Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices

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Main Author: M. Manso
Format: Artículo científico
Language:en
Published: Universidad Nacional Autónoma de México 2006
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author M. Manso
author_facet M. Manso
contents Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices M. Manso A. Luque I. Gómez Biología CRR radar rainsat meteosat calibration matrices The CRR (Convective Rainfall Rate) algorithm was developed to detect intense mesoscale convective cellsand to screen the most probable precipitation associated. It estimates rainfall intensity using the three bandsof the Meteosat-7 and matrices calibrated with earth-based radars. Calibration matrices were performed following an accurate version of the Rainsat techniques but combining the infrared bands to detect convectiveclouds. Matrices were developed, up for the North of Europe, over the Baltic countries, with data from theradar of the Baltex Project provided by the SMHI (Swedish Meteorological and Hydrological Institute) andfor the South of Europe, over the Iberian Peninsula, with radar data as provided by the INM (SpanishMeteorological Institute). In the present research, the CRR calibration methodology is validated, an analysisof calibration matrices differences in both areas over Europe is detailed and CRR resulting images are verifiedin a qualitative manner using rainfall radar images as ground true. 2006 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56519301 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.3 Vol.19
format Artículo científico
id redalyc_56519301
institution Redalyc
language en
publishDate 2006
publisher Universidad Nacional Autónoma de México
spellingShingle Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices
M. Manso
Biología
CRR
radar
rainsat
meteosat
calibration matrices
Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices M. Manso A. Luque I. Gómez Biología CRR radar rainsat meteosat calibration matrices The CRR (Convective Rainfall Rate) algorithm was developed to detect intense mesoscale convective cellsand to screen the most probable precipitation associated. It estimates rainfall intensity using the three bandsof the Meteosat-7 and matrices calibrated with earth-based radars. Calibration matrices were performed following an accurate version of the Rainsat techniques but combining the infrared bands to detect convectiveclouds. Matrices were developed, up for the North of Europe, over the Baltic countries, with data from theradar of the Baltex Project provided by the SMHI (Swedish Meteorological and Hydrological Institute) andfor the South of Europe, over the Iberian Peninsula, with radar data as provided by the INM (SpanishMeteorological Institute). In the present research, the CRR calibration methodology is validated, an analysisof calibration matrices differences in both areas over Europe is detailed and CRR resulting images are verifiedin a qualitative manner using rainfall radar images as ground true. 2006 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56519301 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.3 Vol.19
title Convective rainfall rate multi-channel algorithm for Meteosat-7 and radar derived calibration matrices
topic Biología
CRR
radar
rainsat
meteosat
calibration matrices
url https://www.redalyc.org/articulo.oa?id=56519301