复杂地形上气象场对空气质量数值模拟 结果影响的研究

利用WRF模式三种边界层参数化方案(YSU、MYJ、ACM2)产生的气象场分别驱动多尺度空气质量模式CMAQ,对兰州市西固区冬季2005年1月27日至2月2日期间SO₂和NO₂浓度进行了数值模拟,将模拟结果与同期监测的污染物浓度进行对比分析,结果表明:WRF模式不同边界层参数化方案模拟输出的气象场驱动CMAQ模式所模拟的SO₂和NO₂浓度均可以反映出污染物的时空变化特征,CMAQ模式具有模拟复杂下垫面高分辨率污染物输送特征的能力;WRF模式的边界层参数化方案选为局地与非局地闭合方案(ACM2)时,模拟的气象场驱动CMAQ模式得到的空气污染物浓度分布特征最优,这主要是由于ACM2的湍流输送机制较为合理,模拟的边界层低层气象场更接近实际,从而可以较好地模拟污染物的输送特征;当CMAQ模式的垂直混合方案与WRF模式的湍流输送方案一致时(均采用ACM2方案),模式间的兼容性好.     

我国臭氧污染时空分布及其成因研究进展

近年来,我国城市臭氧(ozone, O_3)污染日益严重,O_3污染特征及其来源分析和防治工作引起了普遍重视。我国O_3污染高值区出现在华东、华北,且污染在典型城市群聚集;污染事件主要集中在夏、秋季,冬季污染较少,大部地区O_3浓度逐年上升;人为排放的挥发性有机化合物(volatile organic compounds,VOCs)和氮氧化物(nitrogen oxides,NOx)是O_3污染产生的重要原因,不同区域对两者敏感性不同;高温、低湿度、低风速条件有利于O_3污染维持和发展;全球气候变暖影响局地对流层O_3浓度,对流层O_3污染也反作用于气候变化。     

京津冀地区一次雾霾过程的污染分布及来源分析

利用气象与化学模块在线耦合的模式WRF-Chem V3. 5(Weather Research and Forecasting Model coupled to Chemistry Version 3. 5)对2016年11月3-6日的一次京津冀污染过程展开了数值模拟,设计进行了包含人为排放源的实验,运用有效的模拟结果对过程进行分析。结果表明:大气稳定度指数能有效量化反映污染过程中的大气稳定状况,且K指数和TT指数相较其他两种指数的指示效果更为准确,是讨论雾霾发生发展原因的有力依据。本次污染高值中心有三个,分别为北京天津一带、河北东北部以及河北南部。PM_(2. 5)、PM_(10)以及SO_2污染物水平分布有明显日变化特征,CO和NO_2则变化不明显,污染从3日开始发展至6日结束,除NO_2外各项污染物都明显受到冷空气的影响,在6日浓度骤降。北京和天津地区的污染是主要来源于河北南部的工业和交通排放的外源型污染,而河北东北部和河北南部的污染则是主要受本地排放影响的内源型污染。污染物主要化学成分为CO,污染物颗粒PM_(2. 5)和PM_(10)量级相当且浓度差别不大,均对本次污染有较大贡献。     

2020年南昌市大气污染特征与潜在源区

基于南昌市大气环境监测、地面气象观料和GDAS等资料,主要采用后向轨迹聚类分析、潜在源贡献因子和浓度权重轨迹分析方法,分析了2020年南昌市大气污染特征和污染物潜在源区。结果表明:1)南昌市春、夏、秋季以O_(3)污染为主,冬季以PM_(2.5)污染为主。2)大气污染物质量浓度日变化具有明显的季节性特征,PM_(2.5)和PM_(10)在春、秋、冬季呈双峰形分布,NO_(2)在秋、冬季呈弱双峰形分布,春、夏季呈单峰分布,O_(3)呈单峰形分布。南昌市东部大气污染较西部更严重。3)南昌市气流输送季节差异明显,春、秋、冬季主要受偏北气流影响,夏季主要受偏南气流影响。本地源是南昌市大气污染的主要潜在源,安徽省南部、湖北省东部、上饶市西部和九江市的区域输送也有一定贡献。     

北京市朝阳区主要大气污染物浓度变化特征

利用2011—2013年北京市朝阳区国家一般气象站PM_(2.5)、O_3、NO、NO_x、CO和SO_2的大气成分监测资料,分析了朝阳区6种主要大气污染物浓度不同时间尺度的变化特征.结果表明:2011—2013年朝阳区PM_(2.5)浓度呈明显增长的趋势,达到重度污染等级的日数增多;而O_3、NO、NO_x、CO和SO_2等气态污染物的年平均浓度变化较小,无明显增长的趋势,5种气态污染物浓度季节差异明显.除O_3浓度为夏季高、冬季低外,PM_(2.5)、NO、NO_x、CO和SO_2浓度均为夏季低、冬季高,可能与冬季采暖期排放的污染物增多有关.污染物浓度的日变化除O_3呈单峰型外,其他5种污染物浓度日变化均大致呈双峰型,可能与人类活动及天气条件有关.朝阳区与宝联、顺义、上甸子地区等代表"城市—近郊—远郊站点的污染物浓度日变化存在极大的差异性,其中PM_(2.5)浓度差异最明显,朝阳站PM_(2.5)浓度日变化呈双峰型,宝联站PM_(2.5)浓度日变化呈三峰型,昌平和上甸子站PM_(2.5)浓度为峰值出现在夜间的单峰型日变化.由此可见,不同地区因城市化发展程度不同,导致局地污染物浓度存在明显的差异.     

