A Unified Model for the Prediction of Spatial and Temporal Rainfall Rate Statistics

This paper presents MORSE (MOdel for Rainfall Statistics Estimation), a unified model for the prediction of spatial (P<sub>S</sub>(R)) and temporal (P<sub>T</sub>(R)) high-resolution rainfall rate statistics. Inputs to MORSE are the convective (M<sub>c</sub>) and total (Mt) rain amounts cumulated in different time intervals, ranging from a few hours for the prediction of P<sub>S</sub>(R) to much longer intervals for the estimation of P<sub>T</sub>(R). Tests performed against P<sub>T</sub>(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 P<sub>S</sub>(R) on hourly basis and of P<sub>T</sub>(R) at any time scale (e.g., monthly, seasonal, yearly).

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