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
作者简介
肖旋,女,硕士研究生,研究方向:机器学习,人工智能,自然语言处理;杨新凯,男,博士,副教授,研究方向:普适计算,自然语言处理,计算机控制系统,计算机网络性能与优化。
