Conversion models, originally devised to turn yearly rainfall statistics from long (e. g. 30 or 60 min) to short integration time T (i.e. 1 min), are assessed for their ability to also predict monthly 1-min integrated statistics, P(R)(1)(m), knowledge of which may be beneficial for specific services (e. g. reconfigurable systems) and for the definition of a reliable approach to estimate monthly (hence worst month) rain attenuation statistics. Tests, performed for 5 <= T <= 60 min against monthly rain-gauge-derived rainfall data collected in some sites worldwide, indicate that the EXponential CELL rainfall statistics conversion (EXCELL RSC) and Lavergnat-Gole models, in force of their physical soundness, provide a good performance when used to predict 1-min integrated rainfall statistics both on yearly and on monthly bases.

Prediction of monthly rainfall statistics from data with long integration time

LUINI, LORENZO;CAPSONI, CARLO
2013-01-01

Abstract

Conversion models, originally devised to turn yearly rainfall statistics from long (e. g. 30 or 60 min) to short integration time T (i.e. 1 min), are assessed for their ability to also predict monthly 1-min integrated statistics, P(R)(1)(m), knowledge of which may be beneficial for specific services (e. g. reconfigurable systems) and for the definition of a reliable approach to estimate monthly (hence worst month) rain attenuation statistics. Tests, performed for 5 <= T <= 60 min against monthly rain-gauge-derived rainfall data collected in some sites worldwide, indicate that the EXponential CELL rainfall statistics conversion (EXCELL RSC) and Lavergnat-Gole models, in force of their physical soundness, provide a good performance when used to predict 1-min integrated rainfall statistics both on yearly and on monthly bases.
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/755629
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