2008年奥运会期间北京地区大气O3浓度模拟分析

利用空气质量模式系统RAMS-CMAQ模拟分析了2008年8月北京及周边地区近地面O3浓度的时空变化。分析结果表明,模式系统可以较好地模拟污染物以及气象要素的变化特征和区域分布情况;奥运会期间的污染控制对O3浓度的降低有明显的作用,但是在一些有利的气象条件下,O3易达到较高浓度:8月2日、24日14时(北京时间)左右O3浓度都在0.22mg.m-3以上,其中2日北京地区处于辐合的弱风场中,风速为1.5～2.5m.s-1,24日则是处于自南向北的有输送作用的风场中,风速为3.5～6.5m.s-1;污染控制对北京周边地区的效果要好于北京市区。     

北京雾、霾天细粒子质量浓度垂直梯度变化的观测

近年来北京城市区域雾霾天气显著增加,不仅严重影响工农业生产和交通运输,还严重影响人体健康.2007年夏秋季节,北京325 m气象塔8、80和240m平台梯度观测结果表明,雾、霾、晴三种典型天气状况大气细粒子质量浓度垂直分布各有特点,雾天(11月5～6日)低层浓度明显偏高,6日从低到高3层PM2.5(空气动力学直径小于等于2.5μ的大气气溶胶)浓度日均值分别为352.6±79.3、224.7±69.0、214.8±32.8 μg·m~(-3);霾天(8月19～20日)细粒子上下混合均匀,19日从低到高3层PM2.5浓度分别为89.8±29.3、88.9±29.8、90.0±31.7 μg·m~(-3);晴天(8月22～23日)细粒子昼夜变化明显,夜间在80 m高度出现明显分层,23日80 m以下平均值为32.6±13.1μg·m~(-3),240 m平均值为27.4±13.5μg·m~(-3).雾天细粒子主要来源于局地,霾天细粒子污染表现为时空分布十分均匀的城市群区域污染特征且污染物积累;连续晴天细粒子明显被清除.     

BCC-AGCM-Chem0模式对20世纪全球O_3气候平均态及季节变化特征的模拟研究

利用由国家气候中心最近研发的全球大气环流化学模式BCC-AGCM-ChemO对1871-1999年全球大气O_3浓度进行了模拟,并利用全球臭氧和紫外线辐射数据中心(WOUDC)提供的O_3台站观测资料以及第5次耦合模式国际比较计划(CMIP5)整理的一套全球O_3分析资料对BCC-AGCM-ChemO模拟的O_3的气候平均态及季节变化特征进行了评估。结果表明:(1)BCC-AGCM-ChemO模式模拟出了全球年平均的O_3空间分布特征,表现为北半球O_3浓度高于南半球,O_3的经向分布大致呈由低纬向高纬递增;模式可以再现台站观测的O_3浓度垂直分布结构;相对于CMIP5分析数据,BCC-AGCM-ChemO模拟的O_3气柱总量在40°S以南的南大洋区域,模拟值偏低3~6 DU,在40°S-50°N中低纬地区略偏高3~6DU,陆地地区差异明显大于海洋地区,这些模拟偏差与地面排放和模式中O_3水平和垂直平流输送的影响有关。(2)BCC-AGCM-ChemO模式对全球O_3浓度的季节变化特征也有较好的模拟能力,模拟的O_3柱浓度与CMIP5资料的结果在1、4、7和10月的全球格点空间相关系数分别达到0.89,0.97,0.86和0.91;模式再现了南、北半球O_3浓度春季偏大、秋季偏小的特点;(3)从模式模拟和台站观测的对比分析来看,500 hPa以上的对流层中高层与以下的对流层中低层的O_3季节变化峰值存在明显的不一致性,表明500 hPa以下的中低层区域O_3变化可能受地面排放和干、湿等过程的影响较大,而对流层中高层的O_3变化可能与化学过程和平流层向下的输送影响较大有关。     

凉山州工业排放PM10的数值模拟研究

利用CALPUFF耦合MM5的大气扩散模型,对四川省凉山彝族自治州2007年工业排放PM10的扩散传输进行数值模拟,分析了污染物的浓度时空分布以及影响污染物浓度分布的主要因素.结果表明:CALPUFF耦合MM5模型对凉山州2007年工业排放PM10的浓度模拟有着较好的适用性;污染物主要沿着安宁河和黑水河分布,浓度分布特征随时间变化,其中冬季污染较为严重;各市(县)的PM10浓度值有空间差异,西昌和甘洛污染最为严重,季平均浓度分别为67.81μg/m3和57.23μg/m3;凉山州PM10的浓度分布受气象条件、地形和污染源的地理位置的综合影响.     

北京及其周边地区冬季SO2的变化与输送特征

利用实施北京市奥运空气质量保障计划"北京市与周边地区空气污染物的输送、转化及北京市空气质量目标研究"项目的有利时机,于2007年1月15～27日在中国科学院大气物理研究所北京站、香河站和兴隆站,采用先进的差分吸收光谱仪(DOAS)和SO2气体分析仪取得了高质量SO2浓度的连续观测资料,同时还获取了相应的常规气象资料和系留气艇探测的常规气象参数廓线资料.分析和讨论了北京及其周边地区的SO2污染的变化过程特征、日变化特征、输送特征、源排放特征以及与天气过程和气象条件的紧密联系.研究表明:1)北京站、香河站和兴隆站的SO2浓度逐日变化明显,变化趋势一致,通常处于同一个天气系统控制之下,SO2污染呈现区域性分布特征.2)冬季SO2浓度日变化明显,夜晚最高,15时(北京时)最低.3)SO2浓度与大气稳定度、风速、风向密切相关,风速越小、大气越稳定,SO2浓度越高;当吹西南风时,SO2浓度升高,西北风时浓度明显降低.4)HYSPLIT后向轨迹数值模拟结果和OMI卫星反演表明周边地区的SO2长距离输送对站点的贡献不能忽视.     

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.     

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.     

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