Abstract:

To improve the fine-grained forecasting and early warning level of high-impact weather in cities, this paper utilizes 7 categories of data from the HMB-KPS millimeter-wave cloud radar at Rongcheng meteorological station of Xiong’an, including radar reflectivity factor, radial velocity, etc and surface meteorological observations, as well as weather analysis, radar echo image morphology analysis and other methods to analyze the major high-impact weathers in Xiong’an from January 2020 to December 2023， such as torrential rains，strong winds，fog，haze，and sand-dust weathers.The results are as follows: 1) The millimeter-wave cloud radar clearly and stereoscopically detects the structural distribution of cloud systems in high-impact weather including precipitation. In spring, summer and autumn, when clouds with echoes intensity equal to or more than 21 dBZ (15 dBZ in winter) and vertical extension height equal to or more than 5 km (2 km in winter) appear, and the lowest cloud base reaches 150 m, it can be considered as the characteristic index of start time of surface precipitation, and the average time advance is about 20 minutes. Conversely，when echo intensity weakens and cloud base height rises, precipitation tends to end. Among all levels of precipitation events, torrential rains have the maximum vertical extensions, liquid water content, etc. 2) When the extension height of the echo top reaches more than 8 km and then the height of the cloud top falls rapidly to less than 2 km, the ground is prone to strong winds of more than 8 magnitudes. The echo characteristic of precipitation accompanied by strong winds is that obvious U or V notch is formed in the strong echo area, and the maximum radial velocity in the notch area is 12.5 m·s^-1. 3) Cloud radar inversion droplet spectrum data products can better reflect the particle distribution characteristics of precipitation with different levels. The Vertically Integrated Liquid Water (VIL) has an early warning significance for precipitation and wind, and the advance is 0-30 min or more. 4) For non-precipitation high-impact weather (fog, haze, sand-dust), the millimeter-wave radar echoes are overall weaker, with indistinct transitions between weather phenomena. However, during weather transitions, the radar can rapidly and clearly detect the precipitation clouds, improving fine-grained forecasting and early warning capabilities of precipitation.

Key words: millimeter-wave cloud radar, torrential rain, strong wind, high impact weather, forecasting and early warning

摘要：

为提高城市高影响天气的精细化预报预警水平，利用雄安新区2020年1月—2023年12月容城气象站Ka波段毫米波云雷达反射率因子、径向速度等7种产品及地面气象资料和天气学、雷达回波图像形态分析等方法对雄安新区暴雨、大风、雾、霾及沙尘等高影响天气进行分析。结果表明：1）云雷达对含降水的高影响天气云体探测结构清晰、垂直分布特征直观。当春、夏、秋季回波强度≥21 dBZ（冬季≥15 dBZ）、伸展高度≥5 km（冬季≥2 km）的云体出现，且云体最低高度达150 m时，可看作地面降水将出现的特征指标，时间提前量平均达20 min左右，当回波强度减弱、云底高度抬升，降水趋于结束；各级降水中，暴雨的强回波伸展高度、云水含量等最大。2）当回波顶伸展高度达8 km之上而后快速下落至云顶高度≤2 km时，地面易出现8级以上大风，降水伴大风的回波特点为强回波区中形成明显的U或V型缺口，缺口区最大径向速度达12.5 m·s^-1左右。3）云雷达反演滴谱数据产品可较好反映各级降水的粒子分布特征；垂直积分液态水含量（Vertically Integrated Liquid Water，VIL）对降水伴大风有预警指示意义，提前量0~30 min或以上。4）非含降水的高影响天气（雾、霾、沙尘等），云雷达回波强度等整体偏弱，各天气现象之间界限不清晰，但与降水天气发生转换时云雷达能快速、清晰地探测出降水云体，有利于提升降水的精细预报预警能力。

关键词: 毫米波云雷达, 暴雨, 大风, 高影响天气, 预报预警