Abstract: Due to the low accuracy rate of maximum temperature prediction in Guizhou Province, the refined guidance forecast SCMOC data and meteorological observations data from 2013 to 2018 were used to study maximum temperature forecast for 24-72 hours of 85 stations in Guizhou. The horizontal prediction model (F1), the vertical forecast model (F2) and the combination model with F1 and F2 (Fzh) were established to forecast daily maximum temperature in Guizhou. The results show that Fzh took a best performance among three models, and for these three models, both mean root-mean-square error (RMSE) and accuracy rate were improved to varying degrees. Compared with SCMOC, the forecast results of F1 in spring and summer were better than that in autumn and winter, and the improvement in the northern areas of Guizhou Province was more obvious than southern areas. The forecast results of F2 were improved all the year round, and the overall improvement was relatively stable. The forecast accuracy rate of Fzh was obviously better than F1 and F2, and RMSE decreased significantly, the mean RMSE decreased 1.0 to 2.0 ℃, the accuracy rate increased by 11% to 13%.

Key words: maximum temperature, SCMOC, root mean square errors, forecast accuracy rate

摘要： 为探究最高气温预报准确率偏低这一现象，采用2013—2018年SCMOC精细化指导预报资料及气象站观测资料，对贵州省85站24～72 h最高气温预报开展研究。通过建立横向预报模型（F1）、纵向预报模型（F2）以及横向与纵向预报相整合的预报模型（Fzh），对贵州日最高气温进行预报试验。结果表明，无论平均均方根误差还是预报准确率，各模型预报效果均有不同程度改进，三种客观订正预报中Fzh表现最优；相对于SCMOC，F1春、夏季的预报优于秋、冬季，且贵州省北部地区改进较南部明显，F2四季均有改进，总体较平稳；Fzh预报结果明显优于F1和F2，均方根误差得到明显改善，平均RMSE下降1.0～2.0 ℃，准确率平均提高11%～13%。

关键词: 最高气温, SCMOC, 均方根误差, 预报准确率