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 Ã. 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 Ã. 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.File | Dimensione | Formato | |
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