2021年秋季我国北方地区降水异常偏多的特征及成因分析

2021年秋季,我国气候总体呈现气温偏高、降水偏多的特点.季内降水总体表现出"北多南少"的空间分布特征,华西秋雨异常偏强.对北方地区降水阶段性异常偏强的成因分析表明,9月至10月上旬,欧亚中高纬度环流呈"西低东高"型分布,贝加尔湖—巴尔喀什湖为显著低槽区,西太平洋副热带高压持续偏强、偏大、西伸明显,秋季前期异常偏北,有...     

2017年秋季我国北方地区降水异常偏多成因分析

根据国家气象信息中心提供的中国台站气温、降水资料,NCEP/NCAR逐日大气环流再分析资料和NOAA提供的月平均海温资料,分析了2017年秋季我国北方地区降水异常偏多的成因。结果表明2017年秋季我国降水阶段性特征明显,9—10月北方地区降水异常偏多主要受东亚环流型组合异常的影响。东亚500 hPa高度距平场从高纬至低纬呈“+-+”的异常分布,极区高度场偏高,极涡分裂偏向东北亚地区,贝加尔湖 巴尔喀什湖地区为显著低槽区,西太平洋副热带高压较常年偏强偏西偏北,有利于华西秋雨偏强。此外,850 hPa距平风场上朝鲜半岛的反气旋式环流异常有利于引导偏东路径的冷湿气流输送至黄河与长江之间的地区,与来自孟加拉湾和南海的暖湿气流交汇,形成水汽通量异常辐合区,造成黄淮及江淮等地降水异常偏多。进一步诊断表明热带中东太平洋海温秋季转为偏冷状态,热带太平洋地区Walker环流明显增强,有利于西太平洋副热带高压偏强西伸偏北;9—10月热带印度洋偶极子维持正位相有利于在孟加拉湾形成反气旋式环流异常,并同样有利于副热带高压西伸偏北。因此,海温外强迫信号的影响加上中高纬环流异常的共同作用造成9—10月东亚环流型异常特征,并进一步导致我国北方地区降水异常偏多。     

2021年山东秋季降水异常偏多成因分析

利用1961—2021年山东123个国家级气象观测站逐日降水资料、ERA5逐月再分析资料和NOAA海温数据,对2021年山东秋季降水异常偏多成因进行分析。结果表明,500 hPa位势高度场上中高纬地区上空存在着“两脊一槽”双阻型的环流形势,贝加尔湖以西地区长波槽加深加强,有助于西路冷空气南下东传影响山东。西太平洋副热带高压(以下简称副高)较常年面积偏大,强度偏强,脊点偏西,脊线偏北,将外围充足的暖湿气流向北输送至黄淮地区,为山东地区提供了充足的水汽。冷空气与暖湿气流交汇于黄淮地区,导致降水异常偏多。进一步分析表明,在赤道中东太平洋冷水状态和印度洋海温持续暖位相的协同影响下,导致副高偏强偏西偏北,从而为暖湿气流输送提供有利的水汽条件。副高异常偏强偏北、南美东海岸和北太平洋海温异常偏暖、赤道中太平洋海温异常偏冷是造成山东9月降水异常偏多的主要原因。     

2020年秋季我国气候异常特征及成因分析

2020年秋季,我国气候总体呈现"暖湿"的特点,但是季节内变率很大,9月降水"南多北少"、10月降水"中间多南北少",11月降水"北多南少"。环流特征显示,秋季欧亚中高纬度总体为"两脊一槽"型,季节内波动大;西太平洋副热带高压(以下简称副高)持续偏强、偏大,西伸明显,但脊线位置的季节内变化大,9月偏南,10月略偏北,11月明显偏北。外强迫信号影响分析显示,热带印度洋全区一致偏暖有利于副高持续偏强、偏大、偏西;而热带中东太平洋El Nino事件春季结束后于秋季进入La Nina状态的海温演变过程,对热带和副热带环流系统具有重要影响,有利于秋季(尤其是10月)副高偏北。9月降水"南多北少"的异常分布与南海区域对流活动偏弱、偏南导致的副高偏南有关。研究显示,海温外强迫演变以及热带对流活动季内变化的共同作用导致了 2020年秋季降水呈现出季节内变率大的特征。     

