河南省层状云降水雨滴谱特征分析

利用2015-2017年河南省层状云降水过程的Parsivel(Partical Size and Velocity)激光雨滴谱观测资料,对层状云降水的雨滴数浓度、含水量、雨滴直径等微物理参量特征及不同尺度的降水粒子对雨强的贡献进行了统计分析,并采用2种拟合方法对层状云降水雨滴谱进行了拟合。结果表明:河南省层状云降水的空间结构不均匀,各微物理参量的变化存在着起伏,雨滴数浓度为10²个/m³量级,个别达到10³个/m³,含水量在10^-2~10^-1 g/m³,粒子平均直径<0.5 mm左右,统计的不同台站平均最大粒子直径为1~2 mm,雨强平均值不超过1 mm/h。直径为<2 mm的雨滴对雨强的贡献占96.23%,直径小于1 mm的雨滴对数浓度的贡献最大。雨强是由雨滴最大直径、平均直径和数浓度3者共同决定。层状云降水雨滴的谱分布较窄,滴谱曲线比较平滑。降水开始时,谱型为单峰结构;降水处于稳定阶段时,谱型为双峰和单峰相结合的结构。层状云拟合M-P分布和Г分布偏差均出现在直径<1 mm的小雨滴端,对于微小粒子随直径增大而增多导致的曲线弯曲没能表现出来,相对而言Г分布拟合效果明显略优于M-P分布的拟合效果。河南省层状云降水的2种分布形式分别为N(D)=7373.9exp(-3.67D)和N(D)=10492.05D1.62exp(-5.11D)。     

河北省中南部暴雨雨滴谱特征

基于2016—2017年河北省中南部暴雨过程的OTT Parsivel激光雨滴谱仪观测资料,对3种类型暴雨过程的降水微结构特征参量、不同尺度降水粒子对雨强的贡献、分雨强下的雨滴谱分布、速度谱等进行分析。结果表明:河北省中南部暴雨不同雨强下雨滴谱基本呈现单峰型分布,低槽冷锋类暴雨雨滴谱谱宽最窄,低涡类暴雨次之,暖切变线类暴雨最宽。不同类型暴雨过程粒子平均直径和峰值直径平均值以低涡类最小,低槽冷锋类次之,暖切变线类最大。雨滴体积中值直径和质量加权平均直径均值以低槽冷锋最小,低涡类次之,暖切变线类最大。河北省中南部暴雨过程主要以直径D 1. 0 mm的小雨滴为主,其中1. 0≤D 3. 0 mm的雨滴雨强对总雨强贡献接近70%,D 4. 0 mm的大雨滴数浓度占总数浓度百分比最小,其雨强对总雨强的贡献也最小。3种类型暴雨分雨强对应雨滴谱多呈单峰型分布,呈双峰分布时对应雨强不同。速度谱上不同类型暴雨雨滴数极大值中心位置一致,且位于经验曲线下方。与目前雷达系统采用的标准Z=300~(I1. 40)关系相比,河北省中南部暴雨过程Z-I关系低估低槽冷锋类暴雨降水,高估低涡类和暖切变线类暴雨降水,其中低涡类暴雨偏差最大。     

黄河上游地区降水雨滴谱特征分析

利用黄河上游地区不同降水云系31次降水的激光雨滴谱仪观测资料,对不同云系降水雨滴物理参量特征及滴谱的演变特征进行统计分析。结果表明:在黄河上游地区,层状云系降水和混合云系降水雨滴粒子呈单峰型分布,对流云系降水雨滴粒子呈双峰型分布。层状云系降水雨滴粒径峰值出现在0.4 mm,粒径范围较窄,雨滴数密度最大;对流云系降水雨滴粒径峰值出现在0.8 mm,粒径分布范围较宽,雨滴数密度最小;混合云系降水雨滴粒径峰值和粒径分布范围介于两者之间。雨滴各微物理参量(平均直径、均方根直径、平均体积直径、中值直径和体积中值直径)由大到小排序依次为对流云降水、混合云降水和层状云降水。降雨强度和雨滴数密度变化趋势一致,对流云和混合云降水强度和雨滴粒子数浓度有较好的相关性。通过雨滴谱特征的研究,有利于认识该地区降水微物理特性及成雨机制,为实施科学人工增雨提供一定的科学依据。     

