杭州市空气负离子变化特征分析

利用2008—2010年杭州西溪湿地和馒头山空气负离子观测资料,分析了杭州市空气负离子的季、月和日变化特征,以及空气负离子与气象环境因子的相关关系。结果表明,湿地负离子浓度要好于市区;杭州市空气负离子浓度冬季最大,夏季最小;一日中早晨空气负离子浓度最高,15时左右最低;夜间高于白天。空气负离子浓度与温度、日照时数和空气污染物呈负相关,与相对湿度、风速、云量和降雨量呈正相关。     

玉溪空气负氧离子预测模型的建立

利用玉溪市九县区14台空气负氧离子自动测报系统实时观测数据和同步气象要素观测资料,使用相关分析、回归分析等方法,分析了影响空气中负氧离子浓度的主要气象因子,以及影响因子与空气负氧离子浓度的关系,并建立预测模型。结果表明,玉溪市空气负氧离子浓度年变化、季节变化与各气象因子之间无显著的相关关系。影响玉溪空气负氧离子浓度日变化的主要气象因子为空气相对湿度和空气温度。当空气温度20.4℃时,空气负氧离子浓度日变化与空气温度呈负相关关系。当空气湿度45.6%时,空气负氧离子浓度与空气湿度呈正相关关系。通过建立负氧离子浓度预测模型,实现了负氧离子预报的定量化。经检验,预报方程效果显著,在预报业务中具有参考价值。     

新乡市大气污染特征与气象因子相关性分析

利用新乡市2015—2016年大气环境质量监测数据和同步常规气象观测数据,分析首要污染物质量浓度变化特征及其与气象因子的相关性,结果表明：PM10和PM25质量浓度冬高夏低,峰值出现在1月或12月,谷值出现在8月;而O3则是夏高冬低,峰值出现在6月,谷值出现在1月或12月。三种首要污染物质量浓度在大多数月份都与海平面气压呈负相关,与24小时变温（ΔT24）呈正相关;PM10和PM25质量浓度多数月份都与10 min风速呈负相关;PM25质量浓度大多数月份与相对湿度呈正相关,与24小时变压（ΔP24）呈负相关;PM10质量浓度与相对湿度在冬季呈正相关,夏季呈负相关,与ΔP24在春季呈正相关,在秋、冬季多呈负相关;而O3质量浓度在所有月份与温度、10 min风速都呈正相关,与相对湿度都呈负相关。     

江西省空气负离子浓度特征与气象因子相关分析北大核心

利用2019年江西省靖安森林试验基地观测资料,分析了靖安森林站空气负离子浓度不同时间尺度的变化特征及其与气象因子的相关性,以及不同天气条件对其的影响。结果表明,靖安市年平均空气负离子浓度为2187个/cm^(3),其中夏季浓度最高为2910个/cm^(3),秋季最低为1756个/cm^(3)。此外,浓度日变化特征也存在明显的季节差异性,其中春夏秋冬四季峰值分别出现在10时(北京时,下同)、06时、09时、13时左右。日尺度上浓度与气温、降水、相对湿度均呈显著的正相关,月尺度上其与降水呈显著正相关。雨天的浓度高于晴天,四个季节雨天峰值分别出现在开始降水的7~9 h、7~15 h、9 h、9~11 h后。当降水量在0~10 mm时,降水对空气负离子浓度没有明显作用,随后浓度随降水量增加而上升,当出现暴雨天气的时候,浓度反而呈现下降趋势。     

婺源县空气负离子分布规律初步分析

在婺源大鄣山卧龙谷景区、鸳鸯湖景区、月亮湾景区、城区和部分村庄选取7个能够代表当地生态环境特征的监测点,进行为期2 d的负离子浓度、温度、风向、风速、空气相对湿度和气压流动监测,并与南昌城区负离子浓度观测资料进行对比,初步分析了负离子分布规律,以及负离子与首要污染物(PM10)的关系.分析结果认为,负离子浓度与植被覆盖率、海拔高度呈正相关,与首要污染物浓度呈负相关;风景区的负离子浓度高于城区:植被状况与瀑布对负离子的空间分布影响最大.     

