An Overview of Nowcasting Development, Applications, and Services in the Hong Kong Observatory

The Hong Kong Observatory （HKO） has been developing a suite of nowcasting systems to support op- erations of the forecasting center and to provide a variety of nowcasting services for the general public and specialized users. The core system is named the Short-range Warnings of Intense Rainstorm of Localized Systems （SWIRLS）, which is a radar-based nowcasting system mainly for the automatic tracking of the movement of radar echoes and the short-range Quantitative Precipitation Forecast （QPF）. The differential, integral （or variational）, and object-oriented tracking algorithms were developed and integrated into the nowcasting suite. In order to predict severe weather associated with intense thunderstorms, such as high gust, hail, and lightning, SWIRLS was enhanced to SWIRLS-II by introduction of a number of physical models, especially the icing physics as well as the thermodynamics of the atmosphere. SWIRLS-Ⅱ was further enhanced with non-hydrostatic, high resolution numerical models for extending the forecast range up to 6h ahead. Meanwhile, SWIRLS was also modified for providing nowcasting services for aviation community and specialized users. To take into account the rapid development of lightning events, ensemble nowcasting techniques such as time-lagged and weighted average ensemble approaches were also adopted in the nowcasting system. Apart from operational uses in Hong Kong, SWIRLS/SWIRLS-Ⅱ was also exported to other places to participate in several international events such as the WMO/WWRP Forecast Demon- stration Project （FDP） during the Beijing 2008 Olympics Games and the Shanghai Expo 2010. Meanwhile, SWIRLS has also been transferred to various regional meteorological organizations for establishing their nowcasting infrastructure. This paper summarizes the history and the technologies of SWIRLS/SWIRLS-Ⅱ and its variants and the associated nowcasting applications and services provided by the HKO since the mid 1990s.     

Ensemble rainfall forecasting with numerical weather prediction and radar‐based nowcasting models

The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd.     

重庆强对流短临业务评分方法

结合重庆本地实际情况,以区/县为单位对强对流中出现的短历时强降水、阵性大风及雷电进行业务质量定量评估.短历时强降水、阵性大风基于加密站观测资料采用分级的方式来评定,对雷电的评定基于ADTD系统观测到地闪资料并判断所在区/县是否有地闪出现.介绍了重庆本地强对流短临业务评分方法及开发的评分软件.从2011年的评分结果看,该评分方法在重庆本地是比较合理的,在业务应用上是可行的.     

提高新一代天气雷达在临近预报中准确率的分析

文章应用新一代天气雷达资料,并结合天气图、T-logp图等资料,对发生于2011年6月13日内蒙古西部巴彦淖尔市东部地区的一次局地强对流天气过程进行了分析。通过分析雷达冰雹概率、垂直累积含水量、回波顶高、风暴追踪信息等产品以及自动站天气实况等发现,用于短时临近预报的雷达冰雹概率及风暴追踪信息产品在该次强对流天气过程中与天气实况并不能很好地符合。其原因:一方面与雷达对风暴的跟踪和SCIT算法有关,另一方面表明天气背景以及短时强对流天气所具有局地性特点在短时临近预报中未能充分考虑。通过该个例的分析,对于业务人员认识本地区的强对流天气发生特点并提高预报准确率具有重要意义。     

两次降雪天气过程预报中边界层风廓线雷达资料的应用

通过分析2009年10月31日至11月1日和2009年11月9-10日北京两次不同类型降雪天气过程中海淀边界层风廓线仪数据发现:①降雪开始前2h内底层偏东气流建立,且该气流里均有风速突然加强的现象,这对短时临近预报中预报降雪的起始时间有一定参考价值;②700 hPa以上出现冷平流或者冷平流加强且高度降低,也是降雪即将开始的一个特征;③风廓线资料计算得到的温度平流廓线可以较好的反应大气稳定度情况,为判断降雪是否为对流性降雪提供可靠依据.在临近预报中加强风廓线和温度平流的监测,对临近转折性天气的预报有指示意义.     

北京雷暴大风气候特征及短时临近预报方法

北京地区雷暴大风的预报准确率低而且时效短.为了提高对这种灾害性天气的预警能力,在气候统计的基础上,研究了潜势预报方法和临近预报算法.对1998-2007年134个雷暴大风过程的统计结果表明,北京地区绝大多数的雷暴大风具有下击暴流特征,而且冰雹的落区附近也是大风的爆发区之一.因此,负浮力的作用和对冰雹具有指示性意义的因子是研究雷暴大风预报方法应主要考虑的因素.500hPa环流背景分析表明,尽管绝大多数雷暴大风爆发时对流层中层有干空气侵入,但是还有少数个例产生在偏南暖湿气流中.目前,对后一类大风产生的机制仍然不清楚.研究表明,当对流层中层有干空气侵入时,有利于雷暴大风出现的环境条件是:下沉气流具有较大的不稳定性,同时对流层低层环境大气的温度直减率较大.此外,还讨论了经验指数--大风指数在北京地区的应用.基于上述的研究,形成了北京地区雷暴大风短时潜势预报方法,还使用相关分析和多元回归分析技术建立了基于雷达观测和环境条件的雷暴大风临近预报方程.个例分析表明,临近预报方程对于飑线和弓形回波等带来的地面大风具有一定的预报能力.     

基于云团特征的短时临近强降水预报技术

通过分析2005-2008年影响浙江的梅汛期强降水云团特征,将云团分为偏北型、居中型和偏南型,研究这三种类型云团云顶亮温与地面1小时强降水极值和10mm/h以上降水覆盖面积关系,结果表明偏南型和偏北型云团有较多相似特征,而居中型云团较其他两种云团则有较多相反特征.通过分析1小时强降水相对于云团中心移动路径的落区,指出梅汛期云顶1小时变温和亮温梯度与地面1小时强降水落区无明显配对模型.随后利用天气形势场资料,分析强降水云团与环境要素场的关系,指出云顶亮温的宏观特征与中高层的垂直速度、水汽通量密切相关,最后尝试建立三种类型强降水云团成熟阶段云顶亮温和地面降水人工神经网络预报方程,给预报员提供参考.     

Application of Radar Reflectivity Factor in Initializing Cloud-Resolving Mesoscale Model. Part Ⅱ: Numerical Simulation Experiments

Microphysics elements and vertical velocity retrieved were incorporated using the nudging method into the initial data assimilation of GRAPES (Global/Regional Assimilation and Prediction System) model.Simulation experiments indicated that nudging technique was effective in forcing the model forecast gradually consistent to the observations, yielding the thermodynamically and dynamically balanced analysis field. As viewed from the simulation results, water vapor is vital to precipitation, and it is a governing factor for the amount and duration of precipitation. The initial cloud water, rain water, and vertical velocity determine the strength distribution of convection and precipitation at the beginning time of forecast; the horizontal wind field steers the motion of the mesoscale weather system embedded in and impacts the position of precipitation zone to a large extent. The simulation experiments show that the influence of the initial retrieval data on prediction weakens with the increase of forecast time, and within the first hour of forecast, the retrieval data have an important impact on the evolution of the weather system, but its influence becomes trivial after the first three hours. Changing the nudging coefficient and the integral time-spacing of numerical model will bring some influences to the results. Herein only one radar reflectivity was used, the radar observations did not cover the whole model domain, and some empirical parameters were used in the retrieval method, therefore some differences still lie between simulation and observation to a certain extent, and further studies on several aspects are expected.     

奥运短时临近预报实时数据处理

详细分析了目前短时临近预报系统对自动气象站数据质量控制、探测数据更新频率、组网雷达时间同步观测与基数据实时传输、探测数据的实时传输技术、基于目录监控的数据监控与分发机制、基于开源的软件开发、数据格式等方面的需求.在此基础上,建立了北京奥运短时临近预报数据快速收集处理系统并已经投入业务运行,该系统实现了探测数据的实时传输、组网雷达时间同步观测和基数据实时传输、基于消息驱动的数据实时监控和分发、探测数据格式规范化等功能,基本满足北京2008年奥运短时临近预报系统的数据预处理业务需求.