基于Modis地表温度的青藏高原东部及其邻近地区气温估算(英文)

编号 zgly0001585739

文献类型 期刊论文

文献题名 基于Modis地表温度的青藏高原东部及其邻近地区气温估算(英文)

作者 姚永慧  张百平 

作者单位 StateKeyLaboratoryofResourceandEnvironmentalInformationSystem  InstituteofGeographicSciencesandNaturalResourcesResearch  CAS 

母体文献 Journal of Geographical Sciences 

年卷期 2012年01期

年份 2012 

分类号 P423 

关键词 landsurfacetemperature  MODIS  airtemperatureestimation  spatio-temporalanalysis  theHeng-duanMountains  TibetanPlateau 

文摘内容 Climatic conditions are difficult to obtain in high mountain regions due to few meteorological stations and, if any, their poorly representative location designed for convenient operation. Fortunately, it has been shown that remote sensing data could be used to estimate near-surface air temperature (Ta) and other climatic conditions. This paper makes use of recorded meteorological data and MODIS data on land surface temperature (Ts) to estimate monthly mean air temperatures in the southeastern Tibetan Plateau and its neighboring areas. A total of 72 weather stations and 84 MODIS images for seven years (2001 to 2007) are used for analysis. Regression analysis and spatio-temporal analysis of monthly mean Ts vs. monthly mean Ta are carried out, showing that recorded Ta is closely related to MODIS Ts in the study region. The regression analysis of monthly mean Ts vs. Ta for every month of all stations shows that monthly mean Ts can be rather accurately used to estimate monthly mean Ta (R2 ranging from 0.62 to 0.90 and standard error between 2.25℃ and 3.23℃). Thirdly, the retrieved monthly mean Ta for the whole study area varies between 1.62℃ (in January, the coldest month) and 17.29℃ (in July, the warmest month), and for the warm season (May-September), it is from 13.1℃ to 17.29℃. Finally, the elevation of isotherms is higher in the central mountain ranges than in the outer margins; the 0℃ isotherm occurs at elevation of about 4500±500 m in October, dropping to 3500±500 m in January, and ascending back to 4500±500 m in May next year. This clearly shows that MODIS Ts data combining with observed data could be used to rather accurately estimate air temperature in mountain regions.