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.

Analysis of Short-term Heavy Precipitation in Ulanqab City from 2017 to 2022

Based on the data of hourly precipitation in 11 national stations and 262 regional stations in Ulanqab City from 2017 to 2022,the annual,monthly and daily variations of short-term heavy precipitation in Ulanqab City were statistically analyzed.The results show that the frequency of short-term heavy precipitation in Ulanqab City was high in the south and low in the north,and was closely related to the terrain.Short-term heavy precipitation in Ulanqab City was mainly concentrated from June to August,of which it was the frequentest in July.Short-term heavy precipitation mainly occurred from the afternoon to evening,and was concentrated from 13:00 to 20:00,especially at 19:00.The rainfall in Ulanqab City ranged mainly from 20 to 30 mm,accounting for 74.7%,and the rest accounted for 25.3%.

Analysis on Radar Characteristics of a Short-time Heavy Rainfall Event in Wuchuan County

Using minute rainfall data of automatic ground station and a variety of products from new generation Doppler weather radar in Wuchuan, the characteristics of a short-time heavy precipitation process on April 23, 2022 were analyzed. The results showed that the appearance of differential reflectivity(ZDR) column and big-value zone of high-elevation ZDR had better indication on short-term heavy rainfall process in Shichao station. Ice phase process played a very important role in particle growth. The storm tracking information product can predict the path of the storm 15 min in advance. The storm stayed and moved less or even turned back to more than two to three scanning volumes in one place, indicating the occurrence of short-term heavy rainfall. One-hour accumulated precipitation(OHP) had a good effect on the estimation of continuous precipitation in a large area where the hourly rainfall exceeded 50 mm for more than two stations. It had the ability to estimate short-term heavy precipitation in areas lacking automatic stations.

Application research of wind profile radar in short-term heavy rainfall forecast of typhoon in Fujian Province

Based on wind profile radar data,this paper aims at different typhoon processes landed and affected Fujian from 2011 to 2019,according to the nature of typhoon rainstorm,it can be classified into outer precipitation before typhoon landed,main body precipitation and precipitation at the rear of typhoon,the change of the characteristic quantities in approaching time of the occurrence of short-term heavy rainfall was analyzed,and the typhoon case in 2020 was back calculated.The results show that,the characteristics of low-level jet streams(maximum wind speed at low altitude,minimum height of jet streams,and low-level jet stream index),as well as the magnitude of vertical wind shear below 700 hPa,have important indicative significance for the occurrence of short-term heavy rainfall.(1)More than 80%of short-term heavy rainfall occurred 3 h before the low-level jet stream already existed.The maximum wind speed below 2 km was basically close to a normal distribution,and the occurrence of heavy precipitation showed a bimodal pattern.The percentage of wind speed between 8 and 32 m/s was the highest,exceeding 85%.The wind direction of the strong wind is mainly NE,SE,and SW.Classification analysis showed that the distribution characteristics of wind speed of the main precipitation were the same as before,but the wind direction SE was higher than NE.The wind speed of pre-landfall precipitation was basically skewed,and the occurrence time of heavy precipitation followed a normal distribution.The percentage of wind speed between 16 and 32 m/s was the highest,and the wind direction was the same as before classification.The maximum wind speed of precipitation in the rear was basically bimodal distribution,with a relatively even distribution,and the wind direction was mainly SE and SW.(2)In the 3 h before the occurrence of short-term heavy precipitation,there was an increase in the maximum wind speed value,a decrease in the minimum extension height,and an increase in the low-level jet stream index I.As short-term heavy rainfall approached,the intensity of the low-level jet stream remained high and its proportion increased.The minimum achievable extension height gradually decreased and remained stable at a low value.In the first 2 h of heavy rainfall,the wind speed reached its maximum,the extension height was the lowest,and the lowlevel jet stream index I was the highest.Classifying and discussing it,the precipitation in the rear was different,and the lowest height decreased to the lowest at the time of occurrence,at which point the I value reached its maximum.The characteristics of the other two categories were the same as before the classification.(3)The vertical wind shear from the ground to different isobaric surfaces gradually decreased with the increase of height.With the approach of short-term heavy rainfall,the vertical wind shear of each layer basically decreased gradually,after the beginning of heavy rainfall,which decreased to the minimum.The characteristics of main body precipitation were the same as before the classification.Pre-landfall precipitation,in addition to the gradual decrease of vertical wind shear from the ground to 925 hPa,both 850 hPa and 700 hPa increased first and then decreased,vertical wind shear decreased to the minimum after the beginning of heavy rainfall.Precipitation at rear of typhoon,vertical wind shear from ground to 700 hPa increased compared with that before the occurrence of heavy rainfall,while wind shear from ground to 925 hPa and 850 hPa showed the characteristics of decreasing when heavy rainfall occurred.(4)The median values of various physical quantities before the occurrence of typhoon short-term heavy rainfall were selected as the thresholds of short-term heavy rainfall will occur.The intensity of LLJ is about 21 m/s,the lowest height is about 0.65 km,the LLJ index I is about 36×10^(−3) s^(−1).Vertical wind shear from the ground to 925 hPa,850 hPa and 700 hPa are respectively about 15.9×10^(−3) s^(−1),11.2×10^(−3) s^(−1) and 5.1×10^(−3) s^(−1).

