Effects of Different Initial Fields on GRAPES Numerical Prediction

In this paper,a heavy rainfall process occurring in the Huaihe River Basin during 9-10 July 2005 is studied by the new generation numerical weather prediction model system-GRAPES,from the view of different initial field effects on the prediction of the model.Several numerical experiments are conducted with the initial conditions and lateral boundary fields provided by T213 L31 and NCEP final analyses,respectively. The sensitivity of prediction products generated by GRAPES to different initial conditions,including effects of three-dimensional variational assimilation on the results,is discussed.After analyzing the differences between the two initial fields and the four simulated results,the memonic ability of the model to initial fields and their influences on precipitation forecast are investigated.Analyses show the obvious differences of sub-synoptic scale between T213 and NCEP initial fields,which result in the corresponding different simulation results,and the differences do not disappear with the integration running.It also shows that for the same initial field whether it has data assimilation or not,it only obviously influences the GRAPES model results in the initial 24 h.Then the differences reduce.In addition,both the Iocation and intensity of heavy rain forecasted by GRAPES model Further is very close to the fact,but the forecasting area of strong torrential rain has some differences from the fact.For the same initial field when it has assimilation, the 9-12-,12-24-,and 0-24-h precipitation forecasts of the model are better than those without assimilation. All these suggest that the ability of GRAPES numerical prediction depends on the different initial fields and lateral boundary conditions to some extent,and the differences of initial fields will determine the differences of GRAPES simulated results.     

Recent Advances in Predictability Studies in China （1999-2002）

Since the last International Union of Geodesy and Geophysics (IUGG) General Assembly (1999), the predictability studies in China have made further progress during the period of 1999-2002. Firstly, three predictability sub-problems in numerical weather and climate prediction are classified, which are concerned with the maximum predictability time, the maximum prediction error, and the maximum allowable initial error, and then they are reduced into three nonlinear optimization problems. Secondly, the concepts of the nonlinear singular vector (NSV) and conditional nonlinear optimal perturbation (CNOP) are proposed,which have been utilized to study the predictability of numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be revealedby NSV and CNOP. Thirdly, attention has also been paid to the relations between the predictability and spatial-temporal scale, and between the model predictability and the machine precision, of which the investigations disclose the importance of the spatial-temporal scale and machine precision in the study of predictability. Also the cell-to-cell mapping is adopted to analyze globally the predictability of climate,which could provide a new subject to the research workers. Furthermore, the predictability of the summer rainfall in China is investigated by using the method of correlation coefficients. The results demonstrate that the predictability of summer rainfall is different in different areas of China. Analysis of variance, which is one of the statistical methods applicable to the study of predictability, is also used to study the potential predictability of monthly mean temperature in China, of which the conclusion is that the monthly mean temperature over China is potentially predictable at a statistical significance level of 0.10. In addition,in the analysis of the predictability of the T106 objective analysis/forecasting field, the variance and the correlation coefficient are calculated to explore the distribution characteristics of the mean-square errors.Finally, the predictability of short-term climate prediction is investigated by using statistical methods or numerical simulation methods. It is demonstrated that the predictability of short-term climate in China depends not only on the region of China being investigated, but also on the time scale and the atmospheric internal dynamical process.     

Comparative Experiments on the Effect of Radar Data Assimilation and Increasing Horizontal Resolution on Short-term Numerical Weather Prediction

To examine the effect of radar data assimilation and increasing horizontal resolution on the short-term numerical weather prediction, comparative numerical experiments are conducted for a Huabei (North China) torrential rainfall event by using the Advanced Regional Prediction System (ARPS) and ARPS Data Analysis System (ADAS). The experiments use five different horizontal grid spacings, i.e., 18, 15, 9, 6, and 3 km,respectively, under the two different types of analyses: one with radar data, the other without. Results show that, when radar data are not used in the analysis (i.e., only using the conventional observation data), increasing horizontal resolution can improve the short-term prediction of 6 h with better representation of the frontal structure and higher scores of the rainfall prediction, particularly for heavy rain situations. When radar data are assimilated, it significantly improves the rainfall prediction for the first 6 h, especially the locality and intensity of precipitation. Moreover, using radar data in the analysis is more effective in improving the short-term prediction than increasing horizontal resolution of the model alone, which is demonstrated by the fact that by using radar data in the analysis and a coarser resolution of the 18-km grid spacing, the predicted results are as good as that by using a higher resolution of the 3-km grid spacing without radar data. Further study of the results under the radar data assimilation with grid spacing of 18-3 km reveals that the rainfall prediction is more sensitive to the grid spacing in heavy rain situations (more than 40 mm) than in ordinary rain situations (less than 40 mm). When the horizontal grid spacing reduces from 6 to 3 km, there is no obvious improvement to the prediction results. This suggests that there is a limit to how far increasing horizontal resolution can do for the improvement of the prediction. Therefore, an effective approach to improve the short-term numerical prediction is to combine the radar data assimilation with an optimal horizontal resolution.     

