1998年“4.18”强沙尘暴分析及数值模拟

对1998年4月18－19日发生在新疆、甘肃、宁夏、内蒙古等地的一次强沙尘暴天气过程从天气事实、天气学成因等方面进行了分析和诊断，然后利用非静力MM5模式对这次沙尘暴天气进行了数值模拟。结果表明，西西伯利亚强冷空气迅速东移，在新疆西部上空形成强锋区，对应的地面冷锋东移至前期增暖显著的新疆、内蒙古、甘肃、宁夏等地形成了本次大风、强沙尘暴天气。用非静力MM5模式较好地模拟出了此次强沙尘暴天气过程的地面强风系统、高空锋区的发生发展。     

一次强沙尘暴天气成因与诊断分析

利用常规气象资料,对2002—03—19西北地区出现的一次强沙尘暴天气过程．从天气成因、物理量诊断等方面进行分析。结果表明：西伯利亚强冷空气东移南压,在新疆至河西上空形成强锋区．地面蒙古气旋强烈发展是引发此次沙尘暴天气的主要原因。沙尘暴发生在冷锋后强下沉气流和较强气压梯度区。锋生函数和总能量的变化特征、高空急流与干暖舌的形成与维持,与这次沙尘暴过程实况、强度、落区等有良好的对应关系,对宁夏沙尘暴预报具有较好的指示意义。     

一次强沙尘暴天气的大尺度环流分析

１９９８年４月１４～１９日蒙古和我国北方连续发生２次强沙尘暴天气,沙尘暴减弱后的浮尘随高空西风急流东移,跨越黄海到达韩国南部。通过分析认为,这是一次发生于纬向环流中的沙尘暴天气,主要影响系统是蒙古西部热低压和地面冷锋。     

一次特异强沙尘暴天气成因分析

针对 2 0 0 1年 3月 2 6日出现在我国河西走廊东部和蒙古地区的一次强沙尘暴、大风、浮尘天气过程 ,从天气形势、气候成因、动力诊断等方面进行了探讨。分析结果表明 ,蒙古强冷空气南压 ,入侵河西东部 ,加之该区今春以来干旱严重 ,气温偏高 ,地表干土层增厚 ,形成了大风、强沙尘暴、浮尘天气。     

北京春季一次持续浮尘和污染天气过程分析

2001年4月底5月初北京地区出现了一次以浮尘天气为主，夹杂轻雾、雷阵雨、烟幕等复杂天气过程的持续重污染事件，给北京地区的生产和生活带来了较大的影响。文章主要从天气形势上分析了北京浮尘天气形成的原因和持续空气污染的气象条件。结果表明，此次过程是由于高空冷涡发展东移，蒙古气旋发展和地面冷锋移动经过蒙古国南部和华北北部等干燥、疏松的地表形成扬沙、沙尘暴，大量的细小沙尘粒子随高空偏西气流携带而至北京，形成浮尘天气。本地低空处于弱辐合区，层结稳定，风速小、逆温频繁，这些均不利于沙尘粒子和本地污染物的扩散，导致连续可吸入颗粒物重污染的形成。     

“4．5”西北区浮尘沙尘暴天气初析

初步分析了１９９４年４月５日－１１日西北区浮尘和沙尘暴天气，指出这次天气具有持续时间长、范围广、强风时间短、沙尘密、沉降量大和地域性显著的特征。它是在天气环流热力和动力作用下形成的，主要成因是热浪进入青藏高原加强，西北区上空大气异常增温，地面气旋性热环流发展是浮尘天气的启动因子，蒙古冷高压底部强气压梯度力的作用激化了浮尘和沙尘暴天气，沙尘暴消散后大气层结稳定使浮尘得以维持呈准静止状态，在强冷空气影响下浮尘天气结束。     

