Abstract：A new temperature interpolating method was put forward based on some factors,such as climate average value,distance and altitude variation.This method was on basis of daily temperature data collected in 35 meteorological stations of Chongqing from 1971 to 2000.It could be used to interpolate missing data in daily average temperature series.The cross verification experiment showed that the Mean Absolute Error(MAE) of the daily average temperature was between 0.2℃ to 0.8℃ with the average of 0.4℃ in the whole Chongqing municipality.It could also simulate daily maximum temperature and daily minimum temperature with highly reliable accuracy.This method was used to simulate hourly average temperature data of all seasons in Shapingba meteorological station.The MAE was less than 0.66℃,while the Mean Relative Error(MRE) was less than 3.2% except that 7.9% in winter.The correlation coefficient between observations and calculations was above 0.95.In this experiment,spring was represented by the first ten days of April,summer the first ten days of July,autumn the first ten days of November,and winter the first ten days of January.So this method could also be used to interpolate missing hourly observed temperature data.
唐云辉;高阳华;. 基于邻域特征的温度缺失值的填补方法[J]. 中国农业气象, 2008, 29(04): 454-457.
TANG Yun-hui,GAO Yang-hua(Chongqing Institute of Meteorological Sciences,Chongqing 400039,China). Imputation Method of Missing Temperature Data Based on Neighborhood Features. Chinese Journal of Agrometeorology, 2008, 29(04): 454-457.