近11 a南京市酸雨变化及其成因分析

本文结合2003—2013年以来南京国家基准气候站的逐日酸雨资料以及地面气象资料和高空探测资料,分析了近11 a来南京地区的酸雨变化特征以及相应的气象和气溶胶影响因子变化。所得结果表明:近11 a来南京地区的酸雨变化总体呈明显恶化态势,表现为酸雨的发生率明显提高,相应的酸度(pH值)显著下降;从影响酸雨变化的气象条件看,酸雨的pH值随着降水量增大而降低;垂直不稳定条件是影响酸雨的另一重要方面,酸雨事件出现时通常伴随出现高空逆温,在冬季有99%的事件出现逆温;分析850 hPa的风速和风向情况发现,冬、夏季分别有47%和52%的酸雨事件出现东风或东北风,这可能说明外部的输入性污染物对酸雨的形成也起着重要的作用。     

石家庄市酸雨污染现状研究

利用1992—2005年石家庄气象站酸雨观测资料,计算了近14 a的年平均降水pH值、酸雨发生频率等反映酸雨强度的参数,分析了酸雨的变化特征以及pH平均值与气象条件、电导率、空气污染的关系。结果表明：1992—2005年石家庄年平均酸雨发生频率为8.7%;酸雨主要发生在夏、秋季,占全年的74.4%;月平均降水pH值与电导率具有相似的变化规律,显著相关系数为0.661;SO2浓度的逐年下降是石家庄市酸雨减弱的主要原因;月平均风速和月平均降水pH值相关不显著;不同降水等级酸雨的发生频率差异较大,暴雨的酸雨发生频率最高为41.67%;采用Daniel趋势检验法分析表明,石家庄酸雨污染呈下降趋势。     

广州酸雨现状及影响因素分析

通过对广州1992—2008年酸雨资料的统计分析表明,广州酸雨年变化明显,17年的年平均pH值为4.05,酸雨年均pH值最低达3.41,最高达4.53;17年的酸雨年均发生频率为86.9%,最低为71.8%,最高为98.6%;酸雨季节变化明显:春季pH值最低,夏季pH值最高;酸雨月平均pH值变化幅度大:pH值最低出现在2月,最高在12月。通过对广州雨水离子组分和污染物浓度分析表明,影响广州雨水酸度的主要离子为: 、Cl-、Ca2+、 和 ,主要大气污染物为SO2和NOx。广州酸雨形成机制不仅与污染源有关,还与污染物在迁移扩散过程的天气系统和边界层气象特征有关。      

贵阳市近年酸雨特征分析

该文利用2005—2010年贵阳酸雨观测资料并结合探空及大气成分资料,分析了近年来贵阳地区的酸雨变化特征,研究了气象条件及大气污染物与酸雨的关系。结果表明:2005—2010年降水平均pH值均小于5.6,且近5 a来,降水pH值呈两端高中间低的分布型。贵阳地区夏、秋两季降水平均pH值及K值较春、冬季节高;pH值及K值随降水量的增大呈下降趋势,而强酸雨频率则随降水量的增大呈上升趋势,酸雨污染严重;当连续发生逆温状况时,酸雨出现频率增大;大气污染物SO2、NO2、PM2.5的浓度与降水pH值呈负相关关系,说明近地层污染物浓度对降水酸度有重要影响。     

2006—2019年山西省酸雨变化特征分析

利用2006-2019年山西省五台山、大同、太原、长治、侯马5个站酸雨观测资料,分析山西省不同时间尺度上酸雨次数和频率、降水pH、电导率K值的变化以及空间分布特征,不同酸度各雨量等级酸雨频率变化特征。结果表明：2006-2019年山西省酸雨次数和酸雨频率均呈下降趋势,年平均pH值范围为5.43-6.49,年平均电导率K值范围为73.4-120 μs·cm^-1;四季中,秋季平均pH最小,为5.70,春季最高,为6.11,电导率K值春季较高;各月相比,9月酸雨pH值最低,为5.58,4月最高,为6.20,月平均酸雨频次和降水pH值呈负相关,相关系数R为0.96。各站相比,太原降水年平均pH以及电导率K值均显著高于其他城市,酸雨pH值依次为太原（6.90）>长治（5.95）>大同（5.71）>侯马（5.57）>五台山（5.55）。不同等级降水酸雨发生频率差别较大,小雨（1.0-10.0 mm）时酸雨发生频率最大,强酸雨和弱酸雨频率分别为54.9%和67.0%,当降水量超过10.0 mm以后强弱酸雨发生的频率均随降水量增加而减小。     

