山东夏季两次切变线暴雨过程对比分析

利用常规观测资料、卫星云图、多普勒天气雷达和NCEP1°×1°再分析资料,对2012年7月30日和2013年7月9日山东出现的两次区域性暴雨进行了对比分析,结果表明：两次850 hPa切变线造成的暴雨,线状MCS(Mesoscale Convective System)组织化程度高,地面辐合线触发了暴雨的发生。不同的是:①“7〖DK〗·30”暴雨500 hPa影响系统为阶梯槽,副高位于朝鲜半岛以东;“7〖DK〗·9”暴雨为典型的东高西低形势,副高控制华东沿海;②“7〖DK〗·30”暴雨受一股较强的东南气流作用,将东海及西太平洋水汽输送到暴雨区,925 hPa水汽通量散度和最强上升速度较“7〖DK〗·9”暴雨分别大-10 g〖DK〗·hPa-1〖DK〗·cm-2〖DK〗·s-1和-0.2 Pa〖DK〗·s-1,“7〖DK〗·9”暴雨由低空西南急流将南海的水汽输送到暴雨区,925 hPa水汽通量和比湿较“7〖DK〗·30”暴雨分别大2~4 g〖DK〗·cm-1〖DK〗·hPa-1〖DK〗·s-1和2 g〖DK〗·kg-1;③两次暴雨过程MCS发生发展过程、形成方式和成熟期组织结构存在显著差异,“7〖DK〗·30”暴雨是对流单体独立发展逐渐合并成β中尺度,最终形成α中尺度对流系统,“7〖DK〗·9”暴雨为多个对流单体合并为β中尺度系统。通过分析得出,切变线暴雨触发机制应着眼于地面辐合线的形成和加强以及冷空气侵入引起的锋生。     

“16·7”石家庄特大暴雨多源观测信息特征分析

利用风廓线雷达、地基GPS水汽、微波辐射计、多普勒天气雷达、卫星云图、闪电定位仪、地面加密自动站等多源观测资料，对“16〖DK〗·7”石家庄特大暴雨的演变特征进行分析，结果表明：①GPS水汽总量和微波辐射计水汽总量的高值阶段对应强降水阶段，水汽总量与降水强度成正相关。降水开始前水汽总量明显上升，突升到高值时间比降水开始时间提前5 h，水汽总量突增对降水开始时间有提示作用。②低层偏东风的厚度和强度与强降水呈正相关，低层风向转西北风预示强降水结束。低空急流出现时间比降水开始时间提前5 h，低空急流消散时间比降水结束时间偏早3 h，超过20 m〖DK〗·s-1的东风急流对强降水有一定指示作用。强降雨对应低空急流最低高度的下降和低层最大风速的增加，也就是对应低空急流指数和0～3 km垂直风切变的峰值区。③此过程以稳定性降水为主，仅在19日伴有弱闪电和雷暴出现。雷达回波和卫星云图表现为大范围层状云和积状云混合降水回波，回波质心低，列车效应明显，属于热带降水类型。〖JP2〗云顶亮温最低值-55 ℃，雷达反射率因子、垂直累积液态水含量和回波顶高最大值分别为55 dBz、15 kg〖DK〗·m-2和11 km，与降水量有明显相关；低层径向速度场对应明显的速度大值区或速度模糊。〖JP〗     

鲁西南2020年两次区域性大暴雨过程形成机制分析

利用常规地面、高空观测和ERA5再分析数据，对鲁西南2020年7月22日（简称“7〖DK〗·22”过程）和8月6—7日（简称“8〖DK〗·6”过程）两次区域性大暴雨及伴随的短时强降水形成机制诊断分析。结果表明：“7〖DK〗·22”过程是一次地面气旋降水过程，大暴雨主要出现在气旋中心至移向右前部的倒槽内，短时强降水是对流不稳定触发后，惯性不稳定的增强造成。“8〖DK〗·6”过程是一次副高边缘暖区降水过程，大暴雨主要出现在低空急流的前端、地面辐合线附近，短时强降水由对流不稳定的触发和释放造成。“7〖DK〗·22”过程暖湿急流较强，水汽通量散度和动力条件显著强于“8〖DK〗·6”过程，超低空强辐合区、水汽通量散度辐合大值区、水平动能大值区边缘的强锋生区以及湿位涡MPV大值区边缘的|MPV2|小值区对短时强降水的出现区域指示较好。两次过程分析均表明垂直上升运动和深厚湿区的配合对短时强降水的出现时间指示较好。     

