Numerical weather predictions provided by world meteorological organizations like ECMWF are unique sources of valuable information about the meteorological situation on a global scale. This paper introduces a technique to derive the spatial distribution of rainfall rate for a given area and time interval, in terms of complementary cumulative distribution function, PS(R), from the knowledge of the corresponding total rain amount, Mt, and of the ratio between convective and total rain amounts ß. The performance of the method is tested against a large database of radar derived rain field data, from which both the inputs to the algorithm and the associated output PS(R)s are obtained.

A technique to derive the spatial distribution of rain intensity from NWP data

CAPSONI, CARLO;LUINI, LORENZO
2009-01-01

Abstract

Numerical weather predictions provided by world meteorological organizations like ECMWF are unique sources of valuable information about the meteorological situation on a global scale. This paper introduces a technique to derive the spatial distribution of rainfall rate for a given area and time interval, in terms of complementary cumulative distribution function, PS(R), from the knowledge of the corresponding total rain amount, Mt, and of the ratio between convective and total rain amounts ß. The performance of the method is tested against a large database of radar derived rain field data, from which both the inputs to the algorithm and the associated output PS(R)s are obtained.
2009
Proceedings of the Geoscience and Remote Sensing Symposium, 2009
978-1-4244-3394-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/567559
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