深圳云地闪时空分布特征研究

利用1997-2011年云地闪电定位探测资料和深圳国家基本气象站1953-2011年的观测资料,对深圳云地闪电（简称地闪）时空分布特征和雷暴日变化趋势进行分析。结果表明：深圳雷暴日数近59 a来呈下降趋势,小波分析显示年雷暴日数存在5 a周期和10-15 a的次周期;年内地闪频次特征表现为6月和8月双峰形特征,8月为全年地闪次数最多的月份;雷暴的活跃程度与太阳辐射热力条件密切相关,地闪活动高峰出现在14-18时;深圳地闪密度呈现西北多、东南少,内陆地区多、沿江沿海地区少的分布特征,地形、海陆分布是影响地闪空间分布的重要原因;地闪强度的分析表明,正、负闪月平均强度峰值分别出现在2月和6月,负闪强度低于正闪,正、负闪日强度峰值均未出现在频次峰值时段。     

Standardized estimates of climate change damages for the United States

Nordhaus (1991), Cline (1992), Fankhauser (1992), and Titus (1992) have published comprehensive estimates of annual climate change damages to the United States in about 2060 that vary from $55 billion to $111 billion ($1990). The estimates are comprehensive because they address market and nonmarket impacts. They based their estimates on different assumptions about the rates of climate change and sea level rise, rates of return on investment, and changes in population and income. In addition, many of the damage estimates, although reported for a 2.5–3.0 °C warming, were based on studies that assumed higher rates of warming. Thus, these studies may have overestimated damages associated with a 2.5–3.0 °C warming. In this paper, the results of these studies were standardized for a 2.5 °C warming, a 50-cm sea level rise, 1990 income and population, and a 4% real rate of return on investments. After standardization, the total damage estimates range from $42.3 billion to $52.8 billion, slightly less than 1% of United States GNP in 1990. Yet, within individual sectors, such as agriculture and electricity, standardized damages differ by more than an order of magnitude. In addition, a significant amount of speculation underlies the damage estimates. Thus, the small range of total standardized damages and apparent agreement about the magnitude of such damages should be interpreted with caution.     

Temporal features in thunder days in the United States

1901–80 data for the contiguous U.S. show that secular variability of thunder days was very much less than that of precipitation or of frequency of extra tropical cyclones. Overall, there may have been a slight decline, but more evident was an increase to the thirties followed by a falling off, broken only by a peak in the seventies. These up-and-down movements were evident in most months of the year and regions of the U.S. The general decrease, however, was clear only in the South East and replaced by an increase in the Upper Great Lakes region. Secular variation in thunder day frequency was slightly correlated positively with that of extra tropical cyclone frequency and negatively with sea level pressure. The analysis also confirmed well known seasonal and regional patterns of thunder activity.     

1961～2017年遵义地区冰雹时空分布特征

本文利用CIMISS、遵义13个气象站月报表等数据,收集了1961年1月1日至2017年12月31日遵义地区气象站的冰雹、大风和降水情况,从冰雹直径、冰雹时间和空间分布、冰雹与大风的关系、冰雹与降水的关系等方面综合分析了遵义地区冰雹时空分布特征。结果表明：遵义地区降雹以小冰雹为主,发生大冰雹的概率小;降雹持续时间以短时降雹为主,降雹点1日内多次降雹可能性小;降雹日数余庆最多,赤水最少,遵义东部降雹日数最多,中部、西部和北部依次递减,大范围降雹的可能性较小;降雹时间集中在2～5月,其中4月最多,旬分布上看,5月上旬降雹日数最多;遵义地区降雹主要出现在夜间,白天集中在14～20 时;冰雹日数的年际变化和年代际变化总体呈下降的趋势,2011～2020年冰雹日数总和很可能跌破历史极值;降雹点出现大风的可能性较小,但整个遵义地区在同一天内既出现降雹又出现大风的概率高达74.23%;冰雹直径和降雨量之间呈弱的正相关。     

