21世纪末华南汛期强降水变化分析

利用英国Hadley气候预测与研究中心的区域气候模式系统PRECIS,基于政府间气候变化专门委员会（IPCC）2000年“排放情景特别报告”（SRES）B2情景下对华南区域2071～2100年汛期（前汛期：4～6月;后汛期：7～9月）强降水的模拟结果进行分析。结果显示PRECIS对华南地区汛期强降水具有较好的模拟能力。相对1961～1990年（以下称气候基准时段）,2071-2100年华南汛期的强降水比例有所增大,强降水日数变化百分数大值中心分布在广西中北部和福建省北部,后汛期大值中心主要分布在广东和福建省。对华南4省（区）除了海南岛外各省逐月变化百分数基本为正值,汛期极端降水的发生频率相比气候基准时段有明显增加。     

未来我国极端温度事件变化情景分析

基于Hadley气候预测与研究中心的区域气候模式系统PRECIS（Providing REgional Climates for Impacts Studies）单向嵌套该中心全球海-气耦合气候模式HadCM3高分辨率的大气部分HadAM3P, 检验PRECIS对我国气候基准时段（1961—1990年）极端温度事件的模拟能力, 分析IPCCSRES（Special Reporton Emission Scenarios）B2情景下未来2071—2100年相对于气候基准时段我国极端温度事件的变化响应。与观测资料的对比分析表明:PRECIS能够较好地模拟我国气候基准时段极端温度事件的局地分布特征。IPCC SRESB2情景下, 预估未来2071—2100年我国大部分地区高温日数出现频率均比气候基准时段高5倍以上; 霜冻日数将呈减少趋势, 我国南方地区的减少趋势大于北方地区; 暖期持续指数整体将呈增加趋势, 我国东北地区、西北地区中西部、华北地区和东南沿海地区增加显著; 冷期持续指数整体将呈减少趋势, 且东北地区、华北地区、西北地区及内蒙古、青藏高原大部地区的减少幅度将达到90%以上。     

SRES A2情景下中国区域21世纪末平均和极端气候变化的模拟

利用Hadley气候预测与研究中心的区域气候模式系统PRECIS单向嵌套该中心全球海-气耦合气候模式HadCM3高分辨率的大气部分HadAM3H,分析了SRES A2情景下2071-2100年相对于气候基准时段（1961-1990年）中国区域的气候变化,包括气温和降水的年际、季节和日时间尺度的变化以及极端气候事件的变化趋势。模拟结果表明：气温呈明显增加趋势,其中新疆和东北地区增温明显。而降水表现了更大的年际变化和季节变化,冬季南方降水减少,但沿黄河流域的降水明显增加,夏季与冬季相比呈现出相反的趋势。此外,连续高温日数呈现增加趋势,而连续霜冻日数呈现减少趋势。连续湿日数也表现出一定的增加趋势。     

“三江源”地区未来气候变化的模拟分析

利用ECMWF1979~1993年的再分析数据(ERA15)作为边界条件,驱动区域气候模式系统PRE-CIS(Providing Regional Climates for Impacts Studies)模拟"三江源"地区的月均降水与台站实际观测资料进行的对比表明,PRECIS模拟的降水值偏大,但总体上能够模拟出降水的季节变化特征。气候基准时段(1961~1990年)的模拟结果与同期观测资料的对比分析表明,PRECIS能够模拟出"三江源"地区降水的季节分布特征和空间差异,但模拟值总体偏大。相对于气候基准时段,SRESA2、B2情景下2071~2100年(2080s时段)"三江源"地区增温明显,两种情景下年均升温分别可达4℃和2.8℃,降水略有增加;冬季升温幅度最大,分别可达4.4℃和3.2℃,降水增加的比例也最大;夏季"三江源"地区的升温达到4.2℃和3℃以上,但有些地区的降水呈减少趋势。夏季降水量的减少和气温的升高会加剧"三江源"地区气候变干的趋势,导致源区水源补给不足。应当采取切实可行的措施保护江河源区的自然生态系统,避免源区气候环境的进一步恶化。     

温室效应引起的江淮流域气候变化预估

 选用英国Hadley中心的RCM-PRECIS模式进行江淮流域气候变化的数值模拟。在验证了PRECIS在江淮流域模拟能力的基础上,对未来CO₂增加后江淮流域的气候变化响应进行了预估。结果表明：在B2情景下,整个江淮流域都将继续增暖,到本世纪末（2071-2100年）区域年平均温度将增加2.9℃,夏季将可能出现更多的高温事件,而冬季极端低温事件减少;降水量呈增加趋势,强降水（尤其是120 mm以上的降水）日数也将增多。     

温室效应引起的江淮流域气候变化预估

选用英国Hadley中心的RCM-PRECIS模式进行江淮流域气候变化的数值模拟。在验证了PRECIS在江淮流域模拟能力的基础上,对未来CO₂增加后江淮流域的气候变化响应进行了预估。结果表明：在B2情景下,整个江淮流域都将继续增暖,到本世纪末（2071-2100年）区域年平均温度将增加2.9℃,夏季将可能出现更多的高温事件,而冬季极端低温事件减少;降水量呈增加趋势,强降水（尤其是120 mm以上的降水）日数也将增多。     

