A stochastic space-time model for the generation of daily rainfall in the Gaza Strip

An important limitation of commonly used single‐site rainfall models is that they are not able to reflect spatial characteristics, while many impact studies demand the accommodation of spatial rainfall correlations. As a result, a number of stochastic models have been developed to produce precipitat...

Full description

Saved in:
Bibliographic Details
Published in:International journal of climatology 2012-06, Vol.32 (7), p.1098-1112
Main Authors: Mhanna, Muamaraldin, Bauwens, Willy
Format: Article
Language:English
Subjects:
daily rainfall
Earth, ocean, space
Exact sciences and technology
External geophysics
Gaza Strip
Markov chain
Meteorology
multisite rainfall model
precipitation
stochastic process
Wilks approach
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An important limitation of commonly used single‐site rainfall models is that they are not able to reflect spatial characteristics, while many impact studies demand the accommodation of spatial rainfall correlations. As a result, a number of stochastic models have been developed to produce precipitation simultaneously at multiple sites. One of these models is the Wilks approach [1998. Journal of Hydrology 210: 178–191], which was the first method that sufficiently reproduces the main statistics of rainfall at a number of sites. So far, however, the literature does not provide many details about the ‘step by step’ procedure proposed by Wilks. In this paper, the Wilks approach is demonstrated for multi‐site, daily rainfall occurrences and amounts in the Gaza Strip. The paper demonstrates a complete methodology taking into account the original Wilks approach and suggests solutions for enhancing the model. The first improvement concerns an analytical calculation of the desired correlations in the random numbers that reproduce the observed correlations between the rainfall occurrence series, through a gamma coefficient. Secondly, the correlations between the rainfall amount series are specified using a rank correlation and then linearly transformed into product‐moment correlations to obtain the required correlations in the random numbers. Statistical analyses on the historical and generated rainfall series confirm that the model generally performs well, as it preserves all major characteristics of daily rainfall, as well as spatial characteristics. Major advantages of this model include its simplicity, its increased efficiency, a significant improvement in computational speed and a considerable gain in the effort for the implementation. Copyright © 2011 Royal Meteorological Society
ISSN:0899-8418
1097-0088
DOI:10.1002/joc.2305