Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20 - 30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23 - 24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16 - 18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

Spatial Pattern Difference of Contribution between Short and Long-duration Heavy Rainfall to Total Heavy Rainfall in China from 1961 to 2015

Many regions are pounded with heavy rainfall, causing flood, casualties, property damage and severe destruction to ecosystem in multiple urban areas. Frequent occurrence of extremely heavy precipitation event under the background of global climate change has caused terrible harm on economic and social development, life security, ecosystem, etc.;brought profound impact on sustainable development of disaster area;become a key factor of global and regional disasters and environmental risk;and been widely concerned by academic circle and all sectors of the society. So severe disasters caused by extreme precipitation events have attracted more and more attention, while the relationship between heavy rainfall with different duration and total heavy rainfall has become the hottest scientific frontier issue. Contribution of heavy rainfall with different duration to the total heavy rainfall has significant spatial differences. Here we used daily rainfall data from 1961 to 2015 of 659 meteorological stations in China. When the rainfall is greater than 50 mm in 24 hours, that is a heavy rainfall event. Heavy rainfall only lasting one day is defined as short- duration heavy rainfall, while heavy rainfall lasting more than two days is defined as long-duration heavy rainfall. Results indicated that: on the basis of duration days defined long-duration heavy rainfall, on the spatial distribution, total rainfall, total heavy rainfall and short-duration heavy rainfall showed "increasing-decreasing-increasing" from the southeast coast to northwest inland in China from 1961 to 2015, and on the whole meteorological station with increasing trend predominant. In the meantime, long-duration heavy rainfall showed "increasing-decreasing" spatial pattern, and on the whole meteorological station with decreasing trend predominant. We detected that there was a belt of becoming drought from northeast to southwest. The contribution of total heavy rainfall to total rainfall as well as long-duration heavy rainfall to total heavy rainfall showed "high in southeast-low in northwest" spatial distribution pattern. On the contrary, the contribution of short-duration heavy rainfall to total heavy rainfall showed "low in southeast-high in northwest" spatial distribution pattern. The contribution trend of total heavy rainfall to total rainfall and short-duration heavy rainfall to total heavy rainfall showed "increasing-mosaic with increasing and decreasing-increasing" spatial distribution pattern from northeast to southwest, and on the whole meteorological station with increasing trend predominant. On the contrary, the contribution trend of long-duration heavy rainfall to total heavy rainfall showed mosaic with increasing and increasing in the northeast, slightly decreasing in the southwest, and on the whole meteorological station with decreasing trend predominant. There was a climate transition zone from northeast to southwest, which was essentially coincident with the arid zone. The results suggested that the precipitation in China was changing to extremely accompanied by short-duration storm increased significantly. Chinese heavy rainfall especially the increase of short-duration heavy rainfall suggests that human activity is likely to be triggered an increasing in extreme precipitation.

Spatiotemporal Characteristics of Rainfall over Different Terrain Features in the Middle Reaches of the Yangtze River Basin during the Warm Seasons of 2016–20

Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.

A time fractional model to represent rainfall process

This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.

Statistical Characteristics of Environmental Parameters for Warm Season Short-Duration Heavy Rainfall over Central and Eastern China

