GRAPES_RAFS系统2 m温度偏差订正方法研究

本文通过对2013年6月20日至7月20日GRAPES(Global and Regional Assimilation and Prediction System)_RAFS(Rapid Analysis and Forecast System)系统每天8个时次每3h的2 m温度预报进行分析,发现各时次的预报均能较好地表征2 m温度日变化特征,但预报与实况存在一定的偏差,其中西藏东部川西高原、云贵高原、江南武夷山脉偏低于实况可达3℃,而华北地区偏高于实况3℃以上.为了减小GRAPES_RAFS系统偏差对2m温度预报的影响,本文采用平均法、双权重平均法、滑动平均法和滑动双权重平均法分别对GRAPES_RAFS系统2 m温度预报产品进行偏差订正,并对订正前后的结果进行检验分析和对比.结果表明:2 m温度订正后的平均误差大部地区减小到(一1～1℃),而均方根误差大部地区降低到2.5℃内.对于偏差较大地区,订正效果更为明显,如西藏东部川西高原,经过订正,平均误差绝对值由订正前3℃以上降低到1℃内,而RMSE由订正前4℃以上控制到3℃内.对比四种订正方法,双权重订正方法与平均法订正整体效果接近,但对个别站点,双权重订正法要优于平均法,经过滑动的订正方法比无滑动的订正方法订正效果更好,订正效果最好的是滑动双权重平均法,全国平均误差大部分在(-0.5～0.5℃)内,不超过(-1～1℃)的范围.     

STUDY OF THE MODIFICATION OF MULTI-MODEL ENSEMBLE SCHEMES FOR TROPICAL CYCLONE FORECASTS

This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble (TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean (BREM) and superensemble (SUP), are compared with the ensemble mean (EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.     

风云三号卫星微波辐射率资料的质量控制

利用双权重算法对观测增量（卫星观测亮度温度与用辐射传输模式模拟的背景场亮度温度之差）进行质量控制,模式背景场采用的是NCEP再分析资料,观测算子使用的是RTTOV（9．3v）（thefast radiative transfer for （A）TOVS model）。质量控制分两步进行：粗检验和离群值检验,目的是剔除受地表发射率或云影响的离群资料。结果表明：质量控制后观测增量标准差显著减小,偏差接近无偏正态分布,FY-3卫星微波温度探测器辐射率数据的质量得到很大的改善,为FY-3微波温度计观测亮温资料在数值预报资料同化系统中的应用奠定基础。