珠三角城市扩张对春季主要气象参数和O3浓度的影响

利用新一代大气化学在线耦合模式WRF-Chem研究城市扩张对珠三角地区春季气象条件的改变及其对地面O3浓度的影响。研究结果表明:受城市扩张的影响,珠三角城区的月平均气温上升0.35℃;城区夜间相对湿度下降幅度为4%～6%,影响程度大于白天;风速在白天和夜间都有不同程度的下降,城市月平均风速下降1.89 m/s;边界层高度在白天和夜间均升高,城市月平均边界层高度上升39.82 m。城市扩张后,城市月平均O3浓度增加0.89 ppbv,增幅大于1.5 ppbv的区域主要在佛山和东莞,白天O3浓度增幅为0.6～1.5 ppbv,夜间增幅及影响范围都大于白天,O3浓度增加区域与主要气象要素变化的区域相一致;白天14:00城区混合层内总臭氧柱浓度增加了80 ppbv;O3浓度对气象要素的敏感程度表现为:温度>边界层高度>风速>相对湿度;白天O3浓度增幅呈U型,其中14:00的O3增幅最小,为0.2 ppbv;夜间O3增幅呈倒V型,其中20:00的增幅最大(>1.5 ppbv)。     

基于耦合湖模式的城市边界层模式研究太湖的气象与环境效应

本文发展了一个耦合的城市边界层—湖泊模式(RBLM-Chem-Lake),通过离线和在线两种方式对模式的模拟效果进行了检验。并通过敏感性实验分析了太湖冬季和夏季对周边地区气象特征和空气污染的影响。结果表明：(1)白天太湖对周边气象环境产生了明显的降温效应,而夜晚出现了明显的升温。冬季夜晚周边地区升温达到0.4～0.6℃,白天可以使得周边气温降低1～2℃。夏季夜晚使周边地区升温可达1～1.5℃,白天使得周边气温降低1～2℃。(2)太湖对周边地区气温的影响范围夏季远高于冬季,夏季影响范围可达到80 km,冬季影响范围平均为5 km。此外,太湖使得湖区平均边界层高度下降,湿度上升,使得苏州市区垂直风速减弱,这种影响同样在夏季更为明显。(3)太湖的存在总体上使湖区和周边地区PM_2.5和臭氧的质量浓度增加。在冬季PM_2.5污染个例中,太湖导致区域夜晚PM_2.5质量浓度下降,下降幅度达到4～5μg·m^-3。而在白天,太湖区域500 m高度以下PM_2.5质量浓度增加,幅度达到25～30μg·...     

土地扩张对城市边界层风热环境影响的模拟研究——以沈阳市为例

利用WRF模式中的UCM+AH城市冠层方案,以2005年8月两个晴天为天气背景,对比研究了1993年与2005年不同下垫面情况下,沈阳市城市扩张对近地层风热环境及边界层的影响。结果表明:UCM+AH方案能够较合理准确地模拟出城市范围的2 m气温与10 m风速的日变化特征,且对2 m气温的模拟效果要优于10 m风速;模拟2 m气温的日较差偏大,模拟10 m风速系统性偏高0.5—1.0 m·s-1;城市土地扩张后,城区普遍增温,且夜间增温幅度较大,扩建城区夜间最大增温能达到7℃,老城区在夜间增温幅度最大可达3℃,上风向增温幅度较大;城区日间增温不明显,在0—1℃;城市土地扩张后,老城区风速普遍减小,但减小值1 m·s-1;扩建城区风速减小近1 m·s-1,城区内可能出现的高温辐合中心对周围近地层风速有加速作用;城市扩张对边界层最显著的影响体现在午后,城区的扩张增大了湍流动能的影响范围,湍流动能在数值上增加0.2—0.3 m2·s-2;扩建城区上空的边界层高度在14时抬升100—200 m,且下风向边界层内部的局地环流与垂直上升运动增强。     

建筑物对周边气温影响的初步研究

随着城市化进程的加快,建筑物成为影响气温观测的最重要因素之一。为了定量研究建筑物对周边气温的影响,应用城市小区尺度模式,选取气象站观测的3个重要时刻(14∶00、20∶00以及02∶00,北京时间),模拟了草地下垫面上长60 m、宽20 m的孤立建筑物,在不同高度(6、18、30m)及不同初始风速(2、4、6、8、10 m·s~(-1))条件下建筑物下风方的气温变化。研究结果表明:(1)由于建筑物的存在,夏季晴天14∶00建筑物下风方最大增温可达2.4℃,夜间20∶00和02∶00建筑物下风方最大降温分别为1.0℃、2.4℃。(2)以影响幅度大于0.1℃为标准,建筑物对下风方气温影响的最大距离在14∶00为11.7倍建筑物高度;而在20∶00和02∶00分别达到36.7倍和21.7倍建筑物高度,超过气象探测环境保护条例规定标准。(3)建筑物导致下风方风速衰减,从而增加了湍流动能中机械产生项的作用,即风速衰减幅度越大,对气温变化影响作用越强;而在白天不稳定层结下,建筑物造成的太阳辐射遮蔽效应对气温变化也有一定影响,建筑物越高,反而会在一定程度上减弱增温效应。     