Water vapor content, instability, and convergence conditions are the key to short-duration heavy rainfall forecasting. It is necessary to understand the large-scale atmospheric environment characteristics of short- duration heavy rainfall by investigating the distribution of physical parameters for different hourly rainfall intensities. The observed hourly rainfall data in China and the NCEP final analysis （FNL） data during 1 May and 30 September from 2002 to 2009 are used. NCEP FNL data are 6-hourly, resulting in sample sizes of 1573370, 355346, and 11401 for three categories of hourly rainfall （P） of no precipitation （P 〈 0.1 mm h-1）, ordinary precipitation （0.1≤ P 〈 20 mm h-1）, and short-duration heavy rainfall （P ≥ 20.0 mm h-1）, respectively, by adopting a temporal matching method. The results show that the total precipitable water （PWAT） is the best parameter indicating the hourly rainfall intensity. A PWAT of 28 mm is necessary for any short-duration heavy rainfall. The possibility of short-duration heavy rainfall occurrence increases with PWAT, and a PWAT of 59 mm is nearly sufficient. The specific humidity is a better indicator than relative humidity. Both 700- and 850-hPa relative humidity greater than 80% could be used to determine whether or not it is going to rain, but could not be used to estimate the rainfall intensity. Temperature and potential pseudo-equivalent temperature are also reasonable indicators of short-duration heavy rainfall. Among the atmospheric instability parameters, the best lifted index （BLI） performs best on the short- duration rainfall discrimination; the next best is the K index （KI）. The three rainfall categories are not well recognized by total totals （TT） or the temperature difference between 850 and 500 hPa （DT85）. Three- quarters of short-duration heavy rainfall occurred with BLI less than -0.9, while no short-duration heavy rainfall occurred when BLI was greater than 2.6. The minimum threshold of KI was 28.1 for short-duration heavy rainfall. The importance of dynamic conditions was well demonstrated by the 925- and 850-hPa divergence. The representativeness of 925-hPa divergence is stronger than that of 850 hPa. Three-quarters of short-duration heavy rainfall occurred under a negative divergence environment. However, both the best convective potential energy （BCAPE） and vertical wind shear were unable to discriminate the hourly rainfall intensities.

Distribution and Diurnal Variation of Warm-Season Short-Duration Heavy Rainfall in Relation to the MCSs in China

Short-duration heavy rainfall（SDHR） is a type of severe convective weather that often leads to substantial losses of property and life. We derive the spatiotemporal distribution and diurnal variation of SDHR over China during the warm season（April–September） from quality-controlled hourly raingauge data taken at 876 stations for 19 yr（1991–2009）, in comparison with the diurnal features of the mesoscale convective systems（MCSs） derived from satellite data. The results are as follows. 1） Spatial distributions of the frequency of SDHR events with hourly rainfall greater than 10–40 mm are very similar to the distribution of heavy rainfall（daily rainfall 50 mm） over China's Mainland. 2） SDHR occurs most frequently in South China such as southern Yunnan, Guizhou, and Jiangxi provinces, the Sichuan basin, and the lower reaches of the Yangtze River, among others. Some SDHR events with hourly rainfall 50 mm also occur in northern China, e.g., the western Xinjiang and central-eastern Inner Mongolia. The heaviest hourly rainfall is observed over the Hainan Island with the amount reaching over 180 mm. 3） The frequency of the SDHR events is the highest in July, followed by August. Analysis of pentad variations in SDHR reveals that SDHR events are intermittent, with the fourth pentad of July the most active. The frequency of SDHR over China's Mainland increases slowly with the advent of the East Asian summer monsoon, but decreases rapidly with its withdrawal. 4） The diurnal peak of the SDHR activity occurs in the later afternoon（1600–1700 Beijing Time（BT））, and the secondary peak occurs after midnight（0100–0200 BT） and in the early morning（0700–0800 BT）; whereas the diurnal minimum occurs around late morning till noon（1000–1300 BT）. 5） The diurnal variation of SDHR exhibits generally consistent features with that of the MCSs in China, but the active periods and propagation of SDHR and MCSs difer in diferent regions. The number and duration of local maxima in the diurnal cycles of SDHR and MCSs also vary by region, with single, double, and even multiple peaks in some cases. These variations may be associated with the diferences in large-scale atmospheric circulation, surface conditions, and land-sea distribution.

海南岛4—9月短时强降水的天气型和环境参数特征

利用海南岛加密自动站逐小时降水资料、ERA5再分析资料,对海南岛短时强降水日环流配置进行了天气学分型,并进一步探讨了各天气型下海南岛短时强降水的时空分布、环流形势和关键环境参数特征。结果表明:(1)海南岛短时强降水有明显的日变化特征,呈单峰型,主要出现在15:00—19:00。(2)海南岛短时强降水的天气型主要有南海低压槽、华南沿海槽、西南低压槽和冷锋型。(3)南海低压槽、华南沿海槽、西南低压槽和冷锋型短时强降水分别占37%,31%,16%和16%。南海低压槽和华南沿海槽型主要出现在7、8和9月;西南低压槽型除9月外,其余各月份均可能出现;冷锋型绝大多数出现在4、5月。(4)南海低压槽和华南沿海槽型整层湿度条件都较好,不稳定能量较大,垂直风切变较弱。西南低压槽型不稳定能量较大,湿度条件一般,垂直风切变较弱。冷锋型存在明显的上干下湿特征,垂直风切变最大,0~6 km风速差75%分位大于10 m/s,不稳定能量最小。