2012年春末昆明大暴雨的中尺度对流系统特征分析

利用常规气象观测资料、NCEP/NCAR逐6 h 1°×1°再分析资料、FY 2E红外云图TBB资料、昆明C波段多普勒雷达探测资料,结合中尺度数值模式的模拟结果,分析了2012年5月24日晚昆明大暴雨期间中尺度对流系统演变特征及形成机理。结果表明,此次大暴雨是在高低空系统最佳配置下产生的。降水峰值出现时,低层增暖湿,从地面到500 hPa呈显著的对流性不稳定层结,700～500 hPa垂直风切变达14 m·s-1。纬向结构上,暴雨中心低层东风增强,300 hPa以下纬向风辐合,中心强度为-28×10-5 s-1,150 hPa以下上升气流中心强度为21 m·s-1,近地面水汽通量辐合为-20×10-5 g·hPa-1·s-1·cm-2;经向上,暴雨中心500 hPa以下南风风速辐合,上升气流增强,强度与纬向一致,低层水汽通量辐合中心强度为-30×10-5 g·hPa-1·s-1·cm-2,强于纬向水汽通量辐合。此外大暴雨中地形对南风的强迫也是显著的,抬升速度在0.4~1.0 m·s-1。这次强降水分为初始、加强、回落和衰减四个阶段,昆明近地层浅薄冷空气加强时,引发其东侧对流单体移向昆明,强降水发生;然后南风出现脉动,局地湿层增厚和垂直风切变加大,促使对流单体两度增强并出现降水峰值;第三次峰值则是弱南风脉动及对流单体合并所造成,由于移入的单体较之原地发展的单体弱得多,原地单体作用的降水峰值也明显小于前面两次。对流降水回波属于暖云性质的热带低质心降水回波。     

2020年内蒙古东南部一次特大暴雪伴冻雨灾害天气特征分析

利用常规气象观测资料、NCEP逐6 h和逐日再分析资料、FY 2G卫星云图资料，从环流形势、水汽条件、动力条件及层结特征方面对2020年11月18—19日内蒙古自治区东南部罕见的特大暴雪伴冻雨过程进行分析。结果表明：①大气环流异常是造成此次灾害性天气的主要环流背景，500 hPa西风槽和南支槽、700 hPa西南低空急流及切变线、850 hPa以下东北急流、地面气旋是此次过程的主要影响系统，具有回流暴雪的天气特征；②低空偏南和偏东急流两支水汽输送路径及水汽强烈辐合为极端暴雪提供了充足的水汽，850 hPa和700 hPa比湿最大分别为5 g〖DK〗·kg-1 和4 g〖DK〗·kg-1；③低空偏南急流代表的暖空气与北方的冷空气剧烈交汇，暖湿空气在低层“冷垫”上爬升，加剧上升运动的发展，导致该区域降雪迅速加强；④非绝热加热项〖WTBX〗F〖WTBZ〗3对锋面生消作用最小，水平运动项〖WTBX〗F〖WTBZ〗1是锋生函数变化的主要贡献项，锋生函数〖WTBX〗F〖WTBZ〗变化与降水强度变化一致，在〖WTBX〗F〖WTBZ〗＞10的较强锋生区都出现暴雪，因此锋面的强迫抬升对暴雪的增幅作用不容忽视；⑤锋区的维持使得低层维持低温天气，锋上逆温，暖湿空气沿锋面抬升，900 hPa 以下“冷垫”与之上的“暖盖”长时间存在，导致暴雪发生并持续；⑥锋上逆温且逆温区存在融化层，这种垂直结构变化有利于降水相态转化，高层和低层为低于0 ℃的冷层，中间形成温度高于0 ℃的暖层，符合融化类冻雨的层结特征。     

1961—2020年青海高原气候变化特征

选取1961—2020年青海高原50个地面气象观测站逐月气温（平均、最高、最低）、降水和风速资料，利用气候变化趋势转折判别模型（Piecewise Linear Fitting Model,PLFIM）、气候倾向率等方法，分析青海高原气候变化的时空分布和年代际趋势转折变化等特征。结果表明：〖JP2〗①近60年来青海高原年平均气温呈显著上升趋势，其中平均最低气温的升温速率尤为明显，为0.62 ℃〖DK〗·（10a）-1;年降水量呈波动上升趋势，进入21世纪后呈显著增加趋势，速率为39.9 mm〖DK〗·（10a）-1;年平均风速整体呈减小趋势，其中以茫崖站最为明显，风速减小速率为-0.56 m〖DK〗·s-1〖DK〗·（10a）-1。〖JP〗②年平均气温和平均最高气温在1972年和1983年发生了年代际趋势转折，平均最高气温第3次转折发生在2009年，平均最低气温没有发生明显的年代际趋势转折。年降水在1972年、1983年和2000年发生年代际趋势转折;年平均风速发生在1998年和2009年。③与旧气候态（1961—1990年）相比，新气候态下（1991—2020年）青海高原年平均气温、平均最高气温和平均最低气温的均值分别上升了1.16 ℃、1.22 ℃和1.81 ℃，向高温方向漂移，且概率密度分布形状更加偏平，气候趋于不稳定;④在全球变暖背景下，青海高原年平均气温和年降水量均呈增加趋势，其中年平均气温的增温速率远超中国、同纬度地区及全球平均水平;降水量年际波动较大，但整体呈增加趋势。     

