东北夏季极端低温的变化特征及其与太平洋海温异常的关系

利用1958—2007年全球海温、位势高度月平均资料和中国东北地区64个测站的夏季地面气温等资料,分析了中国东北地区夏季极端低温的时空变化特征,及其与大气环流和海温异常之间的关系,研究结果如下:(1)近50a来中国东北夏季极端低温事件频数在年际变化的时间尺度上主要存在两种模态:全区一致变化型和南北反相变化型;(2)东北夏季极端低温频数与乌拉尔山高压,东亚大槽,阿留申低压,东北冷涡密切相关;(3)东北夏季极端低温与赤道东太平洋海温存在遥相关关系。在1990s初期以前,在E1 Nino发生年或翌年基本都对应东北夏季极端低温年,但1990s初期开始,El Nino发生年与东北地区夏季极端低温的对应关系遭到破坏;(4)东北夏季极端低温事件频数的年际变化与西太平洋暖池海温异常密切相关。进一步研究表明西太平洋暖池海温异常会影响东北地区上空的环流,致使东北夏季极端低温异常。     

东北地区夏季气温变化特征分析

采用1951～2003年26个气象台站的夏季气温资料对我国东北地区夏季气温变化特征进行了分析。结果表明:近50多年来我国东北地区夏季气温主要经历了冷期、相对正常期和暖期3个阶段,夏季升温趋势达到0·15℃/10a,远超过全球、北半球、东北亚夏季的增暖程度。其对全球气候变暖的响应,一方面表现在夏季变暖、平均气温升高;另一方面表现在夏季气温变率加大;第三,气候变暖使东北夏季低温冷害明显减少、异常高温气候明显增多,但在变暖形势下局部发生低温冷害的现象仍然存在。     

我国东北夏季气温年代际变化特征及与太平洋海温异常关系的研究

利用1951—2008年东北地区夏季平均气温资料,分析了东北地区近58 a来东北地区夏季气温的变化趋势和突变特征,结果表明,东北夏季气温存在明显年代际变化的阶段性特征和总体增暖的趋势。对我国东北夏季气温与太平洋海温的相关分析表明,太平洋年代际振荡(PDO)由冷位相转为暖位相后,我国东北夏季气温与同期赤道中东太平洋海温相关减弱、与黑潮区海温相关增强,我国东北夏季气温与前期各季太平洋海温相关分布差异很大,海温关键区及相关强度都有所改变,这种相关关系的转变可能是造成近几年来利用太平洋海温预测我国东北夏季气温不确定性的原因之一。     

东北夏季(6-8月)气温异常的时空特征分析

利用夏季（6—8月）中国东北地区91站44a气温资料，采用谐波分析方法将该区夏季气温异常变化的年代际、年际尺度分量分离，研究时空特征，然后应用REOF进行气温异常的区划，研究局域异常变化的年代际、年际分量的变化特征。结果发现：1）东北各站夏季异常方差中，东北大部分地区的气温异常的年代际变化分量均明显大于年际变化分量。2）区域气温异常的年代际变化主要特征为线性上升趋势。大范围夏季异常高温（低温）常出现在年代际、年际异常同时为正（负）的年份。3）气温异常可划分为南部型、北部型、东部型、西部型4个型，其中南部型和西部型的年代际变化相对重要，而东部型和北部型的年际变化相对重要。     

东北夏季气温的大尺度环流影响因子分析

利用1961—2010年东北地区3省53站月平均气温资料及分辨率为2.5°×2.5°的NCEP/NCAR再分析资料,采用统计分析方法,分析了东北夏季气温的大尺度环流影响因子。利用200hPa风场要素定义了一个适于描述东北夏季气温的200hPa纬向风切变指数,并给出了该指数的预测方法,以期为东北夏季气温的预测提供一个诊断工具。结果表明:鄂霍次克海和北太平洋中部海平面气压场偶极子,与东北夏季气温关系密切;同期东北地区上空500hPa位势高度场与东北夏季气温呈正相关关系;同期850hPa、200hPa矢量风场和整层水汽通量场在东北及其以西地区上空呈气旋式环流,对应东北夏季气温偏低,反之则偏高,同时来自孟加拉湾的水汽也是造成东北夏季气温异常的因素之一;200hPa纬向风切变指数与东北全区气温呈显著正相关,该指数偏大对应东北夏季气温偏高,反之东北夏季气温偏低。4月和5月热带印度洋和太平洋海温与夏季200hPa纬向风切变指数关系密切。     

