| Cite this article: | 王怀军,曹蕾,俞嘉悦,等.基于EOF分析和GAMLSS模型的淮河流域极端气候事件非平稳特征[J].灌溉排水学报,0,():-. |
| Wang huaijun,Cao lei,YU jiayue,et al.基于EOF分析和GAMLSS模型的淮河流域极端气候事件非平稳特征[J].灌溉排水学报,0,():-. |
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| Non-stationary characteristics of extreme climate events in Huaihe River Basin based on EOF and GAMLSS model |
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Wang huaijun1, Cao lei2, YU jiayue2, Pan Yingping2, Feng Ru2, Yang Yaxue2, Ye Zhengwei2
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1.Wang Huaijun;2.Huaiyin Normal University
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| Abstract: |
| 【Objective】Global changes lead to non-stationarity in extreme climate event, which make a great challenge for consistency assumption in traditional frequency analysis of climate variables. The time coefficient of empirical orthogonal function method (EOF) is used as the analysis object of the generalized additive model (GAMLSS),which will reveal the non-stationary characteristics of extreme climate events at the baisn scale.【Method】This paper takes the Huaihe River Basin as an example, the EOF and GAMLSS was used to analyze the non-stationary characteristics of climate extremes. And covariates of the GAMLSS were time, climate indices and CO2 concentration. 【Result】 The first loading of EOF1 of climate extremes reflects the overall change of the river basin, and the first corresponding principal components (PC1) of precipitation extreme has no significant trend. The PC1 of temperature extremes showed a significant change, with the warm extremes first decreased and then increased. The cold extremes of cold night and frost days continued to decrease; The correlation coefficients between precipitation extremes and the influencing factors are relative low, indicated the stationary change for precipitation extremes. The temperature extremes were non-stationary change, which is significantly related to time and CO2 concentration, and the change of CO2 is the reason of non-stationary change of temperature extreme; The GAMLSS can simulate the stationary and non-stationary changes of the location and scale parameters of the climate extremes. The precipitation extremes is the stationary time series, and Lognormal is its best fitting distribution. Temperature extremes showed non-stationary changes, and CO2 concentration have a significant effect on GAMLSS model parameters; Quintile analysis showed that the precipitation extremes in the Huaihe River Basin showed stationary changes. The warm extremes divided by 1985, and decline first and then rise. For cold extremes, the number of cold nights and frost days showed a continuous downward trend. The non-stationary changes in temperature extremes have led to significant changes in the return level under different return periods. 【Conclusion】The GAMLSS can simulate the stationary and non-stationary changes of the location and scale parameters of the climate extremes. Combined with EOF, the GAMLSS can reduce the uncertainty of non-stationary analysis. |
| Key words: extreme extremes; EOF; GAMLSS; Huaihe River Basin |
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