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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) 被引量:2

Investigating long-term trends of climate change and their spatial variations caused by regional and local environments through data mining
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摘要 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. Climate change is a global phenomenon but is modified by regional and local en- vironmental 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 3D 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 meteoro- logical stations. We conducted a case study in Inner Mongolia based on daily records of pre- cipitation and temperature at 45 meteorological stations from 1959 to 2010. The EMD curves effectively illustrated the long-term trends of climate change. The EMD 3D 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.
作者 谢一春 张扬 兰海 毛立身 曾寔 陈宇璐 XIE Yichun1'2, ZHANG Yang3, LAN Hai4, MAO Lishen, ZENG Shi5, CHEN Yulu(1. Institute for Geospatial Research and Education, Eastern Michigan University, Ypsilanti, Michigan 48197 USA; 2. Guangzhou Institute of Geography, Guangzhou 510070, China; 3. Department of Computer Science, Indiana University, Bloomington, Indiana 47405, USA; 4. Department of Computer Science, New York University, NY 10012, USA; 5. Center for Advanced Spatial Analysis, University College London, London WCIE 6BT, U)
出处 《Journal of Geographical Sciences》 SCIE CSCD 2018年第6期802-818,共17页 地理学报(英文版)
基金 Guangdong Innovative and Entrepreneurial Research Team Program,No.2016ZT06D336 GDAS Special Project of Science and Technology Development,No.2017GDASCX-0101
关键词 气候变化 空间变化 地区性 采矿 环境 EMD 模式分解 数据提取 climate change empirical mode decomposition Inner Mongolia similarity plot trend surface
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