http://www.cnr.it/ontology/cnr/individuo/prodotto/ID296695

Estimates of cumulative rainfall over a large area by weather radar (Contributo in atti di convegno)

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Estimates of cumulative rainfall over a large area by weather radar (Contributo in atti di convegno) (literal)

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Alessandro Mazza; Andrea Antonini; Samantha Melani; Alberto Ortolani (2014)
Estimates of cumulative rainfall over a large area by weather radar
in SPIE.REMOTE SENSING, Amsterdam, Netherlands, 22-25/09/2014
(literal)

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Remote Sensing of Clouds and the Atmosphere XIX; and Optics in Atmospheric Propagation and Adaptive Systems XVII (literal)

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Institute of Biometeorology - National Research Council, Via Gino Caproni 8, 50141 Florence Italy LAMMA Consortium, Via Madonna del Piano 10, 50019 Sesto Fiorentino (FI), Italy (literal)

Titolo

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Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer; Richard H. Picard; Karin Stein; John D. Gonglewski (literal)

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Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer; Richard H. Picard; Karin Stein; John D. Gonglewski (literal)

Abstract

In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky. (literal)

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