雨凇观测判断的探讨

雨凇天气过程复杂,南方出现几率较少,但造成的灾害明显。为了加强对雨凇的观测和判断,对金华雨凇的气候特征进行了统计分析,对雨凇的形成条件、雨凇的判别方法、雨凇的观测发报注意事项进行了探讨。     

吉林省雨凇气候特征及其天气分型

利用1980-2007年吉林省11个气象观测站常规观测资料,采用统计分析的方法,对共计100次雨凇天气的时空分布特征进行了分析。结果表明：吉林省雨凇天气南多北少,丘陵地带及长白山脉的迎风坡一带为雨凇的频发区。雨凇多发于冬初和初春,并且雨凇出现几率在减少。吉林省的雨凇天气的温度层结结构与中国南方省市雨凇的情况存在较大差异：吉林省雨凇天气并不存在融化层和逆温层等结构。通过对地面形势的分析,将雨凇天气分为低压后部型、高压前部型、低压南部型和低压型。它们的共同点是高空均有较深厚的后倾槽移过吉林省,温度槽落后于高度槽;近地面层先升温后降温,850 hPa相对湿度为70 %左右,而地面相对湿度均可达到80 %或以上。强雨凇天气主要发生在东南部地区,强雨凇天气出现时的地面及高空形势与一般的雨凇天气发生时的形势基本相似,但850 hPa和地面的相对湿度比一般情况偏大10 %左右。     

中国雨凇的时空变化

基于1954—2017年中国2426个台站的日雨凇资料分析了中国雨凇日数的气候特征和变化特征。中国的雨凇主要出现在新疆和中国的103°E以东地区,主要区域有三个,分别是陕甘宁三省(区)交界、河南—湖北东部、江西—湖南—贵州—云贵川交界,其中第三个区域范围最大、雨凇日数最多,平均每年单站可达5～50 d,海拔3 047 m的峨眉山雨凇日数(128 d)为全国最多。黄河以南的雨凇区域内,海拔1000 m以上站点雨凇日数易多,峨眉山、南岳、威宁、庐山是我国雨凇日数最多的几个站。我国雨凇基本出现在9月至次年5月,最早出现最晚结束的区域在天山山脉、陕甘宁交界、云贵川交界站点。从范围大小、日数上均以江西—湖南—贵州—云贵川交界区域突出,该区域雨凇日数在出现时段内呈主峰型分布,出现时间主要集中在隆冬季节冷空气最活跃的1月中旬到2月上旬。三个主雨凇区的雨凇开始和结束日期无明显年代际差异,而日雨凇概率有明显的年代际变化特征,1961—2016年期间的前26年明显高于后30年。1961—2016年全国雨凇日数整体呈减少趋势,1990年后除贵州—湖南主雨凇区外,雨凇范围明显减小。     

庐山雨凇积冰日数变化特征及其与海气场关系

利用江西省气象信息中心提供的1970-2016年逐日庐山站电线积冰、NOAA重构延长的逐月海表温度(SST)及NCEP再分析风场等资料,采用线性趋势分析、Man-Kendall检验、Morlet小波分析、合成分析等方法,研究了庐山雨凇积冰日数的变化特征及其与海气场的关系,结果表明:1)庐山雨凇积冰基本发生在当年11月至次年3月。2)雨凇积冰日数总体呈显著下降趋势,且在1981年和2001年分别存在一显著突变,即1970-1980年庐山雨凇积冰日数异常偏多,1981-2001年庐山雨凇积冰均值基本接近常年,2001-2005年庐山雨凇又异常偏少。3)庐山雨凇积冰日数存在2~4年、6~8年及20年左右的振荡周期,2~4年周期变化在20世纪70年代、80年代末到90年代末及2005年以后振荡显著。4)庐山雨凇积冰异常偏多年代,前期410月整个热带太平洋海温异常偏低,同期113月庐山受贝加尔湖异常反气旋东南侧东北气流和来自东太平洋偏南气流的共同影响,有利于出现雨凇积冰。     

