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气象:2019,45(6):745-755
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两种确定性初值形成方案对集合预报技巧的影响研究
陈良吕,陈静,霍振华,夏宇,陈法敬
(重庆市气象科学研究所,重庆 401147; 中国气象局数值预报中心,北京 100081; 南京信息工程大学,南京 210044)
Impact of Two Different Deterministic Initial Condition Formation Schemes on Ensemble Forecast Skills
CHEN Lianglü,CHEN Jing,HUO Zhenhua,XIA Yu,CHEN Fajing
(Chongqing Institute of Meteorological Sciences, Chongqing 401147; CMA Numerical Prediction Centre, Beijing 100081; Nanjing University of Information Science and Technology, Nanjing 210044)
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投稿时间:2018-01-30    修订日期:2018-09-28
中文摘要: 为了进一步提高GRAPES REPS的降水预报性能,将GRAPES Meso业务模式的高分辨率同化分析初值通过动力升尺度方法(简称GRAPES M US方案)产生GRAPES REPS确定性初值,在此基础上进行了连续10 d的集合预报试验,并与基于T639全球模式同化分析初值动力降尺度方案(简称T639 G DS方案)得到的确定性初值以及相应的集合预报结果进行了对比分析及预报检验,重点关注了降水预报的检验结果。结果表明:基于GRAPES M US方案得到的确定性初值相对于T639 G DS方案得到的确定性初值而言,在低层具备更多的中小尺度信息;低层连续性变量预报表现较好,850 hPa的位势高度和温度的均方根误差以及概率预报评分(CRPS)均表现出了一定的改进效果,而中层和高层要素改进不显著,10 m风速均方根误差和CRPS均有较明显的改进效果,2 m温度均方根误差和CRPS则基本相当;对降水预报而言,24 h预报时效的小雨、中雨和大雨量级的TS评分、Brier评分和相对作用特征面积(AROC)均有一定的改进,其余预报时效总体而言基本相当或略有负效果;在2017年8月7日的强降水个例中,对强降水落区和强度的预报表现出了一定的“细化”和“纠偏”效果;总体而言,GRAPES M US方案较T639 G DS方案表现出了一定的优势,特别是在短期降水预报方面。
Abstract:In order to further improve the precipitation forecast skill of the GRAPES Regional Ensemble Prediction System (GRAPES-REPS), this paper uses the high resolution assimilation analysis field of GRAPES-Meso model to generate the deterministic initial condition of GRAPES-REPS by dynamic up-scaling scheme (hereinafter referred to as the GRAPES-M-US scheme). On this basis, a series of 10 d ensemble prediction experiments were carried out. Then the results were compared with the deterministic initial condition which was generated by dynamic down-scaling scheme from the T639 global model assimilation analysis initial filed (hereinafter referred to as T639-G-DS scheme) and the corresponding ensemble forecast results. The test results of the precipitation forecasts were more focused on. The results show that the deterministic initial condition based on the GRAPES-M-US scheme has more small- and mesoscale information at lower levels compared with deterministic initial condition based on the T639-G-DS scheme. Low-level continuous variable forecast skill is better, the root mean square error (RMSE) and continuous ranked probability score (CRPS) of 850 hPa geopotential height and temperature show some improvements, but the improvement of middle- and high-level elements is not significant. The RMSE and CRPS of 10 m wind speed have obvious improvement, and the RMSE and CRPS of 2 m temperature are basically equal. For the precipitation forecast, the TS score, Brier score and AROC of the 24 h forecast are improved to some extent for light rain, moderate rain and heavy rain, and the rest of the forecast lead time is generally equivalent or slightly negative. In the case of severe rainfall on 7 August 2017, the forecast of rainfall area and intensity of severe precipitation show a certain “refinement” and “corrective” effect. In general, the GRAPES-M-US scheme shows a certain advantage over the T639-G-DS scheme, especially in the short-range precipitation forecast.
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基金项目:国家重点研发计划(2018YFC1507200)、重庆市气象局业务技术攻关团队项目(YWGGTD-201715)、公益性行业(气象)科研专项(GYHY201506005)和国家科技支撑计划项目(2015BAC03B01)共同资助
引用文本:
陈良吕,陈静,霍振华,夏宇,陈法敬,2019.两种确定性初值形成方案对集合预报技巧的影响研究[J].气象,45(6):745-755.
CHEN Lianglü,CHEN Jing,HUO Zhenhua,XIA Yu,CHEN Fajing,2019.Impact of Two Different Deterministic Initial Condition Formation Schemes on Ensemble Forecast Skills[J].Meteor Mon,45(6):745-755.