贺兰山东麓极端暴雨的中尺度特征

利用近10年宁夏逐时自动气象站降水、银川CD雷达、FY-2、探空和ECMWF再分析0.125°×0.125°等高分辨率多源气象资料,在中尺度系统分型基础上,对比分析贺兰山东麓6次极端暴雨的中尺度特征。结果表明:(1)低空偏(东)南急流夜间增强并配合贺兰山地形,在东坡山前触发或增强了暴雨中小尺度系统,造成地形处降水增幅,极端暴雨都是伴有短时强降水的对流性暴雨,主要集中在东坡山前,中心在山洪沟口,夜雨特征显著。(2)环境场都满足对流性暴雨的3个基本条件:700 hPa(东)南急流将暖湿水汽输向暴雨区,低层高温高湿促进了大气不稳定与动力、热力、地形抬升触发机制;深对流过程850 hPa无明显急流,水汽主要来自孟加拉湾,水汽输送受限,但大气稳定度更低,更有利于对流性暴雨发生,混合对流过程850 hPa与700 hPa急流路径重合,水汽来自孟加拉湾、南海、黄海和渤海,水汽输送更充沛,更有利于持续性暴雨产生。(3)极端暴雨主要有暖区对流降水、锋面对流降水、锋区层状云降水3种性质;暖区对流主要在山区,地形抬升是触发机制,锋面对流的触发是低层暖湿气流沿着冷垫抬(爬)升,平原和山区皆有;对流系统的移动与低层风场一致,山区和平原分别沿山体和低空急流轴传播,通常移动与传播方向平行,山区低层为偏东风时,移动与传播近似垂直,列车效应明显。(4)线型对流系统过程冷空气弱,以暖区或(和)锋面对流性降水为主,对流系统在山前沿山体传播形成组织化程度高的带状线型回波,移动与传播有平行有垂直,受地形抬升作用,对流系统在山前稳定少动、发展强盛,降水历时短、范围小、雨强大、有间歇性,3~4 h的累计雨量占过程总量的85%左右,区域平均雨量远小于暴雨量级,地形性强对流暴雨特征凸显。(5)非线型对流系统过程冷空气强,以锋面对流性降水和锋区层状云降水为主,对流系统在山前和平原沿山体和急流轴传播和移动形成非线型回波,平原地区传播与移动平行,山区两者垂直,对流系统组织化程度不高、移速快、强度弱,降水历时长、范围大、雨强小,连续降水累计雨量大,区域平均雨量接近或达到暴雨量级,混合性降水特征明显。(6)降水强度R与CAPE增幅、回波强度Z、强回波持续时间、回波顶高、液态水含量呈正相关,与TBB呈负相关,相关性在深对流过程更清晰;Z≥40 dBZ时,Z-R满足关系式:R=3.67×10-8Z5.222+4.835。     

智能网格预报时空协调一致关键技术研发

自2016年起,我国大力推进气象业务向"智能化、无缝隙、精准化"发展。2017年宁夏积极推进智能网格预报业务体系建设,在网格预报智能订正、主客观融合订正、格点/站点/落区一体化、灾害天气智能识别等方面开展了一些尝试,取得了一定的成果,目前各项成果均引入到宁夏智能化天气预报业务平台中。其中一项关键技术,是智能网格预报的时空协调一致技术。该项技术在主客观融合订正、格点/站点/落区一体化中发挥了重要作用。本文重点针对这一关键技术的设计思路和实现方法进行介绍、讨论。     

Circulations and Thermodynamic Characteristics of Different Patterns of Rainstorm Processes in the Eastern Foot of Helan Mountain

Based on the observational hourly precipitation data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) products from 2006 to 2020, 22 rainstorm processes in the eastern foot of Helan Mountain are objectively classified by using the hierarchical clustering method, and the circulation characteristics of different patterns are comparatively analyzed in this study. The results show that the occurrences of rainstorm processes in the eastern foot of Helan Mountain are most closely related to three circulation patterns. Patterns I and III mainly occur in July and August, with similar zonal circulations in synoptic backgrounds. Specifically, the South Asia high and the western Pacific subtropical high are stronger and more northward than those in normal years. The frontal systems in westerlies are inactive, while the water vapor from the ocean surface in the south is mainly transported to the rainstorm area by the southerly jet stream at 700 hPa. The dynamic lifting anomalies are relatively weak, the instability of atmospheric stratification is anomalously strong, and thus the localized severe convective rainstorm is more significant. Comparatively, rainstorm processes of pattern I are accompanied by stronger and deeper ascending motions, and the warm-sector rainstorm is more extreme. Pattern III shows a stronger and deeper convective instability, accompanied by larger low-level moisture. Rainstorm processes of pattern II mainly occur in early summer and early autumn, presenting a meridional circulation pattern of high in the east and low in the west in terms of geopotential height. Moreover, the two low-level jets transporting the water vapor northward from the ocean on the east of China encounter with the frontal systems in westerlies, which makes the ascending motion in pattern II anomalously strong and deep. The relatively weak instability of atmospheric stratification causes weak convection and long-lasting precipitation formed by the confluence of cold air and warm air. This study may help improve rainstorm forecasting in arid regions.     

基于雷达回波强度面积谱识别降水云类型

基于谱分析原理提出了雷达回波强度面积谱的概念及算法,利用宁夏银川多普勒天气雷达回波资料,分析了不同性质降水云的雷达回波强度面积谱,并根据不同性质降水云雷达回波强度面积谱特征,提出了基于雷达回波强度面积谱识别降水云类型的方法,利用强回波面积（回波强度不小于40 dBZ的回波面积）占总回波面积百分比和基本降水回波面积（回波强度不小于20 dBZ的回波面积）占总回波面积百分比作为降水云类型判别的主要因子,提炼出基于雷达回波强度面积谱特征参数的层状云、积层混合云、对流云等不同类型降水云的判别指标,建立了基于雷达回波的降水云类型自动判识模型。利用该模型对2016-2017年6次强降水过程进行了降水云类型判别试验,模型准确判别出6次强降水过程中2次为对流云降水、4次为混合云降水,判别结果较好地反映了降水云类型,验证了判识方法的可行性。     

基于ECMWF的两种温度客观预报订正方法及评估

依据ECMWF细网格模式2019—2020年20:00起报未来24-216h的0.05×0.05°分辨率格点日最高、最低温度和国家气象信息中心格点温度实况资料，采用“动态训练、择优选取”的基本原则，利用递减平均法（DAM）和径向基函数神经网络方法（RBFNN）对温度进行客观预报订正，并与中央台指导预报（NMC）和EC模式预报产品进行格点检验对比分析。结果表明：（1）通过DAM和RBFNN订正后的24—216h日最高、最低温度预报准确率提高3.9～7.8%，均为“正”技巧，对预报准确率偏低的月份预报时效订正效果更显著，且夏、秋季最高温度预报订正效果较好，冬季最低温度订正能力较强；（2）分区域预报检验来看，订正后的最高、最低温度预报产品除沙坡头区的最高温度预报和贺兰山的最低温度预报误差偏大外，其他区域的误差基本都小于2℃，特别是对强降温、寒潮天气的温度预报订正效果明显优于NMC和EC模式预报产品，对预报业务有一定的参考价值。