基于GIS的月平均气温空间化方法的比较研究
发布时间：2018-08-08 17:00
【摘要】：使用1961-2000年全国743个气象台站常规气象观测资料,利用IDW、Kriging以及Spline这3种常用空间插值方法,以及复杂地形下月平均气温分布式模型,生成全国的月平均气温空间分布图,并同时与中国气象数据网提供的中国地面气温月值0.5°×0.5°格点数据集进行比较,结果表明:3种插值方法(IDW、Kriging、Spline)、格点数据集与气温分布式模型的绝对误差分别为1.59℃、1.54℃、1.99℃、1.40℃、0.56℃,气温分布式模型的精度最高,而且其空间分辨率最高,模拟的稳定程度较好,能够很好地体现气温随地形的变化特征。因此,气温分布式模型对于平均气温的模拟性能最好。
[Abstract]:Using the routine meteorological observation data of 743 meteorological stations in China from 1961 to 2000, using the spatial interpolation methods of IDW Kriging and Spline, as well as the distributed model of monthly mean temperature in complex terrain, the spatial distribution map of the monthly mean temperature of the whole country is generated. At the same time, it is compared with the data set of 0.5 掳脳 0.5 掳lattice temperature in China provided by China Meteorological data Network. The results show that the absolute error between the grid data set and the temperature distributed model is 1.59 鈩，
本文编号：2172435
[Abstract]:Using the routine meteorological observation data of 743 meteorological stations in China from 1961 to 2000, using the spatial interpolation methods of IDW Kriging and Spline, as well as the distributed model of monthly mean temperature in complex terrain, the spatial distribution map of the monthly mean temperature of the whole country is generated. At the same time, it is compared with the data set of 0.5 掳脳 0.5 掳lattice temperature in China provided by China Meteorological data Network. The results show that the absolute error between the grid data set and the temperature distributed model is 1.59 鈩，
本文编号：2172435
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