1981-2020年陕西省暖季不同历时强降水时空变化特征

利用1981—2020年陕西省暖季(5—9月)95个国家气象观测站小时降水量资料,结合多种数理统计方法分析4个历时(1h、3h、6h、12h)强降水的时空变化。结果表明:(1)陕西省短历时强降水主要集中在7—8月,4个历时强降水高发区均位于陕南秦巴山区,稀发区位于关中平原中部和陕北长城沿线。(2)各历时降水极值的空间差异均较大,历时越短,极值分布的局地性越强。(3)近40a,陕西省各历时强降水均呈增多增强趋势,尤以3h强降水的增加最为显著。(4)各历时强降水的趋势变化在空间上表现为非均一性,陕北黄河沿线和陕南中南部强降水呈增多趋势,陕北南部和关中平原中部呈减少趋势,且历时越短,强降水呈增多趋势的范围越大。(5)强降水日变化南北不同,历时越短,强降水的日变化越明显,特别是陕北短历时强降水日变化最为突出,且在傍晚或夜间易发生强降水事件,其危害更大。

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.

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。

近20年季风爆发前后珠江三角洲前汛期短时强降水的时空演变特征与成因

相较于暴雨这种日尺度强降水,短时强降水(≥20 mm h^(−1))是造成山洪滑坡与城市内涝等灾害更为直接的因素。本文利用地面气象观测站和ERA5再分析数据,重点研究南海季风爆发前后珠江三角洲地区(简称珠三角)短时强降水的时空演变特征,并探索了短时强降水在季风爆发前后特征差异的可能成因。研究表明:(1)相较于季风爆发前,珠三角地区季风爆发后的降水明显增多,其中短时强降水贡献的比例显著增加。对短时强降水本身而言,区域平均强度以及极端性在季风爆发前后差异总体较小,但短时强降水频率在季风爆发后增加70%。(2)短时强降水高发区主要集中在珠三角东北部和珠江口西侧沿海,季风爆发后上述两个地区的频次增多最明显。短时强降水频率由季风爆发前的单峰型(下午)转为季风爆发后的双峰型(早晨与下午)。(3)短时强降水具有明显的区域性变化特征,短时强降水在季风爆发后的平均雨强和极端性在珠江口西侧沿海较内陆地区明显增强,其频次峰值时间在沿海地区从季风爆发前的午后转为季风爆发后的早晨,内陆地区在季风爆发前后均集中在下午。(4)季风爆发后,短时强降水期间的低层环境水汽超过同期气候态水平的16%。充沛的水汽在夜间在季风加速作用下被输送至沿海,并与陆风作用增强了辐合,这解释了沿海短时强降水的在季风爆发前后频次峰值时间转换现象。(5)相较于季风爆发前,季风爆发后珠三角短时强降水频率与低层水汽通量的相关性明显升高。珠三角沿海地区夜间—早晨短时强降水的增多与中低层风场结构改变造成的动力强迫有关。内陆地区季风爆发前后短时强降水与环境热力和不稳定条件关系更大。这些结果有助于我们更好地了解珠三角地区在季风爆发前后短时强降水的时空分布特征和理解其产生机制。

