期刊文献+

基于ARIMA-小波分析的加拿大气温时空变化趋势研究 被引量:3

Research on the Temporal and Spatial Trend of Canadian Temperature Based on ARIMA and Wavelet Analysis
下载PDF
导出
摘要 为探究全球气候变化的趋势,主要采用ARIMA时间序列分析和小波分析等方法解决问题,构建了ARIMA等模型,选取加拿大1940年~2010年403个气象站点的数据,运用ArcGIS、Python、Matlab等软件进行求解。研究得出:从时间分布上,整体的气温趋势是略下降再上升;从空间温度变化,无论内陆还是沿海,全球温度均有上升趋势;以及海洋表面温度也呈现出变暖的趋势。 In order to explore the trend of global climate change,ARIMA time series analysis and wavelet analysis are mainly used to solve problems.ARIMA and other models are constructed.The data of 403 meteorological stations in Canada from 1940 to 2010 are selected,and software such as ArcGIS,Python,and Matlab are used to solve and research.The study finds that from the perspective of time distribution,the overall temperature trend dropped slightly and then is rising.From the spatial temperature changes,whether inland or coastal,global temperatures have an upward trend.And the surface temperature of the ocean also shows a warming trend.
作者 肖旋 杨新凯 XIAO Xuan;YANG Xinkai(College of Information,Mechanical and Electrical Engineering,Shanghai Normal University,Shanghai 201418)
出处 《计算机与数字工程》 2022年第6期1183-1189,共7页 Computer & Digital Engineering
关键词 全球变暖 极端天气 小波分析 时间序列预测 global warming extreme weather wavelet analysis time series prediction
  • 相关文献

参考文献4

二级参考文献21

共引文献17

同被引文献29

引证文献3

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部