Downscaling of Satellite OPEMW Surface Rain Intensity Data

This paper presents a geostatistical downscaling procedure to improve the spatial resolution of precipitation data. The kriging method with external drift has been applied to surface rain intensity (SRI) data obtained through the Operative Precipitation Estimation at Microwave Frequencies (OPEMW), w...

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Bibliographic Details
Main Authors: Angela Cersosimo, Salvatore Larosa, Filomena Romano, Domenico Cimini, Francesco Di Paola, Donatello Gallucci, Sabrina Gentile, Edoardo Geraldi, Saverio Teodosio Nilo, Elisabetta Ricciardelli, Ermann Ripepi, Mariassunta Viggiano
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
MSG
Online Access:https://www.mdpi.com/2072-4292/10/11/1763
Description
Summary:This paper presents a geostatistical downscaling procedure to improve the spatial resolution of precipitation data. The kriging method with external drift has been applied to surface rain intensity (SRI) data obtained through the Operative Precipitation Estimation at Microwave Frequencies (OPEMW), which is an algorithm for rain rate retrieval based on Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations. SRI data have been downscaled from coarse initial resolution of AMSU-B/MHS radiometers to the fine resolution of Spinning Enhanced Visible and InfraRed Imager (SEVIRI) flying on board the Meteosat Second Generation (MSG) satellite. Orographic variables, such as slope, aspect and elevation, are used as auxiliary data in kriging with external drift, together with observations from Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager (MSG-SEVIRI) in the water vapor band (6.2 µm and 7.3 µm) and in thermal-infrared (10.8 µm and 8.7 µm). The validation is performed against measurements from a network of ground-based rain gauges in Southern Italy. It is shown that the approach provides higher accuracy with respect to ordinary kriging, given a choice of auxiliary variables that depends on precipitation type, here classified as convective or stratiform. Mean values of correlation (0.52), bias (0.91 mm/h) and root mean square error (2.38 mm/h) demonstrate an improvement by +13%, −37%, and −8%, respectively, for estimates derived by kriging with external drift with respect to the ordinary kriging.
ISSN:2072-4292