和预报员谈数值预报

用尽可能非专业的词语,向预报员介绍数值预报的成就、问题与应用。在简单回顾数值预报发展历史的基础上,重点分析了近十几年来数值预报的主要技术进步与有待解决的问题,对比了数值预报与主观经验预报的各自优势与不足,提出了优势互补对于提高业务预报的重要性。还分析了数值预报的技术进步对于数值预报产品释用的影响,以及预报员参与数值预报发展的可能性与必要性。     

业务化数值天气预报50年:科学传承与未来展望

数值天气预报是气象科学在20世纪创造的巨大成就，它给出的计算天气的可行性方案不仅服务于日常生活，也改变了人们对天气预报的认识。在数值天气预报业务开展50年之际，回顾了数值天气预报在科学思想上的脉络，对该领域未来发展进行了展望。     

我国西北高原地区数值预报的几个科学问题

分析了与我国西北地区数值预报相关的几个主要科学问题。指出随着数值预报模式分辨率的提高与预报的精细化,需要关注不同尺度地形对于大气的动力与热力作用的准确数值描述,包括过去被过滤掉的一些动力过程的描写的精度并解决好次网格地形的作用的参数化。还分析了高原地区资料同化的特殊性与集合预报技术的可能应用等。     

Development of 1km-Scale Operational Model in South China

To support short-range weather forecast, a high-resolution model (1km) is developed and technicallyupgraded in the South China Regional Center, including the improvement of the 3D reference scheme and predictor-corrector method for Semi-Implicit and Semi-Lagrangian (SISL) in model dynamical core, as well as the improvementof physical parameterization. Furthermore, the multi-process parallel I/O and parallel nudging techniques are developedand have facilitated rapid updating in the assimilation prediction system and fast-output post processing process. Theexperimental results show that the improved 3D reference scheme and upgraded physic schemes can effectively improvethe prediction accuracy and stability with a longer integration time step. The batch test shows that the precipitationforecast performance of 1-km model is significantly better than that of 3-km model. The 1-km model is in operation withrapidly updating cycle at 12-minute intervals, which can be applied to short-range forecast and nowcasting application.     

湖南省有限区域数值天气预报系统模拟试验

介绍了湖南省有限区域数值天气预报系统，该系统试用结果表明，系统具有较强的稳定性和实用性，降水的时空分布的预报效果较好。数值模拟试验结果表明，模拟降水预报对积云参数化方案、边界层参数化方案、辐射参数化方案等比较敏感。     

数值天气预报模式产品在预报业务中的应用

介绍了数值预报模式产品性能的基本特征,讨论了模式产品误差的地理、季节和层次分布、不同尺度模式产品的可预报性、模式输出要素及物理量、指数的误差特点,并根据目前业务中常见的错误预报思路探讨了应用数值预报模式产品的合理思路,指出现代预报业务中预报员的作用。认为现代预报员应该了解几种基本的数值预报模式的特性及基本原理,集合各种模式的优点,综合本地预报经验,有效利用海量数值预报产品,做出更高质量的预报结果。     

雷达资料和数值模式产品融合技术研究

以雷达外推为基础,配合中尺度数值模式产品作为环境场,提出两种新的雷达资料和数值模式融合技术:动态权重融合法和趋势演变叠加法。且在动态权重融合法中提出用正弦权重、双曲正切权重以及实时滚动权重三种方法计算权重。使用上海及周边地区2009年6月21日的一次对流过程进行个例分析及误差检验,结果表明:利用这两种方法进行融合后的预报结果与雷达外推和数值模式预报结果相比均有所改进,特别是动态权重融合法中的正弦权重和双曲正切权重对于预报结果的改进尤为明显,融合后的结果更接近实况,表明动态权重融合法和趋势演变叠加法这两种方法是有效可行的,对短时临近预报技术研究有较高的参考价值。     

2001年春季寒潮天气中数值预报的应用

2001年4月6-9日，新疆出现了一次全疆性寒潮天气过程。阿克苏地区8县1市普遍出现了强风暴、强降温。但由于我台对数值预报产品的正确释用，成功地报出了这次天气，体现了数值预报的优点。     

神威机上集合数值天气预报系统功能概述

文章对自主研制的基于神威巨型机的并行化集合数值天气预报系统的研制背景、系统组成、主要技术特点和应用发展前景作了一简要介绍。     

并行技术在神威集合数值天气预报系统中的应用

文章讨论了基于神威巨型机的并行化集合数值天气预报系统中实现的各种并行算法, 性能分析结果表明并行方案最大限度的利用了神威机的处理器资源, 设计的并行算法效率较高, 满足了实时业务运行的时效要求。