2003年冬季空气质量趋势预测方法

使用短期气候趋势预报原理与短期空气质量预报相结合的方法，根据1～7月的气候特征（背景）、天气形势以及各种相关气象要素统计分析，对冬季采暖期空气质量进行综合预报。利用上述方法对2003年度（2003．11～2004．3）冬季采暖期空气质量进行了试预测。即：在2003年冬季气候预测的基础上，通过统计分析2003冬季相似年份的天气形势、污染气象条件，确定污染潜势和气象参数。并运用现业务使用的污染物浓度预报方程，计算冬季各月的逐日空气污染物（SO2、NO2、PM10）的浓度。最后综合2003年冬季气候特征预测和日空气质量计算结果，做出冬季空气污染趋势预报。     

太原地区主要污染物污染的气象特征

选用2002年太原地区6个环境监测站主要污染物逐时浓度监测资料和山西省观象台逐时的气象观测资料,系统的统计分析了太原地区主要污染物浓度的时空分布特征,其中包括SO2和可吸入颗粒物PM10平均浓度的逐月变化、采暖期和非采暖期平均浓度的逐时变化,以及主要污染物浓度与地面常规气象要素的相关性。揭示了各代表站主要污染物污染的年、日变化趋势、采暖期和非采暖期日变化的差异,并分析了春季大风天气时PM10与SO2污染浓度的变化特征。     

气象条件与西安污染物的关系及预报方法

对西安1998～2000年的主要污染物PM10的实测浓度值结合部分气象条件进行分析,得出:(1)年内冬季采暖期浓度较高,夏季汛雨期浓度较低,3a来空气质量逐渐好转;(2)污染浓度与降水和风速的关系较为复杂,但仍有规律可循;(3)污染物浓度与某些逆温层特征相关较好;(4)污染物与能见度相互影响.并给出了部分气象条件的预报方法.     

哈尔滨市空气质量变化特征与气象条件的相关性分析

通过哈尔滨市2013-2016年的空气质量指数资料、常规气象资料以及NECP/NCAR再分析资料,对哈尔滨市空气质量变化特征及其与气象要素的关系进行了分析,并从气象因素探讨了哈尔滨市典型污染日发生的天气形势及特点。结果表明近4 a哈尔滨市的空气质量状况总体有所改善,其中8、9月空气质量最好,12月空气质量状况最差;首要污染物主要为PM10和PM2.5,且在冬季PM10和PM2.5最重;冬季哈尔滨市逆温厚度与污染物浓度呈正相关;逆温强度与污染物浓度呈负相关,重污染的典型地面形势主要有高压南部型、高低压过渡型、高压中心型、高压南部型、燃煤供暖型和秸秆燃烧型5类。     

基于API方法的西安城市大气环境质量评价

采用空气污染指数法对西安市2004年大气环境质量进行了评价，结果表明，2004年西安市空气质量达到了国家二级标准，影响该市空气质量的主要污染物为可吸入颗粒物．主要污染时间为1、2、3、11月，采暖期污染源的排放和不利于污染物扩散的气象条件是影响西安市空气质量的两大重要因素。     

成都市大气污染与气象条件关系分析

利用成都市城区2015年12月~2019年12月污染物浓度及气象资料,对PM₁₀、PM_2.5、CO、O₃、 SO₂、NO₂六种大气污染物浓度变化特征以及与气象要素之间的相关性进行分析。结果表明:2016~2019年成都市空气质量冬季最差,秋季最好,年内整体以良为主,重度污染和严重污染的天气较少出现,空气质量逐年变好;主要污染物浓度除O₃外在冬季最高,夏季最低,春秋两季相差不大,O₃浓度变化则相反;主要污染物的日变化特征也较为明显。空气质量综合指数、PM₁₀、PM_2.5、CO、NO₂浓度与气温和降水存在显著负相关性,与气压存在显著正相关性,还与相对湿度呈不同程度的负相关,但与风速相关性不显著;O₃浓度不仅与风速、气温和降水存在显著的正相关,还与气压呈显著的负相关,却与相对湿度的负相关性不显著。      

