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极端气候对平均气候变化的非线性响应及其敏感性试验
引用本文:程炳岩,丁裕国,郑春雨,申红艳.极端气候对平均气候变化的非线性响应及其敏感性试验[J].气候与环境研究,2013,18(1):135-144.
作者姓名:程炳岩  丁裕国  郑春雨  申红艳
作者单位:1. 重庆市气候中心,重庆,401147
2. 南京信息工程大学大气科学学院、江苏省气象灾害国家重点实验室,南京,210044
3. 南京信息工程大学大气科学学院、江苏省气象灾害国家重点实验室,南京 210044;东北电力设计院环保处,长春 130021
4. 南京信息工程大学大气科学学院、江苏省气象灾害国家重点实验室,南京 210044;青海省气候中心,西宁 810000
基金项目:国家自然基金项目40875058,重庆市科委重点自然基金“三峡库区极端气候事件预估研究”项目
摘    要:平均气候与极端气候两者发生的概率具有密切联系.从理论和观测事实两方面证明一地平均气候与其极端气候的对应概率存在着明显的非线性关系.假定气候变量有对称概率分布和非对称概率分布两种状况,从理论上证明,平均气候变化前后所对应的极端气候概率具有非线性变化;通过对若干个代表站及气候场资料的平均值与所对应极值概率计算结果,证明理论符合观测事实.进一步借助于数值试验考察了概率分布模式的各个参数之变化对极端气候概率的影响.根据观测事实的举例,也表明了不同概率分布条件下,基本上都有如此变化规律.

关 键 词:平均气候  极端气候  概率及其分布模式  非线性关系
收稿时间:2009/11/19 0:00:00
修稿时间:1/6/2012 12:00:00 AM

Nonlinear Response and Sensitivity Test for Extreme Climate Relative to Average Climate
CHENG Bingyan,DING Yuguo,ZHENG Chunyu and SHEN Hongyan.Nonlinear Response and Sensitivity Test for Extreme Climate Relative to Average Climate[J].Climatic and Environmental Research,2013,18(1):135-144.
Authors:CHENG Bingyan  DING Yuguo  ZHENG Chunyu and SHEN Hongyan
Institution:Chonqing Climate Center, Chonqing 401147;National Key Laboratory of Meteorological Diseases of Jiangsu, Nanjing University of Information Science and Technology, Nanjing 210044;National Key Laboratory of Meteorological Diseases of Jiangsu, Nanjing University of Information Science and Technology, Nanjing 210044;Environment Protection and Engineering Division, Northeast Electric Power Design Institute,Changchun 130021;National Key Laboratory of Meteorological Diseases of Jiangsu, Nanjing University of Information Science and Technology, Nanjing 210044;Qinghai Provincial Climate Center, Xining 810000
Abstract:Proven theories and observations in specific regions have demonstrated that average climates often exhibit significant nonlinear relationships with extreme climates. Two different types of climate variables that show symmetric and asymmetric probability distributions correspond to nonlinear changes from average to extreme climates. In this paper, the data from several representative stations and relative climatic variable fields are used to prove that theoretical estimated probabilities for extreme climates are more consistent with actual values. Examples are used to demonstrate cases in which the various probability distributions are observed.
Keywords:Average climate  Extreme climate  Probability and its distribution pattern  Nonlinear relation
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