2008年1月我国南方严重冰雪灾害过程分析

2018年1月24日夜间至2月5日贵州出现低温雨雪天气。通过分析其特点,将该过程分为三个阶段,即中东部冻雨主导期、中西部弱雨雪期和中西部降雪发展期。本文利用常规观测资料和美国国家环境预报中心（NCEP）FNL 1°×1°再分析资料,对这一阶段的低温雨雪天气成因开展了分析,并基于观测要素统计结果构建上述三个阶段的探空模型。结果表明：（1）在三个阶段,亚洲中高纬度表现出不同的环流形势,分别出现了乌山阻塞形势、横槽转竖、两槽一脊形势;（2）4次强冷空气影响及静止锋西推是贵州自东向西出现低温雨雪天气的重要原因;（3）前期暖层与高湿区、后期冷区与高湿区的温湿特征造成不同相态降水,29日前有效降水促进了结冰较快增长;（4）三个阶段探空模型显示,不同相态降水均是静止锋后冷气团一侧锋面降水造成的结果,温度层结、湿层高度、逆温梯度、云顶温度、逆温底温度与地面温度对不同降水相态的形成具有重要影响。

     

近53年辽宁雾的时空分布及成因分析

利用1951～2003年辽宁12个代表站的雾资料,分析了雾的时空分布特征及形成条件。结果表明:辽宁年平均雾日地域分布呈现两高三低的形势。雾日的年际变化曲线较平稳,雾日最多的年份和最少的年份相差17d。沈阳与大连雾日变化相反,大连呈下降趋势,沈阳则在平稳中略有上升。辽宁大雾每个月都可形成,但沿海地区和内陆又有所差异,沿海地区主要出现在5～8月,而内陆地区主要出现在8～11月。雾日的天气形势可分为5～7种类型,其中以倒槽型、锋面气旋型、地形槽型、冷高压前部型最为典型。     

1960-2009年辽宁冬季风寒温度时空变化特征

基于1960-2009年辽宁省52个气象站气象资料,采用风寒温度计算公式和适合辽宁地区的分级标准并分类,得出50 a历年各类别风寒温度日数。使用旋转经验正交分解法（REOF）,分别针对各类别风寒温度日数进行区域划分,并分析了其空间分布和变化趋势。结果表明：辽宁省可按4个风寒温度类别分别分区,凉爽至轻度风寒可分为4个区域,而轻度、中度及重度风寒可分为3个区域;辽宁省辽东半岛五个地市所在地理区域为易患风寒日数最少的地域,辽宁北部、东北部五个地市为易患风寒日数最多的地域;辽宁地区各风寒类别所在划分区域的日数变化相位基本一致;年平均易患风寒日数总体变化趋势是在1986年发生一次突变,在1960-1985年相对偏多,1986-2009年相对偏少。     

1971—2008年青岛地区雷电时空分布特征

选取1971—2008年青岛地区7个地面观测站雷暴日资料和2006—2009年闪电定位系统监测资料,统计分析青岛雷暴的时空分布规律,并以某大型石化项目为例,分析了该区域地闪的分布特征。结果表明：近38 a青岛地区雷暴日空间分布自东南向西北逐渐增多,季节性分布特征明显,主要集中在7月和8月。根据闪电定位资料,借助分析软件...     

1971—2008年青岛地区雷电时空分布特征

选取1971—2008年青岛地区7个地面观测站雷暴日资料和2006—2009年闪电定位系统监测资料,统计分析青岛雷暴的时空分布规律,并以某大型石化项目为例,分析了该区域地闪的分布特征。结果表明：近38 a青岛地区雷暴日空间分布自东南向西北逐渐增多,季节性分布特征明显,主要集中在7月和8月。根据闪电定位资料,借助分析软件得出该石化项目附近雷电流强度分布图和雷电流累积概率分布曲线,进而得出对应的雷电流强度值,最大值为41.68 kA。利用闪电定位系统提供的地闪次数计算地闪密度Ng比用人工观测资料计算的结果更为客观,研究结果可为雷电灾害风险评估提供评估参数。     

