复杂地形下浙江夏季气候要素空间插值方法评价

Evaluation of Spatial Interpolation Method About Climatic Elements in Summer in Zhejiang Province Under Complex Topography

利用1988—2017年浙江省68个国家气象观测站气温和降水数据,分别采用ANUSPLIN、反距离加权(IDW)和普通克里格(O-kriging)3种方法,估算夏季平均气温和降水量空间插值。同时,应用交叉验证方法评价3种方法的精度差异,并进行空间误差分析,探讨符合浙江复杂地形条件和气候背景下的气象要素空间插值最优方法。结果表明:(1)3种方法对气温和降水的插值精度总体接近,空间分布较为一致,但对于要素空间异质性大的区域,ANUSPLIN在细节上的表现明显优于IDW和O-kriging方法。(2)ANUSPLIN对气温和降水的插值精度均高于IDW和O-kriging,气温的平均绝对误差(MAE)和均方根误差(RMSE)均小于0.5℃,其中气温RMSE表现为:ANUSPLIN(0.381℃)<O-kriging(0.459℃)<IDW(0.463℃)。降水RMSE表现为:ANUSPLIN(37.8 mm)<O-kriging(42.2 mm)<IDW(49.1 mm)。(3)平原地区的平均气温插值误差低于山区;降水误差空间分布沿海地区误差最大,出现明显低估值。总体来说,ANUSPLIN更适合浙江复杂地形条件和气候背景下的气象要素空间插值处理。

Based on temperature and precipitation data from 68 national meteorological stations in Zhejiang Province from 1988 to 2017,mean summer temperature and precipitation were interpolated using thin-plate smoothing splines(ANUSPLIN),inverse distance weighting(IDW)and ordinary kriging interpolation methods.In order to explore the optimal interpolation method of meteorological elements under complex terrain and climate in Zhejiang Province,the cross-validation method was applied to evaluate the accuracy of three methods,and the spatial error was analyzed.The results are as follows:(1)The interpolation accuracy of temperature and precipitation was generally close by using three methods,and the spatial distribution was relatively consistent.However,ANUSPLIN method was significantly better than IDW and ordinary kriging methods in detail for areas with large heterogeneity of element.(2)The interpolation accuracy of air temperature and precipitation based on ANUSPLIN was higher than that based on IDW and ordinary kriging.For example,the mean absolute error(MAE)and root mean square error(RMSE)of air temperature interpolation were both less than 0.5℃.The RMSE(0.381℃)of temperature interpolation based on ANUSPLIN was smallest,it was second based on ordinary kriging(0.459℃),and it was biggest(0.463℃)based on IDW.The RMSE(37.8 mm)of precipitation interpolation based on ANUSPLIN was smallest,it was second(42.2 mm)based on the ordinary kriging,and it was biggest(49.1 mm)based on IDW.(3)The average interpolation error of temperature in plain area was lower than that in mountainous area.The average interpolation error of precipitation in the coastal area had largest error,showing an obvious low estimation.In conclusion,ANUSPLIN was more suitable for the spatial treatment of meteorological elements in Zhejiang Province under complex terrain and climate background.