Frequency analysis of climate extreme events in Zanjan, Iran
Autor: | Saeed Jahanbaksh Asl, Fatemeh Sarafrouzeh, Ali Mohammad Khorshiddoust, Yagob Dinpashoh |
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Rok vydání: | 2013 |
Předmět: |
Return period
Frequency analysis Environmental Engineering Wind speed Shape parameter law.invention Generalized Pareto distribution law Statistics Generalized extreme value distribution Environmental Chemistry Precipitation Safety Risk Reliability and Quality General Environmental Science Water Science and Technology Mathematics Quantile |
Zdroj: | Stochastic Environmental Research and Risk Assessment. 27:1637-1650 |
ISSN: | 1436-3259 1436-3240 |
DOI: | 10.1007/s00477-013-0701-6 |
Popis: | In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model. |
Databáze: | OpenAIRE |
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