基于DEM的复杂地形气温空间插值研究
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摘要
利用江西省87个国家气象观测站点1987—2016年月平均气温资料,结合数字高程模型(DEM),建立了一个基于江西省DEM的多元线性回归空间插值模型,并与传统的反距离权重法(IDW)、普通克里金插值法(OK)和协同克里金插值法(CK)进行空间插值精度和效果对比。研究表明:基于DEM的多元线性回归空间插值方法(MLR)的误差精度和插值效果均优于其他3种传统插值方法。江西省月(年)平均气温与纬度和海拔高度呈负相关,与经度呈正相关,与坡度、坡向无明显相关性;江西省月平均气温垂直递减率约为0.35—0.65℃/(100 m),年平均气温垂直递减率约为0.49℃/(100 m)。
Using the 1987-2016 monthly average temperature data of 87 meteorological observing stations in Jiangxi,combined with the digital elevation model(DEM),a multiple linear regression spatial interpolation model based on DEM in Jiangxi was established,and the accuracy and effect were compared with those of the traditional inverse distance weighting method(IDW),ordinary Kriging interpolation(OK)and Co-kriging Interpolation(CK).The results showed that the multiple linear regression spatial interpolation method(MLR)based on DEM was superior to other three traditional interpolation methods in terms of error accuracy and interpolation effect.The monthly mean temperature in Jiangxi province was negatively correlated with latitude and altitude while positively correlated with longitude,and had no significant correlation with slope and aspect.The monthly average temperature vertical decline rate in Jiangxi province was about 0.35-0.65℃/(100 m),and the annual average temperature vertical decline rate was about 0.49℃/(100 m).
Using the 1987-2016 monthly average temperature data of 87 meteorological observing stations in Jiangxi,combined with the digital elevation model(DEM),a multiple linear regression spatial interpolation model based on DEM in Jiangxi was established,and the accuracy and effect were compared with those of the traditional inverse distance weighting method(IDW),ordinary Kriging interpolation(OK)and Co-kriging Interpolation(CK).The results showed that the multiple linear regression spatial interpolation method(MLR)based on DEM was superior to other three traditional interpolation methods in terms of error accuracy and interpolation effect.The monthly mean temperature in Jiangxi province was negatively correlated with latitude and altitude while positively correlated with longitude,and had no significant correlation with slope and aspect.The monthly average temperature vertical decline rate in Jiangxi province was about 0.35-0.65℃/(100 m),and the annual average temperature vertical decline rate was about 0.49℃/(100 m).
引文
蔡迪花,郭铌,李崇伟.2009.基于DEM的气温插值方法研究[J].干旱气象,27(1):10-17.Cai D H,Guo N,Li C W.2009.Interpolation of air temperature based on DEM over eastern region of Gansu[J].Arid Meteor,27(1):10-17.(in Chinese)
辜智慧,史培军,陈晋.2006.气象观测站点稀疏地区的降水插值方法探讨---以锡林郭勒盟为例[J].北京师范大学学报(自然科学版),42(2):204-208.Gu Z H,Shi P J,Chen J.2006.Precipitation interpolation research over regions with sparse meteorological stations:A case study in Xilin Gole League[J].J BNormal Univ(Nat Sci Edi),42(2):204-208.(in Chinese)
李柏贞,孔萍,占明锦,等.2017.1961-2015年江西省气温变化特征分析[J].气象与减灾研究,40(3):184-192.Li B Z,K P,Zhan M J,et al.2017.Analysis on the temperature variation in Jiangxi province during 1961-2015[J].Meteor Disaster Reduction Res,40(3):184-192.
马秀霞,黄领梅,沈冰.2017.陕西省月平均气温空间插值方法研究[J].水资源与水工程学报,28(5):100-105.Ma X X,Huang LM,Shen B.2017.Study on spatial interpolation method of monthly mean temperature in Shaanxi Province[J].J Water Res Water Eng,28(5):100-105.(in Chinese)
彭彬,周艳莲,高苹,等.2011.气温插值中不同空间插值方法的适用性分析---以江苏省为例[J].地球信息科学学报,13(4):539-548.Peng B,Zhou Y L,Gao P,et al.2011.Suitability assessment of different interpolation methods in the gridding process of station collected air temperature:A case study in Jiangsu province,China[J].Geo-Inf Sci,13(4):539-548.(in Chinese)
Stewart F,Rogerson P.2018.Spatial analysis and GIS[M].Boca Raton:CRC Press.
王丽,王培法,刘爱利,等.2015.基于DEM的江苏气温空间插值研究[J].南京信息工程大学学报(自然科学版),7(1):79-85.Wang L,Wang P,Liu A,et al.2015.Spatial interpolation of mean temperature of Jiangsu province based on DEM[J].JNanjing Univ Inf Sci Technol(Nat Sci Edi),7(1):79-85.(in Chinese)
Vose R S,Applequist S,Squires M,et al.2014.Improved historical temperature and precipitation time series for US climate divisions[J].J Appl Meteor Climatol,53(5):1232-1251.
Vose R S,Squires M,Arndt D,et al.2017.Deriving historical temperature and precipitation time series for Alaska climate divisions via climatologically aided interpolation[J].J Ser Climatol,10(1):852-859.