低温雨雪冰冻天气地面测报工作的技术处理和观测方法

根据天气学原理对出现雨凇的天气形势和条件及雨凇的形成和认识进行,找出了做好地面测报的一些观测方法。     

山东雨凇的天气气候特征分析

利用常规观测资料,对1971-2008年山东省雨凇天气的气候概况进行了统计分析,结果表明：空间上,山东省发生雨凇的分布极不均匀,鲁西北西部和鲁西南西部最多,鲁中山区和鲁东南地区次之,半岛东部最少;时间上,山东省雨凇有明显的年代际、年际变化特征,全省雨凇日数总体呈现下降趋势;雨凇发生时日平均气温为．2．0℃,雨凇发生时地面常规观测时次的风向大多为偏北风,最大结冰一般在30mm以下;38a共7次系统性雨凇过程,均为先暖后冷型。     

近50年江西省雨凇过程气候特征分析

基于江西省83个常规气象站近50年雨凇观测资料,分析了江西省雨凇天气的时空分布规律。利用Gumbel分布函数,对全省历年雨凇过程的持续时间、影响范围和年雨凇天数等时间序列进行了重现期分析,并对2008年初江西省出现的持续低温雨雪冰冻天气进行了定量的分析评估。结果表明：①江西省雨凇主要出现在冬季,以2月为最多,春、秋季在高海拔站偶有发生;②全省雨凇发生概率以中部和北部鄱阳湖北段沿岸最多,赣东北、赣西北和赣南最少,山区多于平原和丘陵;③2008年初江西省出现的低温雨雪冰冻天气主要致灾因子是大范围、长时间的雨凇天气,其影响范围、持续时间之长均创近50年之最,雨凇过程持续天数之长超过100年一遇,影响范围之广超过30年一遇。     

贵州雨凇灾害指标初探

该文在海拔高度分类之下,通过大量雨凇样本的气象条件概率分布分析,建立贵州雨凇灾害指标,即同时满足以下条件,则当日定为雨凇日:1日最低气温≤0℃;2日平均气温≤1℃(其中威宁站不受该条件约束);3当日无日照(其中威宁站不受该条件约束);4当日有降水,包含微量降水。通过该标准的筛选,所建立的雨凇灾害指标得到的雨凇日数在全省的分布形态基本与实况雨凇资料的结果一致。该指标的建立对雨凇资料的缺测起到一定的补充作用,同时还有利于进一步了解雨凇灾害发生时的气象条件。     

湖南雨凇与大气环流和海温因子的相关分析

雨凇是冬季影响湖南的一种主要气象灾害。对湖南雨凇与大气环流特征量、海温异常的相关性进行了分析。结果表明：亚洲区极涡面积和东亚槽位置对中国湖南雨凇天气影响极为重要。当欧亚纬向环流为低指数时,有利于中国湖南雨凇的形成;当东大西洋欧洲区阻塞高压面积指数为低指数和乌拉尔山区阻塞高压面积指数为高指数时,湖南多雨凇天气发生。冬季西太平洋副热带高压面积偏大、强度偏强、西脊点偏西不利于中国湖南雨凇发展。拉尼娜事件结束年同时为厄尔尼诺开始年的年份湖南雨凇最为严重,厄尔尼诺事件起始年湖南雨凇强度最轻。     

河北省雾凇和雨凇气候特征及气象条件分析

利用1980—2009年河北省142个气象站的雾凇、雨凇资料、河北省南部94个气象站的地面观测资料和邢台探空资料,分析了河北省雾凇、雨凇的时空分布特征;利用箱线图分析了河北省南部适宜雾凇、雨凇出现的温度、湿度和风速等气象条件。结果表明：（1）在空间分布上,雾凇、雨凇主要出现在河北省南部,东部平原多,西部山区少;在时间分布上,雾凇、雨凇均出现在11月至次年3月。（2）适宜雾凇出现的气象条件是雾日并且气温在-7.2～-3.1℃之间、相对湿度≥92%、风速≤1.2 m·s~（-1）;雾凇出现时,95%的情况出现了逆温层。（3）适宜雨凇出现的气象条件是雨日并且气温在-4.1～0℃之间、相对湿度≥87%;雨凇出现时均有逆温层出现。（4）雾凇、雨凇高值区的相对湿度明显高于低值区,因此相对湿度大是雾凇、雨凇高值区形成的主要原因。     

