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1.
为了得到沙尘粒子和沙尘质量浓度的实时定量特征,利用Grimm180粒子仪在塔克拉玛干沙漠对沙尘暴进行了实时观测。通过分析Grimm180粒子仪在2018年5月20日和24日两次沙尘暴过程观测的数据得到:在浮尘、扬沙和沙尘暴期间,PM2.5的质量浓度值随时间变化不大,一般PM2.5浓度值<1500μg·m-3,而PM10在不同阶段的变化比较明显,数值在2000~6000μg·m-3。沙尘粒子谱和沙尘质量浓度谱的分布形状在浮尘、扬沙和沙尘暴基本相同,当粒子直径>0.35μm时,粒子数浓度随直径的增大近似符合M-P分布。从浮尘到扬沙再到沙尘暴,小粒子区(D≤1μm)的占比越来越小,而中粒子区(1μm10μm)的粒子数越来越多并且占比越来越大。当粒子直径为0.35μm左右时,粒子数浓度达到最大值;当粒子直径在25~32μm时,沙尘质量浓度的值最大。在浮尘和扬沙阶段,PM2.5/PM10>25%;每分钟1 L体积内的沙尘粒子总数大约是4×105,最大沙尘质量浓度<20μg·L-1。在沙尘暴阶段,PM2.5/PM10<15%;每分钟1 L体积内的沙尘粒子总数>5×105,最大沙尘质量浓度>25μg·L-1。这些结论为准确地分析沙尘暴的定量特征提供了科学依据。 相似文献
2.
利用2010年9月1日石家庄市区一次飞机探测的气溶胶资料,分析了石家庄市区上空大气气溶胶的数浓度与直径的垂直、水平分布特征及粒子谱分布。结果表明:600—3000 m高度范围内,气溶胶粒子平均数浓度为1443.1个/cm~3,粒子平均直径为0.194μm。3000—6900 m高度范围,气溶胶粒子平均数浓度为95.3个/cm3,粒子平均直径为0.192μm。气溶胶数浓度随着高度增加而迅速减少,受逆温层与云区分布的影响,数浓度曲线呈现一定程度的波动。由于探测当天高空风的影响,粒子数浓度明显比其他霾天气条件下的研究结果要低。云中,气溶胶数浓度与粒子平均直径数呈负相关性。云层对气溶胶的垂直分布影响较大。气溶胶粒子谱覆盖了0.10~1.05μm的尺度范围,粒子主要集中在0.1~0.3μm的范围内。600 m、1200 m、1800 m和3000 m的气溶胶粒子谱呈双峰分布,粒子谱谱型较为相似,4500 m和6900 m粒子谱呈单峰分布。气溶胶粒子尺度谱峰值随高度增加而减少,谱变窄。气溶胶粒子浓度水平变化幅度远小于垂直方向上的变化幅度,受天气条件及下垫面、云区等局地影响因子的影响较大。 相似文献
3.
敦煌地区春季大气气溶胶粒子数浓度的分析 总被引：6，自引：0，他引：6
利用2002年春季在敦煌地区戈壁沙漠和绿洲农田观测的大气气溶胶粒子数浓度资料, 分析了它与沙尘天气的关系、谱分布特征以及两种地表下粒子数浓度的差异.结果表明, 不同天气条件下的大气气溶胶粒子数浓度有着不同的特征.在背景天气下, 敦煌地区的大气气溶胶粒子数浓度通常在104L-1以下, 其中以直径在0.5～1.0 μm之间的极细颗粒为主, 绿洲农田细粒子(直径＜3.0 μm)的数浓度高于戈壁沙漠, 而较粗粒子(直径＞3.0 μm)则相反.当沙尘天气发生时, 该地区的大气气溶胶粒子数浓度增大到105 L-1以上, 直径在1.0～3.0 μm之间的细粒子变为其主要成分, 戈壁沙漠4档的粒子数浓度均高于绿洲农田, 3.0 μm以上的较粗粒子两地的差异更大. 相似文献
4.
