兰州市区地质灾害与暴雨强度

对兰州市区地质灾害的分布、成因、特点进行了分析,着重研究了兰州市区山洪灾害和强度暴雨的时空分布、产生强度暴雨的天气系统以及山洪灾害和暴雨强度之间的关系,确定了临界降雨量指标,提出了防治对策,这对我市开展地质灾害气象预报预警工作是十分必要的。     

柳州市暴雨渍涝气象预警系统

介绍柳州市暴雨渍涝气象预警系统的技术路线及原理,该系统利用城市暴雨内涝灾害仿真模型,并结合了柳州市的地理特征、城市规划、排水系统、防洪工程等多方面的非气象资料,具备一定的暴雨渍涝动态监测预报能力,对拓展城市灾害预报服务领域,提高城市暴雨渍涝灾害监测、预报、灾害风险评估水平具有一定的参考作用。     

Selection of regional historical rainfall time series as input to urban drainage simulations at ungauged locations

It has become established practice during the past 20 years to use high-resolution historical rainfall time series as input to hydrological model packages for detailed simulation of urban drainage systems. However, sufficiently long rain series are rarely available from the exact catchment in question and simulations are hence often based on available rain series from other locations. Extreme rainfall properties of importance to the performance of urban storm drainage systems vary significantly even in regions with only minor physiographic differences. Part of this variation can be explained by regional variations of the mean annual rainfall and the remaining statistical residue can be interpreted as statistical uncertainty.In Denmark, more than 75 high-resolution rain gauges are installed across a total area of 43,000 m. About 40 gauges had sufficiently long records to be included in a comprehensive national investigation where newly developed statistical regionalisation procedures were used to model the regional variation of extreme rainfalls. On this basis, a spreadsheet model was made available for estimation of extreme design rainfalls and the associated uncertainty at any location in the country. Statistics were furthermore computed to classify historical rainfall time series according to the developed regional model, and this makes it possible to assess the uncertainty related with using different historical rain series for simulations at ungauged locations.This research indicates that use of historical point rainfall data at ungauged locations introduces a significant uncertainty that is largely overlooked in today's practice. The engineering recommendation is to select historical rain series based on an evaluation of the local physiographic characteristics (e.g., the mean annual rainfall) and a (pre-defined) desired safety level of the simulations.     

淮河流域(河南段)连续性暴雨天气分型及环流背景

利用19812016年68月河南省淮河流域64个国家自动观测站逐日2020时日降水量资料、常规高空探测和地面观测资料等对淮河流域连续性暴雨时间分布特征、影响系统等进行分析和天气分型,结果表明:1)36年淮河流域共发生45次连续性暴雨,2000年的最多,19982008年是高发期,近10年较少,年出现次数无明显减少趋势,存在2~4年和4~6年两个周期;7月连续性暴雨次数最多,6月的最少,旬分布呈正态分布;最长连续时间5天,连续2天的最多。2)影响系统主要有切变线和高低空急流,高空急流在方向转换的过程中,降水有24h左右的减弱期,低空急流有明显的日变化特征,夜间加强,白天减弱。3)连续性暴雨按照500hPa影响系统,分为低槽型、副高边缘型、西北低涡型三类。4)以不同类型的3次典型连续性暴雨为例,从大尺度环流背景、高度距平场、水汽输送、高低空急流等方面探讨了连续性暴雨的维持成因,3次连续性暴雨的发生与异常的500hPa大气环流、高低空急流、切变线和持续偏强的水汽输送等有关。     

