【摘要】 用直接内插法、气温垂直递减法和多元回归方法分别对中国1961年592个气象站的气温数据进行栅格化,并用另外58个气象站相应的气温指标进行验证发现,直接内插法的计算结果与实测气温值在1月平均气温、7月平均气温和年平均气温3个指标上的相关系数分别为:0 95、0 78、和0 87,标准误差分别为3 4℃、3 6℃和3 3℃;气温垂直递减法的计算结果与实测气温值在3个指标上的相关系数分别为:0 98、0 97、和0 98,标准误差分别为2 4℃、1 1℃和1 3℃;多元回归方法的计算结果与实测气温值在3个指标上的相关系数分别为:0 98、0 97、和0 98,标准误差分别为2 3℃、1 1℃和1 4℃。因此,直接内插法的精度最低,不能用于大范围内的气温数据栅格化。气温垂直递减法和多元回归方法均具有较高的精度,尽管它们各有特点,但都可用于气温数据的栅格化。更多还原

【Abstract】 Direct interpolation, temperatureelevation model and multiple variable regression model were respectively used to rasterize air temperature data from 592 meteorological stations in China in 1961. Air temperature data from other 58 meteorological stations were used to verify these methods. It was found that the temperature calculated by direct interpolation method had a relationship coefficient (r) of 095 and a standard deviation (STD) of 34℃ with January’s mean temperature, r=078 and STD=36℃ with July’s mean temperature, and r=087 and STD=33℃ with annual mean temperature respectively, that the temperature calculated by temperatureelevation method had a relationship of r=098 and STD=24℃ with January’s mean temperature, r=097 and STD=11℃ with July’s mean temperature, and r=098 and STD=13℃ with annual mean temperature respectively, and that the temperature calculated by multiple variable regression method had a relationship of r=098 and STD=23℃ with January’s mean temperature, r=097 and STD=11℃ with July’s mean temperature, and r=098 and STD=14℃ with annual mean temperature respectively. Therefore, direct interpolation method is not suitable for rasterization of temperature data at large scale because of low precision, and the other two methods can be used for rasterization of temperature data.更多还原