西安市温室气体浓度变化规律研究

利用陕西省气象局长安大气科学实验基地(简称秦岭基地)2013年7月—2015年12月温室气体在线连续监测数据及同期气象观测数据,计算分析了两种温室气体(CO_2和CH_4)平均浓度日、月、季变化特征以及气象因素对温室气体浓度变化的影响。结果表明:(1)CO_2和CH_4平均浓度的日变化分布表现为下午低,早晨高的单峰型形态;月变化为明显的两头高中间低;(2)春、夏、秋三季大气中CO_2平均浓度日变化呈较为明显的单峰型,尤以夏季振幅最大,且全天浓度值为各季最小;而冬季CO_2全天浓度值整体高于其他三季。CH_4冬季日平均浓度最高值出现时间略滞后于其他三个季节,春夏两季变化趋势基本同步;(3)CO_2和CH_4采暖季及非采暖季的变化规律与各季节的变化规律极为相似;(4)CO_2和CH_4平均浓度随地面风速的增加而降低,冬季随地面风速的增加降低幅度最小,白天随风速下降的幅度大于夜间;气温越高,CO_2的降低幅度越大,而CH_4则随着气温的升高出现先增加后降低的趋势。     

淮河流域南部丘陵森林地区土壤-植被-大气相互作用:长期野外试验观测的初步分析（英文）

本文简要介绍了包括三部分观测的安徽淮南长期野外试验观测站,特别是土壤-植被-大气的集中观测,对小塔运行前三个月(2018年6月至8月)的数据,并结合同一时段大塔获得的数据,进行了初步分析.结果表明这些资料有合理的变化特征,日变化和夏季值特征显著,各月份间气象变化有明显差异.土壤水分和温度受降雨影响,在不同的下垫面条件下表现出不同的变化.土壤CO_2日平均浓度在2 cm和10 cm处分别为1726和4481 ppm.2018年夏季土壤CO_2浓度随土壤体积含水量的变化而变化,但与土壤温度呈弱相关.     

不同土壤水分控制对东北地区玉米农田土壤呼吸的影响

基于锦州地区土壤水分控制试验,研究不同土壤水分条件(土壤相对湿度分别为86%、96%和105%)对东北地区玉米农田土壤呼吸的影响,分析不同土壤水分条件下玉米农田土壤温度对土壤呼吸速率的影响。结果表明:2013年锦州地区玉米农田不同土壤水分控制影响土壤呼吸速率的大小,同时间不同土壤水分控制条件下玉米农田的土壤呼吸速率均随土壤相对湿度的增加而降低(土壤相对湿度86%土壤相对湿度96%土壤相对湿度105%)。锦州地区玉米农田土壤呼吸的日动态和季节动态变化趋势均不受土壤水分的影响,均呈单峰型,其中土壤呼吸速率日最大值出现在11—14时,土壤呼吸速率季最大值出现在8月。不同土壤水分控制影响玉米农田土壤呼吸对土壤温度的敏感性,土壤呼吸的日动态变化与10 cm土壤温度的日动态变化存在时间滞后性,8月和9月土壤温度最大值较土壤呼吸最大值滞后5—6 h。不同土壤水分条件下玉米农田土壤呼吸速率与10 cm、15 cm、30 cm和45 cm土壤温度均呈显著或极显著的正相关关系,其中土壤呼吸速率与45 cm土壤温度相关性最高。2013年锦州地区不同土壤相对湿度条件下(86%、96%和105%),玉米农田的土壤呼吸速率与45 cm土壤温度均呈指数函数关系,土壤相对湿度为86%、96%和105%时的土壤温度敏感性指数Q_(10)分别为1.92、2.20、1.72。     

