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王长青, 方奕舟, 熊育久.考虑地形起伏的气温插值研究水资源与水工程学报[J].,2023,34(2):17-24
考虑地形起伏的气温插值研究
Temperature interpolation considering terrain fluctuations
  
DOI:10.11705/j.issn.1672-643X.2023.02.03
中文关键词:  气温  空间插值  反距离权重法  地形校正  数字高程模型(DEM)  黄土高原
英文关键词:temperature  spatial interpolation  inverse distance weighting method  terrain correction  digital elevation model (DEM)  Loess Plateau
基金项目:国家自然科学基金项目(42071395、U1911204、51861125203)
作者单位
王长青1, 方奕舟2, 熊育久1,3,4 (1.中山大学 土木工程学院 广东 珠海 519082 2.广州市珠江前后航道流域事务中心 广东 广州 510641 3.中山大学水资源与环境研究中心 广东 广州 510275 4.南方海洋科学与工程广东省实验室(珠海) 广东 珠海 519000) 
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中文摘要:
      气温是地球水热过程的关键因子,反映着气候变化,对气温进行准确测量以探明其时空分布特征对水热研究和气候变化研究具有重要意义。空间插值是获取气温空间分布的重要手段,但地形(如海拔)严重影响气温的空间插值结果,制约了气温空间分布数据的准确性。为深入探讨海拔对气温空间插值结果的影响,以地形起伏较大的黄土高原为研究对象,基于研究区的33个国家气象站观测数据、1 km SRTM 和DEM数据,系统研究了不同时间尺度下(逐小时、日、月)海拔校正对气温插值结果的影响。结果表明:在小时、日、月3种时间尺度下,气温空间插值结果考虑海拔校正与否存在明显差异,其差值随着海拔的增加而增大;当海拔低于1 000 m时,地形校正前后气温月尺度差异相对较小(均值低于0.5 ℃),当海拔超过2 000 m时,地形校正前后气温差异可达3 ℃,当海拔超过3 000 m时,其差异高达6 ℃;随着时间尺度从逐时到逐日、逐月变化,海拔对气温空间插值结果的影响有弱化趋势。
英文摘要:
      Temperature is directly affected by the earth’s energy process and is an important indicator of climate change, the accurate measurement and the grasp of spatiotemporal distribution of temperature is of great significance for the study of energy process and climate change. Spatial interpolation is an important method to obtain temperature spatial distribution; however, terrain fluctuations affect the interpolation results greatly, which restricts the accuracy of estimated data of spatial temperature. To address such challenge, we performed a case study to test temperature interpolation with and without considering terrain fluctuations in the Loess Plateau with huge elevation variations. Based on the temperature observations from 33 national meteorological stations and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) of 1 km, differences between temperature values interpolated with and without considering terrain fluctuations were systematically studied at hourly, daily, and monthly scales, respectively. The results show that at these three scales, the interpolation results vary greatly before and after terrain correction, and the difference increases with the increase of elevation. When the elevation is below 1, 000 m, the temperature difference before and after terrain correction is relatively small (the mean value is less than 0.5 ℃), whereas it can reach 3 ℃ when the elevation exceeds 2, 000 m, and 6 ℃ when the elevation is greater than 3, 000 m at monthly scale. Moreover, the influence of elevation fluctuations on interpolation results tends to weaken when the temporal scale changes from hourly to daily and to monthly.
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