川西高原甘孜州汛期短时强降水的时空分布特征

利用2012—2021年4—10月甘孜州18个基准(基本)气象站和489个区域气象站逐小时降水观测资料,分析川西高原甘孜州汛期短时强降水的时空分布特征。结果表明:(1)2012—2021年甘孜州汛期短时强降水总频次为1906站次,平均每年190.6站次,且频次随量级增大呈指数衰减,15~25 mm/h短时强降水占84%以上。(2)短时强降水易发生在午后到上半夜,其日变化特征为双峰型,峰值出现在20—22时(北京时),峰值最高和次高分别为22时和20时;月变化呈单峰型,7月最多发(占30.16%),6月和8月次之;年际变化不均,2012年短时强降水发生频次最少,仅38站次,而2020年短时强降水发生频次最多,达336站次。(3)短时强降水空间分布不均,呈东多西少、南多北少的特征。发生频次最高地区位于泸定县南部,次高地区为九龙县南部。(4)受复杂地形与区域环流的共同影响,甘孜州短时强降水与海拔高度有密切关系,主要出现在1100~<3900 m海拔高度,尤其在1100~<1900 m海拔高度最易发生,其雨强最大峰值(63.3 mm/h)出现在1100~<1300 m高度范围内。

中国长短历时暴雨时空变化格局及其对总暴雨贡献的研究(1951—2010)

采用中国1951—2010年659个站点的日值降水数据,以暴雨持续长短为标准对短和长历时暴雨计算,结果表明:在空间上,中国短历时暴雨量从1951到2010年呈现出由东南沿海向西北内陆梯次减少的现象,而长历时暴雨量则主要集中在广东、广西、海南等东南沿海地区。在时间上,中国年际和年代际短和长历时暴雨均呈现增加趋势。在降水贡献率占比上,1951—2010年中国总暴雨量占总降雨量以及总暴雨日占总降雨日的比例分别为6.1%—27.7%和0.6%—2.5%;同期中国短历时暴雨量在总暴雨量和短历时暴雨日在总暴雨日中的比例分别为75.9%—89.4%和75.6%—89.2%,短历时暴雨占主导地位;而长历时暴雨量在总暴雨量和长历时暴雨日在总暴雨日中的比例分别只占10.6%—24.1%和10.8%—24.4%。在降水贡献率变化趋势上,在1951—2010年间,中国总暴雨对总降雨的贡献率呈增加趋势,其雨量和雨日的贡献率趋势分别为2.1%/10a和0.2%/10a;短历时暴雨对总暴雨的贡献率也呈增加趋势,其雨量和雨日的贡献率趋势分别为0.5%/10a和0.4%/10a;而长历时暴雨对总暴雨的贡献率呈减少趋势,其雨量和雨日的贡献率趋势分别为-0.5%/10a和-0.4%/10a。以上结果表明中国降水在朝着极端化方向变化,短历时暴雨增多显著。

中国短历时和长历时暴雨对总暴雨贡献的空间差异性研究(1961-2015)

采用1961-2015年659站日值降水数据,以持续1 d和持续2 d及以上暴雨作为短和长历时暴雨标准,分析不同历时暴雨变化趋势,结果表明,中国总降雨、总暴雨和短历时暴雨从东南沿海向西北内陆依次呈"增-减-增"的分布特征,且整体以增加趋势的站点占主导,而长历时暴雨则呈现出"增-减"的分布特征,且整体以减少趋势的站点占主导,并且检测出中国自东北向西南存在一条变干带。同时中国总暴雨对总降雨、长历时暴雨对总暴雨的贡献呈现出"东南高-西北低"的分布特征,而短历时暴雨对总暴雨的贡献呈现出"东南低-西北高"的分布特征。中国总暴雨对总降雨、短历时暴雨对总暴雨贡献的变化趋势呈现出"增-增减镶嵌-增"的分布特征,且以增加趋势的站点占主导,而长历时暴雨在东部沿海地区呈现出增减镶嵌的趋势,而西北内陆地区呈略微减少趋势,且以减少趋势的站点占主导,也检测出自东北向西南存在一条气候过渡带并与上述变干带基本重合。