全球变暖情景下中国东部地区不同等级降水变化特征分析

利用日本东京大学气候系统研究中心、 日本环境研究所和日本地球环境研究中心联合研制的全球海气耦合气候模式MIROC_Hires输出的逐日降水资料, 分析了全球变暖背景下中国东部地区不同等级降水的变化特征。为了检验模式模拟未来中国不同地区降水变化趋势的可信程度, 首先评估该模式对1971-2000年夏季降水的模拟能力, 结果表明, 该模式无论从空间分布还是时间变化上均可以较好地模拟中国1971-2000年的降水情况。在此基础上, 将中国东部地区划分为华南、 江淮、 华北、 东北4个区域, 分析在全球变暖情景下未来（2071-2100年)较近期(1971-2000年)各个地区不同等级的降水量和降水频数的变化特征, 发现华南地区无降水和强降水（≥24 mm·d-1）的频数增加幅度均较大, 分别达到13\^8 d·a-1和4.2 d·a-1, 弱降水（1~12 mm·d-1）的频数减少; 江淮地区年降水量增加, 强降水的频数增加了3\^6 d·a-1, 弱降水的频数减少; 华北地区年降水量增加幅度在4个地区中最大, 达到30\^5%, 无降水频数减少, 8 mm·d-1以上的降水频数增加; 东北地区的降水强度和频数均增加。即中国东部地区降水变化趋势呈现华南地区暴雨频数增加, 江淮、 华北和东北地区降水量增多, 降水强度也增加的情形, 因此, 4个地区极端降水事件发生的频数增加。     

1951～2009年东亚地区日降水趋势特征分析

研究大陆或次大陆尺度日降水长期趋势变化规律,对于检测、理解区域气候和陆地水循环对全球气候变暖的响应特征十分重要。利用美国国家气候资料中心(NCDC)和中国基准气候站、基本气象站网降水观测资料,在对该站点资料进行基本质量控制基础上,选取东亚地区619个站1951～2009年日降水数据,按照百分位阈值对降水进行分级,共分为弱、中、强、极强4个级别,用经纬度网格面积加权平均方法构建区域平均的时间序列,分析了各类降水事件长期变化趋势的时空特征。结果表明:东亚地区近59年平均总降水量表现出不显著下降趋势,降水日数没有出现趋势性变化,平均日降水强度略有减小;区域平均的年降水量、降水日数和日降水强度在中国北方大部、蒙古东部、俄罗斯远东地区南部和日本列岛多呈减少趋势,而在俄罗斯中西伯利亚南部、朝鲜半岛南部和中国长江中下游流域一般表现为增加。从季节上看,近59年东亚区域平均的冬、春季降水量、降水日数和日降水强度均呈增加趋势,而夏、秋季一般呈减少趋势,仅夏季日降水强度略有增加。降水的年内分配出现均匀化趋势。从不同级别降水事件看,近59年来东亚区域平均的各级别降水量均为下降趋势,中降水、强降水和极强降水日数也呈现下降趋势,弱降水日数表现出较明显增加;仅有全区秋季强降水量、日数减少趋势和冬季中降水量、日数增加趋势通过了显著性水平检验。分析还发现,近30年(1980～2009年)东亚地区日降水趋势变化出现了新的特征,主要表现为大部分地区降水日数呈现增加,日降水强度减少,45°N以南多数台站降水量也增加,全区降水有向非极端化方向发展趋势。     

未来气候变化对黄河流域水文过程的影响

使用NASA/NCAR有限区域大气环流模型FvGCM结果驱动高分辨率区域气候模式RegCM3 (20 km),进行1961～1990年当代气候模拟(控制试验)和2071～2100年IPCC A2排放情景下未来气候模拟(A2情景模拟试验)。将RegCM3径流模拟结果同大尺度汇流模型LRM [分辨率0.25°(纬度)×0.25°(经度)]相连接,模拟预估未来气候变化对我国黄河流域水文过程的影响。结果表明:相对于当代气候,未来黄河流域呈现气温升高、降水增加(夏季7～8月降水减少)和蒸发增大的趋势,且空间分布极不均匀,造成河川径流在5～10月减少,加剧流域夏季的水资源短缺;未来气温升高使得融雪径流增加,可能导致更早和更大的春季径流,使径流过程发生季节性迁移,引起黄河流域水资源年内分配发生变化。     

21世纪黄河流域上中游地区气候变化趋势分析

 气候变化预估常用的全球气候模式（GCM）难以提供区域或更小尺度上可靠的逐日气候要素序列,针对这一问题,应用统计降尺度模型（statistical downscaling model,SDSM）将HadCM3的模拟数据（包括A2、B2两种情景）处理为具有较高可信度的逐日站点序列。以1961-1990年为基准期,分析了21世纪黄河流域上中游地区未来最高气温、最低气温与年降水量的变化。在A2、B2两种气候变化情景下,日最高气温、日最低气温均呈升高趋势;但A2的变化较显著,日最高气温的升高趋势在景泰站最明显,日最低气温的升高趋势在河曲站最显著。流域平均的年降水量变化范围为-18.2%～13.3%。A2情景下降水量增加和减少的面积基本相等,宝鸡站降水量增加最多;B2情景下大部分区域降水减少,西峰镇降水量减少最显著。     

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;