重庆城市热岛环流结构和湍流特征的数值模拟

利用中尺度模式WRF（V3.9）对2016年8月17～18日重庆一次城市热岛环流个例进行了数值模拟，探讨了山地城市热岛环流的三维结构和演变特征，分析了热岛环流期间湍流动能和各项湍流通量的特征。结果表明:15:00（北京时，下同）乡村风开始出现，随着热岛强度增强乡村风增大，18:00热岛环流结构最显著，次日02:00热岛环流结构被破坏，仅低层存在微弱的乡村风。其中，重庆市城市热岛环流最强时，水平尺度约城市尺度的1.5～2倍，垂直厚度约1.3 km，水平风速约2～4 m s?1，最大上升速度约0.5 m s?1。受地形、河流以及背景风的影响，环流呈现非对称的结构，且强度较弱。湍流特征分析结果表明，城市区域的湍流动能明显大于其它区域。此外，城市热岛环流通过湍流运动将郊区的水汽输向城市；高层湍流动量补充边界层中因热岛环流发展而造成的动量耗散。     

污染天气下成都东部山地—平原风环流结构的数值模拟

本文利用中尺度模式WRF（V3.9）对2016年12月7日成都东部（龙泉山）一次污染过程下的山地—平原风环流进行了模拟，旨在探讨冬季污染天气下山地—平原风环流的结构和演变特征。此外，通过减少气溶胶光学厚度（AOD，Aerosol Optical Depth）的敏感性试验探究气溶胶污染对山地—平原风环流的影响。结果表明:冬季污染大气条件下成都平原地区存在显著逆温。龙泉山南北长、东西窄且高度较低，由于东、西坡辐射能量的不均匀分布和背景风的强迫，上午、凌晨和夜间均出现越山下坡风环流，上午强度较强，凌晨和夜间强度较弱。午后开始出现平原风环流，最大影响范围为山体宽度的3～4倍，17:00（当地标准时，下同）左右结束。各阶段环流在南北方向上差异较大，越山下坡风环流在南段最强，中段最弱；中、南段山体较低窄，平原风环流易被湍流掩盖，北段平原风环流最为明显。AOD减小后辐射及地表热通量均有所增加，中、南段湍流更加旺盛，边界层显著抬升且降低时间滞后，山体与平原间感热通量差异增加，北段平原风环流增强、持续时间增长。     

山地中尺度环流中的大气边界层湍流摩擦效应

建立了一个三维原始方程数值模式，模拟在光滑下边界和无滑脱下边界两种情况下，山区中尺度环流的演变过程，指出在弱层结条件下，边界层湍流摩擦效应有利于流场的分离和涡旋偶极子环流的发展；在强层结条件下，表面摩擦效应削弱了分离气流和涡旋性环流的强度，但使其范围扩大。边界层湍流摩擦效应引起的分离流场和尾流区环流与非粘性动力过程引起的流场分离现象，虽然从其表现形式上看完全相同，但是其形成则是由完全不同的物理机制所控制。边界层湍流摩擦效应在上述两种分离流场的演变过程中表现出完全相反的作用。地转科氏力的调整作用在山地背风坡上促进了气旋性辐合环流的发展，而抑制了反气旋性环流的发展。     

盆地环流型及冷湖的形成和消散的数值研究

本文建立了一个三维原始方程数值模式，模拟三维盆地中的环流，重点讨论在热力强迫环流型的转变过程中能量场的动量场的配置情况及环流演变过程。模拟结果表明，夜间地面强烈的辐射冷却过程引起盆地各坡面冷迳流的发展，盆地中成为冷空气湖，逆温层结建立。日出后对流边界层从大气低层向上发展，逆温从底部随之消蚀，仅在上层存在了夜间逆温残余，即所谓稳定核，上坡风在对流边界层发展，而稳定核内仍维持夜间下坡风环流。     

