我国台站季气温、降水的气候变化特征及其显著性检验
投稿时间:2020-02-20  修订日期:2020-03-01  点此下载全文
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作者单位E-mail
段明铿 南京信息工程大学 mingkeng@sina.com 
李欣 南京信息工程大学  
王盘兴 南京信息工程大学  
中文摘要:利用1951―2010年中国160站气温、降水资料,分析了冬季和夏季我国代表性台站气温、降水的气候值和气候变率在前后30年间变化的差异,并对结果使用不同方法进行了显著性检验。分析结果表明,季气温气候平均值的变化总体与全球增暖一致,以升温为主,但夏季在秦岭以南及长江中游地区有局部变冷的情况发生;季气温气候变率的变化相对较小,冬季的变化总体不显著,夏季也仅有少数台站变化显著。降水的气候变化总体不明显,季降水气候值的变化空间分布复杂,冬季南方地区、夏季东部地区总体增加,气候变率的变化均不显著。理论检验方法(t检验、F检验)与随机模拟方法(EMC法)对气温的显著性检验结果差别较小,对降水的差别较大,这与样本距平序列是否服从正态分布有关。EMC法可在确保样本统计特征不变的情况下,通过多次随机模拟,无需考虑其理论统计分布特征,使检验结果更为可靠。
中文关键词:气温,降水,气候变化,显著性检验,经验蒙特卡洛方法
 
Climate Change Characteristics of Seasonal Temperature and Precipitation of China Weather Stations and Their Significance Tests
Abstract:Based on the temperature and precipitation data of 160 stations in China from 1951 to 2010, the climate average and climate variability of temperature and precipitation at these representative stations of China in winter and summer are analyzed, as well as the differences between their changes in the former and later 30 years. Furthermore, the differences are tested by two different types of significance methods. The analysis results show that: for the temperature, the changes of the climate average of the seasonal temperature are generally consistent with global warming, but local cooling occurs in the south of the Qinling Mountains and the middle reaches of the Yangtze River in summer. The changes of the climate variability of the seasonal temperature are relatively small. The change in winter is not significant, and only a few stations have significant changes in summer. For the precipitation, generally the climate change of the seasonal total precipitation is not obvious. The spatial distribution of the seasonal precipitation climate value changes is complex, which increases in southern China in winter and eastern China in summer. The changes in climate variability are not significant in both seasons. For the difference between the theoretical test method (t-test, F-test) and the stochastic simulation method (EMC (empirical Monte Carlo) method), it is small for the temperature, relatively large for the precipitation, which is related to whether the sample anomaly series obeys the normal distribution. Under the condition that the statistical characteristics of the samples are unchanged, the EMC method can make the test results more reliable by multiple random simulations which is no need to consider the theoretical statistical distribution characteristics of the samples.
keywords:temperature  precipitation  climate change  significance test  empirical Monte Carlo method
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