2011•Desert and Oasis MeteorologyRequires access

The Application of Gumbel-Logistic Model to Simulate the Regional Rainstorm

Ding Yu-guo

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Abstract

Based on the observed daily rainfall data during 1951-2007 over Yangtze-Huaihe area,this study proposes the use of Gumbel logistic model to analyze the joint distribution of regional annual maximum storm peaks and the corresponding storm station number which are mutually correlated.In this paper,the moment method was used to estimate the distributed parameters.On the basis of the marginal distributions of these random variables and the conditional probability,the associated return periods can be readily deduced.Results show that the model is suitable for representing the joint distribution of correlated storm peaks and station number that are Gumbel distributed.

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What this paper is about

Based on the observed daily rainfall data during 1951-2007 over Yangtze-Huaihe area,this study proposes the use of Gumbel logistic model to analyze the joint distribution of regional annual maximum storm peaks and the corresponding storm station number which are mutually correlated.In this paper,the moment method was used to estimate the distributed parameters.On the basis of the marginal distributions of these random variables and the conditional probability,the associated return periods can be readily deduced.Results show that the model is suitable for representing the joint distribution of correlated storm peaks and station number that are Gumbel distributed.

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Available abstract

Based on the observed daily rainfall data during 1951-2007 over Yangtze-Huaihe area,this study proposes the use of Gumbel logistic model to analyze the joint distribution of regional annual maximum storm peaks and the corresponding storm station number which are mutually correlated.In this paper,the moment method was used to estimate the distributed parameters.On the basis of the marginal distributions of these random variables and the conditional probability,the associated return periods can be readily deduced.Results show that the model is suitable for representing the joint distribution of correlated storm peaks and station number that are Gumbel distributed.

Key concepts: Gumbel distribution, Storm, Marginal distribution, Joint probability distribution, Environmental science, Meteorology, Moment (physics), Yangtze river

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