基于空间观测差异的地面气温资料质量控制算法研究

A quality control method for the surface temperature based on the spatial observation diversity

本文提出一种基于空间观测差异的地面气温资料质量控制算法(SDF算法).SDF算法在分析目标区域内不同观测站空间观测差异的基础上,通过引入观测差异曲面函数构造质量控制方程.同时,为权衡质量控制中的两类统计错误,提出均方根检错率概念(MSR),结合均方根误差(RMSE)、平均绝对误差(MAE)和纳什效率系数(NSC)共同检测SDF算法的有效性.利用SDF算法对国家气象中心提供的14个地面观测站2005-2014年02:00、08:00、14:00、20:00定时气温观测资料进行质量控制分析,并与反距离加权法(IDW)和空间回归检测法(SRT)进行对比.试验结果表明:通过多组独立测试,SDF算法的质量控制效果均优于IDW算法和SRT算法,具有稳定性高、适应性强的特点,但三种方法均受观测台站密集度和地形地貌影响.

This article aims to propose a new quality control method based on the spatial observation diversity for the surface temperature （SDF）. In order to weight the two type errors, Mean Square Ratio （MSR） was employed to evaluate the new method with Root Mean Square Error （RMSE）, Mean Absolute Error （MAE） and Nash-Sutcliffe Model Efficiency Coefficient （NSC）. The examples indicate that the new method outperforms IDW and SRT for different stations at 02：00, 08：00, 14：00 and 20：00 during 2005-2014. The results of the comparison led to the recommendation that the SDF method is an effective quality control method in identifying the seeded errors for the surface temperature with the best robustness and adaptability, but all these three methods are affected by the topography and density of the stations.