Analysis of Heavy Precipitation Process in North China from August 23 to 24, 2020

In order to better understand the formation mechanism of rainstorm in China and promote disaster prevention and reduction, based on the meteorological data of National Meteorological Information Center and Japan Meteorological Agency, this paper draws the isobaric surface map of 850 hPa and 500 hPa, relative humidity and precipitation distribution map. In this study, synoptic methods were used to analyze the heavy precipitation process in North China from August 23th to 24th, 2020. The results show that 1) The formation of short-term heavy precipitation requires sufficient water vapor and very strong upward movement;2) the heavy precipitation in August 23th to 24th 2020 in North China was influenced by the upper-level trough line, cold vortex and cold front, which made the warm and cold air strongly converge over North China, resulting in strong convective weather;3) the heavy rainfall over North China was also influenced by Typhoon Bawei, which caused maximum precipitation and air humidity.

一次大暴雨中尺度短时强降水回波特征分析

为了做好江西宜丰大暴雨天气的预警预报服务,使用常规天气图、宜丰自动站雨量、江西雷达拼图等资料,采用天气学、雷达气象学等原理,对2022年6月3日江西宜丰地区大暴雨过程进行分析。结果表明,通过对6月3日宜丰大暴雨年月日统计特征进行分析,1981—2022年宜丰每年大暴雨出现频次在0~2次,主要集中出现在6月份。宜丰此次大暴雨过程前期雨势不大,但由于云系发展和地形、环境等条件的影响,在6月3日08时小时雨强达到了65 mm,到了09时小时雨强达到最大的70 mm,造成了局地的超短时强降水。受低槽及低层切变东移影响,边界层及地面增温明显,动力抬升加强。850 hPa低涡东侧的切变线一直延伸至赣北北部,切变线南侧西南急流达到14 m/s,宜丰处在西南急流的左前方,同时地面辐合线稳定在宜丰附近并与低层切变耦合,导致辐合扰动加强,有利于强风暴在辐合线附近发生。回波形态为絮状回波带结构,絮状回波带包含着多个较强单体回波,影响宜丰的组合反射率CR回波最强达到50 dBZ,≥45 dBZ回波稳定在宜丰南部,为短时强降水的生成形成了非常有利的条件,随着回波顶高的升高,加强了该单体回波的降水效率,08时出现了小时雨强65 mm/h的超强降水。

河南省近30年分级短时强降水时空分布特征分析

利用1992-2021年4-10月河南省101个台站逐时降水资料并结合地形,统计分析了河南省不同量级短时强降水的时空演变特征及其与地形的关系。结果表明:(1)R1h≥20 mm·h^(-1)的短时强降水和3个不同量级的短时强降水频次分布均呈东多西少的分布特征,短时强降水和[20 mm·h^(-1),50mm·h^(-1))量级的短时强水出现的频次均呈南多北少的分布特征,[50 mm·h^(-1),80 mm·h^(-1))量级的短时强水出现的频次表现为南北之间差别不大,而[80 mm·h^(-1),+∞)量级的短时强水出现的频次呈南少北多的分布特征。各月短时强降水频次的空间分布为东多西少,7月、8月和10月南北之间差别不大,其他月份呈南多北少的分布特征。(2)短时强降水年际变化差别大,月变化呈单峰型,6月下旬-8月上旬是各量级短时强降水多发时段。(3)短时强降水频次日变化分布呈双峰型,16-21时的发生频次最高,00-05时的次之,09-14时的最低。6-8月短时强降水频次的日变化特征呈双峰型,其他月份的双峰特征不明显。4-10月16-21时出现日峰值的站点最多,00-05时的次之,空间分布呈东大西小、南大北小的分布特征,各月00-05时出现日峰值的站数最多,16-21时的次之。(4)最大雨强和短时强降水量的占比均呈东高西低、北高南低的分布特征。(5)短时强降水的空间分布、日变化空间分布、最大雨强高值区和短时强降水量占比等均与河南省地形关系密切,地形对短时强降水有增(减)幅作用。

