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。
Direct interpolation, temperatureelevation 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 095 and a standard deviation (STD) of 34℃ with January's mean temperature, r=078 and STD=36℃ with July's mean temperature, and r=087 and STD=33℃ with annual mean temperature respectively, that the temperature calculated by temperatureelevation method had a relationship of r=098 and STD=24℃ with January's mean temperature, r=097 and STD=11℃ with July's mean temperature, and r=098 and STD=13℃ with annual mean temperature respectively, and that the temperature calculated by multiple variable regression method had a relationship of r=098 and STD=23℃ with January's mean temperature, r=097 and STD=11℃ with July's mean temperature, and r=098 and STD=14℃ 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.
出处
《资源科学》
CSSCI
CSCD
北大核心
2003年第6期83-88,共6页
Resources Science
基金
国家科技基础性工作专项资金课题(编号:2001DEA30027 9)
中国科学院知识创新工程项目(编号:INF105 SDB 1 18)
中日合作课题-全球变化对中国的影响研究(AIM Impact)。