Using cloud water path and cloud top temperature for estimating convective and stratiform rainfall from SEVIRI daytime data

被引:0
作者
Mourad Lazri
Soltane Ameur
机构
[1] University of Mouloud MAMMERI,Laboratoire LAMPA
来源
Arabian Journal of Geosciences | 2016年 / 9卷
关键词
Rainfall; Cloud water path; Cloud top temperature; SEVIRI; Radar;
D O I
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中图分类号
学科分类号
摘要
A satellite rainfall retrieval technique is proposed here. The relationships of rain rate with each of cloud water path (CWP) and cloud top temperature (CTT) are investigated. The CWP and CTT are retrieved from SEVIRI data (spinning enhanced visible and infrared imager), and corresponding rain rates are measured by weather radar. The rain rates are compared to corresponding CWP and then to corresponding CTT. The investigation demonstrates an exponential functional dependency between rain rates and CWP for low and moderate rain rates (stratiform rainfall). Conversely, the rain rates are more closely related to CTT for high rain rates (convective rainfall). Therefore, two separate relationships are established for rain rate retrievals. The results show rain rates estimated by the developed scheme are in good correlation with those observed by weather radar.
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[1]  
Adler RF(1988)A satellite infrared technique to estimate tropical convective and stratiform rainfall J Appl Meteorol 27 30-51
[2]  
Negri AJ(2002)Precipitation measurement by satellites: towards community algorithms Adv Space Res 183 371-391
[3]  
Barrett EC(1987)The adding method for multiple scattering calculations of polarized light Astron Astrophys 158 50-65
[4]  
De Haan JF(2015)Comparison and evaluation of high resolution precipitation estimation products in Urmia Basin-Iran Atmos Res 32 2353-2376
[5]  
Bosma P(2011)An intercomparison of 10-day satellite precipitation products duringWest African monsoon Int J Remote Sens 112 D01202-1495
[6]  
Hovenier JW(2007)Comparison of microwave and optical cloud water path estimates from TMI, MODIS, and MISR J Geophys Res 49 1477-143
[7]  
Ghajarnia N(2010)Rainfall rate assignment using MSG SEVIRI data—a promising approach to spaceborne rainfall rate retrieval for midlatitudes J Appl Meteorol Climatol 141 129-50
[8]  
Liaghat A(2014)Improving the accuracy of rainfall rates from optical satellite sensors with machine learning—a random forests-based approach applied to MSG SEVIRI Remote Sens Environ 147 38-1226
[9]  
Arasteh PD(2013)Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG J Adv Space Res 42 1218-1233
[10]  
Jobard I(2013)Identification of raining clouds using a method based on optical and microphysical cloud properties from meteosat second generation daytime and nighttime data Appl Water Sci 42 1227-372