双低空急流影响下华南初夏降水日变化的时空分布特征

利用2010—2016年5—6月ERA5逐小时再分析数据集和国家气象信息中心逐小时降水量融合产品,对影响华南地区的低空急流事件进行筛选和分类,并分析天气系统相关的低空急流(Synoptic-system-related Low-Level Jet, SLLJ)和边界层急流(Boundary Layer Jet, BLJ)的日变化及其影响下的华南降水日变化的时空分布特征。结果表明,BLJ和SLLJ在白天减弱、夜间增强,并在凌晨达到峰值,其日变化主要与边界层惯性振荡引起的非地转风的顺时针旋转有关。双急流日华南地区降水量显著增加,且降水日变化有明显的区域差异,这与双急流的演变和配置密切相关。广西中北部主要为SLLJ左前方发生的夜间山区降水,且降水量仅有凌晨的单峰。广西沿海和广东地区存在早晨和午后两个峰值,BLJ出口区辐合和SLLJ入口区辐散的维持有利于降水频率的增大,从而导致午后峰值的出现,而早晨的峰值除了受双急流有利配置的影响外,主要归因于早晨降水强度的增加。     

1964-2008年辽宁省旱涝时空分布特征及演变趋势

利用1964—2008年辽宁51站降水量资料,采用Z指数和区域旱涝HL指数分析了全区近45a旱涝变化。结果表明：近45a辽西、辽北以及辽东南地区单站旱涝发生频率均明显高于辽中、辽东地区;区域性洪涝指数逐渐减小,区域性干旱指数逐步增大。对辽宁51站Z指数进行了EOF和REOF分析,可知辽宁旱涝的空间分布特征除受大尺度天气系统所带来的降水量变化影响外,同时还受地理位置、海陆分布等多种因子影响。通过REOF方法可将全区分为4个区域,即Ⅰ辽西地区,Ⅱ辽北、辽西北地区,Ⅲ辽中、辽东地区和Ⅳ辽东南地区。     

1964-2008年辽宁省旱涝时空分布特征及演变趋势

利用1964-2008年辽宁51站降水量资料,采用Z指数和区域旱涝HL指数分析了全区近45a旱涝变化.结果表明:近45 a辽西、辽北以及辽东南地区单站旱涝发生频率均明显高于辽中、辽东地区;区域性洪涝指数逐渐减小,区域性干旱指数逐步增大.对辽宁51站Z指数进行了EOF和REOF分析,可知辽宁旱涝的空间分布特征除受大尺度天...     

Spatial and Temporal Variability of Drought Patterns over the Continental United States from Observations and Regional Climate Models

The aim of this study is to analyze the spatial and temporal structure of drought over the continental United States(CONUS) and their teleconnection at different timescales from observations and climate models. We use the standardized precipitation evapotranspiration index(SPEI) at 12-and 24-month timescales as the drought index. Spatial patterns of drought regimes are delineated by using the principal component analysis(PCA) while the temporal characteristics of the variability of each drought pattern and teleconnection with climate indices are analyzed by using the wavelet analysis. Wavelet coherence of the drought pattern and four climate indices: El Ni?o–Southern Oscillation(ENSO), Pacific decadal oscillation(PDO), Atlantic multidecadal oscillation(AMO), and North Atlantic Oscillation(NAO) are analyzed. The results show that major drought patterns are located over the Northwest, South, Upper Midwest, and East regions. The spatial pattern of the drought regimes is similar for the 12-and 24-month timescale drought. ENSO influences the drought over West and South at decadal timescales throughout the study period(1950–2015) while intermittent significant coherence is observed at interannual timescale. The coherence of NAO and PDO with SPEI-12 is decreased during recent decades. Generally, regional climate model(RCM)-simulated drought patterns are more localized in a smaller area over the region compared to the spatial extent of observed drought patterns. Power spectra of seasonal to interannual variability(2–5-yr period) of all four drought patterns from RCM simulations are similar to those from the observations. However, at larger periodicities(decadal variations)among-RCM spread increases with increasing periods.     

