深圳市气温空间插值方法比较

Comparison of Spatial Interpolation Methods for Temperature in Shenzhen

作者：

何轮凯中国科学院深圳先进技术研究院深圳 518055
孙立群中国科学院深圳先进技术研究院深圳 518055
李晴岚中国科学院深圳先进技术研究院深圳 518055
谢坤深圳市气象局深圳 518040
王书欣深圳市气象局深圳 518040
王德立深圳市气象局；深圳南方强天气研究重点实验室深圳 518040
徐倩香港大学香港

中文摘要：

利用深圳市地区的128个气象站点气温资料，采用反距离权重法（IDW）、局部多项式插值法（LPI）、普通克里金（OK）、协同克里金（Cokriging）和Anusplin软件的薄板样条函数插值（TPS）等5种方法，对深圳地区2017年的月平均气温空间插值结果进行了交叉验证。结果表明，在深圳地区5种插值方法的插值效果最好的是TPS。LPI、IDW、OK和Cokriging的交叉验证误差与高程之间有显著的相关性，受地形影响较大，在海拔较高的地区误差较大。TPS的插值误差与高程之间相关性较小，更加适合于深圳地区复杂地形的气温插值。本研究对气象插值业务的开展有较大的实用价值。

中文关键词：

气温，薄板样条函数，空间插值，高程，交叉验证

KeyWords：

temperature, thin plate spline function, spatial interpolation, altitude, cross-validation

Abstract：

Using the temperature data of 128 meteorological stations in Shenzhen, five methods, including inverse distance weighting method (IDW), local polynomial interpolation (LPI), ordinary kriging (OK), Cokriging and thin plate spline interpolation (TPS) of Anusplin, are applied to cross-validate the spatial interpolation of the monthly mean temperature of Shenzhen in 2017. The accuracy of the five interpolation methods in Shenzhen shows that TPS performs the best. The cross validation errors of LPI, IDW, OK and Cokriging are significantly correlated with the altitude. These 4 methods are greatly affected by the altitude and the errors are larger in areas with higher altitude. The correlation coefficient between TPS interpolation errors and altitude is smaller than the other four methods. This result indicates that TPS method is more suitable for the temperature interpolation of complex terrain like Shenzhen. This study has great practical value for meteorological interpolation business.