Native Trees as Biomonitors of Chemical Elements in the Biodiversity Conservation of the Atlantic Forest

The Atlantic Forest, a hotspot in the world with a great diversity of plants and animals, is located in the most industrialized area of Brazil, a potential source of chemical elements for the atmosphere. From its original area about 10% has been preserved mainly through the implementation of conservation units, among which the Parque Estadual Carlos Botelho (PECB) is one of the most representative. Here, leaves of the predominant species in the PECB were analyzed by instrumental neutron activation analysis (INAA) for the establishment of natural backgrounds of As, Ba, Br, Ca, Cd, Ce, Co, Cs, Fe, Hg, K, Na, Rb, Sc, Se, Sr and Zn. Biomonitoring of the Atlantic Forest was realized through the tree community study taking in account the interspecies and the intraspecies variability of chemical concentrations. Results pointed out the low status of pollution based on the concentrations of chemical elements of environmental concerning. However, Br concentrations were higher in the understory species, which could be related to the possible effects of atmospheric pollution or sea influence. In addition, some Hyeronima alchorneoides trees showed to be hyperaccumulators of Co.     

非轴对称双涡相互作用的研究

在平流动力学的框架内,用准地转正压涡度方程模式实施了19组试验,研究双涡合并的条件及较大尺度涡旋自组织的问题。结果指出:(1)存在着两个影响双涡合并的因素,即初始双涡中心之间的距离和初始涡旋的非轴对称分布。初始两个对称涡旋合并具有明显的临界距离效应,但初始两个非轴对称涡旋能否合并还受到初始涡旋的非对称结构的复杂影响。(2)存在着两类不同的较大尺度涡旋的自组织过程,形成较大尺度涡旋。第一类,初始两个涡旋相同,均呈轴对称分布。双涡作用经历了缓变、快变,以及涡量羽翼的生成、拉伸和发展的过程,合并后呈对称性流型;终态涡内区涡量的堆积来源于两个初始涡,终态涡外区的螺旋带来源于两个初始涡外缘线涡量羽翼的拉伸。第二类,初始两个涡旋不同,一个为椭圆型,一个为偏心型,均呈非轴对称分布。双涡作用中,椭圆涡一边互旋,一边向计算区域中心靠近,同时涡量范围加大,形成了终态涡的内核区;偏心涡一边互旋,一边被不断拉伸,形成了终态涡的螺旋带区;表现出终态涡内区的涡量堆集来源于椭圆涡,终态涡外区螺旋带主要来源于偏心涡的反复拉伸及断裂的特性。     

贵州铜仁2019年1月两次空气污染过程及其气象条件特征分析

2019年1月铜仁市发生了中到重度污染过程,本文利用铜仁市城区逐时环境监测资料,高空及地面气象观测资料,分析了本次污染过程气象条件特征。结果表明,此次首要污染物为细颗粒物（PM2.5）。污染天气发生时,铜仁上空是高压脊或一致的西南气流,地面为冷高压或均压区控制,气压梯度小,风小;当转为高空槽前,地面有冷空气补充,气压梯度增大时,污染物浓度得到降低。同时风速和相对湿度大小跟污染物浓度也有一定关系,地面风速小,空气干燥时,污染物浓度增加;相反,风速增大达4m/s以上,空气相对湿度增大达90%以上,特别是明显的雨雪天气发生时,污染物浓度得到快速降低。另外,污染天气伴随有近地层逆温层持续影响,逆温层厚度越厚,且逆温强度越强,抑制了大气垂直方向的湍流交换,有利于污染物浓度累积增长。受梵净山地形阻挡作用,当近地层为弱偏东风影响时,污染物不能翻越梵净山向西扩散,会在山的东侧堆积,导致铜仁城区污染物在本地循环累积,污染浓度维持较大值。上述研究结果,可为铜仁市空气质量预报及污染防控提供新的参考依据。     

