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DOI | 10.1002/joc.6339 |
Uncertainty of stationary and nonstationary models for rainfall frequency analysis | |
Ouarda, Taha B. M. J.; Charron, Christian; St-Hilaire, Andre | |
2019-10-30 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
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ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2019 |
文章类型 | Article;Early Access |
语种 | 英语 |
国家 | Canada |
英文摘要 | The development of nonstationary frequency analysis models is gaining popularity in the field of hydro-climatology. Such models account for nonstationarities related to climate change and climate variability but at the price of added complexity. It has been debated if such models are worth developing considering the increase in uncertainty inherent to more complex models. However, the uncertainty associated to nonstationary models is rarely studied. The objective of this article is to compare the uncertainties in stationary and nonstationary models based on objective criteria. The study is based on observed rainfall data in the United Arab Emirates (UAE) where strong nonstationarities were observed. In this study, a nonstationary frequency analysis introducing covariates into the distribution parameters was carried out for total and maximum annual rainfalls observed in the UAE. The generalized extreme value (GEV) distribution was used to model annual maximum rainfalls and the gamma (G) distribution was used to model total annual rainfalls. A number of nonstationary models, using time and climate indices as covariates, were developed and compared to classical stationary frequency analysis models. Two climate oscillation patterns having strong impacts on precipitation in the UAE were selected: the Oceanic Nino Index and the Northern Oscillation Index. Results indicate that the inclusion of a climate oscillation index generally improves the fit of the models to the observed data and the inclusion of two covariates generally provides the overall best fits. Uncertainties of estimated quantiles were assessed with confidence intervals (CIs) computed with the parametric bootstrap method. Results show that for the small sample sizes in this study, the width of the CIs can be very large for extreme nonexceedance probabilities and for the most extreme values of the climate index covariates. The weaknesses of nonstationary models revealed by the bootstrap uncertainties are discussed and words of caution are formulated. |
英文关键词 | arid-climate climate oscillation index nonstationary frequency analysis parametric bootstrap rainfall teleconnection uncertainty United Arab Emirates |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000493168700001 |
WOS关键词 | WIND-SPEED ; L-MOMENT ; PROBABILITY-DISTRIBUTION ; MONTHLY PRECIPITATION ; CLIMATE-CHANGE ; INTENSITY ; ENSO ; EXTREMES ; TELECONNECTIONS ; DISTRIBUTIONS |
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/187852 |
专题 | 气候变化 |
作者单位 | INRS ETE, Canada Res Chair Stat Hydroclimatol, 490 Couronne, Quebec City, PQ G1K 9A9, Canada |
推荐引用方式 GB/T 7714 | Ouarda, Taha B. M. J.,Charron, Christian,St-Hilaire, Andre. Uncertainty of stationary and nonstationary models for rainfall frequency analysis[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2019. |
APA | Ouarda, Taha B. M. J.,Charron, Christian,&St-Hilaire, Andre.(2019).Uncertainty of stationary and nonstationary models for rainfall frequency analysis.INTERNATIONAL JOURNAL OF CLIMATOLOGY. |
MLA | Ouarda, Taha B. M. J.,et al."Uncertainty of stationary and nonstationary models for rainfall frequency analysis".INTERNATIONAL JOURNAL OF CLIMATOLOGY (2019). |
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