一次特大暴雨过程中涡旋暴雨云团的演变特征分析

利用MODIS卫星、多普勒天气雷达和地面观测资料,对2013年6月30日四川遂宁一次特大暴雨天气过程中涡旋暴雨云团的演变特征进行了详细分析。主要结论是:(1)涡旋暴雨云团与其北侧的积云云团呈前倾结构,说明暴雨云团经历了先由弱积云发展为深对流云、再到云毡的逐步发展成熟过程;(2)涡旋暴雨云团从南到北围绕低涡中心东侧最多时有6条降水云带,其中南部的降水云带碰并增长带(-1~-10℃层)厚度大于凝结增长带(3~-1℃层)厚度,北部降水云带刚好相反,表明南部以碰并增长过程为优势物理过程,利于较快拓宽云滴谱,使得云滴迅速长大形成雨滴降落下来;(3)涡旋暴雨云团中最强降水云带位于其南部的资阳至遂宁一带,分析雷达回波垂直剖面图发现有8个对流单体分布在云带中,且不断有新生单体移向遂宁,并从南至北依次增强,形成"列车效应",其成熟阶段-10℃高度以下碰并增长很充分,厚度为6 km左右,-10℃高度以上存在一个深厚的冰相增长带,厚度5~8 km,发展到成熟阶段碰并增长和冰相过程均为优势微物理过程,云中碰并增长和冰化增长过程向下传递明显,这些特点利于快速形成降水,导致当日10—17时遂宁站连续出现强降水。     

山东三类降水云雨滴谱分布特征的观测研究

利用激光雨滴谱仪2009年8月—2010年10月观测获取的滴谱资料,分析了山东省三类云降水雨滴微结构参量特征及滴谱随降水过程的演变特征。按照降水云系不同分别对各微物理参量进行比较,结果表明,各值由大到小排序依次均为积雨云、混合云和层状云。三类云降水过程中雨强与雨滴数浓度和最大直径间存在较好的相关关系;层状云和混合云降水以直径小于2 mm的雨滴为主,而积雨云降水以1~3 mm的雨滴对雨强贡献最大。层状云降水雨滴谱很窄,呈单峰或双峰型;积雨云降水雨滴谱宽,在大滴端呈多峰结构;混合云降水谱宽介于前两者之间。另外,统计得到该地区三类云降水的Z-I关系式,为雷达定量测量降水提供了一定的参考。     

春季粤北地区降水微物理特征分析

为揭示春季粤北降水微物理过程,选取2020年2—3月粤北2个站点雨滴谱仪观测资料,统计分析了春季粤北地区层云降水、混合性降水、对流性降水的微物理特征,结果表明:(1)对流性降水过程中大雨滴是影响雨强大小的重要因素;层云降水过程,小雨滴数浓度占比大于90%,平均雨强小于1 mm/h,雨滴数是影响雨强的重要因素。(2)层云性降水雨滴谱呈单峰结构,谱宽小;对流性降水雨滴谱为多峰结构,谱宽最大;混合性降水谱型与对流性降水相似。3类降水峰值均在0.2~0.3 mm范围,均是Gamma分布谱型拟合最优。(3)春季粤北地区对流性降水的Z-I关系为Z=173.9I^(1.452),混合性降水的Z-I关系为Z=72.77I^(1.97),层云性降水过程的Z-I关系为Z=194.3I^(1.296)。     

2003年春季陕西省层状云降水的雨滴谱特征

文章给出了陕西省春季（2003年）层状云降水雨滴谱部分特征,这些特征与降水天气系统密切相关。降水产生于混合云,各层系统配置适当,有较厚冷层云和相接的暖层云,雨滴数浓度大可达10³m^-3,雨滴谱较宽可达0.32 cm。反之数浓度较小(10²m^-3,谱较窄（0.22 cm）。其中直径0.1 cm以下雨滴谱约占总浓度的80%以上,而对雨强的贡献小于20%。0.1～0.2 cm雨滴是雨强的主要分量,它平均占48%～77%。雨滴谱多数呈非单调下降分布,三参数分布n（D_i）=n₀D^αe^-λD明显优于指数分布n（D_i）=n₀e^-λD。     

