基于日常预报业务应用的欧洲中期天气预报中心（ECMWF）、日本气象厅（JMA）和中国气象局（CMA）所提供的地面最低气温预报资料，在贵州境内展开多模式集合预报研究，为使预报效果更优化，进一步将滑动系数应用于预报模型中，并将其结果与简单的多模式集合平均和各业务中心预报进行比较。结果表明，在2013年1月1日～2014年4月30日24～120 h 预报中，多模式集合预报（SUP）结果明显降低了预报的均方根误差，结果远优于 ECMWF 和集合平均预报（EMN），在整个贵州区域中，均方根误差＜1．5℃的区域远高于 ECMWF 和 EMN；EMN 在一定程度上相对各中心预报有所改善，效果与 SUP 一样优于 ECMWF，但在48 h 后效果改善不明显。
Application of Multi-model Ensemble Method for Minimum Temperature in Guizhou Province
Based on the data taken from China Meteorological Administration (CMA), Japan Meteorological Agency (JMA) and European Cen-tre for Medium-range Weather Forecasts (ECMWF), the multi-model ensemble forecast methods for minimum temperature were carried out in Guizhou Province.The slipping coefficient was applied in the forecast model, which result was compared with single multi-model ensemble mean and the routine forecast.The result showed that the multi-model ensemble method evidently reduced the forecast RMSE in the forecast of 24 -120 h from Jan.1, 2013 to Apr.30, 2014.And there was a considerable improvement on forecast skill over the ECMWF EMN.The areas of RMSE less than 1.5 ℃ was higher than ECMWF and EMN in Guizhou, and also, the EMN was better than ECMWF in 24 -48 h, however, it had not obvi-ous improvement after 48 h.
国家科技期刊平台
NSTL
万方数据
维普
