复杂山地环境下气候要素的空间插值方法比较研究
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摘要
复杂山地环境下气候要素的空间插值长期以来是地理科学研究的一大热点和难点问题.该文以中国康滇区为研究区域,以康滇区基准气象站点的分布图和1km精度的数字高程模型为实验数据,借助传统的普通克里格法和反距离加权法以及将海拔高程引为变量的薄板光顺样条插值方法,对多年月平均温度和降水量进行空间插值方法的比较研究.结果表明,康滇区温度的空间分布呈现出明显的地带差异,而降水量的空间分布没有明显的地带差异;均方根误差等统计指标评价薄板光顺样条插值方法的插值精度最高.与普通克里格法和反距离加权法相比,薄板光顺样条插值方法更适宜用于复杂山地环境下气候要素的空间插值.
Spatial interpolation for climate data in mountainous regions with complex topography has always been a hot issue in the geographical information science.In this study,we used three interpolation methods including Inverse Distance Weight(IDW),Ordinary Kriging(OK)and Thin Plate Smoothing Spline(TPS)incorporated with elevation to interpolate monthly average temperature and precipitation data based on the meteorological stations in Kangdian region of China and digital elevation model at the spatial resolution of 1 km.Results showed that there was significant regional variations in the spatial distribution of temperature in Kangdian region while not in precipitation.TPS performed best for the spatial interpolation of temperature and precipitation in Kangdian region based on the statistics index of root mean squared error.It's concluded that TPS was more appropriately applied for mountainous regions with complex topography,compared to IDW and OK.
Spatial interpolation for climate data in mountainous regions with complex topography has always been a hot issue in the geographical information science.In this study,we used three interpolation methods including Inverse Distance Weight(IDW),Ordinary Kriging(OK)and Thin Plate Smoothing Spline(TPS)incorporated with elevation to interpolate monthly average temperature and precipitation data based on the meteorological stations in Kangdian region of China and digital elevation model at the spatial resolution of 1 km.Results showed that there was significant regional variations in the spatial distribution of temperature in Kangdian region while not in precipitation.TPS performed best for the spatial interpolation of temperature and precipitation in Kangdian region based on the statistics index of root mean squared error.It's concluded that TPS was more appropriately applied for mountainous regions with complex topography,compared to IDW and OK.
引文
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[2]MACKEY B G.Predicting the potential distribution of rainforset structural characteristics[J].Journal of Vegetation Science,1994,5(1):43-54.
[3]于凤鸣,卓义,姜春龙,等.GIS空间插值方法在内蒙古气温插值中的应用[J].内蒙古气象,2013,41(3):11-14.YU F M,ZHUO Y,JIUANG C L,et al.GIS spatial interpolation application in temperature interpolation of Inner Mongolia[J].Meteorology Journal of Inner Mongolia,2013,41(3):11-14.(Ch).
[4]邱新法,仇月萍,曾燕.重庆山地月平均气温空间分布模拟研究[J].地球科学进展,2009,24(6):621-628.QIU X F,QIU Y P,ZENG Y.Distributed modeling of monthly mean air temperature of rugged terrain of Chongqing[J].Advances in Earth Science,2009,24(6):621-628.(Ch).
[5]仲嘉亮.基于GIS的新疆多年平均降水量空间插值精度比较研究[J].沙漠与绿洲气象,2010,4(4):51-54.ZHONG J L.A Comparative study of spatial interpolation precision of annual average precipitation based on GIS in Xinjiang[J].Desert and Oasis Meteorology,2010,4(4):51-54.(Ch).
[6]姜贵祥,孙旭光.格点降水资料在中国东部夏季降水变率研究中的适用性[C].中国气象学会年会s4东亚气候变异成因和预测.2015.JIANG G X,SUN X G.Application of grid precipitation datasets in summer precipitation variability over East China[J].Journal of the Meteorological Sciences,2015.(Ch).
[7]金志凤,李波,袁德辉.基于GIS的浙江省年平均气温空间模拟研究[J].气象科学,2010,30(6):836-840.JIN Z F,LI B,YUAN D H.A research on simulating spatial distribution of mean annual temperature in Zhejiang province based on GIS[J].Scientia Meteorologica Sinica,2010,30(6):836-840.(Ch).
[8]邬伦,吴小娟,肖晨超,等.五种常用降水量插值方法误差时空分布特征研究——以深圳市为例[J].地理与地理信息科学,2010,26(3):19-24.WU L,WU X J,XIAO C C,et al.On temporal and spatial error distribution of five precipitation interpolation models:a case of Shenzhen[J].Geography and Geo-Information Science,2010,26(3):19-24.(Ch).
[9]李丽双,张颖.基于GIS的东北地区气象要素空间插值方法[J].安徽农业科学,2012,40(9):5541-5543.LI L S,ZHANG Y.Spatial interpolation method of the meteorological factor in northeast China based on GIS[J].Journal of Anhui Agricultural Sciences,2012,40(9):5541-5543.(Ch).
[10]李彦,王丽娜,蒋镇.一种针对气象要素的空间插值算法[J].重庆理工大学学报自然科学版,2014,28(6):94-98.LI Y,WANG L N,JIANG Z.One kind of spatial interpolation algorithm for meteorological elements[J].Journal of Chongqing University of Technology(Natural Science),2014,28(6):94-98.(Ch).
[11]何英,李丽,吴巩胜.气候要素空间插值技术的研究进展[J].科协论坛,2010(3):59-61.HE Y,LI L,WU G S.Research progress of the spatial interpolation technology for climate factor[J].China Association for Science and Technology,2010(3):59-61.(Ch).
[12]HIJMANS R J,CAMERON S E,PARRA J L,et al.Very high resolution interpolated climate surfaces for global land areas[J].International Journal of Climatology,2005,25(15):1965-1978.
[13]赵冠华,刘正佳,胡云锋,等.DEM的不确定性对温度插值精度的影响[J].地理与地理信息科学,2016,32(2):21-26.ZHAO G H,LIU Z J,HU Y F,et al.Impacts of DEM uncertainty on temperature interpolation accuracy[J].Geography and Geo-Information Science,2016,32(2):21-26.(Ch).
[14]张宝堃.中国气侯区域挂图[M].北京:地图出版社,1958.ZHANG B K.Climate Regionalization Map of China[M].Beijing:Map Press,1958.(Ch).
[15]张玮玮,申双和,刘敏,等.湖北省茶树种植气候区划[J].气象科学,2011,31(2):153-159.ZHANG W W,SHEN S H,LIU M,et al.Climate division of tea planting in Hubei province[J].Journal of the Meteorological Sciences,2011,31(2):153-159.(Ch).
[16]于飞,郑小波,谷晓平,等.复杂山地环境下气候要素空间插值精度比较研究[J].贵州气象,2008,32(3):3-6.YU F,ZHENG X B,GU X P,et al.Comparision study on meteorological spatial interpolation accuracy in complex mountainous of China[J].Journal of GuiZhou Meteorology,2008,32(3):3-6.(Ch).
[17]HUTCHINSON M F.On thin plate splines and kriging[M]//Computing and Science in Statistics,Volume 25.1993:55-62.
[18]HONG Y,NIX H A,HUTHINSON M F,BOOTH T H.Spatial interpolation of monthly mean climate data for China[J].International Journal of Climatology,2005,25(10):1369-1379.