景德镇地区大气CO2浓度变化特征

利用景德镇温室气体监测站CO_2观测数据,分析了景德镇地区2017年12月—2018年11月大气CO_2浓度变化特征,同时对其浓度进行了筛分,以剔除污染数据,使其更具区域代表性。研究表明:景德镇地区大气CO_2浓度昼降夜升,早上最高,傍晚最低;春季最高,秋季最低;春、夏季NNE、NE、ENE风向,秋季NE、ENE风向以及冬季W、WSW、SW、SSW、S风向上CO_2浓度较高。同时,春、夏和秋季大气CO_2浓度大致随风速的增加而不断降低,冬季风速对大气CO_2浓度无明显影响。筛分后数据显示景德镇地区年均大气CO_2浓度为422.1×10~(-6),浓度日均值年振幅73.96×10~(-6),夏半年CO_2浓度低于冬半年。     

珠江三角洲地区大气CO2浓度特征及地面风的作用

利用光腔衰荡光谱(CRDS)技术在线观测了广州番禺大气成分站(GPACS)的大气CO₂浓度特征,分析了地面风对CO₂的作用。结果表明：(1)大气CO₂在珠江三角洲地区存在明显的地域不均匀特征,2014—2016年期间GPACS的年均本底浓度比全球背景地区平均增加了22.5×10^-6(22.5 ppm);(2)大气CO₂浓度在春季最高,冬、秋季次之,夏季最低,年均值为426.64±15.76 ppm;(3) CO₂的日变化为双峰结构,峰值分别在05:00—07:00和21:00—22:00,谷值在13:00—15:00,表明受到了自然过程以及人为排放源的复合影响;(4)风场显著影响CO₂的浓度分布,春、夏季CO₂浓度距平日变化与地面风速为显著负相关,秋、冬季则为显著正相关。在春、夏季,S-WSW和NNE-N风向上CO₂浓度较低,在秋、冬季,SSE-S和N方向均导致CO₂浓...     

粤北暴雨中心的降水气候特征分析

基于广东省1967—2018年气象观测站和2003—2018年自动监测站降水数据,统计分析了粤北暴雨中心的降水气候统计特征。结果表明:(1)粤北暴雨中心范围主要集中在清远南部-广州东北部-惠州北部,最大年平均降水量(2 488. 6 mm)和强降水日数(12. 3 d)均出现在龙门的南昆山,特殊地形分布特征与粤北暴雨中心形成密切相关;(2)从化和增城降水年际变化呈较明显增多趋势,其余变化趋势不明显;中心区域内降水主要集中在汛期(4—9月),而前汛期(4—6月)降水量约占汛期的60%～70%;(3)降水月变化呈单峰型分布,峰值出现在5—6月;(4)降水日变化特征与降水性质密切相关,5—6月季风影响期间降水概率显著增加,夜雨和白天降水均明显;短时强降水出现概率集中在5—6月08:00、15:00和21:00前后。     

乌鲁木齐城市热岛强度的日变化和季节特征

运用2013—2014年28个自动气象站的逐小时气温观测资料,分析了乌鲁木齐地区气温的日变化特征及季节特征。结果表明:(1)城郊日最高气温出现频率最大的时次均为北京时间17时,出现频率在20%以上。日最低气温出现频率最大的时次为08时,频率在30%以上;(2)城郊年平均气温差异即城市热岛强度在夜晚较大,07时左右达到最大,在1.5℃以上,白天较小,16时左右最小,仅有0.3℃左右;(3)城郊日最高气温出现时间与城区基本一致,但日最低气温出现时间有差别,冬季郊区最低气温出现滞后城区1 h,其他季节保持一致;(4)城区逐小时城市热岛强度日变化可分为3个阶段:08—17时为下降时期,17—22时为迅速上升时期,22—08时为稳定的强热岛时期;(5)候平均气温城市热岛强度年内变化,最大值发生在年终的第72候,为1.53℃,最小值发生在秋末第67候,为0.33℃;(6)综合来看,各季代表月平均城市热岛强度春季(4月)夜晚较强,夏季(7月)夜晚和白天都相对较弱,秋季(9月)夜晚最强,但白天最弱,甚至白天部分时刻(15—18时)出现了负值。冬季白天和晚上都比较强,是四季代表月份平均热岛强度最强的季节。日内变化即日变化,大家公认的。     