四川两次极端暴雨强降水特征及与雷达回波和闪电关系分析

选取了2020年8月四川两次历史性极端暴雨过程,根据量级和持续时间对强降水进行划分,分析其时空分布特征及与雷达回波和闪电的关系。结果表明:短时强降水主要发生在22时—次日03时,降水强度为30~<50 mm/h的站次最多,区域集中在盆地西部。随着降水量级的增加,站点对应的闪电密度均增大,小时平均回波、最强回波、最弱回波均呈增强的趋势。随着降水持续时间的增加,站点对应的负地闪平均强度增强。第一次过程强降水站次与闪电频次的高值中心具有良好的对应关系。第二次过程随着降水量级增大,对应的回波均方根误差减小,而第一次过程则相反。

吕梁山两次夜间暴雨的边界层特征及能量来源与转换

利用常规观测、NCEP/NCAR 1°×1°再分析、FY-2E卫星数据等资料,对分别由β-中尺度持续拉长状对流系统(MβECS)和中尺度对流复合体(MCC)造成的两次吕梁山夜间暴雨过程进行数值模拟和粒子后向轨迹追踪,结果表明:过程1受边界层南风急流和西南气流影响,山西西部低空急流偏西分量和晋中盆地边界层西南气流的增强是对流不稳定能量重建的重要因子。过程2则受边界层南风和东风急流作用,南风急流被显著抬升到对流层中高层,形成含有冰晶层的中高层云系,东风急流则供应低空水汽。两次过程边界层(0.8-1.2 km)粒子携带的水汽均明显超过低层(1.5-3 km),是夜间短时强降水所需水汽的最大贡献者。700 hPa及以上非绝热作用产生扰动有效位能,之后向扰动动能的转化是两次过程中短时强降水发生所需能量的主要来源。

吉林省短时强降水时空特征分析

文章利用吉林省51个国家地面气象观测站1994—2023年4—10月逐小时降水资料,通过对短时强降水时间尺度、空间尺度进行分析,揭示吉林省短时强降水时空分布特征及变化规律。结果表明:1994—2023年短时强降水频次呈现先下降后上升的趋势;5—9月为吉林省短时强降水集中期,其中7—8月发生频次最多;短时强降水最早出现在5月15日前后,最晚出现在9月10日前后;降水日变化呈现双峰结构;降水空间分布不均匀。研究结果以期为短时强降水的预报提供气候背景,为预报预警服务提供参考依据。

滇中地区不同影响系统下3次短时强降水过程的大气环境特征和雷达特征分析

利用常规观测资料、NCEP 1°×1°再分析资料、逐时和逐5 min自动站降水资料以及昆明CINRAD/CC多普勒雷达资料,针对滇中地区2021年主汛期不同影响系统下的3次短时强降水过程,对比分析了降水特征、环流形势、大气环境特征以及雷达回波的结构、形状、演变的基本特征。结果表明:3次短时强降水过程影响系统差异主要在于500 hPa天气系统不同,700 hPa都有切变线影响,但是形成原因各异,地面均有辐合线或弱冷锋配合。3次过程的环境条件在不稳定层结、近地层水汽、垂直风切变方面与中国其他地区短时强降水发生的环境条件具有一致性,但是在大气整层可降水量、对流有效位能、SWEAT指数等方面存在明显差异。对流回波的形状有点状回波、块状回波、带状回波、絮状回波等。对流风暴分为高质心型、低质心型以及混合型;短时强降水有单独出现某种对流风暴类型的阶段,也有多种对流风暴类型同时出现的阶段;CAPE值和SWEAT指数与对流风暴类型具有一定的相关关系。强回波剖面呈柱状结构或者塔状结构,35 dBz强回波接地,而没有悬垂特征。短时强降水多产生于长时间停滞型或移动缓慢型的对流回波,还有部分短时强降水产生于“列车效应”中。短生命周期的单体生消形成的短时强降水持续时间绝大部分在1 h以内,但是单体合并组织和反复生消或者“列车效应”形成的短时强降水持续时间常在1~3 h。高质心型对流风暴产生的瞬时雨强可达10 mm·(5min)-1以上,低质心型和混合型对流风暴可产生的雨强范围较大,大多在3~10 mm·(5min)-1,少数也可达到10 mm·(5min)-1以上。

