Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.5867 |
Non-stationary peaks-over-threshold analysis of extreme precipitation events in Finland, 1961-2016 | |
Pedretti, Daniele1; Irannezhad, Masoud2,3 | |
2019-02-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2019 |
卷号 | 39期号:2页码:1128-1143 |
文章类型 | Article |
语种 | 英语 |
国家 | Finland; Peoples R China |
英文摘要 | There is an urgent need to understand and predict how extreme precipitation events (EPEs) will change at high latitudes, both for local climate change adaptation plans and risk mitigation and as a potential proxy anticipating the impact of climate change elsewhere in the world. This paper illustrates that a combination of non-stationary modelling approaches can be adopted to evaluate trends in EPEs under uncertainty. A large database of daily rainfall events from 281 sparsely distributed weather stations in Finland between 1961 and 2016 was analysed. Among the tested methods, Poisson distributions provided a powerful method to evaluate the impacts of multiple physical covariates, including temperature and atmospheric circulation patterns (ACPs), on the resulting trends. The analysis demonstrates that non-stationarity is statistically valid for the majority of observations, independently of their location in the country and the season of the year. However, subsampling can severely hinder the statistical validity of the trends, which can be easily confused with random noise and therefore complicate the decision-making processes regarding long-term planning. Scaling effects have a strong impact on the estimates of non-stationary parameters, as homogenizing the data in space and time reduces the statistical validity of the trends. Trends in EPE statistics (mean, 90 and 99% percentiles) and best-fitted Generalized Pareto parameters in the tails of the distributions appear to be stronger when approaching the Polar region (Lapland) than away from it, consistent with the Arctic amplification of climate change. ACPs are key covariates in physically explaining these trends. In particular, the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) can explain statistically significant increases in extreme precipitation in Lapland, Bothnian and South regions of Finland, particularly during summer and fall seasons. |
英文关键词 | climate change extreme precipitation extreme value analysis Generalized Pareto non-stationarity Poisson distribution |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000459665000036 |
WOS关键词 | ATMOSPHERIC CIRCULATION PATTERNS ; CLIMATE-CHANGE PROJECTIONS ; FREQUENCY-ANALYSIS ; TRENDS ; STATIONARITY ; TEMPERATURE ; DISTRIBUTIONS ; VARIABILITY ; STATISTICS ; RAINFALL |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/37099 |
专题 | 气候变化 |
作者单位 | 1.Geol Survey Finland GTK, PO 96, Espoo, Finland; 2.Southern Univ Sci & Technol SUSTech, Sch Environm Sci & Engn, Shenzhen, Peoples R China; 3.Univ Oulu, Water Resources & Environm Engn Res Unit, Oulu, Finland |
推荐引用方式 GB/T 7714 | Pedretti, Daniele,Irannezhad, Masoud. Non-stationary peaks-over-threshold analysis of extreme precipitation events in Finland, 1961-2016[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2019,39(2):1128-1143. |
APA | Pedretti, Daniele,&Irannezhad, Masoud.(2019).Non-stationary peaks-over-threshold analysis of extreme precipitation events in Finland, 1961-2016.INTERNATIONAL JOURNAL OF CLIMATOLOGY,39(2),1128-1143. |
MLA | Pedretti, Daniele,et al."Non-stationary peaks-over-threshold analysis of extreme precipitation events in Finland, 1961-2016".INTERNATIONAL JOURNAL OF CLIMATOLOGY 39.2(2019):1128-1143. |
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