2019年秋季我国气候异常及成因分析

2019年秋季,我国大部地区气温较常年同期偏高,全国平均气温为1961年以来同期第三高;降水空间分布非常不均匀,呈“西多东少、北多南少”的特征。异常成因分析表明,秋季欧亚中高纬度槽脊活动频繁,冷空气势力接近常年同期,西太平洋副热带高压较常年同期偏强偏西偏北,副热带高压西段位于南海西侧上空,有利于西南暖湿水汽向我国西部地区输送,菲律宾东北部为较强的气旋距平环流控制,导致我国南方地区受偏北气流控制,水汽条件偏差。进一步研究表明,海温异常是影响2019年秋季我国气候异常的最主要外强迫因子,2019年7月弱的中部型El Ni〖AKn~D〗o事件结束,秋季海温分布偏向于中部型El Ni〖AKn~D〗o。东亚副热带环流显示出清晰的响应。     

2018年秋季我国气候异常及成因分析

2018年秋季我国气候异常特征总体表现为：气温呈“东高西低”的分布;东部降水呈“南北多、中间少”的分布,其中内蒙古中东部、东北、江南南部和华南大部地区降水异常偏多,而华北至江南北部降水异常偏少,且江南和西南地区降水出现明显的季节内反向分布转变特征。异常成因分析表明,秋季欧亚中高纬度槽脊活动频繁,冷空气活跃,西太平洋副热带高压较常年同期偏强偏西,脊线季节内南北波动较大,西南水汽输送偏强,导致我国东部降水南北多、中间少。进一步研究表明,海温异常是影响2018年秋季我国气候异常的最主要外强迫因子,季节内El Ni〖AKn~D〗o由中部型向东部型发展,热带印度洋海温偶极子正位相持续,副热带南印度洋偶极子正位相发展。秋季后期El Ni〖AKn~D〗o影响增强,东亚副热带大气环流发生明显的季节内响应。因此,El Ni〖AKn~D〗o和印度洋海温的演变及其对东亚环流的影响,加上欧亚中高纬环流异常的季节内调整,二者共同导致了我国南方地区降水出现明显的东西反向的季节内变化。     

2020年汛期气候预测效果评述及先兆信号分析

2020年汛期准确预测了"我国气候状况总体偏差,极端天气气候事件偏多""涝重于旱"的总体特征,对长江中下游、黄河中上游、海河流域以及松花江流域降水较常年同期偏多和辽河流域降水偏少的预测与实况吻合。较好把握了华南前汛期雨季开始偏早、梅雨开始偏早和结束偏晚、华北雨季开始偏晚等雨季进程;但低估了长江中下游降水偏多的异常程度,对江淮西部、汉水降水明显偏多预测不准确,对四川盆地降水异常偏多也估计不足。对全国气温偏高以及我国南方高温日数偏多等主要趋势特征的预测与实况一致,对汛期台风数量较常年偏少及前期生成偏少后期生成偏多,以及在夏末至秋季较常年同期活跃的变化趋势的预测也均与实况吻合。2020年汛期预测重点考虑了前冬赤道中东太平洋弱暖水衰减的演变趋势对东亚夏季环流的滞后影响,同时热带印度洋的持续暖海温的接力作用有利于西太平洋副热带高压持续偏强偏西、菲律宾异常反气旋偏强。预测中低估了热带印度洋的异常偏暖程度及其对长江中下游、江淮地区降水的影响,导致预测中出现了较大偏差。国家气候中心模式对我国东部地区降水整体偏多的特征把握较好,这主要与模式对夏季平均的热带和副热带主要环流系统的空间分布型预测准确有关。但对季节内尺度的环流变化特征把握不好,包括中高纬欧亚地区在6—7月表现出的"两脊一槽"双阻型环流,以及7月副热带高压脊线位置持续偏南,季节进程较常年明显偏晚。     