甘肃省春季一次连续浮尘天气过程分析

2013年3月8~9日甘肃省出现了一次区域性的大风沙尘暴天气过程,此后到14日甘肃中东部一直维持浮尘天气,这样范围广、持续时间长的沙尘天气为近年来罕见。本文分析了此次沙尘天气过程的天气气候特征以及特殊气象条件对连续浮尘天气的影响,并以兰州市为例基于HYSPLIT-4轨迹模式探讨了浮尘天气过程的沙尘颗粒传输特征。结果表明:(1)前期暖干的气候背景有利于此次大范围沙尘天气的发生;(2)8~9日冷锋后的偏北大风引发甘肃省出现区域性大风沙尘暴天气,11日河西再次出现扬沙、沙尘暴天气,沙尘粒子沿西北气流向下游地区输送,致使12日河东出现浮尘天气的站数明显增多;(3)9日大风沙尘暴天气过后,甘肃省中东部边界层处在弱的偏东风环境中,大气层结长时间较稳定,沙尘污染物不易扩散;(4)在连续浮尘天气期间,甘肃省各地上空频繁出现逆温层,且逆温层高度在9日沙尘暴天气过后有明显抬升,阻挡了低层空气的上升运动,以致沙尘粒子聚集在700 h Pa以下。同时还发现,边界层上部逆温层的逆温温差越大,厚度越厚,造成浮尘天气的强度越强;(5)兰州市9~10日出现的浮尘天气起源于8日河西走廊及蒙古地区的沙尘暴,11日河西走廊再次爆发的沙尘暴天气对河东的浮尘天气影响较大。此外,10~13日陕西南部也出现了浮尘天气,"东高西低"的地面形势使此地上空漂浮的沙尘粒子处在偏东风的环境中,对甘肃中东部地区的浮尘天气有一定的回流输送作用。     

2006年春季一次引起华北地区强沉降的沙尘暴过程的模拟研究

2006年春季是我国北方地区2000年以来强沙尘暴过程最多的一年,浮尘和扬沙天气更是频繁发生.尽管,4月16～17日过程不是2006年春季最强的沙尘暴过程,但其在华北地区引起了严重的沉降,尤其对京津地区影响较大.这是一次由蒙古气旋引发的强沙尘暴过程.利用沙尘天气预测系统(IAPS 2.0)对该次强沙尘暴过程进行了模拟试验,结果表明:该系统对沙尘天气的起沙和输送过程有较好的模拟能力,基本模拟出了这次强沙尘暴的发生和移动;沙尘受对流层中低层偏西风的作用输送到华北地区,并从山东半岛越过渤海湾向东输送;主要的沙尘源地是蒙古国南部和我国西北的内蒙古、新疆西部、甘肃、陕西北部,而起尘最大的地区在蒙古国和内蒙古的沙漠、戈壁地区;沉降最严重的地区是沙尘源区及其附近,可达到50 g*m-2,其他地区的总沉降量在10 g*m-2左右.     

京津冀地区一次持续时间较长浮尘天气的分析

2017年5月3—4日京津冀地区出现了一次持续较长时间的浮尘天气,给京津冀地区的生产和生活带来了较大的影响。从气象条件方面分析了浮尘天气的成因及维持机制,并使用气象、环境观测、激光雷达探测、后向轨迹模式产品等分析了此次浮尘天气的观测事实。结果表明,此次过程是在蒙古气旋强烈发展东移的过程中,经过蒙古国中部、甘肃、内蒙中西部的沙源地后形成扬沙、沙尘暴,大量的沙尘粒子随高空偏西西北气流漂至京津冀上空后沉降而形成的,本地沙源没有补充。激光雷达可以清晰地监测到沙尘的传输高度基本在2～4 km。浮尘天气期间,沙尘高度在2 km以下。浮尘维持30 h以上的原因:(1)高空受东、西两槽间的纬向环流控制,地面处于鞍型场,风速小,不利于沙尘粒子的扩散;(2)边界层内湍流活动旺盛,且中低层基本是中性层结状态,沙尘粒子不易沉降。     

东亚沙源地与下游影响区沙尘天气频数变化对比分析

基于1999—2019年地面气象观测资料,对东亚主要沙尘源地(蒙古国、中国新疆和内蒙古)及中国沙源地下游地区的沙尘天气频数演变特征进行了分析,结果表明：蒙古国是沙尘天气发生最严重的地区,且有明显增加的趋势,扬沙、沙尘暴和强沙尘暴均远高于其他区域。中国整体沙尘天气数量显著减少,新疆快速增多,内蒙古和下游地区明显减少。新疆浮尘发生频次最高,近21 a线性倾向呈明显上升趋势;内蒙古扬沙频次最高,强沙尘暴最少,4类天气均呈逐年减少趋势;我国下游地区多发浮尘和扬沙,沙尘暴和强沙尘暴发生次数很少,全部沙尘天气呈减少趋势。1999—2004年为我国沙尘天气高发期,2005—2019年明显减少,其中2010—2014年减少速度最快。沙尘源地对我国沙尘天气总数的贡献持续增大,从2000年初的39%增长到2015年之后的71%。作为沙尘源地,蒙古国对沙尘天气产生的作用有所增强,而内蒙古则在减弱;国内沙尘源地导致的能够影响并扩展至中国下游地区和下游国家的强沙尘天气显著减少。     

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;