南方三个省电线积冰时空分布特征

基于1961—2019年贵州、湖南、江西191个气象站点电线积冰资料,统计分析了研究区域内电线积冰的日数、标准冰厚极值、最大连续积冰日数的时空分布特征以及电线积冰起止日的时间变化;构建电线积冰风险指数,评估了出现电线积冰的风险。结果表明:电线积冰日数整体呈下降趋势,在20世纪80年代达到最大值,月分布以1月出现最多,电线积冰以雨凇型积冰为主。标准冰厚极值集中在20～50 mm,极值大部分出现在湖南;大部分站点极值出现在2011—2019年。最大连续积冰日数集中在5～15 d,整体上贵州的最大连续积冰日数高于湖南和江西。电线积冰的起始日的年际变化整体上呈提前趋势,而终止日整体上呈推迟趋势。电线积冰风险指数年变化整体上呈减小的趋势;电线积冰的高风险区域主要位于贵州中西部、湖南中部和江西北部,风险指数大于0.6。     

湖南省近60年雨凇的气候特征

采用湖南97个地面气象站点气象观测资料、运用经验正交函数、旋转经验正交函数、一元线性回归、Mann-Kendall、小波分析等方法分析了湖南雨凇的时空分布特征及变化趋势,并与高山站的变化趋势进行了比较.结果表明:湖南雨凇发生在11月至翌年3月,空间分布特征呈现为南多北少、东多西少、迎风坡多、背风坡少、“三心二带”、高低交错.湖南雨凇日数空间分布既有全区一致性,也存在着南北反向变化的差异,空间分布大致可分为湖南南部、北部及中部、西北部3个异常区.湖南年雨凇日数和南岳高山站年雨凇日数呈现出的周期变化相同,即均存在2a、4a、9a和24 a左右的准周期,2a和4a周期尺度雨凇日数多和少转换频繁,9a周期尺度在1970年代末以前振荡明显,在24 a准周期尺度上经历了1960年代初期、1970年代中期、1990年代初期、2000年代中期4个转折年份.在过去60年全省年雨凇日数呈显著减少趋势,南岳高山站年雨凇日数趋势变化不明显,但存在明显的年际和年代际变化.     

中国冰冻天气的气候特征

研究冰冻天气的空间分布和变化规律对于冰冻灾害的预测、预估以及防灾减灾具有重要意义。利用1961—2008年603个站点雾凇和雨凇天气现象资料,283个站点的电线覆冰资料,采用计算多年平均值、标准冰厚转换、EOF以及求趋势变化等方法,研究了我国冰冻天气的空间分布和气候变化特征。结果表明:全国大部分地区都有冰冻天气出现;雾凇主要出现在北方地区,雨凇主要出现在南方。年冰冻日数随海拔高度增加而增加,但海拔3100 m高度以上冰冻日数较少。冰冻厚度较大的地区位于东北东南部、华北东部、西北地区东南部、西南地区东部、江南东北部。在全球气候变暖背景下,我国大部分地区冰冻天气发生频次减少,但强度增强。     

河北省输电线路冰害的气象要素时空分布特征

冰害是电网的主要气象灾害之一,电线积冰与雾凇和雨凇密切相关。利用1980—2009年河北省142个气象观测站的雾凇、雨凇日数和20个气象站的电线积冰、相对湿度、气温、风速及站点海拔高度,以及近年来输电线路冰害事故和附近区域站同期气温、相对湿度、风速等资料,采用逐步回归等统计分析方法,对雾凇、雨凇和电线积冰的时空分布特征、冰害与气象要素的关系进行分析,并构建电线积冰的逐步回归预报模型。结果表明:1980—2009年,河北省雾凇和电线积冰日数均呈现先升后降的阶段性变化特征,1980年代末至1990年代中期为一高峰期,而雨凇日数年变化特征不明显;在空间上,雾凇、雨凇多出现在平原地区,雨凇中心比雾凇中心更偏东。电线积冰与雾凇、雨凇以及站点海拔高度密切相关,相关系数分别为0.988 5、0.760 6、-0.601 8,但仅雾凇日数和站点海拔高度被引入电线积冰日数预报方程。对河北省电线线路冰害事故分析发现,当气温低于3℃时,导线可能出现舞动;导线舞动或冰闪时的相对湿度都在60%以上,舞动时风速大于5 m·s~(-1)。     

2008年贵州省持续性雨凇过程气候成因分析

2008年初中国南方低温雨雪冰冻过程中贵州出现长时间持续性雨凇。该文使用2008年1—2月逐日要素、环流、海温等资料对此次贵州省雨凇过程特征,大气环流、海温和海冰等气候因子及其影响进行分析,得到以下结论：①2008年初贵州的持续性雨凇过程主要分两个阶段：1月13日—2月2日东西向的省中部大范围强雨凇阶段及2月3日—2月15日南北向的省西部小范围强度相对较弱的雨凇阶段;②0 ℃日最高气温是雨凇出现与否的重要临界点;700 hPa与850 hPa温度差表征的逆温范围和强度可用于监测和预测强雨凇过程;③环流上,南掉到青藏高原西侧的切断低涡堆积的冷空气分南北两路绕过青藏高原东移,是此次持续性雨凇过程的直接原因;④秋季北极海冰密集度减少和减少幅度是冬季西伯利亚高压偏强、强冷空气堆积南下的前期主要信号,可作为贵州雨凇预测的早期信号之一;⑤2008年1月热带印度洋暖海温与赤道中东太平洋明显冷海温呈现非一致性变化,冬季热带印度洋暖海温通过二级热力适应对西太平洋副热带高压起到加强的作用,而拉尼娜冷海温对东亚冬季风起到偏强的影响,应当关注这两个区域冬季海温非协同性变化对贵州雨凇的影响和预测。     

