Stochastic simulators can effectively generate the intrinsic variability of the rainfall process,which is an important issue in the analysis of the projections uncertainties. In this paper, a procedurefor stochastic modeling of precipitation at monthly scale is proposed. The model adopts variabletransformations, which are finalized to the deseasonalization and the Gaussianization of the monthlyrainfall process, and includes a procedure for testing the autocorrelation. The model was appliedto a homogeneous database of monthly rainfall values registered in 12 rain gauges in the region ofCalabria (Southern Italy). After the estimation of the model parameters, a set of 10^4 years of monthlyrainfall for each rain gauge was generated by means of a Monte Carlo technique. Then, dry andwet periods were analyzed through the application of the standardized precipitation index (SPI).Some results, confirmed through the application of the drought severity index (DSI), showed thatthe proposed model provided a good representation of the monthly rainfall for the considered raingauges. Moreover, the results of the SPI application indicate a greater probability of dry conditionsthan wet conditions, especially when long-term precipitation patterns are considered.

An Analysis of the Occurrence Probabilities of Wet and Dry Periods through a Stochastic Monthly Rainfall Model

SIRANGELO, BENIAMINO;FERRARI, Ennio
2016

Abstract

Stochastic simulators can effectively generate the intrinsic variability of the rainfall process,which is an important issue in the analysis of the projections uncertainties. In this paper, a procedurefor stochastic modeling of precipitation at monthly scale is proposed. The model adopts variabletransformations, which are finalized to the deseasonalization and the Gaussianization of the monthlyrainfall process, and includes a procedure for testing the autocorrelation. The model was appliedto a homogeneous database of monthly rainfall values registered in 12 rain gauges in the region ofCalabria (Southern Italy). After the estimation of the model parameters, a set of 10^4 years of monthlyrainfall for each rain gauge was generated by means of a Monte Carlo technique. Then, dry andwet periods were analyzed through the application of the standardized precipitation index (SPI).Some results, confirmed through the application of the drought severity index (DSI), showed thatthe proposed model provided a good representation of the monthly rainfall for the considered raingauges. Moreover, the results of the SPI application indicate a greater probability of dry conditionsthan wet conditions, especially when long-term precipitation patterns are considered.
monthly rainfall; stochastic model; dry and wet periods
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/135727
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 20
social impact