| 基于动态重现期的极端高温气候评估方法研究 |
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| 引用本文： | 涂锴,严中伟,范丽军,李珍.基于动态重现期的极端高温气候评估方法研究[J].气候变化研究进展,2023,19(1):11-22. |
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| 作者姓名： | 涂锴 严中伟 范丽军 李珍 |
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| 作者单位： | 中国科学院大气物理研究所东亚区域气候-环境重点实验室，北京 100029 |
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| 基金项目： | 中国科学院战略性先导科技专项“地球大数据科学工程”地球大数据支撑气候行动可持续发展目标研究(XDA1909012201);中国科学院战略性先导科技专项“地球大数据科学工程”一带一路极端气候和灾害星地观测(XDA19030402) |
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| 摘 要： | 利用全国754站逐日最高气温观测序列，在论证极端温度概率分布与非平稳性关系的基础上，构建和比较了多种非平稳广义极值模型，定义了极端高温的动态重现期和重现水平，提出了一种极端高温事件的新型评估思想和方法，并将其应用于极端气候变化研究。通过该方法可以更好地解释极端事件的真实极端性，有效地增强极端事件之间的可比性，从而保留更多历史极端气候事件的信息。动态重现期的变换运用可对当前极端事件发生的真实状态和趋势提出更准确评估。该方法的提出可有效澄清学术领域和公共舆论对于多年一遇极端事件的理解上长期混淆重现期的绝对值和概率性这一分歧和谬误。
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| 关 键 词： | 极端高温 动态重现期 广义极值分布 非平稳模型 |
| 收稿时间： | 2022-01-17 |
| 修稿时间： | 2022-04-18 |
Study of evaluation method on the climate of extreme high temperatures based on dynamic return periods |
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| TU Kai,YAN Zhong-Wei,FAN Li-Jun,LI Zhen.Study of evaluation method on the climate of extreme high temperatures based on dynamic return periods[J].Advances in Climate Change,2023,19(1):11-22. |
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| Authors: | TU Kai YAN Zhong-Wei FAN Li-Jun LI Zhen |
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| Institution: | Key Laboratory of Regional Climate and Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China |
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| Abstract: | For 754 homogenized daily maximum temperature series across rapid warming China during past 40 years, dynamic return periods and return levels were investigated based on various nonstationary Generalized Extreme Value (GEV) models, and new method of evaluation for high temperature extremes was proposed. By this method, the extremality of extreme climate events can be better explained. This method also enhances the comparability between climate extremes, thus more historical information can be well preserved. Transformed applications of dynamic return periods between stationary and nonstationary models can provide more accurate and reliable assessment about current state of climate extremes in climate change studies. Finally, some long-existing disagreements and mistakes in understanding “once-in-N-year” extreme events (i.e., as a value or a probability) between academic circles and public opinions are clarified effectively via the new method. |
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| Keywords: | Extreme high temperature Dynamic return periods Generalized Extreme Values (GEV) Nonstationary models |
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