吴链.2017.三维插值法在湖南省气温精细化预报中的应用与检验[J].气象与减灾研究,40(1):30-35.Wu L.2017.Application and verification of a three-dimensional interpolation method for refined temperature forecast in Hunan province[J].Meteor Disaster Reduction Res,40(1):30-35.(in Chinese)
岳文泽,徐建华,徐丽华.2005.基于地统计方法的气候要素空间插值研究[J].高原气象,24(6):974-980.Yue W Z,Xu J H,Xu L H.2005.A study on spatial interpolation methods for climate variables based on geostatistics[J].Plateau Meteor,24(6):974-980.(in Chinese)
张莉莉,陶忠良,张京红.2012.基于GIS海南岛气象要素空间插值法比较分析[J].热带农业科学,32(4):57-61.Zhang L L,Tao Z L,Zhang J H.2012.Analysis and comparison of the spatial interpolation methods for climate factors in Hainan island[J].Chin J Trop Agric,32(4):57-61.(in Chinese)
周婷婷,陈文惠.2011.基于MODIS数据和气象观测数据的气温空间插值方法比较[J].地理科学进展,30(9):1143-1151.Zhou T T,Chen W H.2011.Comparation of temperature spatial interpolation methods based on MODIS data and meteorological observation data[J].Prog Geo,30(9):1143-1151.(in Chinese)
辜智慧,史培军,陈晋.2006.气象观测站点稀疏地区的降水插值方法探讨---以锡林郭勒盟为例[J].北京师范大学学报(自然科学版),42(2):204-208.Gu Z H,Shi P J,Chen J.2006.Precipitation interpolation research over regions with sparse meteorological stations:A case study in Xilin Gole League[J].J BNormal Univ(Nat Sci Edi),42(2):204-208.(in Chinese)
李柏贞,孔萍,占明锦,等.2017.1961-2015年江西省气温变化特征分析[J].气象与减灾研究,40(3):184-192.Li B Z,K P,Zhan M J,et al.2017.Analysis on the temperature variation in Jiangxi province during 1961-2015[J].Meteor Disaster Reduction Res,40(3):184-192.
马秀霞,黄领梅,沈冰.2017.陕西省月平均气温空间插值方法研究[J].水资源与水工程学报,28(5):100-105.Ma X X,Huang LM,Shen B.2017.Study on spatial interpolation method of monthly mean temperature in Shaanxi Province[J].J Water Res Water Eng,28(5):100-105.(in Chinese)
彭彬,周艳莲,高苹,等.2011.气温插值中不同空间插值方法的适用性分析---以江苏省为例[J].地球信息科学学报,13(4):539-548.Peng B,Zhou Y L,Gao P,et al.2011.Suitability assessment of different interpolation methods in the gridding process of station collected air temperature:A case study in Jiangsu province,China[J].Geo-Inf Sci,13(4):539-548.(in Chinese)
Stewart F,Rogerson P.2018.Spatial analysis and GIS[M].Boca Raton:CRC Press.
王丽,王培法,刘爱利,等.2015.基于DEM的江苏气温空间插值研究[J].南京信息工程大学学报(自然科学版),7(1):79-85.Wang L,Wang P,Liu A,et al.2015.Spatial interpolation of mean temperature of Jiangsu province based on DEM[J].JNanjing Univ Inf Sci Technol(Nat Sci Edi),7(1):79-85.(in Chinese)
Vose R S,Applequist S,Squires M,et al.2014.Improved historical temperature and precipitation time series for US climate divisions[J].J Appl Meteor Climatol,53(5):1232-1251.
Vose R S,Squires M,Arndt D,et al.2017.Deriving historical temperature and precipitation time series for Alaska climate divisions via climatologically aided interpolation[J].J Ser Climatol,10(1):852-859.
吴链.2017.三维插值法在湖南省气温精细化预报中的应用与检验[J].气象与减灾研究,40(1):30-35.Wu L.2017.Application and verification of a three-dimensional interpolation method for refined temperature forecast in Hunan province[J].Meteor Disaster Reduction Res,40(1):30-35.(in Chinese)
岳文泽,徐建华,徐丽华.2005.基于地统计方法的气候要素空间插值研究[J].高原气象,24(6):974-980.Yue W Z,Xu J H,Xu L H.2005.A study on spatial interpolation methods for climate variables based on geostatistics[J].Plateau Meteor,24(6):974-980.(in Chinese)
张莉莉,陶忠良,张京红.2012.基于GIS海南岛气象要素空间插值法比较分析[J].热带农业科学,32(4):57-61.Zhang L L,Tao Z L,Zhang J H.2012.Analysis and comparison of the spatial interpolation methods for climate factors in Hainan island[J].Chin J Trop Agric,32(4):57-61.(in Chinese)
周婷婷,陈文惠.2011.基于MODIS数据和气象观测数据的气温空间插值方法比较[J].地理科学进展,30(9):1143-1151.Zhou T T,Chen W H.2011.Comparation of temperature spatial interpolation methods based on MODIS data and meteorological observation data[J].Prog Geo,30(9):1143-1151.(in Chinese)