东疆黑戈壁近地大气边界层气象要素季节变化规律

利用东疆红柳河黑戈壁下垫面陆气相互作用观测站2017年近地大气边界层梯度探测资料和红柳河气象站天气现象观测数据,分析该地区典型晴天条件下的近地层风速、温度和比湿的四季廓线特征。结果表明:四季近地层风廓线变化规律明显。典型晴天条件下,在0.5～4 m高度内风速随高度的增加而变大的速度较快,在4～32 m范围内,白天风速随高度增大较缓慢,但夜间出现快速增大;存在明显的夜间逆温,逆温层主要集中在4～32 m,冬季逆温强于夏季,晨间0.5～32 m间的温度差可达4.6℃,且红柳河四季的气温日较差均较大,秋季可达到15.7℃;夜间比湿高于白天,秋、冬季夜间逆湿层出现在10～32 m,其比湿差为0.15 g/kg左右,夏季无逆湿现象。     

公路路面热效应对环境气温的影响分析

为定量研究公路对气温观测的影响,本文使用2014年1—5月在陕西省开展的两组公路观测试验的逐分钟温度、风向、风速等气象资料,对比分析了合阳县国道和渭蒲高速公路在不同季节、不同天空状况以及不同背景风速条件下对周围环境气温观测的影响程度和影响距离。试验结果表明:公路对周围的环境温度有一定的增温影响,合阳国道对环境温度的增温影响至75m,增温效应达0.25~0.4℃。高速公路的增温影响至125m,增温效应达0.2~0.4℃。冬季,两条公路白天增温效应较夜间明显,春季,高速公路夜间增温更明显。晴天、多云天气比阴天、降雨天气增温程度大。公路对气温的增温影响存在风速阈值,当风速小于对应阈值时,增温效应明显。公路上来往车流量对气温有一定的叠加增温影响,合阳国道白天车流量150~350辆,叠加增温效应0.05~0.1℃,蒲渭高速白天车流量2000~3500辆,叠加增温效应0.16℃。     

近58年来西沙海区的气温变化特征

采用西沙海区永兴岛气象观测站(59981)1958—2015年的气温资料,对近58年来西沙海区的气温变化进行了分析,结果表明:近58年来西沙海区气温按年代呈阶梯式显著上升趋势,增长率为0.02℃/年,升温幅度夜间大于白天;四季中冬季升温幅度最大,秋季升温幅度最小。     

帕米尔高原近地层气象要素垂直变化特征

利用中国与巴基斯坦交界的红其拉甫口岸帕米尔高原陆气相互作用观测站 32 m 梯度铁塔资料，分析了帕米尔高原在不同天气下近地层气温、湿度和风速等气象要素廓线日变化特点和脉动特征，结果表明：（1）晴天，日间风速随高度升高而增大，夜间风速随高度升高呈波动减小；阴雨天，风速整体随高度升高而增大；不同天气下各高度层脉动风速概率分布均呈现高度越高，脉动风速分布越集中的特征。（2）气温廓线在晴天表现为夜间辐射型、早上过渡型、白天日射型和傍晚过渡型四种类型，气温脉动随着高度的降低而增大；阴雨天气时气温廓线均为白天日射型，各高度层的气温脉动变化特征与晴天相反。（3）不同天气的比湿廓线分布均随高度增加而减小，比湿脉动范围晴天大于阴雨天，且在时间序列上波动性均具有一致性。     

WRF模式对济南地区夏季近地面气象场模拟效果评估

不同地区中尺度气象模式WRF的模拟性能存在明显差异,本文利用数值模拟和统计方法,评估了WRF模式在济南地区的模拟性能,并对比研究地形和土地利用对WRF模式模拟性能的影响,为WRF模式在济南地区的业务化运行提供参考。结果表明:WRF模式能较准确的模拟济南地区近地面气象场及其时间变化特征;统计分析发现,WRF模式对济南地区近地面气温、比湿、风速及风向的模拟准确率分别为72.5%、59.6%、29.4%和36.2%。WRF模式模拟的济南地区夏季比湿偏低、风速偏高,模拟的风速存在系统性偏差。下垫面对WRF模式的模拟结果有显著影响,10 m风速的均方根误差(RMSE)与地形、坡度、模式格点和观测站点的地形偏差显著相关,与坡度的相关系数最大;2 m气温的RMSE仅与地形偏差显著相关,在复杂地形区比较站点观测气温与模式格点气温时,需考虑地形偏差的影响。     

屋顶绿化对城市降温效应的模拟分析——以南京市为例

利用WRF模式耦合单层城市冠层模式,针对屋顶绿化对城市降温效果进行了模拟,结果表明:(1)南京夏季绿化后的屋顶反照率约为0.15,较水泥及其他反光材料的反照率略小,在白天可造成约0.2℃的升温。(2)绿化后的屋顶热容量明显增加,可使白天气温下降0.33℃;在夜间,可使气温升高0.21℃左右。(3)在植被阻挡作用及土壤层阻挡作用下,屋顶的导热率降低。在白天,净辐射能很难向下层传递,从而转化为感热加热大气,造成气温升高。(4)土壤湿度的改变使更多净辐射能转化为潜热释放。在白天可使温度降低1.23℃;在夜间,平均降温幅度为0.44℃。除此之外,模拟不同季节的统计结果表明,屋顶绿化降温效果在夏季最为明显,最大降幅可达1.22℃,春季0.96℃,秋季0.75℃,冬季只有0.38℃。     

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.     

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