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选取2010—2014年广东省86个国家气象站和2 300多个区域中尺度气象站的小时雨量数据,分析了广东短时强降水的时空分布特征,结果表明:(1)广东的短时强降水多发区集中在3大暴雨中心以及珠三角城市群和西南部的湛江、茂名地区;短时强降水的空间分布与地形关系密切,多产生于河谷、湖泊和喇叭口地形区。(2)短时强降水有明显的月变化,5月份短时强降水次数爆发性增长,次数可占全年总次数的25%,其次是6和8月。(3)短时强降水的日变化总体表现为双峰型,主峰在午后至傍晚时段(14:00—20:00),次峰在早晨前后(04:00—09:00),而午夜(22:00—02:00)是短时强降水发生最少的时段。 相似文献
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利用青藏高原边坡临夏地区6个国家级自动气象站和66个乡镇区域自动气象站2010—2019年5—9月逐小时降水资料，详细分析了临夏地区短时强降水的时空分布及海拔地形特征，结果表明：近10 a短时强降水频次总体呈上升趋势，短时强降水频次与西太副高脊线位置和北界位置有密切关系。短时强降水主要发生在5—9月，集中时段为7月中旬到8月中旬，19:00～23:00为高发时段，属于傍晚型和夜雨型。近10 a临夏地区短时强降水的极端性逐年增大，单站年均频次在0.2～2.6次之间，平均为0.8次，短时强降水空间分布差异较大，总体呈西南多、东部和北部少，山区多、川区少的分布特征。临夏地区降水分布与海拔高度有明显关系，5—9月平均降水量随海拔高度升高而增大，不同海拔地形下短时强降水频次分布呈现两个极端：海拔较高的山地喇叭口地形区域和海拔较低的河谷地区，是临夏地区汛期短时强降水的重点关注区域。 相似文献
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利用惠东县2012—2021年间17个气象观测站逐小时降水资料，分析惠东县短时强降水时空分布特征。结果表明：(1)短时强降水发生次数大体上呈递增趋势，但各年差异较大；(2)在月际变化上阶段性明显，呈现“双峰型”特征，8月短时强降水最为活跃，其次是5至6月；(3)惠东短时强降水频率的日变化呈现“三峰型”特征，主峰出现在14:00—17:00,次峰分别出现在02:00—05:00和08:00—11:00;(4)短时强降水存在较强的局地性，其中南部沿海的平海、铁涌、黄埠和东部山区的高潭的短时强降水发生概率相对较高。 相似文献
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利用2010—2018年夏季阿勒泰地区112个自动气象站逐时降水资料,采用常规统计方法分析了阿勒泰地区夏季短时强降水时空分布特征。结果表明,2010—2018年夏季阿勒泰地区短时强降水的空间分布极不均匀,主要发生在阿尔泰山和沙吾尔山迎风坡、地形陡升区、喇叭口地形、戈壁和乌伦古湖交界区等复杂地形附近;发生次数年际变化大,2017年出现最多达95次,2010年出现最少为10次;极大值出现在2017年6月30日15:00哈巴河县合孜勒哈克村（37.5 mm/h）,极小值出现在2015年8月9日17:00福海县工业园区（22.5 mm/h）。旬、日发生频次变化均呈单峰型,旬峰值出现在7月上旬,日高峰值时段出现在午后至傍晚（19时左右）;各站短时强降水持续时间为1—2 h,区域性短时强降水最长持续时间为5 h;2017年短时强降水出现最多、持续时间最长、范围最广、强度最强。 相似文献
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采用2010—2015年肇庆市146个自动站3—10月的时雨量和最大风速资料,统计分析肇庆市短时强降水和雷暴大风的时空分布特征。结果表明:(1)肇庆短时强降水和雷暴大风发生的高峰期是5—8月,峰值位于5月。(2)肇庆短时强降水和雷暴大风日变化都有日强、夜弱的特征,高发期在白天的午后。短时强降水的峰值出现在17:00前后,雷暴大风的峰值则在15:00。3—6月的短时强降水在凌晨07:00前后有一个小高峰,雷暴大风在凌晨05:00有小高峰。(3)肇庆短时强降水空间分布受地形影响较明显,3—10月多发于山区与平原过渡的地区。3—6月短时强降水多发范围远大于7—10月。3—6月有呈南北向的弱(西部偏西)、强(中东部)两带,小中心分布与地形山脉间的山谷走向接近;7—10月的多发区在肇庆东部,小中心主要位于东部的东南迎风坡。(4)肇庆雷暴大风多发地多处于平原、盆地、西江沿岸等地形较为开阔处,在封开县江口附近有一个高频的多发中心。 相似文献
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基于2016—2019年防城港市自动气象站小时雨量,结合地形分析短时强降水时空分布特征,结果表明：十万大山南北两侧短时强降水次数从北到南递增,大值区位于十万大山南侧的迎风坡及喇叭口地形;各月的短时强降水的分布有差异,短时强降水主要发生在4—9月,6月短时强降水分布不均匀,7—8月短时强降水最强盛;受对流日变化、低空急流、海陆风等影响,短时强降水日变化特征明显,前汛期市南部短时强降水高峰期出现在清晨、市北部出现在凌晨和午后,后汛期市南部出现在清晨和午后、市北部出现在午后到傍晚,非汛期短时强降水出现的时段呈多峰值态势。 相似文献
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《气象与环境学报》2017,(4)
利用1971—2003年辽宁省53个地面国家级气象站降水自记纸记录的经数字信息化处理后的逐小时降水量数据和2004—2014年自动气象站的降水观测资料,分析了4—10月辽宁省短时强降水的时空变化特征。结果表明:1971—2014年辽宁省短时强降水的发生次数与年降水总量分布对应,均呈东部地区多、西部地区少的分布特征,与辽宁地区的地形和低空西南急流的风向等气候特征密切联系。1971—2014年辽宁地区年平均短时强降水发生次数为1.5—3.5次/a,并呈剧烈的振荡变化,短时强降水发生次数与辽宁省旱涝变化具有较好的对应关系。7月和8月辽宁地区短时强降水发生最多,辽宁省东部的丹东地区短时强降水发生次数明显偏多;6—8月旬短时强降水发生次数呈先增加后减少的变化,7月下旬短时强降水发生次数达到峰值,辽宁地区不同地域短时强降水发生次数的变化趋势也不同。受辽宁地区地形和低空急流的日变化影响,辽宁地区短时强降水发生次数的日变化也具有明显的地域性,辽宁省北部和最西部地区短时强降水发生次数的日变化不明显;辽宁省南部地区短时强降水多出现在后半夜至早晨,其他地区短时强降水多出现在下午。 相似文献