基于RAMMS数值模拟的短时强降雨型泥石流危险性评价

浙江省由短时强降雨诱发的泥石流灾害频发,严重威胁当地居民的生命财产安全,因此对此类泥石流进行危险性评价对浙江省“灾害智治”工作具有十分重要的理论与实际应用价值。为研究浙江短时强降雨诱发小型泥石流的危险性,选取武山坑泥石流为对象,通过现场调查、三维倾斜摄影与数值模拟等手段,查明了武山坑泥石流的地质环境与发育特征,揭示了由短时强降雨诱发的泥石流灾害链生过程特征,选用RAMMS软件对不同降雨频率下泥石流运动特征进行了模拟,获取了泥石流深度、流速、堆积范围等特征参数,并基于特征参数进行了泥石流危险性评价。研究结果表明:陡坡处松散岩土体在短时强降雨作用下发生浅层滑坡,随后在坡面与沟道地形控制下向沟口运移,运动过程中通过侵蚀作用扩大泥石流规模,最终在宽缓堆积区沉积。随着研究区降雨强度增大至50 a一遇及100 a一遇,泥石流冲出规模扩大,但受限于堆积区宽缓的地形条件,未能于沟口形成有效冲出;但堆积扇上游居民区泥石流深度、流速等强度指标显著增大,堆积区内高强度区域面积大小由7276 m^(2)增大至12660 m^(2)。结合泥石流活跃性分析结果,采取形成区雨量监测、主沟谷流通区构建刚性、柔性或狭缝拦挡坝以及堆积区设置导流渠相结合的治理措施,可有效保障居民生命财产安全。研究成果可为武山坑及浙江省此类泥石流危险性评价、防治工程设计提供参考。

产生青海“22·8”极端强降水的三维环流结构分析

利用探空资料、台站逐时观测资料和ERA5逐时再分析资料,以包含对流层高层气温特征的三维环流结构为切入点,系统分析了2022年8月17—18日引发青海省西宁市大通县山洪灾害的短时极端强降水的精细化特征。结果表明,强降水发生前,中国西北地区上空300 hPa存在明显暖异常,随着时间推移暖异常略向东南方向移动且强度逐渐增强,并在降水峰值时刻达到最强。在静力平衡的调控作用下,对流层高层暖异常上层出现位势高度正异常,下层出现位势高度负异常。与这种配置相对应,对流层高层出现反气旋式环流异常,为高层辐散创造了有利条件。随着暖异常移动增强,高空西风急流异常向东南移动增强。另外,对流层中、低层出现气旋式切变,低层偏东气流转变为气旋前部偏南气流,为降水地区低层暖湿条件增强、大气不稳定度增大创造了有利条件。这种三维环流结构不仅为强降水形成提供了有利的高、低层环流条件与水汽条件,还为不稳定能量的积蓄奠定了基础。同时,在大通县西北高、东南低的喇叭口地形影响下,低层偏南气流携带的丰富水汽在此处聚集,配合较强的不稳定能量,共同促成了此次短时极端强降水过程。

甘肃河东夏季区域性短时强降水环流形势分类特征

甘肃河东地区短时强降水易致灾,预报预警难度大。利用2010-2021年夏季加密观测站逐小时降水资料和NCEP/NCAR再分析资料,筛选出甘肃河东50次区域性短时强降水天气过程,基于这些天气过程的500 hPa位势高度距平场,使用K均值客观聚类分析和主观天气学检验相结合的方法进行天气尺度环流形势分类,并通过合成分析和中尺度对流天气环境场条件分析方法构建不同类型的天气尺度系统配置概念模型。结果表明:(1)甘肃河东区域性短时强降水的天气尺度环流形势可分为高原槽东移型、副高边缘西南气流型、两高切变型和西北气流型四类。(2)副高边缘西南气流型引发的区域性短时强降水次数最多,两高切变型和高原槽东移型发生频率相当,西北气流型发生次数最少。(3)四种类型的环流形势在天气系统配置、抬升条件、水汽条件和不稳定条件等方面存在显著差异。高原槽东移型、副高边缘西南气流型、两高切变型三种类型发生时西太平洋副热带高压(以下简称西太副高)所处的位置逐渐向西向北推进,水汽条件和不稳定条件逐渐趋好,当高空槽引导冷空气东移南下,斜压锋生形成大范围短时强降水。高原槽东移型抬升条件最好,短时强降水落区偏南;两高切变型冷空气偏北且主要由对流层低层侵入,短时强降水落区偏北;副高边缘西南气流型冷暖气团交汇最剧烈,斜压锋生最强,短时强降水范围及强度也更大。西北气流型的动力条件和水汽条件是四类中最差的,但强烈的中高层干冷平流叠加低层暖湿气流或温度暖脊形成了四类中最好的不稳定条件,短时强降水落区较分散。