两个相似路径台风残余造成局地特大暴雨的成因机制和能量收支对比分析

本文利用ERA-Interim 0.5°×0.5°再分析资料、自动站小时和分钟加密资料、风云2G（FY-2G）卫星红外云图及多普勒雷达和风廓线雷达资料对2015年路径高度相似的“苏迪罗”和“杜鹃”台风在浙江沿海引发的局地特大暴雨进行对比分析。这两次降水过程都是在台风减弱为热带低压甚至残压并深入内陆远离浙江沿海后发生的。结果表明,“苏迪罗”降水过程是由低层强东南和偏南急流长时间辐合加上有利地形共同作用导致的;经向环流背景下来自季风持续的水汽输送有利于“苏迪罗”维持较长的生命史和稳定的降水。“杜鹃”残压特大暴雨的触发系统则是高纬地面冷高压底部的东东北出流南下与“杜鹃”北象限的东东南风交汇形成的中尺度倒槽;纬向环流和强盛副热带高压造成的弱引导气流及夏季风南撤和低涡卷挟造成的水汽通道断裂是“杜鹃”登陆后快速减弱为残压和降水维持时间较短的原因。两次台风降水过程中均无外部动能输送和来自有效位能的动能转换。动能收支的主要影响因子为中低层局地次网格运动间的能量转换、旋转风和散度风效应及下垫面的摩擦耗散。所以,虽然“杜鹃”的对流有效位能很小,但仍可造成强对流和特大暴雨。此外,降水过程中释放的凝结潜热造成的局地非绝热加热使气柱中显热能大量累积,促使地面中小尺度涡旋和倒槽不断加深,造成降水的增幅。     

汛期西南涡暴雨的数值模拟研究

利用西南区域数值预报模式系统SWCWARMS,结合全国汛期高空加密观测资料,对2013年6月29—30日的一次西南涡暴雨过程进行数值模拟和敏感性试验。结果表明,与控制试验相比,同化试验模拟的降雨与实况更为接近,并成功模拟出四川东部的强降雨中心,对于西南涡的模拟,同化试验西南涡出现时间更早,强度更强。并且,通过两组试验初值差异对比发现,同化试验初值在四川盆地对流层中低层表现出更强的低压,更强的涡度以及更强的旋转风扰动,四川盆地西部边坡也存在更强的上升气流,这都有利于西南涡的发生、发展。另外,同化汛期高空加密观测资料对强降雨中心单站的预报改进也较明显。因此,加强汛期加密气象观测,有利于揭示西南涡的发生、发展及其降雨天气影响,也有助于提升数值预报业务技术水平。     

高低空急流在云南大范围暴雨过程中的作用及共同特征

通过对1980—1991年出现的46次云南全省性大范围暴雨过程的主要影响系统进行分型,找出云南暴雨的主要影响系统,利用美国国家环境预测中心NCEP再分析资料,对暴雨出现次数最多的11次冷锋切变型全省性大范围暴雨过程进行合成分析,揭示了在冷锋切变环流形势下云南大范围暴雨发生前后对流层高低空急流或强风速带的演变特征及其与大范围暴雨发生之间的关系,找出了它们的共同特征,并提取造成云南暴雨的强信号,以期对今后的暴雨预报提供依据。     

强降水云物理过程的三维数值模拟研究

利用改进的三维完全弹性强对流云模式,模拟了1998年7月21日晨发生在武汉附近的特大暴雨个例,结果显示,该模式模拟得到的降雨量与实测接近,计算得到的雷达回波强度最大值也与实际观测相一致,说明该模式对实际对流性强降水具有较好的模拟能力.在此基础上,通过冷云和暖云两种不同情况的比较分析,研究了云微物理过程在强降水形成过程中的作用.模拟结果表明,详细云物理过程的考虑对深入理解武汉这次强降水的形成过程是有意义的.该个例雨水的形成主要是暖雨过程,冰相微物理过程对该对流性强降水过程的发展和演变有重要的促进作用.在形成雨水的冷相过程中,霰的融化及其在0 ℃层下碰并云水形成雨水的过程是主要的.模式云在0 ℃层附近存在明显的雷达回波亮带,亮带中间含有强回波核和及地下挂回波.分析表明,这种强回波核和下挂回波的产生主要是由于冰相粒子在0 ℃层融化形成的,融化的冰相粒子与云滴碰并又加速雨水的产生.在这些融化的冰相粒子中,贡献最大的是霰粒.文中还分析了该强降水暴雨云维持长时间强降水的云物理机制.在低层大气温暖高湿和环境风切变有利条件下,倾斜上升气流和下沉气流之间的准稳态结构可能是暴雨强降水得以长时间维持的重要原因.     

NUMERICAL PREDICTION OF AN EXTREME RAINSTORM OVER THE PEARL RIVER DELTA REGION ON 7 MAY 2017 BASED ON WRF-ENKF

An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm.