鹤壁市雷暴短时监测和临近预报流程

利用卫星云图数字化资料、雷达探测和雷电定位探测资料对雷暴天气进行短时监测 ,并与多种短期预报方法集成 ,建立时效为 3～ 6小时的雷暴临近预报流程 ,从而达到预测强对流天气之目的。     

基于循环神经网络的单站能见度短临预报试验

由于能见度具有局地性和复杂的非线性变化特征,一直是精细化预报的难点。人工神经网络对复杂变化过程的模拟能力较高,为解决这一难题提供了可能性。本文采用循环神经网络,利用福州气象观测站地面观测数据,建立了福州单站能见度短临预报模型,并就预报能力进行了评估。随机检验结果表明,在1 h、3 h、6 h时效上,循环神经网络的预报与观测的变化趋势一致性较好;均方根误差比基于实况的预报分别减小15.75%、31.66%、41.26%,说明具备较好的预报能力;平均绝对值误差比传统BP神经网络分别减小12.90%、24.45%、 38.99%,表明循环神经网络对能见度预报具有优势,为能见度的精细化短临预报提供了新途径。     

一种基于卫星遥感的临近预报方法

中尺度对流系统(MCS)是形成强对流天气的主要原因,云团在MCS生命周期中的分裂合并问题是临近预报的难点。为解决这一问题,本文提出了FCC方法,该方法使用质心位移和FY-2卫星数据预测多个对流单体的运动轨迹。多个案例分析证明,FCC算法在MCS的各个生命周期均能进行有效的预测,包括初生、成熟和消散阶段。此外,通过列联表方法验证了所提算法的有效性。     

多普勒天气雷达资料对中尺度模式短时预报的影响

利用中尺度模式ARPS(The Advanced Regional Prediction System)及其资料分析系统ADAS(ARPS Data Analysis System),将国内新一代多普勒雷达(CINRAD)反射率及径向风资料直接用于中尺度数值模拟,通过一次华北地区暴雨过程的模拟对比试验,分析了雷达资料对初始场的改进效果及其对模拟结果的影响,结果表明:(1)利用雷达径向风资料对初始风场进行调整后,自近地面到对流层顶的u,v,w都发生了变化,调整后的初始风场在对流层中层变化最大.(2)利用雷达反射率进行微物理调整和云分析能调整初始场中的云水信息,使得雷达回波附近3 km以下的水汽混合比(qv)增加,4 km以下的雨水混合比(qr)增加,对流层(约10 km以下)的云水混合比(qc)增加,4～9 km的对流层上部云冰混合比(qi)和雪混合比(qs)增加.ADAS通过非绝热初始化调整温度场,从而得到了一个动力和热力上平衡的初始场.(3)模拟的1 h雨量与实况的对比表明,同时利用雷达反射率和径向风改进过的初始场能明显增强3 h内的降水强度和落区预报,改善中尺度数值模式短时定量降水预报.模拟的1 h流场对比分析表明,经雷达径向风调整后,能够在初始场中增加气旋性涡旋等中小尺度风信息,明显减少模式的spin-up时间.(4)通过对雷达径向风和反射率对模式初始场和模拟结果影响的对比分析发现,雷达径向风主要是改进初始风场,而雷达反射率主要是改进初始场中的湿度参数,增加初始场中云水等的含量,调整温度场.通过模拟的6 h降水对比发现,利用雷达径向风调整初始场后,对降水模拟有一定的改进,但效果不甚明显,而雷达反射率资料对定量降水预报改进效果明显,同时使用雷达径向风和反射率资料改进初始场后对降水的模拟效果最明显.     

2011年盛夏石家庄一次短时暴雨分析

2011年7月26日石家庄市出现一次暴雨冰雹天气,其特点是500 h Pa及以上高空强冷空气导致高空形势在12 h内发生剧变,短波槽快速南下,致使探空观测和数值预报失灵。本文对其他监测资料进行分析,发现这种剧烈变化的天气有明显特征:卫星云图上河套北部逗点云系尾长而粗壮,有向南发展趋势,云系后部的暗区表明干冷空气侵入,与低层暖湿空气形成对流云,尾部断裂表明冷空气加速南下。单站要素变化显示,石家庄地面假相当位温比正常值高了8℃,出现异常不稳定能量。强对流天气发生在假相当位温密集带内,能量中心假相当位温最高达到90℃以上,100 km内假相当位温温差超过25℃,最大降雨出现在假相当位温密集带内。雷达回波呈西南—东北带状排列,前部最大强度为65 d BZ,强回波前形成阵风锋,正负最大速度均超过20 m/s,飑线自西向东移动,它的移向和发展程度决定降雨和冰雹的路径和强度。石家庄市区风向转变和形成地面辐合线分别较降水起始时间提前21 min和30 min。     

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.     

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.