《干旱气象》2015,(3)
利用2009年9月8日华北中南部上空的飞机探测资料,分析了石家庄市和邯郸市区附近大气气溶胶的粒子数浓度、直径、尺度谱分布等时空变化特征。分析表明,降水天气条件下,气溶胶粒子平均数浓度约为137.6个/cm3,平均直径约为0.26μm。气溶胶主要集中于2 000 m以下的对流层低层,气溶胶浓度总体上随高度增加而降低;雨后阴天轻雾天气条件下,气溶胶粒子平均数浓度约为164.7个/cm3,平均直径约为0.16μm。气溶胶在逆温层下累积现象明显,云内气溶胶数浓度明显减少。气溶胶粒子浓度水平变化受下垫面、云区分布等局地因子影响较大。石家庄600 m和6 600 m气溶胶粒子谱呈单峰分布,3 000 m粒子谱呈双峰分布。邯郸6 400 m粒子谱宽较窄,呈单峰分布。 相似文献
5.
《高原气象》2018,(5)
针对兰州大学半干旱气候与环境观测站在敦煌地区的沙尘气溶胶加强观测试验,选取2012年春季自然和污染沙尘两种典型天气个例,利用激光雷达退偏观测的优势分离粗(沙尘)、细(背景气溶胶)粒子,反演并对比分析了沙尘气溶胶消光系数及质量浓度的垂直分布特征。研究发现,以4月26日为代表的自然沙尘,粒子退偏比垂直廓线均大于30%,质量浓度呈现单峰结构,1.5 km出现最大值(1 070μg·m~(-3));以4月6日为代表的污染沙尘,有明显的气溶胶分层现象,粒子退偏比介于5%～20%,沙尘质量浓度介于2～45μg·m-3;由于局地污染的影响,污染沙尘的质量消光系数(0.79m~2·g~(-1))明显大于自然沙尘(0. 48 m~2·g~(-1))。因此,为了准确评估沙尘气溶胶的质量浓度,对沙尘天气进行分类,并利用粒子退偏比有效分离沙尘气溶胶尤为重要。 相似文献
6.
利用河北省2005年10月份的3次气溶胶飞机观测资料和宏观天气资料,综合分析石家庄地区不同天气条件下气溶胶的垂直分布和尺度谱分布特征。分析结果表明:气溶胶浓度的分布与大气环境情况密切相关。气溶胶数浓度最大值的变化范围是103~104cm-3,平均数浓度为103cm-3,粒子平均直径为0.120~0.150μm;21日近地面有霾,相对湿度为58%,近地面气溶胶浓度较17和29日略低,但粒子平均直径(0.165μm)比其余两次要大,可见相对湿度较大,大气中水汽含量较多,有利于小粒子凝结水汽,使粒子直径增大;逆温层结下,粒子在逆温层下累积,无逆温时数浓度最大值出现在近地面附近。气溶胶粒子谱呈单峰分布。 相似文献
7.
北京及周边地区2003年夏秋季气溶胶和云滴分布特征 总被引：15，自引：0，他引：15
对2003年夏秋季利用机载PMS在北京及周边地区进行的不同天气状况下6次气溶胶粒子探测资料进行了分析.结果表明,北京及周边地区气溶胶粒子的分布,在不同天气背景时有较大差别.粒子平均浓度的最大值为3.46×102cm-3,最大粒子浓度为5.26×103cm-3,相差一个量级;粒子平均最大直径为1.392μm,最大直径为2.75μm.粒子平均浓度的最小值为25.7cm-3.在有雾的天气条件下,气溶胶粒子浓度在近地层基本随高度的增加而减小,粒子尺度变化较为复杂.在阴雨天气情况下,气溶胶粒子浓度和尺度都有增加的现象.另外,逆温层底存在明显的气溶胶粒子累积.0℃层以下气溶胶粒子呈单峰分布,0℃层以上气溶胶出现双峰结构.小云粒子一直是多峰结构,峰值直径分别在3.5μm、12.5μm、23.5μm处. 相似文献
8.
利用北京市空气质量监测数据和气象资料,对2013年2月28日和3月9日两次沙尘污染过程PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物,即细颗粒物)、PM10(空气动力学当量直径小于等于10μm的颗粒物,即可吸入颗粒物)浓度及PM2.5浓度/PM10浓度比值的变化特征进行了分析,研究结果表明:(1)沙尘开始影响北京时,PM2.5与PM10浓度表现出反位相变化,PM10浓度在两次沙尘过程中2 h内分别上升50.8%与202.4%,最高达800μg m-3以上;PM2.5浓度分别下降58.3%与50.9%,直至下降至35μg m-3以下,PM2.5有明显改善现象。(2)虽然PM2.5浓度在沙尘到达前有缓升的迹象,但沙尘抵达后,PM2.5浓度持续快速下降,PM2.5浓度/PM10浓度比值由沙尘影响前的0.75以上降至0.25以下。沙尘影响前,PM2.5日均值均超过150μg m-3,北京地区处于重度污染水平。这说明沙尘来临前以人为污染为主,主要由细粒子"贡献",沙尘来临后的空气污染,主要由巨、大粒子的沙尘"贡献"。 相似文献
9.
