| 不同气候背景下我国冬夏两季极端气温特征分析 |
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| 引用本文： | 任晨辰,段明铿,智协飞.不同气候背景下我国冬夏两季极端气温特征分析[J].大气科学学报,2017,40(6):803-813. |
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| 作者姓名： | 任晨辰 段明铿 智协飞 |
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| 作者单位： | 南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/东亚季风与区域气候变化科技创新团队, 江苏 南京 210044;南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/东亚季风与区域气候变化科技创新团队, 江苏 南京 210044;南京信息工程大学 气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/东亚季风与区域气候变化科技创新团队, 江苏 南京 210044;南京大气科学联合研究中心, 江苏 南京 210008 |
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| 基金项目： | 国家重点研发计划项目（2016YFA0600703）；北极阁开放研究基金南京大气科学联合研究中心重点项目（NJCAR2016ZD04）；国家自然科学基金资助项目（91437218；41575104）；江苏高校优势学科建设工程资助项目（PAPD） |
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| 摘 要： | 利用全国175个测站1960—1999年间的日平均气温资料,分别选取1960—1989年(气候态A)、1970—1999年(气候态B)作为气候背景,采用蒙特卡洛显著性检验法检验了这两个气候态背景下我国冬夏两季季节平均气温的差异显著性。并在此基础上利用气候百分位法分别分析了在这两个气候态背景下2000—2010年间我国冬夏两季的极端气温特征。分析结果表明,相对于夏季,冬季气候态A、B背景下季节平均气温的差异更为显著。冬夏两季,我国大部分地区极端低温事件的发生频率相对较低,而极端高温事件的发生频率相对较高。由于气候态B包含了全球变暖特征最为显著的20a,故在气候态B背景下,冬夏两季极端低(高)温事件的发生频率要高(低)于气候态A,这与全球变暖的趋势相吻合。
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| 关 键 词： | 极端温度 气候百分位法 蒙特卡洛显著性检验法 气候态 |
| 收稿时间： | 2016/3/2 0:00:00 |
| 修稿时间： | 2016/11/2 0:00:00 |
Characteristics of extreme surface air temperature in winter and summer over China under different climate backgrounds |
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| REN Chenchen,DUAN Mingkeng and ZHI Xiefei.Characteristics of extreme surface air temperature in winter and summer over China under different climate backgrounds[J].大气科学学报,2017,40(6):803-813. |
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| Authors: | REN Chenchen DUAN Mingkeng and ZHI Xiefei |
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| Institution: | Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD)/East Asia Monsoon and Regional Climate Change Research Team, Nanjing University of information Science & Technology Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD)/East Asia Monsoon and Regional Climate Change Research Team, Nanjing University of information Science & Technology Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster(CIC-FEMD)/East Asia Monsoon and Regional Climate Change Research Team, Nanjing University of information Science & Technology Nanjing 210044, China;Nanjing Joint Center for Atmospheric Research(NJCAR), Nanjing 210008, China |
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| Abstract: | Based on the daily mean temperature data of 1960-1999 at 175 meteorological stations over China,this paper firstly analyzes the characteristics of the two climate backgrounds(Climate background A contained the years from 1960 to 1989,while the climate background B contained the years from 1970 to 1999).Monte Carlo significance test method is applied to examine the difference in winter and summer under the two climate backgrounds.Respectively based on the two different climate backgrounds,the study applies climate percentile method to analyze the variation characteristic of the extreme temperature over China from 2000 to 2010.The result showed that the difference of winter average temperature under the two climate backgrounds is more significant than the difference in summer.The extreme low temperature events in winter(summer) happen less frequently than extreme high temperature events in winter(summer) over China.Because the climate background B contained the years from 1980 to 2000 and the global warming was most serious during this period,when we use climate background B as the background during 2000-2010,the extreme low temperature events in winter(summer) happen more frequently than using climate background A as the background.The situation of extreme high temperature in winter(summer) is contrary to the situation of extreme low temperature events in winter(summer) from 2000 to 2010.These results are consistent with the trends of global warming. |
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| Keywords: | extreme temperature climate percentile method Monte Carlo significance test climate background |
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