东北和华北东部气温异常特征及其成因的初步分析

采用REOF，SVD分析方法，首先指出东北和华北东部气温异常是全国气温异常的第一主分量，进而分析其异常特征及成因。结果表明：全区年、季气温均呈上升趋势，其中冬季增温最大，极端低温较极端高温升高明显。近百年来，全区增温幅度明显高于20世纪全球平均增暖水平。冬季，对流层中、低层上，当纬向西风偏强时，东北和华北东部易高温；而当经向风强盛时，易低温。夏季，气温异常与东北冷涡活动有关；1980年代以来气温显著变暖与对流层中、低层气压场的年代际突变有关。冬夏季气温与东亚冬夏季风、Nino3区海温的关系并不显著，但在1990年代以前，东北夏季低温与El Nino的对应关系较好。     

东北夏季气温变化与北半球温度及极涡的关系

利用1961-2002年中国东北地区80个气象站夏季6-8月逐日气温、美国NCAR/NCEP再分析资料和国家气候中心环流因子资料,采用相关分析、SVD分解等方法,对中国东北夏季气温变化与中高纬主要环流系统的关系进行探讨.结果发现:中国东北位于东西伯利亚变温区南缘,其夏季气温年际变化规律和东西伯利亚一致;北极极涡边缘的形态变化影响东北夏季气温,不同的边缘形态对应东北不同的温度分布特征,主要是极涡边缘70 °N左右的150～180 °E和60～90 °W两个关键区,其高度场的变化决定着东北夏季气温的变化.     

太平洋年代际振荡与中国气候变率的联系

利用 195 1～ 1998年的太平洋年代际振荡 (PDO)指数、全球海洋和大气分析资料及中国降水和气温站点观测资料 ,分析了太平洋年代际振荡在海洋中的特征及其与东亚大气环流和中国气候变率的联系。结果表明 ,PDO与东亚大气环流及中国气候年代际变化关系密切。对应于PDO暖位相期 (即中纬度北太平洋异常冷、热带中东太平洋异常暖 ) ,冬季 ,阿留申低压增强 ,蒙古高压也增强 (但东西伯利亚高压减弱 ) ,中国东北、华北、江淮以及长江流域大部分地区降水偏少 ,东北、华北和西北地区气温异常显著偏高 ,而西南和华南地区气温偏低 ;夏季 ,海平面气压在北太平洋的负异常较弱 ,而在东亚大陆的正异常较强 ,东亚夏季风偏弱 ,西太平洋副热带高压偏南 ,热带太平洋信风减弱 ,赤道西风增强 ,此时华北地区降水异常偏少而长江中下游、华南南部、东北和西北地区降水异常偏多 ,东北、华北及华南地区气温异常偏高 ,而西北、西南和长江中下游地区气温异常偏低。对应于PDO冷位相期 ,上述形势相反。结果还表明 ,处于不同阶段的ENSO事件对中国夏季气候异常的影响明显受到PDO的调制。在PDO冷位相期 ,当ENSO事件处于发展阶段 ,华南地区夏季降水偏少 ,东北地区夏季多低温 ,在其衰减阶段 ,华北地区和长江流域降水偏多 ,淮河地区降水偏少 ;     

热带和中纬太平洋海温异常对东北夏季低温冷害影响的诊断分析研究

利用1995~1997年东北地区23个测站的地面气温资料、1950~1996年太平洋地区月平均海温资料以及1980~1994年全球月平均风场资料,分析了东北夏季低温冷害的时空特征和变化规律,探讨了太平洋各区域的海温异常与低温冷害之间的可能联系及其影响机理。结果表明,用EOF分解得到的前三个特征向量（占总方差的84.28%）基本表示了东北夏季气温的变化,用这三个特征向量重建的气温距平场,存在着3~4年、6~8年和准16年的主周期,其中6~8年的主分量信号最强。在年代际尺度上,在1979年前后发生了由气温偏冷向偏暖的突变。热带西太平洋暖池（140°E~180°,10°S~10°N）是影响东北夏季气温的关键海域,那里前期冬季海表温度变化是预测东北夏季低温冷害的强信号。另一个关键海域是中纬西太平洋（130°E~180°,10~30°N）,前期春季的海温变化也与东北夏季低温有较密切的联系。     

欧亚大陆中高纬积雪消融异常对东北夏季低温的影响

利用美国冰雪资料中心提供的1979~2007年月平均积雪水当量资料、NCEP/NCAR的逐月再分析资料 以及中国743站的逐日气温资料,讨论了欧亚中高纬春季融雪异常分布与中国东北夏季温度的联系及其可能的影响机理。结果表明:欧亚大陆中高纬西部春季融雪偏多、东部春季融雪偏少时,我国东北夏季易出现低温。春季东部融雪量少,导致夏季剩余积雪偏多;夏季积雪融化吸热增多,加上后期的土壤湿度增加会导致该地区夏季温度异常偏低,高度场下降,500 hPa上欧亚中高纬东部的长波槽加深,槽后偏北气流加强;来自极地的冷空气容易入侵东亚中高纬地区,引起我国东北夏季低温。     

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;