编号
zgly0001583948
文献类型
期刊论文
文献题名
通过数据挖掘调查气候变化的长期趋势及其因区域和地方环境而产生的空间差异(英文)
作者单位
InstituteforGeospatialResearchandEducation
EasternMichiganUniversity
GuangzhouInstituteofGeography
DepartmentofComputerScience
IndianaUniversity
DepartmentofComputerScience
NewYorkUniversity
CenterforAdvancedSpatialAnalysis
Univ
母体文献
Journal of Geographical Sciences
年卷期
2018年06期
年份
2018
分类号
P467
关键词
climatechange
empiricalmodedecomposition
InnerMongolia
similarityplot
trendsurface
文摘内容
Climate change is a global phenomenon but is modified by regional and local environmental conditions.Moreover,climate change exhibits remarkable cyclical oscillations and disturbances,which often mask and distort the long-term trends of climate change we would like to identify.Inspired by recent advancements in data mining,we experimented with empirical mode decomposition(EMD) technique to extract long-term change trends from climate data.We applied GIS elevation model to construct 3 D EMD trend surface to visualize spatial variations of climate change over regions and biomes.We then computed various time-series similarity measures and plot them to examine spatial patterns across meteorological stations.We conducted a case study in Inner Mongolia based on daily records of precipitation and temperature at 45 meteorological stations from 1959 to 2010.The EMD curves effectively illustrated the long-term trends of climate change.The EMD 3 D surfaces revealed regional variations of climate change,while the EMD similarity plots disclosed cross-station deviations.In brief,the change trends of temperature were significantly different from those of precipitation.Noticeable regional patterns and local disturbances of the changes in both temperature and precipitation were identified.The trends of change were modified by regional and local topographies and land covers.