This paper presents MORSE (MOdel for Rainfall Statistics Estimation), a unified model for the prediction of spatial (PS(R)) and temporal (PT(R)) high-resolution rainfall rate statistics. Inputs to MORSE are the convective (Mc) and total (Mt) rain amounts cumulated in different time intervals, ranging from a few hours for the prediction of PS(R) to much longer intervals for the estimation of PT(R). Tests performed against PT(R)s on yearly (curves included in the DBSG3 database) and monthly (distributions derived from rain rate time series) basis provide very satisfactory results, which makes MORSE a reliable global model for the prediction of PS(R) on hourly basis and of PT(R) at any time scale (e.g. monthly, seasonal, yearly).
A Unified Model for the Prediction of Spatial and Temporal Rainfall Rate Statistics
LUINI, LORENZO;CAPSONI, CARLO
2013-01-01
Abstract
This paper presents MORSE (MOdel for Rainfall Statistics Estimation), a unified model for the prediction of spatial (PS(R)) and temporal (PT(R)) high-resolution rainfall rate statistics. Inputs to MORSE are the convective (Mc) and total (Mt) rain amounts cumulated in different time intervals, ranging from a few hours for the prediction of PS(R) to much longer intervals for the estimation of PT(R). Tests performed against PT(R)s on yearly (curves included in the DBSG3 database) and monthly (distributions derived from rain rate time series) basis provide very satisfactory results, which makes MORSE a reliable global model for the prediction of PS(R) on hourly basis and of PT(R) at any time scale (e.g. monthly, seasonal, yearly).| File | Dimensione | Formato | |
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MORSE_PR_prediction.pdf
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