基于WebGIS的气象服务产品制作系统及关键技术

基于WebGIS技术采用服务即是软件、软件即是服务的建设思路,结合可扩展框架技术,实现基于服务集成的气象服务产品在线制作系统的建设,从一定程度上解决了系统产品制作面临的不能集中部署、规范不统一、效率低下、更新复杂等问题。系统分为服务器端和客户端两部分,服务器端负责服务接口的开发和发布,客户端负责各级调度管理和运行。该系统解决了服务的注册、标准化、流水线化、参数序列化、多级任务调度等多个关键技术,系统具备可扩展性、产品标准化、流程规范化、跨平台等特点,系统建设的完成增加了气象服务产品制作的规范性、接口化,产品制作时间由原来的1~2 min降至10 s以内。     

基于GIS的三门峡市苹果种植气候适宜性区划

为了探明三门峡市苹果气候适应性及种植规模扩展空间,利用三门峡、灵宝、卢氏、渑池4个县级气象站点和苹果种植区及周边19个区域多要素气象站点资料,依据海拔高度将苹果种植区划分为塬区、浅山区和中山区3种区域,运用模糊隶属度评价各区气候因子,筛选出年均气温、年降水量、6—8月平均气温作为区划指标,针对不同气候要素采用克立格或反距离权重的GIS方法进行小网格插值,最终形成精细化的三门峡市苹果种植气候适宜性区划图。区划结果表明:最适宜区多位于三门峡市中部和中南部,适宜区多位于东部和北部,不适宜区为北部边缘地带。当前三门峡市苹果种植主要分布于灵宝中部、南部和陕县西南部,是苹果的主产区和优质区;其他未开展苹果种植的卢氏县北部、陕县东南部处于最适宜区域,渑池县大部分处于适宜区,是未来苹果种植面积扩展的首选地区,但尚需综合考虑土壤、地形、气候等因素对苹果品质的影响。     

安顺两次特大暴雨过程的TBB和螺旋度对比分析

利用自动站观测资料、探空资料及NCEP再分析资料,对2010年6月27日夜间和2012年7月12日夜间贵州南部局地大暴雨天气过程进行对比分析。结果表明,安顺的两次特大暴雨天气过程主要是受高空槽和中低层切变共同影响,并配合低空急流,形成了有利于强降水的环流背景。安顺处于假相当位温的高能舌区和K指数、螺旋度的大值区,为特大暴雨的形成提供了很好的能量和动力条件。MCC是造成安顺特大暴雨天气的直接原因,强降水发生在云团的冷核中心内,最强降水均出现在MCC的成熟期。关岭滑坡现场与周围环境明显的海拔高度差和温度差造成的热力差异,为关岭岗乌两次特大暴雨提供了动力源和暖湿气流,并造成了关岭岗乌多次的强降水。     

Dominant cloud microphysical processes of a torrential rainfall event in Sichuan,China

High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting (WRF) Model were used to study the dominant cloud microphysical processes of the torrential rainfall. The results showed that: (1) In the strong precipitation period, particle sizes of all hydrometeors increased, and mean-mass diameters of graupel increased the most significantly, as compared with those in the weak precipitation period; (2) The terminal velocity of raindrops was the strongest among all hydrometeors, followed by graupel’s, which was much smaller than that of raindrops. Differences between various hydrometeors’ terminal velocities in the strong precipitation period were larger than those in the weak precipitation period, which favored relative motion, collection interaction and transformation between the particles. Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity, and the stronger the precipitation was, the greater the differences between them were; (3) The orders of magnitudes of the various hydrometeors’ sources and sinks in the strong precipitation period were larger than those in the weak precipitation period, causing a difference in the intensity of precipitation. Water vapor, cloud water, raindrops, graupel and their exchange processes played a major role in the production of the torrential rainfall, and there were two main processes via which raindrops were generated: abundant water vapor condensed into cloud water and, on the one hand, accretion of cloud water by rain water formed rain water, while on the other hand, accretion of cloud water by graupel formed graupel, and then the melting of graupel formed rain water.     