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重庆东北部短时强降水时空分布及概念模型 总被引：1，自引：0，他引：1
该文利用2007—2011年重庆东北部区域气象观测站和自动气象观测站的逐小时降水观测资料以及MICAPS高空、地面观测资料,分析了短时强降水的时空分布特征,发现:渝东北短时强降水事件逐年增多,降水站次显著增加,强降水雨量占年雨量比例逐年加大;短时强降水月际变化呈单峰型分布,7月为全年峰值所在;短时强降水夜间发生概率最大,其次是午后,上午发生的概率相对较小,其中,03—06时和18时前后发生短时强降水的可能性极大,且强度较强;空间特征方面,开县、云阳、巫溪中西部以及万州东部是短时强降水的高发区,渝东北地形对降水的影响主要包括喇叭口地形、狭管效应、山谷风环流等。根据短时强降水事件的高空环流场,建立了6个渝东北地区短时强降水概念模型,分别为:高原槽型、两高切变型、高原波动型、脊前北风型、低涡型和偏南气流型,各模型皆具备冷暖气流的交绥、不稳定层结、充足水汽以及抬升触发机制。 相似文献
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2008～2016年重庆地区降水时空分布特征 总被引：1，自引：0，他引：1
利用2008~2016年国家气象信息中心提供的0.1°分辨率的中国地面与CMORPH融合逐小时降水产品,分析了重庆地区的降水时空分布特征,尤其是小时强降水的时空分布特征。结果表明:(1)年均降水量总体呈西低东高分布,大值中心位于重庆东北和东南部,且存在一定的季节性差异,特别是夏季,西部降水明显增强,总降水呈两高(西部、东部)一低(中部)的分布;降水频次、降水强度与地形的相关性较高,海拔高度较高的山区(海拔高度>1000 m)降水频次多大于盆地和丘陵区(海拔高度<1000 m),降水强度与之相反,且小时强降水多发生在迎风坡前侧的过渡区域,说明高海拔区域易出现降水,但降水强度不强,而地形抬升则是触发强降水的重要原因,导致山前降水明显大于山峰。(2)重庆地区降水主要集中在5~9月,降水量、降水强度和小时强降水频次均呈单峰型分布,峰值出现在6~7月,降水频次呈双峰型分布,一个峰值出现在5~6月,另一个峰值出现在10月,7~8月为低频期,与副高控制下的连晴高温天气有关。(3)重庆地区降水存在明显的日变化特征,降水以夜雨为主,且降水峰值出现时间表现为向东延迟的特征,重庆西部日峰值出现在凌晨02:00(北京时,下同),中部出现在清晨05:00,东北部出现在早上08:00。从不同季节来看,春季、秋季和冬季降水日变化呈单峰型分布,主要集中在清晨,而夏季受午后局地对流性天气的影响,在下午17:00左右存在一个次峰值。(4)强降水的主要集中在夏季,在空间上存在三个大值中心,受西南涡及地形的相互作用,夏季在缙云山以西的盆地区域,小时强降水频次明显较高。 相似文献
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Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d. 相似文献
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Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region. 相似文献
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Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms. 相似文献
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The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics. 相似文献
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《大气和海洋科学快报》2013,(1):67
正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted 相似文献
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<正>With the support of specialized funds for national science institutions,the Guangzhou Institute of Tropical and Marine Meteorology,China Meteorological Administration set up in October 2008 an experiment base for marine meteorology and a number of observation systems for the coastal boundary layer,air-sea flux,marine environmental elements,and basic meteorological elements at Bohe town,Maoming city,Guangdong province,in the northern part of the South China Sea. 相似文献
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《大气和海洋科学快报》2014,7(6):F0003-F0003
AIMS AND SCOPE
Atmospheric and Oceanic Science Letters （AOSL） publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome. 相似文献
Atmospheric and Oceanic Science Letters （AOSL） publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome. 相似文献
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《大气和海洋科学快报》2014,(5):F0003-F0003
AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome. 相似文献
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《大气和海洋科学快报》2012,(3):273
正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences 相似文献