globalchange  > 气候变化与战略
CSCD记录号: CSCD:5887560
论文题名:
冬季极端低温日数预测方法研究
其他题名: Prediction of Extreme Winter Cold Days
作者: 单机坤1; 梁潇云2; 孙林海2; 龚振淞2; 刘芸芸2
刊名: 高原气象
ISSN: 1000-0534
出版年: 2016
卷: 35, 期:6, 页码:213-218
语种: 中文
中文关键词: 全球海气耦合模式 ; 逐步回归 ; 统计降尺度 ; 冬季极端低温日数
英文关键词: Atmosphere-ocean coupled model ; Stepwise regression ; Statistical downscaling model ; Extreme winter cold days
WOS学科分类: METEOROLOGY ATMOSPHERIC SCIENCES
WOS研究方向: Meteorology & Atmospheric Sciences
中文摘要: 随着全球变暖极端事件越来越频繁,开展极端事件预测变得非常重要。基于我国700多个地面台站的逐日最低温度观测资料和国家气候中心第一代海气耦合模式的动力预测结果数据,采用逐步回归的统计降尺度方法,建立了一个针对我国冬季极端低温日数的动力-统计降尺度预测方法。结果表明,该预测方法所预测的1983-2010年历史回报结果与实况资料的相关在我国大部均超过了95%的显著性水平。用该预测方法还对2011 /2012年冬季极端低温日数进行了实时预测,事实证明该预测方法对2011 /2012年冬季极端低温日数的预测趋势基本正确,可以推广到预测业务中应用。
英文摘要: Extreme events become more and more frequent under the global warming. It is very important to provide an extreme events prediction. Based on daily minimum temperature data for more than 700 observation stations over China and 1983-2010 winter hindcasts of the first generation atmospheric-ocean coupled model in Beijing Climate Center,a new prediction of extreme winter cold days(EWCD) over China is developed by using the stepwise regression statistical downscaling model(SRSDM). Results show that the correlation coefficient of EWCD between predictions using SRSDM and observations for 1983-2010 years exceed the 95% significant level in most of China. Moreover,inter-annual variability of EWCD predicted by SRSDM is well agreed with observations during 1983-2010. The realtime prediction of EWCD in 2011 /2012 using the SRSDM was carried out. It is very well that the prediction is successfully and the prediction of EWCD by SRSDM in 2011 /2012 is basically in accordance with the observation. Above all proved the method to predict EWCD over China by SRSDM can be employed in operational application.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/150891
Appears in Collections:气候变化与战略

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作者单位: 1.南京信息工程大学大气科学学院, 南京, 江苏 210044, 中国
2.中国气象局国家气候中心, 北京 100081, 中国

Recommended Citation:
单机坤,梁潇云,孙林海,等. 冬季极端低温日数预测方法研究[J]. 高原气象,2016-01-01,35(6):213-218
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