上海市气象场与SO2浓度数值模拟

采用地形坐标系下适合于复杂地形且满足地-气耦合的静力学三维中-β尺度气象预报模式,使用08时的实测流场经变分法初始化后得到的初始流场,模拟研究了上海地区的局地流场时空演变特征。模式较细致地考虑了湍流、长短波辐射、凝结、蒸发、地表热力平衡等因子,在此基础上,使用有限元法数值求解一阶闭合的三维欧拉平流扩散方程,模拟了上海地区的SO₂浓度分布。结果表明:上海的局地流场具有明显的日变化特征,受海陆温差的影响明显,日间风速较夜间风速大,风向呈顺时针旋转;在不稳定层结情况下,高架点源排放的高空污染物对地面的污染物浓度有贡献,会造成地面污染物浓度升高。     

贵阳市严重大气污染的数值模拟

使用三维地形跟踪坐标系上的动力学流场模式和平流扩散方程浓度场模式、模拟了造成贵阳市冬季严重二氧化硫污染的局地环流特征以及相庆的ＳＯ２浓度分布，结果表明冬季稳定冷高压系统控制下的晴朗小风天气是造贵阳市严重大气污染的主要天气条件，其基本特点是地面小风，边界层下部较强的逆温层和城市盆地周围山坡的夜间冷泄流。     

冬季呼市地面流场特点及成因分析

受大气环流影响和地形作用，冬季呼市地面流场主要呈地方环流特征，风速小、静风频率高，不利于大气中污染物的稀释和扩散。而下垫面的局地作用是形成呼市地方环流的关键影响因子。     

狭谷地形下污染物扩散的模拟

采用三维二阶矩高阶闭合ＰＢＬ模式和随机游动扩散模式组合建立狭谷地形下扩散的模拟系统。运用此系统能够较客观地揭示流场结构，从而得到狭谷地形下较接近实际的扩散特征和污染物浓度的分布。     

地形对太原市污染物稀释扩散影响的模拟试验

文中利用CAPPS模式进行了模拟试验 ,试图研究在不同环流背景下 ,太原附近簸箕型地形对该地主要污染物(SO2 ,NOx,PM10 )稀释扩散的影响。结果表明 :采用仿真模式地形 ,局地环流背景下 ,簸箕型地形阻碍了主要污染物的稀释和扩散 ,加剧近地层空气的污染 ;大尺度环流背景下 ,且地面为偏南风或偏东风时 ,簸箕型地形有助于主要污染物的稀释和扩散 ,SO2 ,NOx,PM10 浓度减小 ,地面为偏北风或偏西风且风速≥ 5m /s时 ,SO2 ,NOx 浓度减小 ,PM10 浓度剧增。此外 ,还探讨了簸箕型地形对太原市主要污染物稀释扩散作用的机制 ,采用仿真模式地形 ,大尺度环流背景时 ,簸箕型地形对垂直运动具有增幅作用 ,且地形越高 ,增幅越明显。     

三维非静力中─β尺度动力学预报模式的应用 Ⅱ:海陆风的数值模拟

本文利用已建立的三维非静力中－β尺度动力学预报模式［1］，以1993年9月3日为实例，模拟研究深圳大鹏湾海岸地区地形的动力和热力效应形成的海陆风环流特征。模拟结果与实测资料合理的一致，并且表明：起伏地形对垂直流场及低层风场影响较大；不规则海岸线对地面流场的走向有显著影响；海角的辐散（或辐合）较强；地面温度波的振幅直接影响到海陆风环流的强度；海陆风转换期间，风速较小风向多变。     

山谷地形流场和扩散的数值研究

运用三维非表力E－ε闭合模式，模拟了山体和山谷地形下的流场、湍流场和不同位置低矮点源扩散的污染物浓度分布。发现在不稳定时湍能的热力产生率并非在任何位置都是主要的。当风速较大时，在山谷底部机械产生率也可能超过热力产生率。对污染扩散的分析表明：在近地面源条件下，稳定层结时如果出现小风，无论源在何处，都人造成一定范围内的严重污染，当污染源位于山前或山顶时，谷底的污染不剧烈。当污染源位于谷底时，无论何种层结、何种来流风速，都会造成山谷地区的严重污染。污染源位于山体沿来流方向的中心线上的谷底时，如果风速大，污染物沿回流输送；如果风速小，则沿来流方向输送。     

复杂地形上稳定边界层二维流场的数值模拟

建立了一个二维局地尺度数值模式，对水平扩散采用了水平平滑处理方法，提出了一种在地形追随坐标系中具有较高计算精度的差分近似方法，此方法兼具了地形追随坐标系和直角坐标系的优点，特别适用于地形特征尺度较小和垂直分层要求较细的情况。数值试验表明：该模式具有模拟局地尺度环流的能力，且计算机内存和ＣＰＵ时间都较节省，算法稳定。利用所建立的模式对经过重庆市中区的某一实际地形下的流场进行了数值模拟。     

三峡坛子岭单点地面矢量风分析

利用UVW三轴风速仪三峡坛子岭单点地面风观测资料分析了三峡坝区地面风速量值、风向风速出现频率分布、风的日变化规律等，并根据这些观测资料、结合一些地形风理论知识和观测现象推测了三峡坛子岭附近地面风平面流场特征，从而揭示了河道地形回流风这一特殊小地形下的局地风现象。三峡坛子岭附近地面的这种回流风尺度在百米到千米量级，与由于地形热力因子引起的山地风不同，是由于小地形的动力作用引起的，其风向与长江河道引导的山地风相反。     

复杂地形气象场对污染物浓度空间分布影响的研究

利用WRF模式与多尺度空气质量模式(CMAQ)系统模拟了试验期间(2005年1月30-2月2日)兰州市城区SO2的地面浓度,并根据模拟结果进一步分析了兰州市冬季污染物的空间分布特征。研究结果表明西固区和城关区各有一处污染物高浓度区域;受排放源空间分布和气象场的综合影响,夜间SO2地面污染范围小于日间,夜间污染物地面最大浓度明显高于日间,夜间模拟区域平均值低于日间;水平流场和山谷风环流形成的垂直运动均对污染物地面浓度有明显影响。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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.     

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.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi 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