摘要
为了提高气象要素空间化的精度,本文提出通过预先对气象数据进行处理,然后再进行空间化,以比较直接插值与原始数据处理之后再插值的精度的变化。文中采用数据为全国743个常规气象站40 a(1961—2000年)整编气象资料及2005年的常规气象资料;插值方法有反距离加权法(IDW)、克立格法(Kriging)和样条函数法(Spline);数据预处理方法采用距平处理。结果发现:使用IDW、Kriging和spline对平均温度距平进行插值精度比较,发现IDW方法最优;温度距平精度的提高比降水和相对湿度要好;降水距平误差呈现由东向西递增的趋势。由此可见,对气象要素做距平处理可以有效提高插值精度。
In order to improve the interpolation accuracy of meteorological elements,the meteorological data were firstly processed,and then the changed data were interpolated.The 40 a meteorological data during 1961-2000 and the observation data of 2005 from 743 conventional stations in China,the interpolation methods including IDW,Kriging and Spline,and the data pretreatment method was processed based on anomaly processed.Results show that IDW is better than Kriging and Spline for average temperature anomaly; the improvement of temperature is better than that of precipitation and relative humidity;precipitation anomaly deviation presents the increasing trend from east to west.Thus,the pretreatment methods of meteorological data can improve interpolation accuracy.
出处
《气象科学》
北大核心
2017年第2期278-282,共5页
Journal of the Meteorological Sciences
基金
四川省科技支撑计划项目(2015NZ0035)
关键词
距平插值方法
气象数据处理
交叉验证
插值精度
Anomaly interpolation method
Meteorological data processing
Cross-validation
Interpolator accuracy