贵州普定县人居环境气候条件分析

利用普定国家气象观测站1971年1月1日-2022年2月28日逐日平均气压、平均气温、平均相对湿度、平均风速、降水量等气象资料以及普定县空气污染物日均浓度、空气质量指数（AQI）等资料,运用人体舒适度指数、气象要素与污染物浓度的相关性、人体舒适度与空气质量相关性分析方法,分析普定县近50a的人居环境气候条件。结果表明：普定县平均气温、平均风速以及日照时数呈增加趋势,相对湿度、降水量以及气压呈降低趋势。常年体感主要为凉（3级）～最舒适（5级）之间,全年体感无寒冷及酷热等级,且体感舒适（含凉舒适及最舒适）月份主要为4-10月,占全年58%。普定县气温上升、风速增大、气压下降的趋势有利于污染物浓度降低,空气质量好,而相对湿度降低、降水量减少的趋势不利于污染物浓度降低,影响空气质量。普定县空气质量以4-5月、7-11月为优,且其四季空气质量均为优,表明空气质量好,人体舒适度高,适宜人居。     

2014—2015年上海地区冬夏季大气污染特征及其污染源分析

利用上海地区冬、夏季空气质量数据和常规地面观测数据,分析了2014—2015年冬、夏两季大气污染特征,并通过聚类分析法和后向轨迹模式对污染物输送路径进行统计分析。结果显示：上海市冬、夏两季空气质量均以优良为主,首要污染物分别以PM2.5和O3;来自夏季的西北输送路径对应PM2.5和O3浓度最高,分别为62.8和130.2 μg·m-3,来自冬季的西北和西南方向的输送路径对应PM2.5浓度较高;进而基于潜在源区贡献和污染源排放强度等要素建立了传输指数。总体而言,江苏中南部、浙江中北部以及安徽中南部等地对上海地区夏季空气质量影响较为显著,而冬季周边区域的传输指数范围有所扩大,主要包括河北南部、河南中东部、山东、安徽、湖北中东部、江苏以及浙江中北部等地。     

2001—2007年兰州市主要大气污染物污染特征分析

以兰州市2001-2007年空气污染指数资料为基础,对每日空气污染指数(Air Pollution Index,API)、空气质量级别和PM10浓度等的年、季、月变化特征以及采暖期和非采暖期污染变化差异进行了分析。结合甘肃省地面气候资料集兰州市日观测资料,通过单因素方差分析和线性相关分析,找出不同季节对PM10浓度有显著影响的气象要素,得到不同季节与PM10浓度呈显著线性相关的气象因子。结果表明:(1)兰州市的首要污染物仍以PM10为主,其中冬季和春季污染最严重,PM10浓度在冬季12月有一主峰值,在春季3,4月份有一次峰值;(2)近年来,兰州市污染天数有减少趋势,并与兰州市烟、粉尘年排放量减小趋势一致;(3)采暖期PM10浓度有明显减小趋势,而非采暖期PM10浓度减小趋势不明显,污染日越来越集中在采暖期;(4)与PM10浓度呈显著线性相关的气象要素存在季节差异,但总体上风速、气温和湿度(或降水)是影响兰州市PM10浓度的主要气象因子,因此湿度、温度和风场条件的改变将对兰州市的大气环境产生影响。     

郑州市空气质量统计预报方法探讨

根据2005年、2006年采暖期RegCM 3模式输出产品和郑州市环境监测中心逐日监测资料,利用逐步回归方法建立了PM10、SO2、NO2等污染物质量浓度预报方程。该方法在2007年采暖期的试报中效果不理想,预报准确率明显低于历史拟合率。为了提高预报准确率,针对目前采用的统计方法中存在的不足,即在选择预报因子时没有考虑预报因子之间的相关性,挑选的预报因子由于非正交,使回归计算的结果不稳定。将自然正交分解和多元回归分析结合起来,以采暖期各污染物的日均质量浓度为预报对象,建立预报模型。结果表明,采用新方法制作的空气质量预报准确率有一定程度提高。     

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