四川地区EC细网格模式2m温度偏差订正研究

本文选取2017年1~12月ECMWF(European Centre for Medium-Range Weather Forecasting)细网格模式168h预报时效的2m温度场和对应时段四川地区157个国家站的观测资料,对比分析了模式温度预报的系统性偏差特征,采用15日周期的滑动双权重平均法对2m温度预报产品进行偏差订正,并与四川省气象台现有的主、客观预报产品进行对比,结果表明:(1)EC模式对低温的预报准确率远高于高温预报准确率;订正后高、低温预报准确率均有显著提高,其中低温平均提高了20.5%,高温提高了31.2%,平均绝对误差分别减小约1.1℃和2.9℃。(2)EC模式高温预报的逐月差异明显比低温预报逐月差异大,订正后差异明显减小,且各月的高、低温预报准确率均有显著提升,订正后各月高、低温的平均绝对误差均在2℃之内。(3)EC模式对于低温和高温的预报在全省均大致呈现负的系统性误差,且高温预报的系统性误差明显比低温预报的系统性误差大,订正后2m温度预报的系统性误差均明显降低,全省大部分地区维持在±1℃之间。(4)与四川省气象台现有的主、客观预报产品对比显示,对于高低温预报均是EC订正后准确率最高、平均绝对误差最小,订正效果较为理想。

Study on 2m Temperature Bias Correction of EC Model in Sichuan Province

Based on the 2m temperature 168h forecast of ECMWF during the period from January to December 2017 and the observation data of the same period,the systematic deviation characteristics of 2m temperature prediction are analyzed.Then the bi-weight moving mean method with a 15 day sliding period is conducted to the model to acquire a correction field,which is compared with the existing subjective and objective forecast products in Sichuan Meteorological Observatory.The results show that:(1) The prediction accuracy of lowest temperature is much higher than that of highest temperature for EC model,and both of them have been obviously improved after the correction.On average the lowest temperature accuracy has increased by 20.5% while the highest temperature accuracy has increased by 31.2%.The average absolute errors have decreased about 1.1℃ and 2.9℃ respectively.(2) The monthly difference of accuracy for the highest temperature,which has been markedly reduced after correction,is significantly greater than that for the lowest temperature.The accuracy for both the highest and lowest temperature have been significantly increased,while the mean absolute error for all months are within 2℃.(3) The forecasts of the lowest temperature and highest temperature both present negative systematic bias in the whole province,and the systematic bias of the highest temperature is obviously larger than that of the lowest temperature.The systematic biases have been significantly decreased after the correction,maintaining between ± 1℃ in most parts of the province.(4) The comparison with the existing subjective and objective forecast products in Sichuan Meteorological Observatory shows that the highest and lowest temperature correction field has the highest accuracy and the minimum average absolute error.