黄山光明顶雪,雨凇和雾凇的气候特征研究

本文用黄山1956—1996年气象资料,比较详细地分析讨论黄山雪、雨凇和雾凇的气候特征,结果表明：（1）年降雪日数、雨凇日数和雾凇日数均为一多波振动的时间演变规律,年际变化具有阶段性,并存在准12年周期的低频振荡。（2）10月到次年5月都有降雪、积雪、雨凇和雾凇出现,冬季出现日数最多;3月比冬季略少,但雨凇日数多于12月．（3）降雪最早初日为9月17日,最迟终日5月26日;积雪、雨凇和雾凇最早初日在10月,最迟终日在5月上、中旬。（4）日最大纯降雪量为30．0mm,出现在3月中旬;电线积冰量大重量为12148g／m,出现在12月。（5）雨凇保持阶段的气温在-4．5—0．8℃之间,比雾凇和雨雾凇高,次数按风向分布也无明显差异;雾凇和雨雾凇在NW风向附近次数最多。     

水城县半个多世纪雨凇气候特征分析

选取水城县1956—2008年11月—次年3月雨凇资料,分析了水城县雨凇出现日数及年一次最长持续时间的变化特征。结果表明:水城县53 a来雨凇出现日数呈减少趋势,冬季气候变暖的特征趋于明显;12月雨凇出现日数呈减少趋势,1月呈略增多趋势,2月呈明显减少趋势;20世纪80年代冬季气候最为异常,雨凇出现日数最多和最少均发生在该年代,相对冷、暖气候特点非常明显。     

近50a华东地区夏季极端降水事件的年代际变化

利用中国华东地区90站点1960--2009年夏季（6—8月）逐日降水资料,分析了近50a来华东地区各类极端降水事件的强度和发生频次的年代际变化。结果表明：华东地区极端降水事件年代际变化特征明显。近20a来,不论是极端降水事件的平均强度还是发生次数都要明显高于前30a;1990年代是极端事件多发且强度较强的年代;华东区域极端强降水过程事件的连续降水日数多在9d以下,而极端连续降水日数事件基本在9d以上;较之华东地区其他区域,福建地区存在更多的强度大、持续久的降水过程;华东地区最大极端降水量出现在江西北部与安徽南部的交界区域。极端降水事件频发带存在南北摆动的年代际变化,这一特征在极端日降水事件和极端强降水过程事件上表现得更为明显。同时,存在两个极端事件频发带,分别位于长江流域附近。在后3个年代,这两个频发带呈现出分一合一分的年代际变化特征。     

2016—2020年哈密市暖季降水特征及其与海拔高度的关系

利用2016—2020年暖季(5—9月)哈密市6个国家气象站及71个区域自动站逐小时降水资料,分析了降水量、降水日数及其与海拔高度的关系。结果表明：(1)哈密市暖季降水集中在6—8月,降水量(日数)以小雨最多,暴雨最少。(2)暖季平均降水量(日数)及各等级降水量(日数)均呈西北—东南向的带状分布,沿天山山脉向两侧递减;各等级降水量和降水日数的大值区在天山山脉两侧海拔较高区域,东北部以及西南部的戈壁区域降水很少,且西南部的戈壁区域未出现过暴雨。(3)暖季降水量与降水日数呈显著正相关,在2 600 m以下,海拔高度平均每升高100 m,降水量增加约12.3 mm,降水日数增加2.1 d。(4)在海拔1 000 m以上各等级降水量均存在相对偏少区,海拔2 400～<2 600 m中雨及以下降水日数最多,2 200～<2 400 m大雨及以上降水日数最多。     

贵州区域性暴雨过程的定量化评估及气候特征

利用贵州省84个气象观测站点1961—2020年逐日降水数据,定义贵州省区域暴雨标准,构建了综合考虑暴雨过程持续时间、暴雨范围、平均暴雨量3个指标的贵州区域性暴雨过程综合强度评估方法和雨涝年景指数,分析近60a贵州区域暴雨过程次数、强度和雨涝年景指数等特征和变化。结果表明：贵州区域性暴雨过程共出现721次,平均每年12.0次,2015年最多达20次,1961年最少仅4次;区域性暴雨过程3—9月均可出现,6—7月最为集中,6月最多,3月最少;区域性暴雨过程以0.4次/10a 的速率呈弱的上升趋势,年际和年代际特征明显;区域性暴雨过程的影响范围多为6～19站,持续天数为 1～5 d,平均暴雨量多为60～80mm;强、特强暴雨过程呈显著增加趋势,较强暴雨过程呈略微增加趋势,一般性暴雨过程呈略微减少趋势;雨涝年景指数呈显著上升趋势,7个强雨涝年2014、2020、1996、1999、1995、2000和1991年均出现在1990年后。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

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.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

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.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

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.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on