基于风廓线仪的华南地区夏季边界层湍流统计特征研究

采用双权重算法,使用2015年6—8月我国东南部业务风廓线雷达资料,通过湍流脉动垂直速度方差和偏度的计算和分析,对晴空和低云主导情况下的边界层湍流特征以及中小尺度局地环流对于边界层湍流的影响进行研究。主要结论如下:(1)晴天情况下垂直速度标准差和垂直速度偏度都具有明显的日变化特征,湍流主要由下垫面加热驱动发展;(2)在低云主导情况下,湍流明显弱于晴天对流边界层的湍流强度,边界层内湍流的发展不仅受地面加热的影响,而且在边界层上部存在明显的自上而下发展的湍流,这主要是由于边界层顶云辐射冷却造成的;(3)除了上述两种情况,边界层湍流发展同时受到局地中小尺度环流或者天气系统的影响,因而呈现出更多的复杂性。      

局地环流与大气边界层湍流相互作用的数值研究

本文建立了一个二维定常大气中尺度数值模式，并用该模式讨论了由下垫面粗糙分布非均匀（局地动力强迫）和温度分布非均匀（局地热力强迫）而产生的局地大气环流与大气边界层湍流的相互作用。结果指出：下垫面存在温度分布非均匀时运动方程中的湍流交换项与水平气压梯项一样可促使局地热力环境的形成，由粗糙度分布非均匀强迫产生的局地环流与由下垫面温度分布非均匀强迫产和的局地热力环流间的非线笥相互作用是通过湍流交换实现的。     

海陆交界处平流辐射雾的二维数值模拟

本文采用二维非定常数值模式,模拟了大气边界层内海陆交界处的平流辐射雾的形成和演变规律。在模式中考虑了平流、辐射及湍流等物理因子及其相互作用。模拟结果表明,夜间盛行风将暖湿空气带入陆地,水汽经辐射冷却形成雾,地面陆风环流起了一定作用。      

大理苍山—洱海局地环流的数值模拟

利用耦合了湖泊模型的WRF_CLM模式模拟了秋季大理苍山—洱海地区的局地环流特征。结果表明:模式对近地面温度、风向、风速的模拟与观测基本一致,模拟结果能较好地再现该地区山谷风和湖陆风相互作用的局地环流特征。在秋季,大理苍山的谷风起止时间为08:00~17:00(北京时,下同),湖风起止时间为09:00~19:00。局地环流受高山地形及洱海湖面影响明显,山谷风形成早于湖陆风1 h,夜间山风、陆风强盛于白天谷风、湖风。白天苍山谷风与洱海湖风的叠加作用会驱动谷风到达2600 m的高度,而傍晚最先形成的苍山山风则会减弱洱海的湖风环流。夜间盆地南部在两侧山风、陆风的共同作用下,形成稳定而持续的气旋式环流。日出以后,对流边界层迅速发展,边界层高度逐渐增高。陆地17:00温度达到最高,边界层高度也达到峰值2000 m,之后逐渐降低。日落后形成稳定边界层,边界层高度在夜间基本保持在100 m。相对于陆地,湖面白天边界层高度低300 m,夜间边界层高度高100 m。     

云贵高原洱海湖泊效应的数值模拟

采用耦合湖泊模型的WRF_CLM模式模拟山谷盆地中洱海的湖泊效应,并利用陆面(农田)和湖面的站点观测资料对模式进行了验证和校验。基于数值模式的模拟结果,分析了季风和非季风期间,洱海存在与否对山谷盆地局地环流及大气边界层结构的影响。发现非季风期湖泊对局地环流及大气边界层影响显著。相对于陆地,湖泊白天湍流通量输送少,湍流发展弱,大气边界层高度低。如果湖泊不存在,白天苍山山谷风只能上升至约200 m的高度,没有明显的山谷风环流形成;夜间则山风较强,两侧山风共同作用在山谷,环流高度约600 m。季风期,受降水天气影响,局地环流发展不充分。白天湖面辐散以及夜间湖泊南部的气旋式环流弱,湖泊作用没有非季风期明显。云的形成导致边界层高度较低。夜间,湖泊增强释放潜热、感热作用明显;此时湍流发展,夜间边界层反而比白天高。     

北京地区一次特大强风过程边界层结构的研究

利用北京325 m气象塔资料对1993年4月9日北京地区出现的一次特大强风过程的边界层结构（风、温、风切变及阵风特征）进行了分析。随着该次大风的过境，边界层内风场出现数个风速高值中心，高度位于200～300 m，时间间隔1～3 h。伴随上层风速垂直切变和阵风特性。湍流能谱的计算结果表明了大尺度涡旋对边界层湍流微结构的影响。     

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;