摘要
以夏季高温有效积温的多年平均值作为判断夏季高温炎热程度的标准,借助CART算法探究东亚夏季风指数,夏季印缅槽,夏季北大西洋涛动(NAO),赤道太平洋海温等多项气候因子与高温的关系,得到高温预测规则集,建立高温的预测模型。研究中选取1955—2012年福建漳州夏季的日最高气温等站点气温资料,通过计算58 a的夏季高温有效积温数值来判定夏季的炎热程度。将同一时期的多项气候因子数据作为输入变量输入,算法会随机选出其中46 a的数据得到10条分类规则集,建立的预测模型准确率达到91. 49%。用剩下的12 a数据进行检验,准确率达到91. 67%。研究结果较好地验证了高温预测模型的可行性和有效性,为灾害性天气模型的研究提供了新思路。
The average value of effective accumulated high temperature in summer for many years was considered as a standard to judge the extent of a hot summer. The CART algorithm was employed to explore the relationship between the high temperature and the climatic factors such as East Asian summer monsoon index, summer India-Myanmar trough, summer North Atlantic Oscillation( NAO) and equatorial Pacific sea temperature,and the high-temperature prediction rule set was obtained to build a high-temperature prediction model. The study selected the daily maximum temperature data in summer among 1955—2012 in Zhangzhou of Fujian Province. The extent of a hot summer was determined through the effective accumulated temperature of high temperature in summer for 58 years. A number of climatic factors in the same period were input as the input variables,and 46 a data were randomly selected to get10 classification rule sets. The accuracy of the built predication model reached 91.49%. The remaining12 a data were used for test,with an accuracy up to 91.67%. Generally speaking,the results of this paper have verified the feasibility and validity of the high temperature prediction model,which provides a newidea for the research of the catastrophic weather model.
作者
官雨洁
王伟
刘寿东
GUAN Yujie;WANG Wei;LIU Shoudong(Key Laboratory of Meteorological Disaster,Ministry of Education/International Joint Laboratory on Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Yale-NUIST Center on Atmospheric Environment,Nanjing University of Information Science & Technology,Nanjing 210044,China;School of Atmospheric Sciences,Nanjing University of Information Science & Technology,Nanjing 210044,China)
出处
《气象科学》
北大核心
2018年第4期539-544,共6页
Journal of the Meteorological Sciences
基金
教育部长江学者和创新团队发展计划项目(PCSIRT)
江苏高校优势学科建设工程项目(PAPD)
关键词
CART
高温有效积温
夏季高温
预测模型
CART
High temperature effective accumulated temperature
Summer high temperature
Prediction model