大气气溶胶粒径分布特征与气象条件的相关性分析

通过温度、相对湿度和风速等气象因素与不同粒径大气气溶胶粒子数浓度和质量浓度的相关性,分析气象条件对大气气溶胶的影响和作用机制。结果表明：气象因素对0.2—0.6 μm的气溶胶影响最大。温度升高既有利于增强大气扩散作用也有利于二次气溶胶生成,因此温度与超细气溶胶(小于0.1μm)呈正相关性,而与粒径较大的气溶胶呈负相关。风速主要影响气溶胶的水平扩散,对超细气溶胶无显著影响,而与粗粒径气溶胶呈负相关。相对湿度会促进超细气溶胶的聚积,使之生成较大粒径气溶胶。因此相对湿度与超细气溶胶呈较强的负相关,而与较粗粒径气溶胶呈正相关。     

2009—2011年包头市急性心肌梗塞发病与气象因素的关系分析

文章利用2009—2011年包头市5家医院497例急性心肌梗塞的临床资料及同时气象资料,对包头市急性心肌梗塞的发病规律与气温、气压、相对湿度等气象要素进行相关分析。发现包头市急性心肌梗塞发病具有明显的季节变化和年龄变化,冬春季发病率高,夏季发病率低,60~70岁为高发年龄段;急性心肌梗塞发病与月平均气温和湿度呈负相关,与月平均气压呈正相关,气压上升、湿度下降、气温剧降使急性心肌梗塞发病率增加。     

降水过程中气象条件对郑州市区气溶胶浓度的影响

利用郑州大气成分站的气溶胶浓度资料和气象资料,对郑州市区PM10、PM2.5、PM1浓度的日变化和月变化特征进行了分析,并对气温、降水、风速、气压等气象要素在降水过程中与气溶胶浓度的关系进行相关分析,结果表明,气溶胶浓度与气压呈正相关,与气温、降水量、风速等气象要素呈明显负相关,且随季节变化有所差异。     

降水过程中气象条件对郑州市区气溶胶浓度的影响

利用郑州大气成分站的气溶胶浓度资料和气象资料,对郑州市区PM10、PM2.5、PM1浓度的日变化和月变化特征进行了分析,并对气温、降水、风速、气压等气象要素在降水过程中与气溶胶浓度的关系进行相关分析,结果表明,气溶胶浓度与气压呈正相关,与气温、降水量、风速等气象要素呈明显负相关,且随季节变化有所差异。     

彭州市大气污染物浓度变化特征研究

本文利用2017年彭州市大气污染物(SO₂、NO₂、O₃、CO、PM₁₀、PM_2.5)小时浓度数据并结合地面气象观测资料,统计分析了该地区大气污染物浓度的演变规律及影响因素。结果表明:该地区细粒子(PM₁₀和PM_2.5)污染较为严重,O₃次之,其它污染物浓度水平则低于国家新二级标准限值。观测期间,各污染物浓度表现出明显的日变化与季节变化,其中SO₂、O₃呈单峰型日变化,NO₂、CO和细粒子则呈双峰型日变化;污染物浓度的季节变化基本表现为冬高夏低、春秋次之的变化特征(O₃为夏高冬低),并且固态污染物(PM₁₀、PM_2.5)与气态污染物(NO₂、CO)之间有显著的相关性。在污染物浓度与气象要素相关性分析中表明,湿度对于污染物浓度的影响整体上要弱于温度和风速,除了O₃与温度、风速呈正相关外,其它污染物与两者均呈负相关。除此以外,风向对于当地各种大气污染物的积累与清除也有直接的影响。      

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.     

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.     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.