对积雨云、层状云降水雨滴谱个例对比分析

利用北京市人工影响天气办公室2008年获取的典型积雨云、层状云降水过程雨滴谱资料,通过雨强、雨滴空间浓度、最大雨滴等特征值对比分析了两类降水过程的微物理特征。,个例中积雨云和层状云的谱宽分别是6mm和4mm,但雨滴算数平均直径都是0．96mm,在过程平均空间浓度上积雨云高了近一倍,达到318m^-3而两个例中直径超过1mm的雨滴所占总空间浓度的比例均接近1／4、积雨云强中心和边缘的降水雨滴谱、雨强的差别很大,强中心直径大于4mm的大滴占总雨强的比例达到55％,谱宽达到6mm,而强中心过后的降雨边缘谱宽则小于4mm。稳定的层状云降水的雨滴谱、雨强在时空上存在分布不均匀和大、小滴空间浓度反向变动的特征。     

一次暴雨过程中云微物理特征的卫星反演分析

利用卫星反演技术和云微物理分析方法,以陕北2006年7月2日发生的暴雨过程为例,反演了云顶粒子有效半径(Re)、云顶温度(T)等云物理特征参数,通过卫星不同时次对暴雨云团的探测资料,分析了暴雨发展过程.暴雨云团表现为多单体特征,发展旺盛期对流单体的数量明显增加、云团尺度大幅增加.根据暴雨云系中的对流云、层云、过冷水云、低云(未被高云遮挡住)4种类型,分别选择了9个代表区,用于分析这次暴雨过程中不同类型云的物理特征和垂直结构.结果表明:此次暴雨云团由多种高度的云组成,低云高度较低,温度较高,云顶在0--10℃;层云高度略高,T为-10--20℃,Re为10-20 μm,并含有连片分布的过冷水云(Re为10 μm左右);高度最高的云为对流云,镶嵌在系统性层云中或在其上发展,T最低达到-80℃左右.从云底至0℃层存在一个较厚的凝结增长带,Re为5-10μm;0--10℃层存在一个碰并增长带,Re从13-15μm增长到20～25μm,但其厚度小于凝结增长带;T<-10℃层以上存在一个深厚的冰相增长带,表明在对流云团的发展成熟期,冰相增长过程为优势云物理过程.随着云的逐渐发展,混合相增长带由厚变薄,冰化增长带增厚,晶化温度升高、高度降低,表明在对流云团发展到成熟的过程中,冰化增长带在下传,云中冰化增长过程向下传递明显.     

伊犁河谷汛期一场短时强降水雨滴谱特征分析

利用常规地面、高空资料、新一代天气雷达资料、雨滴谱资料,对2012年8月3日发生在伊犁河谷的一次较大范围暴雨的天气背景、雷达回波特征和降雨微物理特征等进行深入分析。结果表明,200hPa西西伯利亚西风槽、500hPa中亚低涡和地面冷锋是这次强降雨过程的主要影响系统。河谷喇叭口地形对气流的机械挤压、东高西低地形对对流的触发、地形强迫抬升对对流和降水的增强具有重要影响。这场降水过程属于积层混合云降水,其中大面积的层状云中嵌有多个对流云团,这些云团连接在一起就构成了对流性雨带,通过对暴雨雨滴谱演变分析得出,这次暴雨主要降水由对流性云团造成,对流云团微物理结构存在明显的不均匀性,其中存在多个强降水中心,其水平尺度多维持在10km左右,持续时间维持在5分钟到10分钟之内,降水集中且雨滴数浓度较高,一般在1000m-1个以上,雨滴谱宽及分布差异很大,小于1mm粒子数浓度很高,对雨强的贡献占两成以上。     

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.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

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