2018年夏季海洋大气特征及对我国气候的影响

为更好地了解2018年夏季（6—8月）我国主要气候异常特征及成因,本文利用我国气象要素站点资料、再分析大气环流资料和全球海温数据分析了2018年夏季我国降水和气温的异常特征、东亚大气环流特征及海温对我国气候的影响。结果显示2018年夏季全国平均降水量较常年同期偏多9.6%,我国中东部地区降水呈现“南北多、中间少”的分布特征,北方和华南大部降水较常年同期偏多、长江中下游降水明显偏少。降水的上述异常特征受到东亚副热带和中高纬大气环流的共同影响。2018年夏季东亚副热带高空急流和西太平洋副热带高压位置都明显偏北,东亚沿岸由南至北为“负—正—负”的高度距平分布, 呈现出“东亚—太平洋型”遥相关负位相的特征,菲律宾附近对流层低层大气维持异常的气旋式环流,东亚副热带夏季风异常偏强。同时,欧亚中高纬度大气呈现“两槽一脊”的异常高度分布特征。在副热带和中高纬大气环流的这种配置下,我国北方地区以异常偏南风为主,有利于暖湿气流的输送,降水偏多;华南地区在偏强的热带对流活动影响下,降水也总体偏多;而长江中下游地区则以明显的辐散下沉运动为主,降水偏少。从外强迫因子来看,2017年10月至2018年4月发生的La Nina事件对东亚夏季风偏强及我国降水“南北多、中间少”的异常特征起到了重要作用。     

2020年夏季我国气候异常特征及成因分析

2020年夏季我国天气气候极为异常,全国平均降水量为373.0 mm,较常年同期偏多14.7%,为1961年以来次多;季节内阶段性特征显著,6—7月多雨带主要位于江南大部—江淮地区,8月则主要在东北、华北及西南地区,致使2020年夏季雨型分布异常,不是传统认识上的四类雨型分布。通过对同期大气环流和热带海温等异常特征分析发现,6—7月,欧亚中高纬环流表现为“两脊一槽”型,东亚副热带夏季风异常偏弱,西太平洋副热带高压(以下简称西太副高)较常年同期显著偏强、偏西,第一次季节性北跳偏早,第二次北跳明显偏晚,且表现出明显的准双周振荡特征;使得来自西北太平洋的转向水汽输送偏强,并与中高纬不断南下的冷空气活动相配合,水汽通量异常辐合区主要位于长江中下游地区,导致江淮梅雨异常偏多。热带印度洋持续偏暖对维持6—7月西太副高偏强偏西及东亚夏季风异常偏弱起到了重要作用。8月,欧亚中高纬环流调整为“两槽一脊”型,蒙古低压活跃;西太副高也由前期偏纬向型的带状分布转为“块状”分布,脊线位置偏北;沿西太副高外围的异常西南风水汽输送延伸至华北—东北南部,形成自西南到东北的异常多雨带,与6—7月江淮流域降水异常偏多的空间分布有明显不同。异常的热带大气季节内振荡活动是导致8月中低纬大气环流发生调整的重要原因。     

2017年秋季四川阴雨寡照特征及成因分析

利用四川省气象台站逐日降水、日照时数资料,NCEP/NCAR逐日及逐月再分析资料和NOAA提供的月平均海表温度资料,通过现代学统计方法研究了2017年秋季四川阴雨寡照的主要特征及其成因。结果表明：2017年9—10月四川秋绵雨天气特征明显,呈现出雨日偏多、日照偏少、阴雨寡照持续时间长等特点。9月对流层中层贝加尔湖至巴尔喀什湖地区上空为宽广倾斜的低压槽,有利于冷空气东移南下影响四川,同时西太平洋副热带高压偏强西伸,冷暖空气交汇于四川上空,形成持续性降水。10月对流层中层西太平洋副热带高压偏北偏西偏强和印缅槽加深共同作用,有利于来自孟加拉湾和西太平洋的水汽向四川输送,为四川带来持续性降水。进一步分析发现,9月Rossby波能量频散特征有利欧亚中高纬环流的持续和维持,能量频散是巴尔喀什湖至贝加尔湖地区上空低压槽稳定维持的重要原因。此外,9—10月赤道中东太平洋海温明显偏低,且不断加强发展,是西太平洋副热带高压偏强偏西偏北和印缅槽偏深的重要外强迫源。因此,由海温外强迫和Rossby波能量频散造成的大气环流异常,导致了9—10月四川秋雨期阴雨寡照天气的持续。     

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;