2014年一次渝东北大暴雨天气成因诊断分析

采用常规观测资料、NCEP 1°×1°再分析资料及自动站、SWAN、风廓线等资料对2014年8月31日至9月1日渝东北地区出现的一次大暴雨天气进行诊断分析,结果表明：①持续性的强降水产生于有利的环流形势下。华南地区副热带高压稳定维持,副高北侧高空低槽缓慢东移,与低空切变线形成了持续性的大尺度强迫作用,使得强降水长时间维持。②强西南暖湿气流与偏东冷流在渝东北地区交汇,锋生作用显著,暴雨期间锋区呈准静止状态,锋区对流层中低层显著的θse差动平流有利于锋区对流性不稳定增强。③风廓线雷达显示暴雨期间西南低空急流显著增强,1～3 km高度低空急流维持超过8 h,最大风速超过18 m〖DK〗·s-1,并存在显著的高空辐散、低空辐合。④地形对降水的增幅作用显著。TREC风场显示大巴山南麓维持西南气流,风向与山脉走向近乎垂直,地形的强迫抬升作用加大了山前降水,形成了与山脉走向基本一致的大暴雨区。     

2020年春末夏初浙江省三次暖区暴雨过程诊断分析

利用常规观测资料、FNL再分析资料、FY 2H静止卫星以及双偏振雷达数据，对发生在2020年5月25—26日、29—30日及6月2—3日浙江省的3次暴雨过程（简称“5〖DK〗·25”、“5〖DK〗·29”和“6〖DK〗·2”过程）进行了诊断分析，比较了3次暴雨的落区、强度、成因及云团等差异。结果表明：①3次暴雨均发生在高空槽前的低空切变线上，高空槽深浅、中尺度切变线位置、南部急流脉动强弱等因素是造成3次暴雨落区和强度差异的主要原因。②暴雨落区位于湿辐合带西侧，700 hPa湿〖WTHX〗Q〖WTBZ〗矢量散度场负值区对暴雨落区有较好的示踪作用。③3次暴雨过程均存在锋生作用和冷暖中心对，“5〖DK〗·25”过程中层锋生先于低层，有弱温度平流，为短历时强降雨，其降水效率低，“5〖DK〗·29”和“6〖DK〗·2”过程则有强冷暖平流，为长历时强降雨，降水效率高。④“5〖DK〗·25”过程暴雨云团尺度相对较小且生命史较短，降水稳定；“5〖DK〗·29”过程云体密实、云顶亮温低、回波质心高度高且偏向于混合性降水；“6〖DK〗·2”过程主要为α中尺度对流云团，冷云盖尺度大、存在柱状对流回波、回波质心高度高且偏向于对流性降水。     

2006-2017年成都地区酸雨变化特征及趋势分析

利用成都地区温江、简阳两个酸雨观测站2006—2017年的历史酸雨观测资料，结合主要大气污染物浓度数据以及降水量、风等地面气象要素，分析成都地区的酸雨变化特征及趋势。研究结果表明：温江站多年平均pH值为4.74，酸雨频率为51.6%，简阳站多年平均pH值为5.64，酸雨频率为27.2%，酸雨频率在地理区域上分布呈现不均一性；降水pH值和电导率(K)季节变化特征显著，降水pH值夏季最高，冬季最低，而降水K值则相反，夏季最小，冬季最大；近年来酸雨年变化有年平均pH值上升、酸雨频率下降和强度减弱趋势特征，年平均K值减小规律明显：温江K值以每年约3.5 μS〖DK〗·cm-1〖DK〗·a-1的速率下降，简阳以每年约3.7 μS〖DK〗·cm-1〖DK〗·a-1的速率下降；降水pH值与大气污染物SO2、NO2的负相关较为明显，相关系数为-0.488，硫氧化物对酸雨污染贡献逐渐减小；降水K值和大气主要污染物有较强的正相关，相关系数为0.657，与PM10、PM2.5相关性好于与SO2、NO2，近地层大气污染颗粒物浓度对降水K值影响较大；降水pH值与降水量级的变化不明显,但降水量越大其K值越小，且随平均风速的增大降水pH值相对偏大而K值偏小。     

大别山区茶叶气候生产潜力评估

基于大别山区35个气象观测站1971—2020年逐日气象资料、DEM数据，采用气候统计分析、逐步订正法和趋势面插值等方法，对茶叶光合生产潜力（YQ）、光温生产潜力（YT）和气候生产潜力（YW）时空变化特征、气候资源贡献率及其对气候变化的响应进行了分析。结果表明：大别山区茶叶YQ和YW呈下降趋势，降幅分别为0.58和0.05 t〖DK〗·hm-2〖DK〗·(10a)-1，YT呈增加趋势，增幅为0.36 t〖DK〗·hm-2〖DK〗·(10a)-1；空间分布上，YQ随纬度的增加而增加，YT随纬度和海拔的增加而减少，YW随纬度的增加而减少、随海拔的增加而增加；太阳辐射、温度和降水对YW的贡献率分别为26%、48%、26%，温度的促进作用与太阳辐射和降水的抑制作用相互抵消，致使YW总体呈动态平衡趋势；气候变化背景下，大别山区北部地区较南部地区YQ下降趋势更加明显，南部地区较北部地区YT增加趋势更加明显，YW在低海拔地区呈增加趋势而在高海拔地区呈下降趋势。研究结果可为大别山区茶叶产业充分利用气候资源、高效趋利避害、合理优化产业布局提供科学依据。     

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