河北沧州市臭氧质量浓度与气象因子的关系分析

利用2014—2020年河北沧州逐小时气象与环境监测数据,对沧州市臭氧(O_(3))污染加剧现状及其与气象因子的关系进行分析。结果表明:(1)沧州地区O_(3)污染呈加剧态势,且O_(3)已上升为该地区首要污染物;O_(3)污染集中出现在5—9月,O_(3)质量浓度日变化呈单峰单谷型,最大浓度出现在16:00前后;(2)5—9月O_(3)日最大8 h平均质量浓度(简称“O_(3)-8 h”)所处时段,平均气温、最高气温、相对湿度、总辐射辐照度与O_(3)质量浓度的相关性较好,本站气压、水汽压和平均风速与O_(3)质量浓度的相关性未通过显著性检验;(3)5—9月O_(3)-8 h时段,当同时满足8 h平均气温高于30.9℃、最高气温高于32.7℃、平均相对湿度低于42.1%、平均总辐射辐照度高于505.8 W·m^(-2)时,出现O_(3)污染的概率达84%;(4)气象因子不是O_(3)小时质量浓度快速增长的充分条件。     

阿克达拉大气本底站臭氧浓度变化特征分析

利用阿勒泰平原地区阿克达拉大气本底站2010年1月1日—2016年12月31日的臭氧质量浓度数据与PM_(10)等相关气象资料相结合,对臭氧质量浓度的日、周、月、季节、年变化特征以及影响臭氧浓度变化的主要因素进行了分析。结果分析表明:臭氧每小时平均质量浓度日变化规律呈显著单峰型,夜晚的变化较小,白天变化较大,01:00前后达到最小值,16:00左右达到峰值;臭氧每日平均质量浓度变化不具有较为明显的"周末效应"现象,峰值出现在星期六,日平均质量浓度为63.2μg·m~(-3),最低值出现在星期一,日平均质量浓度为60.0μg·m~(-3),日平均质量浓度最高值和最低值仅相差3.2μg·m~(-3);臭氧月平均质量浓度最高出现在2014年5月,为85.1μg·m~(-3),最低月平均质量浓度出现在2015年11月,为32.2μg·m~(-3);春、夏季臭氧质量浓度较高,秋季和冬季明显低于春季和夏季;2010—2016年臭氧浓度趋势线整体呈下降趋势,其中2012—2014年臭氧浓度连续月变化有明显的单峰型年度变化规律;臭氧浓度与PM_(10)质量浓度变化具有明显的逆向变化趋势,同时存在时间变化上的延迟性,并且臭氧的浓度变化早于PM_(10)质量浓度的变化。     

西宁近地面臭氧特征及其影响因素

利用青藏高原东北部城市西宁2015—2017年O_3质量浓度和各气象要素数据(紫外辐射、最高气温等),分析近地面O_3变化特征及其影响因素,结果表明:该地区臭氧平均质量浓度呈现单峰型日变化规律。每年6—8月O_3质量浓度最大,12月至翌年2月最小。依据环境空气质量指数AQI统计分析,6—8月污染天气O_3占首要污染物总天数的72%。O_3与NO_2、CO呈极显著负相关,臭氧日最大1 h平均质量浓度与紫外辐射、日最高气温呈极显著正相关,与日平均气压、日最高气压、日最低气压呈极显著负相关,与日平均相对湿度相关性不显著。不同季节不同高度风速大小和风向频率对O_3质量浓度影响不同,500 h Pa盛行风向以WNW为主时有利于扩散。2017年青海省大部地区O_3月平均质量浓度总体呈先增加后减小变化趋势。纬度越低,海拔越高的地区,O_3质量浓度升高越早。降水量的差异对O_3质量浓度影响较小。     

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.     

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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.