短时强降水诊断物理量敏感性的点对面检验

对诊断物理量的准确认识可以帮助提高短时强降水的预报准确率,并帮助理解产生短时强降水的可能机制。考虑我国降水观测网的布设特点,结合NCEP最终分析资料的物理量场,以大气水汽总量和最优抬升指数为例,通过点对面检验分析了多个用于表征短时强降水环境特征的诊断物理量的敏感性。结果表明:常规的点对点检验是点对面检验的特殊情况。大气水汽总量和最优抬升指数对短时强降水的指示均存在最佳阈值,且140 km范围内的大气状况才对某点3 h内能否出现短时强降水有直接影响。对于水平分辨率为1°×1°的NCEP资料,建议点对面检验的搜索半径和记录数阈值分别为140 km和2个记录。对多个诊断物理量对比分析显示,短时强降水对水汽相关量最为敏感,其次是表征热力条件的物理量,而表征动力条件和垂直风切变的量的指示意义不够显著。

CMORPH卫星-地面自动站融合降水数据在中国南方短时强降水分析中的应用

对比分析了国家级气象观测站逐时地面降水资料和CMORPH卫星-地面自动站融合降水数据在反映中国南方地区2008—2013年4—10月短时强降水时空分布特征上的差异,并在此基础上利用融合降水数据分析了短时强降水与暴雨的关系,结果表明:(1)融合降水数据所反映的短时强降水的大尺度特征与站点资料一致,并能更好地描述地形的影响;(2)短时强降水的季节变化与东亚夏季风进程和雨带的季节性位移密切相关;(3)短时强降水与暴雨日的空间分布特征和季节变化趋势相似,4月下半月—10月上半月,超过60%的短时强降水发生在暴雨日,同时短时强降水也是暴雨形成的重要因素,短时强降水暴雨日数占总暴雨日数的比例(68.6%)普遍高于非短时强降水暴雨日(31.4%),但是短时强降水暴雨日的发生具有显著的季节和区域差异。

上海地区短时强降水特点及其影响

利用2009-2013年上海市加密观测自动站降水资料和110报警信息资料,对上海市短时强降水进行统计分析,了解其地理分布特征、概率分布特点的同时,找出降水极端性与暴雨红色预警标准的对应关系,以及110报警次数与短时强降水的关系。结果表明：1）自动站1 h雨量≥30 mm、≥50 mm和3 h雨量≥50 mm、≥100 mm的5 a累计频数的大值区基本集中在市区及其周边地区,郊区次数明显减少,出现次数最多的是3 h雨量≥50 mm的情况,出现次数最少的为3 h雨量≥100 mm的情况。2）从不同降水强度的发生概率分布来看,郊区弱降水发生概率大于市区的,市区强降水（1 h雨量≥25 mm）发生概率大于郊区的。3）对流降水情况下,降水累积概率为1%时,对应的1 h雨量市区为63.6 mm、郊区为58.7 mm,接近暴雨红色预警标准;对应的3 h雨量市区为90.8 mm、郊区为86.8 mm,较暴雨红色预警标准的阈值小。4）报警次数与降水量的关系：1当1 h雨量〈40 mm或3 h雨量〈60mm时,报警次数变化不大,基本在10次以下;当1 h雨量≥40 mm或3 h雨量≥60 mm时,报警次数逐渐增多,大部分在20次以上;当1 h雨量≥60 mm（达到暴雨红色预警标准）、3 h雨量≥80 mm（未达到暴雨红色预警标准）时,报警次数明显增多,基本超过30次,最多达100次以上。从报警次数的角度来看,暴雨红色预警的3 h标准设定为80~90 mm更合适。2当逐1 h和逐3 h雨量不是很大、但累积降水量较大（特别是累积降水量超过100 mm）时,报警次数急剧增多,很多超过100次,说明报警次数还与降水的持续时间有关。3当累积降水量、逐1 h和逐3 h雨量都增加时,报警次数增加最快。4报警次数的极值并非都出现在逐1 h和逐3 h雨量大值时,在1 h雨强不是很强,但降水持续时间长,累积降水量大的时候,也十分容易出现报警极值。