Assessment of Temperature Extremes in China Using RegCM4 and WRF

This study assesses the performance of temperature extremes over China in two regional climate models(RCMs),RegCM4 and WRF, driven by the ECMWF's 20 th century reanalysis. Based on the advice of the Expert Team on Climate Change Detection and Indices(ETCCDI), 12 extreme temperature indices(i.e., TXx, TXn, TNx, TNn, TX90 p, TN90 p,TX10 p, TN10 p WSDI, ID, FD, and CSDI) are derived from the simulations of two RCMs and compared with those from the daily station-based observational data for the period 1981–2010. Overall, the two RCMs demonstrate satisfactory capability in representing the spatiotemporal distribution of the extreme indices over most regions. RegCM performs better than WRF in reproducing the mean temperature extremes, especially over the Tibetan Plateau(TP). Moreover, both models capture well the decreasing trends in ID, FD, CSDI, TX10 p, and TN10 p, and the increasing trends in TXx, TXn, TNx, TNn, WSDI, TX90 p,and TN90 p, over China. Compared with observation, RegCM tends to underestimate the trends of temperature extremes,while WRF tends to overestimate them over the TP. For instance, the linear trends of TXx over the TP from observation,RegCM, and WRF are 0.53?C(10 yr)^-1, 0.44?C(10 yr)^-1, and 0.75?C(10 yr)^-1, respectively. However, WRF performs better than RegCM in reproducing the interannual variability of the extreme-temperature indices. Our findings are helpful towards improving our understanding of the physical realism of RCMs in terms of different time scales, thus enabling us in future work to address the sources of model biases.     

Role of the 10–20-Day Oscillation in Sustained Rainstorms over Hainan,China in October 2010

Hainan, an island province of China in the northern South China Sea, experienced two sustained rainstorms in October2010, which were the most severe autumn rainstorms of the past 60 years. From August to October 2010, the most dominant signal of Hainan rainfall was the 10–20-day oscillation. This paper examines the roles of the 10–20-day oscillation in the convective activity and atmospheric circulation during the rainstorms of October 2010 over Hainan. During both rainstorms,Hainan was near the center of convective activity and under the influence of a lower-troposphere cyclonic circulation. The convective center was initiated in the west-central tropical Indian Ocean several days prior to the rainstorm in Hainan. The convective center first propagated eastward to the maritime continent, accompanied by the cyclonic circulation, and then moved northward to the northern South China Sea and South China, causing the rainstorms over Hainan. In addition, the westward propagation of convection from the tropical western Pacific to the southern South China Sea, as well as the propagation farther northward, intensified the convective activity over the northern South China Sea and South China during the first rainstorm.     

Quantifying Changes in Extreme Weather Events in Response to Warmer Global Temperature

Global warming is expected to affect both the frequency and severity of extreme weather events, though projections of the response of these events to climate warming remain highly uncertain. The range of changes reported in the climate modelling literature is very large, sometimes leading to contradictory results for a given extreme weather event. Much of this uncertainty stems from the incomplete understanding of the physics of extreme weather processes, the lack of representation of mesoscale processes in coarse-resolution climate models, and the effect of natural climate variability at multi-decadal time scales. However, some of the spread in results originates simply from the variety of scenarios for future climate change used to drive climate model simulations, which hampers the ability to make generalizations about predicted changes in extreme weather events. In this study, we present a meta-analysis of the literature on projected future extreme weather events in order to quantify expected changes in weather extremes as a function of a common metric of global mean temperature increases. We find that many extreme weather events are likely to be significantly affected by global warming. In particular, our analysis indicates that the overall frequency of global tropical cyclones could decrease with global warming but that the intensity of these storms, as well as the frequency of the most intense cyclones could increase, particularly in the northwestern Pacific basin. We also found increases in the intensity of South Asian monsoonal rainfall, the frequency of global heavy precipitation events, the number of North American severe thunderstorm days, North American drought conditions, and European heatwaves, with rising global mean temperatures. In addition, the periodicity of the El Niño–Southern Oscillation may decrease, which could, in itself, influence extreme weather frequency in many areas of the climate system.