Based on the initial field temperature data of ECMWF 850 hPa from Jan- uary 2012 to December 2015, linear interpolation method of ECMWF was employed to calculate the 850 hPa temperature values at 8：00 and 20：00 of 7...Based on the initial field temperature data of ECMWF 850 hPa from Jan- uary 2012 to December 2015, linear interpolation method of ECMWF was employed to calculate the 850 hPa temperature values at 8：00 and 20：00 of 7 stations （Jiamusi, Tangyuan, Huachuan, Huanan, Fujin, Tongjiang, Fuyuan）. Combined with the observed daily minimum and maximum air temperatures at the same time of the 7 stations, the correlations of the 850 hPa temperature values at 8：00 and 20：00 with the daily maximum or minimum air temperature of the ground meteorological obser- vation stations were established, and the ground observation data in accordance with the relevant analysis and correlation test principle of the prediction equation for factor were primarily selected. Regression method was used to establish forecast e- quation dividing into counties, month by month. The results showed that the 850 hPa temperature values at 8：00 and 20：00 were significantly correlated with the daily maximum or minimum air temperature, and the established temperature fore- cast equation was of certain guiding significance for the forecast of daily minimum and maximum temperature, which could help to improve the forecast accuracy.展开更多
文摘Based on the initial field temperature data of ECMWF 850 hPa from Jan- uary 2012 to December 2015, linear interpolation method of ECMWF was employed to calculate the 850 hPa temperature values at 8：00 and 20：00 of 7 stations （Jiamusi, Tangyuan, Huachuan, Huanan, Fujin, Tongjiang, Fuyuan）. Combined with the observed daily minimum and maximum air temperatures at the same time of the 7 stations, the correlations of the 850 hPa temperature values at 8：00 and 20：00 with the daily maximum or minimum air temperature of the ground meteorological obser- vation stations were established, and the ground observation data in accordance with the relevant analysis and correlation test principle of the prediction equation for factor were primarily selected. Regression method was used to establish forecast e- quation dividing into counties, month by month. The results showed that the 850 hPa temperature values at 8：00 and 20：00 were significantly correlated with the daily maximum or minimum air temperature, and the established temperature fore- cast equation was of certain guiding significance for the forecast of daily minimum and maximum temperature, which could help to improve the forecast accuracy.