基于SPEI的1961—2015年淮北地区干旱时空分布特征

基于标准化降水蒸散指数（SPEI）,利用淮北地区108个气象站逐月气温、降水观测资料,采用线性趋势、M K突变检验等方法,从不同时间尺度（年、季）和干旱程度（轻旱、中旱、重旱和特旱）分析了淮北地区1961—2015年干旱频率和时空变化特征。结果表明：淮北地区1961—2015年总体呈干旱略加强趋势,其中1998—2001年干旱发生最频繁,干旱强度、极端干旱及中等干旱的频次均呈增加趋势。2011年淮北地区干旱程度发生了突变性增强;20世纪90年代起淮北地区夏季经历了先湿后干的转变,2013年是夏季转向干旱化的突变点。秋冬两季是淮北地区发生干旱频率较高的季节。秋季干旱分布广、旱情最为严重,淮北地区北部是秋季干旱的高发区;冬季发生中旱以上干旱的地区分布较广,主要位于淮北地区内的安徽片西部和江苏片中部。春夏季发生高频率干旱的区域相对较小。     

德清县雷电时空分布特征及雷击灾害风险区划

利用近4 a德清县地闪数据,采用网格法绘制地闪密度图,并对近40 a德清雷县暴日数据进行分析,同时对雷击灾害风险进行区划研究。结果表明：20世纪70—80年代德清县雷暴日较90年代和2000年以后偏多;1971—2000年雷暴日呈下降趋势,但2000年后雷暴日数呈上升趋势;除12月以外每月均有雷暴发生,7月和8月为雷暴日高发期;春夏季雷暴日较多,秋季次之,冬季较少发生雷暴。雷电主要出现在12—13时和15—16时。至2010年,德清县大部分乡镇地闪密度均大于4次/km2,落雷密集区面积逐年增加,高密集区有向山区和东北部乡镇扩散的趋势。落雷的分布与地形有密切关系,西北部高海拔山区和海拔在50—200 m的低坡丘陵地带落雷密度较大。德清县莫干山至对河口水库一带、县城武康北部、洛舍和钟管镇交界一带及雷甸镇西南部均为雷电灾害高风险区。     

Modelling European winter wind storm losses in current and future climate

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (?22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.     

德清县雷电活动时空分布特征及雷击灾害风险区划

利用近4 a德清县内地闪数据,采用网格法绘制地闪密度图,并对近40a的德清雷暴日数据进行分析,同时对雷击灾害风险进行区划研究。结果表明：20世纪70-80年代德清县雷暴日较90年代和2000年以后偏多|1971-2000年雷暴日呈现下降的趋势,但2000年后雷暴日数呈上升趋势|除12月以外每月均有雷暴发生,7月和8月是雷暴日高发期|春夏季雷暴日较多,秋季次之,冬季较少发生雷暴。雷电主要出现在12-13时和15-16时。至2010年,德清县大部分乡镇的地闪密度均大于4次/km²,落雷密集区面积逐年增加,高密集区有向山区和东北部乡镇扩散的趋势。落雷的分布与地形有密切关系,西北部高海拔山区和海拔在50-200m的低坡丘陵地带落雷密度较大。德清县莫干山至对河口水库一带、县城武康北部、洛舍和钟管镇交界一带及雷甸镇的西南部均为雷电灾害高风险区。     

Temporal and spatial variability of the global water balance

An analysis of simulated global water-balance components (precipitation [P], actual evapotranspiration [AET], runoff [R], and potential evapotranspiration [PET]) for the past century indicates that P has been the primary driver of variability in R. Additionally, since about 2000, there have been increases in P, AET, R, and PET for most of the globe. The increases in R during 2000 through 2009 have occurred despite unprecedented increases in PET. The increases in R are the result of substantial increases in P during the cool Northern Hemisphere months (i.e. October through March) when PET increases were relatively small; the largest PET increases occurred during the warm Northern Hemisphere months (April through September). Additionally, for the 2000 through 2009 period, the latitudinal distribution of P departures appears to co-vary with the mean P departures from 16 climate model projections of the latitudinal response of P to warming, except in the high latitudes. Finally, changes in water-balance variables appear large from the perspective of departures from the long-term means. However, when put into the context of the magnitudes of the raw water balance variable values, there appears to have been little change in any of the water-balance variables over the past century on a global or hemispheric scale.