误差订正在辽宁地区冬季温度预报中的应用

摘要

The interpolation results of 2 m temperature forecast products produced by the meso-scale operational model in winter of 2014 in Liaoning province were corrected using methods of 7-day bias correction (7DBC)and running mean bias correction (RMBC).The correction results were compared to products of MOS (model output statistics)forecast.The forecast accuracy of the three methods,MOS forecast,7DBC and RMBC,were analyzed. The results show that forecast accuracy of the two bias correction methods is higher than that of NWP (numerical weather prediction)interpolation method.The RMBC method is better than the 7DBC method.As to 24 h maxi-mum temperature forecast,the forecast accuracy of the RMBC method is the highest.For minimum temperature forecast,the forecast accuracy of RMBC is higher than that of NMC (National Meteorological Center)MOS fore-cast at 08:00,while less than MOS forecast at 20:00.The method of RMBC needs accumulated data of 1 to 15 days.Compared to MOS method,the method of RMBC needs less data and is easy to operate,which is more suit-able for areas without long-term records to conduct numerical model revisions for temperature.%利用7 d固定误差订正和滑动误差订正方法对2014年冬季辽宁地区中尺度业务模式2 m温度预报产品插值结果进行订正，并将订正结果与中央气象台MOS预报进行对比，分析MOS、7 d固定误差订正和滑动误差订正3种数值模式后处理方法对辽宁地区冬季温度预报准确率的影响。结果表明：经过两种误差订正后的预报结果准确率均比数值模式预报插值结果高，滑动误差订正效果优于7 d固定误差订正；24 h最高气温预报中，滑动误差订正结果的准确率最高；最低气温预报中，08时滑动误差订正结果准确率高于中央气象台MOS预报，但20时滑动误差订正结果准确率低于MOS预报。滑动误差订正需1—15 d的资料积累，比MOS方法所需资料少且操作简单，适合观测资料积累少的地区开展数值模式的温度订正。