大连地区短时强降水天气特征及预报指标研究

利用2004—2013年4—10月大连地区7个气象站和249个自动气象站逐小时降水观测数据及常规气象观测数据,对大连地区短时强降水的时空分布特征及气候特征、演变趋势和环流背景进行了分析,并建立了强降水天气预报指标。结果表明:2004—2013年大连地区各气象站短时强降水年平均发生次数为2.2—2.8次,南部和东部地区短时强降水年平均发生次数呈略增多的趋势,中部和西北部地区短时强降水年平均发生次数变化较小,中北部地区短时强降水年平均发生次数呈略下降的趋势。大连地区短时强降水最早出现在4月,最晚出现在10月,7—8月为短时强降水集中出现的月份,强降水多出现在02—10时。短时强降水发生次数具有明显的区域分布特征,由东部向中部和西部呈递减的趋势,大连东北部地区短时强降水发生次数最多,南部地区次之,西北部瓦房店地区短时强降水发生次数最少;其中7月北部地区短时强降水发生次数最多,8月东部地区短时强降水发生次数最多,其他月份短时强降水发生次数较少,说明大连地区短时强降水发生分散性较强。925hPa与850hPa平均比湿、700hPa温度露点差、850hPa与500hPa温度差平均值、K指数平均值、0℃层平均高度及暖云层平均厚度等参数阈值可用于短时强降水实际预报业务中,可为大连地区强降水预报提供参考。     

洛阳市城市环境气象监测预报服务研究

利用洛阳市环境监测资料和气象资料,分析了洛阳市污染物浓度的日变化、季节变化、年际变化规律,并分析了污染物浓度与气象因子的关系.在此基础上,通过回归分析预报方法、污染潜势预报方法、CAPPS模式预报方法对洛阳市3种主要污染物的浓度和级别进行了24 h和48 h预测,并建立了气象局与环保部门共享的气象和污染数据库平台,为双方今后的合作奠定了基础.     

江苏省2006年酸雨分布特征及其与气象条件的关系分析

统计江苏省4个酸雨监测站2006年的酸雨监测资料得到:徐州、南京的年酸雨发生频率高于常年同期,年平均pH值低于常年同期;常州、淮安的年酸雨发生频率比常年同期偏少,年平均pH值高于常年同期;各站的月酸雨发生频率呈逐月上升趋势,秋冬季酸雨发生频次均高于历史同期.结合同步的气象要素分析发现,降水强度、风、前期气候状况以及天气系统等都与酸雨的发生有密切关系.     

杭州市酸雨特征分析

利用杭州市气象局1992-2008年的酸雨监测资料,包括年平均降水、pH值、酸雨频率、风速风向等,分析杭州市酸雨形成的因子,并对酸雨形成的原因进行探讨。结果表明:杭州市酸雨17年间pH平均值为4.40,酸雨污染问题比较严重。从年变化趋势来看,酸雨强度较大,受酸性降水污染较重,但近几年来有逐年减缓的趋势;从季节变化趋势来看,酸雨春季和冬季较为严重,酸雨频率也比较大,而夏季和秋季降雨酸度和酸雨频率均比较小。杭州市酸雨形成的主要原因是大气中SO2、NOX等污染物浓度超标,同时与降水量、风向、风速、大气层结等气象条件密切相关,并根据其原因提出控制酸雨的措施和策略。     

广州酸雨观测站2008年-2012年酸雨资料分析

利用广州酸雨观测站2008年-2012年的酸雨观测数据,分析广州市年、月、季平均酸雨pH值及酸雨发生频率,并对广州市酸雨变化情况进行分析总结,结果表明：五年中广州的年酸雨平均pH值为4.48,年平均发生频率为75.8％.年平均酸雨最大pH值为4.67,年平均酸雨最小pH值为4.22.酸雨发生频率最高是2009年,为95.9％,最低则是2012年,为82.3％.按照酸雨PH值标准划分来看,2008至2010年年平均pH值属于较强酸性降水,而2011至2012年年平均pH值属于弱酸性降水.月平均酸雨最大pH值出现在11月,pH值为4.71,月平均酸雨最小pH值出现在2月,pH值为3.29;而酸雨频率月变化则可以看出6月份酸雨发生频率最高,为90.4％,而10月份酸雨发生频率最低,为44.0％.按季节分析,广州市秋季降水pH值最高,冬季降水pH值最低,秋季出现酸雨频率最小,冬季出现酸雨频率最大.四季轻雾日数与降水pH值呈显著的负相关,与酸雨频率呈显著的正相关.对风速与酸雨平均pH值分析,说明风速增大时,容易造成外来污染物的入侵,使污染加剧,酸雨平均值减小,酸雨频率增大.而雨量的变化对四季酸雨平均pH值有着显著的影响.     

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.     

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     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

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.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.