United States during the warm season. Lightning information is coupled with a modified IR-based convective?stratiform technique (CST) and produces a lightning-enhanced CST (CSTL). Both the CST and CSTL are then applied to the training (2002?04) and independent (2005?08) datasets. In general, this study shows significant improvement over the IR rainfall estimates (rain area, intensity, and volume) by adding lightning information. The CST and CSTL display critical skill in estimating warm?season precipitation and the performance is very stable. The CST can generally identify the heavy (convective) and light rain regions, while CSTL further identifies convective areas that are missed by CST and removes convective cores that are incorrectly defined by CST. Specifically, the CSTL improves the convective cell detection by 5% and reduces the convective false alarm rate by more than 30%. Similarly, CSTL substantially improves the CST in the overall estimate of instantaneous rainfall rates. For example, when compared with passive microwave estimates, CSTL increases the correlation coefficient by 30%, reduces the bias by 50%, and reduces RMSE by 25%. Both CST and CSTL reproduce the rain area and volume fairly accurately over a region, although both techniques show some degree of overestimation relative to radar estimates. | |
publisher | American Meteorological Society | |
title | Combining Satellite Infrared and Lightning Information to Estimate Warm‐Season Convective and Stratiform Rainfall | |
type | Journal Paper | |
journal volume | 53 | |
journal issue | 1 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAMC-D-13-069.1 | |
journal fristpage | 180 | |
journal lastpage | 199 | |
tree | Journal of Applied Meteorology and Climatology:;2013:;volume( 053 ):;issue: 001 | |
contenttype | Fulltext |