| Autor: |
WANG Huaijun, CAO Lei, YU Jiayue, LU Yuanyuan, FENG Ru, YANG Yaxue, YE Zhengwei, SUN Xiaohui |
| Jazyk: |
čínština |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Guan'gai paishui xuebao, Vol 40, Iss 5, Pp 125-134 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1672-3317 |
| DOI: |
10.13522/j.cnki.ggps.2020299 |
| Popis: |
【Objective】 Global climate change results in nonstationary extreme climate events which cannot be analyzed using traditional frequency analysis method. The objective of this paper is to test the feasibility of time coefficient of empirical orthogonal function method (EOF) and the generalized additive model (GAMLSS) to analyze non-stationary extreme climate events. 【Method】 We took data measured from the Huai river basin in 1965-2015 as an example, analyzing the nonstationary extreme climate events in it using the EOF and GAMLSS, with climate indices and atmospheric CO2 concentration taken as covariates. 【Result】 The first loading of EOF1 of the climate extremes reflects the change in extreme climate events in the basin. The first corresponding principal component (PC1) of the extreme precipitations did not show significant trend, but of the extreme temperature did with the warm extremes decreasing first followed by an increase from 1965—2015. The cold night extremes and the number of frost days had both been in decrease, and the correlation coefficient between extreme precipitations and their contributing factors was low. In contrast, extreme temperature was nonstationary and correlated to CO2 concentration at significant level, largely because the change in CO2 was nonstationary. The GAMLSS model can describe both stationary and nonstationary climate extremes. Overall, the temporal change in extreme precipitation was approximately stationary and can be described by a logistic distribution. The number of warm extremes had been in decline until 1985, but has seen an increase since then. The nonstationary change in extreme temperature led to a significant change in the period of return, with the 20-year return in the first principal component of warm days increasing from 40 d in 1965 to 60 d in 2015, while the 20-year return in the first principal component of the cold night decreasing from 90 d in 1965 to 25 d in 2015. 【Conclusion】 GAMLSS can describe both stationary and nonstationary climate extremes; combining it with EOF can reduce analysis uncertainty. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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