A stochastic disaggregation model, based on coupling of the modified version of the Bartlett-Lewis Rectangular Pulse stochastic rainfall model and proportional adjusting procedure, is shown to disaggregate daily observed precipitation to hourly scale. Furthermore synthetic hourly time series are generated.This model requires the identification of a set of parameters that allow to reproduce, as well as possible, the statistical properties of the observed precipitation. The identification is formulated as a global optimization problem. A comparison between observed and modeled statistics of the precipitation time series is presented for the weather station of San Martino Valle Caudina (Southern Italy).
Stochastic models for the disaggregation of precipitation time series on sub-daily scale: identification of parameters by global optimization
DI SERAFINO, Daniela;
2015
Abstract
A stochastic disaggregation model, based on coupling of the modified version of the Bartlett-Lewis Rectangular Pulse stochastic rainfall model and proportional adjusting procedure, is shown to disaggregate daily observed precipitation to hourly scale. Furthermore synthetic hourly time series are generated.This model requires the identification of a set of parameters that allow to reproduce, as well as possible, the statistical properties of the observed precipitation. The identification is formulated as a global optimization problem. A comparison between observed and modeled statistics of the precipitation time series is presented for the weather station of San Martino Valle Caudina (Southern Italy).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