利用2010年11月6日在珠江三角洲的佛山、江门等地区上空进行的一次飞机探测数据,初步分析气溶胶粒子的垂直和水平分布特征。结果表明,气溶胶粒子在不同的高度有较大的差异,自下而上存在着累积层、递减层和增加层,在1 033 m以下的大气边界层存在气溶胶粒子的累积,气溶胶粒子最小浓度为1 151.15/cm3,高度1 033 m;最大浓度为7 307.38/cm3,高度627 m;平均浓度5 775.63/cm3,平均直径0.212 μm,最大直径0.219 μm,最小直径0.189 μm。在1 033 m以上,气溶胶粒子浓度随高度增加而递减,但在逆温层附近气溶胶粒子的浓度出现了随高度增加而增加的现象。在江门鹤山上空3 800 m的高度层平飞时段,气溶胶粒子数浓度平均为19.74/cm3,变化范围1.97～53.65/cm3。对不同高度粒子谱分析表明,其谱型为多峰型,且高度越高,谱宽越窄,大粒子基本集中在1 000 m高度以下。 相似文献
10.
沙尘传输路径上气溶胶浓度与干沉降通量的粒径分布特征 总被引：1，自引：0，他引：1
利用2002年春季中国北京、青岛和日本福冈3个地区的分级气溶胶浓度资料,结合改进的Wil-liams模型,分析了沙尘传输路径上空气动力学直径≤11μm气溶胶(PM11)浓度和干沉降通量的粒径分布特征,并估算了黄海海域春季PM11的干沉降通量及不同粒径气溶胶的贡献。结果表明:3个地区PM11浓度粒径分布在非沙尘时期呈双峰分布,两个峰值分别出现在细颗粒(<2.1μm)部分和粗颗粒(2.1～11μm)部分;沙尘时期,3个地区PM11浓度粒径分布均趋于单峰分布,峰值位于粗颗粒部分,并且越靠近沙尘源地,这种趋势越明显。较强沙尘天气时期,粗颗粒部分的浓度峰值粒径从沙尘源地附近到黄海西岸、东岸呈降低趋势,但在一般沙尘天气时期,这种现象并不明显。沙尘时期和非沙尘时期,3个地区粗颗粒的干沉降通量均随粒径增加而增大,细颗粒的干沉降通量随粒径的变化不明显。虽然沙尘时期粗颗粒沉降通量较非沙尘时期有明显增加,但粗颗粒对PM11干沉降通量的贡献与非沙尘时期相比,并没有明显的变化。较强沙尘天气时期,3个地区粗颗粒的干沉降通量明显高于一般沙尘天气时期;细颗粒的干沉降通量较一般沙尘天气时期略有增加。黄海海域春季沙尘时期PM11的干沉降通量约为31.70～58.59mg.m-2.d-1,非沙尘时期约为8.33～15.94mg.m-2.d-1。粗颗粒是黄海海域春季PM11干沉降通量的主要贡献者,约占PM11干沉降通量的94.2%以上。 相似文献
11.
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 Nio3.4 index in summer and autumn but negatively correlated in spring and winter. 相似文献
12.
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. 相似文献
13.
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(Stl), 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. 相似文献
14.
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. 相似文献
15.
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. 相似文献
16.
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. 相似文献
17.
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. 相似文献
18.
Fei LIU Chen XING Jinbao LI Bin WANG Jing CHAI Chaochao GAO Gang HUANG Jian LIU Deliang CHEN 《大气科学进展》2020,37(7):663-670
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. 相似文献
19.
Yuepeng PAN Mengna GU Yuexin HE Dianming WU Chunyan LIU Linlin SONG Shili TIAN Xuemei Lü Yang SUN Tao SONG Wendell W. WALTERS Xuejun LIU Nicholas A. MARTIN Qianqian ZHANG Yunting FANG Valerio FERRACCI Yuesi WANG 《大气科学进展》2020,37(9):933-938
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 相似文献
20.