黑龙江省气候变暖对极端天气气候事件的影响

黑龙江省1980年以来气候变暖已成为事实，气候变暖导致天气气候极端事件的发生，主要表现在：①大雨暴雨次数增加；②30℃以上极端最高气温平均日数下降；③-30℃以下极端最低气温平均日数明显减少；④初霜日平均后延2～5天；⑤终霜日，北部中部提前3～5天而南部延长；⑥夏季低温次数明显减少，北部减少多于南部；⑦大旱年次数增多，大涝次数北少南多，西南部地区为旱涝敏感区。     

1951—2015年通辽市科尔沁区日气温特征分析

文章利用通辽国家基本气象站1951—2015年逐日最高气温、最低温度和日平均气温,计算了3个要素序列的算数平均值、中位数、众数及样本标准差等基本统计量,分析了每个气温等级出现的频次和不同气温段的气温日较差出现日数、日最高气温〉30℃日数和日最低气温≤-20℃日数等。结果表明：（1）该地极端最高气温达39.4℃,极端最低气温为-33.9℃,最高气温出现在7月12日,最低气温出现在1月17日。（2）全年26.1~28.0℃的最高气温出现频次和16.1~18.0℃的日最低气温出现频次最高。（3）一年中,日最高气温在0℃以上的天数占全年总日数的75%;日最低气温在0℃以下的日数占全年总日数的46%;日较差〉10℃的日数占全年总日数的69%。（4）1981—2015年平均气温比1951—1981年明显升高,表现为低温日数明显减少,而近10a不仅冬季低温日数减少而且夏季高温日数明显增多。     

海南岛汛期降水变化特征及其与旱涝的关系

选用海南岛18个市县气象观测站1981-2017年日降水资料,利用线性趋势、相关分析等方法研究了海南岛汛期降水变化特征及其与旱涝之间的关系,结果表明:汛期小雨日数的大值区主要分布在中部山区,中雨、大雨日数的大值区主要分布在中部、东南部地区,暴雨、大暴雨日数的大值区主要分布在中部、东部地区,而特大暴雨日数的大值区主要分布...     

1961—2021年四川省区域性暴雨过程时空变化特征

利用四川省156个国家气象观测站1961—2021年逐日降水资料,运用暴雨过程综合识别方法及评价指标,探讨四川省区域性暴雨过程时空变化特征。研究表明：1961—2021年四川省共出现875次区域性暴雨过程,过程次数逐年变化整体呈弱增长趋势,综合强度在20世纪90年代到21世纪初持续偏弱,21世纪以后呈现较明显增强趋势。四川区域性暴雨过程主要发生在6月下旬到9月上旬,大多持续1～2 d,区域性暴雨日数大值中心主要分布在盆地西部和东北部,阿坝州中部和东部、甘孜州东南部及攀西地区东北部,6—8月区域性暴雨日数大值中心从盆地东部逐渐向西部变化,9月则在盆地北部;盆地各月平均过程雨量以西部和东北部最强,攀西地区6、9月区域性暴雨日数偏少,但中部和东北部过程雨量强度未明显减弱。     

1981-2015年招远市气温变化征分析

文章利用招远国家气象观测站1981-2015年气温观测资料,运用趋势滑动平均和线性倾向估计方法对招远气象站气温变化特征进行了分析.结果表明:1981-2015年招远气象站年平均气温以0.22℃/10a的速率呈明显上升趋势,且具有明显的阶段性变化特征.季节平均气温均以不同速率上升,冬季气温上升趋势最为显著.年平均最高气温、最低气温均呈上升趋势,年平均最低气温上升趋势最显著.受热岛效应的影响,年平均最低气温的上升速率远大于年平均最高气温.除夏季平均最高气温呈缓慢下降趋势,其他季节均呈上升趋势,且冬季平均最低气温上升趋势最为明显.平均最低气温的快速上升使得气温日较差呈减小趋势.     

黄山雾凇气候特征及旅游气象指数预报

利用1956年至2018年黄山风景区气象观测资料,分析了黄山雾凇气候变化特征。结果表明: 黄山年均雾凇日数63.3天,最多年份为82天,最少为35天,年雾凇日数呈减少趋势;雾凇出现最早月份在10月,最迟在5月,冬季月份雾凇日数占全年约为7成,最多为1月,最少为5月;黄山雾凇的平均初日为11月7日,最早初日为10月8日,平均终日为4月7日,最迟终日为5月12日,连续最长雾凇日数为32天;近20年黄山雾凇出现气温范围为-18.7～1℃,风速范围为0～20.6m/s,任何风向均能出现雾凇;南北向的雾凇直径、厚度和重量略大于东西向,最大值出现在1、2月份,最大直径为230mm,最大厚度为105mm,最大重量为1138g/m。气温、湿度和风速均与雾凇强度呈现显著性相关,最低气温和水汽条件是影响黄山雾凇形成的关键气象因子,风速主要影响雾凇大小。占绝大多数的微量雾凇日数达不到雾凇景观标准,能形成雾凇景观的日数年均20.1天。利用影响雾凇景观形成的关键气象因子建立了黄山雾凇旅游气象指数,经实践检验准确率良好,可为气象业务应用提供预报参考,提升黄山旅游气象服务品质。     

一次转折性天气的预报

1 简 述 1992年绥化地区严重的干旱持续到初夏,6月上旬中受强冷空气侵袭,我区出现了5—7天的低温阴雨天气,降水明显偏多,发生了历史同期罕见的局地大雨和暴雨,本旬气温偏低4℃—5℃,出现了夏季冷害,对这次转折性天气,预报准确,取得很好的服务效果。     

1981—2015年招远市气温变化特征分析

文章利用招远国家气象观测站1981—2015年气温观测资料,运用趋势滑动平均和线性倾向估计方法对招远气象站气温变化特征进行了分析。结果表明:1981—2015年招远气象站年平均气温以0.22℃/10a的速率呈明显上升趋势,且具有明显的阶段性变化特征。季节平均气温均以不同速率上升,冬季气温上升趋势最为显著。年平均最高气温、最低气温均呈上升趋势,年平均最低气温上升趋势最显著。受热岛效应的影响,年平均最低气温的上升速率远大于年平均最高气温。除夏季平均最高气温呈缓慢下降趋势,其他季节均呈上升趋势,且冬季平均最低气温上升趋势最为明显。平均最低气温的快速上升使得气温日较差呈减小趋势。     

广西气候之最

最热的地方是北海市涠洲岛,年平均气温为23.0℃。最冷的地方是乐业县,年平均气温为16.3℃。极端最高气温出现在1958年4月23日的百色县,高达42.5℃。极端最低气温出现在1963年1月15日的资源县,低至-8.4℃。日最大降雨量出现在1971年5月31日的灵山县,降雨量为498.3毫米。年最多降雨量出现在1968年的东兴站,这一年的雨量为3531.7毫米。     

连云港市暴雨天气形势分析

用连云港市7个气象观测站的常规观测资料,对1971-2008年的38 a中29次区域性暴雨天气过程进行数理统计,对连云港市的暴雨天气变化趋势进行探讨,连云港市暴雨天气主要发生在6-9月,7-8月次数最多,占总数79％,雨量极值出现在西连岛站,暴雨日数及雨量极值趋于增大且趋势比较明显.同时,对全市区域性暴雨天气的高空影响系统进行了分类,划分为4种类型:台风减弱型、低压型、横槽类型、低槽类型,各类型几乎各占总暴雨数的1/4.     

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.     

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     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;