基于融合资料的天津短时强降水环境物理量可信度及特征分析

针对2009—2017年6—9月天津地区140次短时强降水天气过程,将NCEP FNL(1°×1°)全球分析资料与地面气象观测数据融合,计算天津地区短时强降水的环境物理量参数,通过偏差和偏差区间占有率等分析融合环境物理量的可信度,并在大量样本统计基础上给出不同月份的短时强降水环境参量特征和指标。结果表明:(1)基于NCEP FNL分析资料与地面气象观测数据融合的环境物理量在短时强降水潜势判断中具有较高的可信度,融合CAPE、LI、LCL平均绝对误差分别为260.7 J/kg、0.9℃、14 hPa,与融合前的NCEP FNL物理量相比绝对误差分别降低了58.1%、48.0%、49.0%。(2)不同月份短时强降水发生所必需的水汽、热力和能量等环境条件差异显著,TPW、K、LI、CAPE、LCL和Z0均呈现明显的月变化特征。(3)若以75%短时强降水发生的环境条件作为预报指标,7—8月TPW、K、CAPE、Z0、LCL物理量阈值极为相近,短时强降水多发生在TPW>45 kg/m2、K>32℃、CAPE>835 J/kg、LCL>882 hPa、Z0>4300 m条件下,6月物理量指标要求明显降低,如TPW>34 kg/m2、K>30℃、CAPE>353 J/kg、LCL>880 hPa、Z0>3900 m,9月预报指标要求则最低。

济南市区短时强降水特征分析与天气分型

利用2007—2015年济南市区及历城区自动气象观测站的逐小时降水量资料,以及常规高空、地面观测资料,统计了198次短时强降水过程的范围和强度特征,年际、月际变化特征,按照短时强降水发生时的天气形势和影响系统,分为切变线型、低槽冷锋型、西风槽型、冷涡型、台风外围型及无系统型6类,并分析了不同类型和不同范围短时强降水的关键环境参量。研究表明:短时强降水的强度与范围有较好的相关性,7月中旬—8月中旬出现强降水的次数最多;切变线型短时强降水发生范围与强度分布最广,7、8月的低槽冷锋型过程极易造成大范围高强度降水;地面露点(Td)、850 h Pa假相当位温(θse)、对流有效位能(CAPE)以及暖云层厚度能较好地区分不同范围的短时强降水过程。在天气分型的基础上,结合不同降水范围和不同降水类型环境参量箱线图与阈值表,可为济南市区短时强降水的预报提供有价值的参考。

甘肃省短时强降水的时空特征

基于甘肃省81个自动气象站2002—2012年逐小时降水数据,分析了甘肃省近11 a来短时强降水的时空变化特征。结果表明:短时强降水频次自甘肃省西北向东南逐步递增,陇东南地区是甘肃省短时强降水发生频次最多、强度最强的地区。短时强降水存在2个高发中心,一个在以合水为中心的陇东地区,另一个在以徽县为中心的徽成盆地。短时强降水主要发生在午后至前半夜,出现时段集中在16:00—00:00,17时前后是短时强降水天气高发时段。短时强降水主要出现在5—9月,其中7—8月是一年中出现最多的月份,其次是6月。近11 a来,短时强降水频次呈上升趋势,2006年和2010年出现了2个峰值,其中2010年最多,发生52次,2004年最少只有17次。

川渝盆地主汛期短时强降水事件日变化特征研究

利用四川盆地和重庆地区1980-2012年主汛期(5-9月)基本站小时降水观测资料,分析了短时强降水事件降水量、频次和强度的日变化特征,研究了短时强降水事件日峰值位相和空间分布特征,事件极值降水日变化和持续时间等分布特征,得出以下主要结论:1)川渝盆地短时强降水事件开始时间的日变化上(01:00-24:00时,北京时间,下同),表现为"V"型结构下典型夜间峰值位相特征;结束时间的日变化上,表现为多个峰值型结构分布.强降水事件持续时间的日变化上,频次和降水量均呈双峰型结构,频次极大峰值出现在3h,而强度上随着持续时间的延长,呈现逐渐增加的趋势;2)短时强降水事件极值开始时间空间分布上,极大频次和极大降水量出现在20:00-01:00时内,主要分布在盆地南部和西部大部分地区;日峰值频次结束时间主要发生在20:00-01:00时和08:00-13:00时两个时段内,主要分布于盆地南部、中部和西部大部分地区;3)短时强降水事件极值降水的日变化上,降水量和频次呈现单峰型结构,白天多为短时间(2~4h)强降水事件出现极值,而傍晚开始至第二天清晨,持续2~10h强降水事件出现极值均有发生;强降水事件极值降水持续时间日变化,1~24h内呈单峰型结构,峰值出现在2h.