基于区域气候模式CCLM的中国极端降水事件预估

doi:10.11849/zrzyxb.20160314

自然资源学报 ›› 2017, Vol. 32 ›› Issue (2): 266-277.doi: 10.11849/zrzyxb.20160314

基于区域气候模式CCLM的中国极端降水事件预估

景丞¹, 陶辉³, 王艳君¹, 苏布达^{1, 2, 3}, 黄金龙³, 姜彤^{1, 2*, *}

1. 南京信息工程大学气象灾害预报预警与评估协同中心/地理与遥感学院,南京 210044;
2. 中国气象局国家气候中心,北京 100081;
3. 中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室,乌鲁木齐 830011

收稿日期:2016-03-25 出版日期:2017-02-15 发布日期:2017-02-15
作者简介:景丞（1992- ）,男,江苏泰州人,硕士研究生,研究方向为气候变化影响评估与风险管理。Email:jingc1992@163.com *通信作者简介：姜彤（1962-）,男,博士,研究员,主要从事气候变化影响研究。E-mail: jiangtong@cma.gov.cn
基金资助:
全球变化国家重大科学研究计划项目（2013CB430205）; 新疆维吾尔自治区高层次引进人才项目（Y642091&Y644131）

Projection of Extreme Precipitation Events in ChinaBased on Regional Climate Model CCLM

JING Cheng¹, TAO Hui³, WANG Yan-jun¹, SU Bu-da^1,2,3, HUANG Jin-long³, JIANG Tong^1,2

1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science &Technology, Nanjing 210044, China;
2. National Climate Center, China Meteorological Administration, Beijing 100081, China;
3. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China

Received:2016-03-25 Online:2017-02-15 Published:2017-02-15
Supported by:
Major National Science Research Program, No. 2013CB430205; Xinjiang Uygur Autonomous Region High-level Talents Introduction Project, No. Y642091&Y644131. ]

摘要/Abstract

摘要： 选用中国气象局国家气候中心由逐日观测资料插值而成的格点化观测数据集,评估了区域气候模式COSMO-CLM（CCLM）对中国极端降水的模拟能力,并对2016—2050年中国极端降水事件进行预估。文中主要采用强度-面积-持续时间（Intensity-Area-Duration,IAD）方法,识别了既定时间尺度下具有一定强度和影响面积的极端降水事件,分析未来中国极端降水事件的特征和变化趋势,结果表明：1）区域气候模式CCLM对中国极端降水的空间分布和变化趋势均有较强的模拟能力;2）2016—2050年中国极端降水事件整体呈增加趋势,RCP 8.5情景下变化更为显著,事件强度更大;3）未来不同情景下,均有可能发生强度或影响面积超过基准期最大值的事件,其中影响面积大的事件多发生在华北和东北,强度大的事件多发生在西南和华南。

关键词: 气候变化, 极端降水事件, IAD方法, 区域气候模式, 预估

Abstract: A gridded observation data set interpolated with daily observation data by the National Climate Center is selected to evaluate the capability of a regional climate model COSMO-CLM（CCLM）for simulating extreme precipitation in China. The paper mainly applies the Intensity-Area-Duration (IAD) method to identify the extreme precipitation events with certain intensity in certain area at the given time scale, and project the trend of extreme precipitation events in the future (2016-2050) based on the CCLM output. The research results show that: 1) CCLM can well capture the distribution and trend of the extreme precipitation in China. 2) The extreme precipitation events in China will increase during 2016-2050. The increasing trend is more significant and the events are more intensive in RCP 8.5 scenario than in RCP 2.6 and RCP 4.5. 3) Extreme precipitation events beyond the maximum intensity/coverage of baseline period are likely to occur in all emission scenarios during 2016-2050. The events with larger area will mainly distribute in North China and Northeast China. The events with higher intensity will mainly distribute in Southwest China and South China.

Key words: climate change, extreme precipitation events, IAD method, regional climate model, projection

中图分类号:

P426.6

景丞, 陶辉, 王艳君, 苏布达, 黄金龙, 姜彤. 基于区域气候模式CCLM的中国极端降水事件预估[J]. 自然资源学报, 2017, 32(2): 266-277.

JING Cheng, TAO Hui, WANG Yan-jun, SU Bu-da, HUANG Jin-long, JIANG Tong, . Projection of Extreme Precipitation Events in ChinaBased on Regional Climate Model CCLM[J]. JOURNAL OF NATURAL RESOURCES, 2017, 32(2): 266-277.

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基于区域气候模式CCLM的中国极端降水事件预估

Projection of Extreme Precipitation Events in ChinaBased on Regional Climate Model CCLM

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