基于机器学习的黑龙江省强降水致灾预估方法研究

采用黑龙江省1984—2019年各县强降水灾情资料和逐日降水资料,以逻辑回归和长短时记忆网络模型为基础,建立了黑龙江全省、大兴安岭、小兴安岭、松嫩平原、三江平原和东南半山区的强降水致灾与否二分类预估模型。通过机器学习,得到黑龙江省以及5个地区判断强降水致灾与否的最佳观测天数在4~6 d、最佳的日降水量阈值为16~20 mm。比较全连接逻辑回归模型、优先考虑日期的部分连接逻辑回归模型D、优先考虑站点的部分连接逻辑回归模型S和长短时记忆网络LSTM模型等四个模型的表现,前三种逻辑回归模型表现差距不大,相对表现最好的全连接模型,其在大部地区所表现的准确率、精确率、召回率和F1分数均在0.7以上,而LSTM模型只在大兴安岭表现更好一些。

京津冀暖季短时强降水环境特征对比分析

利用2013—2021年暖季(6—9月)京津冀地区逐时降水资料和ERA5再分析资料,根据天气形势对短时强降水进行天气学分型,统计短时强降水发生的时空特征,对比动力、水汽和热力不稳定条件等环境要素特征。结果表明:短时强降水以冷涡型和副高型为主,占到55%,且主要发生在7月中下旬到8月上中旬,强降水主要集中在下午到前半夜。对比发现,不同类型短时强降水空间分布特征区别明显,分型合理;各类型大多表现为低层辐合和高层辐散,西南涡型动力强度表现最强,且随降水临近是增加的,弱天气强迫型在降水前各个时段动力表现最弱;副高型、台风型和西南涡型水汽最为充沛,副高型925 hPa比湿中位数达到19.14 g·kg~(-1),西南涡型在高低层相对湿度均较大,低层平均相对湿度中位数达到87%,弱天气强迫型相对较差,为74%,各类型整层大气可降水量在降水前随时间基本是增加的;弱天气强迫型的热力不稳定性最为突出,850 hPa和500 hPa温度差中位数最大为25.74℃,西南涡型最小,除弱天气强迫型外,各类型热力条件随时间是减弱的。

江苏省夏季梅雨和台风型短时强降水雨滴谱特征差异分析

利用2019—2020年夏季的江苏省自动站和雨滴谱站网观测资料,从不同天气类型(梅雨和台风)和级别(20~50和>50 mm·h^(-1))将短时强降水区分为梅雨20、梅雨50、台风20以及台风50四种类型,对比分析了其雨滴谱(DSD,raindrop size distribution)特征之间的差异。统计结果表明:梅雨型强降水的雨滴平均粒径(数浓度)明显高于(低于)台风型强降水。台风型强降水的小雨滴(粒径≤2 mm)对降水的贡献率明显高于梅雨型。此外,随着降水强度的增加,梅雨50相对梅雨20的大雨滴数浓度有明显增长,雨滴平均粒径明显增大;台风50相对台风20的雨滴数浓度明显增加,粒径增长不明显。因此,台风不同级别强降水均主要由高浓度的小粒径雨滴贡献,而梅雨极端强降水则由更多大雨滴贡献,DSD特征更为复杂。选取的典型个例也观测到类似的结果,表明梅雨型强降水的雨滴谱变化相对台风型更为明显。