云底高度的地基毫米波云雷达观测及其对比

对2014年11月20日—12月31日中国气象局大气探测综合试验基地Ka波段毫米波云雷达、Vaisala CL51激光云高仪、L波段高空探测系统观测的云底高度进行对比分析。结果表明:在低能见度条件下,毫米波云雷达对云的探测能力明显优于激光云高仪,随着能见度的增加,两设备云探测能力差距在减小;毫米波云雷达与激光云高仪同时观测到有云时,二者观测的云底高度相关系数为0.92;毫米波云雷达与探空观测云底、云顶高度的相关系数分别为0.93和0.78;云雷达观测的云底高度均略低于激光云高仪和探空,云雷达观测的云顶高度略高于探空。     

毫米波云雷达功率谱密度数据的检验和 在弱降水滴谱反演中的应用研究

本文首先利用数值模拟的方法,分析了利用毫米波云雷达功率谱密度反演雨滴谱时,降水粒子米散射效应、空气湍流、空气上升速度等对雨滴谱和液态水含量等参数反演的影响;建立了功率谱密度处理及其直接反演雨滴谱、液态水含量、降水强度和空气上升速度的方法;并利用2012年7月在云南腾冲观测的二次弱降水数据,采用毫米波雷达和Ku波段微降水雷达观测的回波强度、径向速度垂直廓线以及780 m高度上的功率谱密度对比的方法,以及毫米波云雷达观测的780 m高度上功率谱密度、回波强度与地面雨滴谱计算得到的这些量的对比方法,分析了毫米波雷达数据的可靠性;并将780 m高度上毫米波雷达反演的雨滴谱与地面雨滴谱数据进行了对比,分析了毫米波雷达反演的雨滴谱的准确性;分析了毫米波雷达回波强度偏弱的原因,讨论了该高度以下降水对毫米波雷达衰减的影响。结果表明:空气湍流对弱降水微物理参数反演影响不大,而空气上升速度和米散射效应均对反演结果有一定影响;毫米波雷达观测到的径向速度和功率谱密度与微降水雷达比较一致,回波强度的垂直廓线的形状与微降水雷达也比较一致,但毫米波雷达观测的回波强度偏弱;与雨滴谱计算值相比,毫米波雷达观测的低层的回波强度也偏弱,天线上的积水是造成毫米波雷达回波强度变弱的主要原因。毫米波雷达观测的低层的功率谱密度与地面雨滴谱观测的数据形状比较一致,但有一定的位移。毫米波雷达反演的雨滴谱与地面观测的谱型和粒子大小也比较一致。这些结果初步验证了毫米波雷达观测的功率谱密度及其反演方法的可靠性。     

毫米波云雷达与探空测云数据对比分析

应用中国气象局大气探测综合试验基地2015年8—12月数据,对Ka波段毫米波云雷达与L波段探空云底高、云顶高及云垂直结构的探测进行对比分析,从分析结果可以看出,毫米波云雷达发射的电磁波能够穿透厚度较大的云层,探测出云垂直结构,所探测的云底高和云顶高与L波段探空结果保持良好的一致性。进一步分析一些云底、云顶高度差异较大的个例,得知与探空气球的漂移造成地域偏差和L波段探空相对湿度探测的误差相关。研究结果表明,Ka波段毫米波云雷达不仅探测能力强,探测精度也较高,是地基云探测的一种有效手段。     

毫米波雷达与无线电探空对云垂直结构探测的一致性分析

在众多种针对云垂直结构的探测中,毫米波雷达可获取云底、云顶、云厚等完整的云垂直结构信息,并可以连续监测云的垂直剖面变化,是有力的探测手段之一。而无线电探空因其直接的测量优势,能直观、确切地描述大气湿度垂直结构,可将其进一步处理生成云垂直结构信息,并作为一种数据源用于与毫米波雷达云垂直结构探测结果进行比对,以评估毫米波雷达针对云宏观垂直结构的探测性能,为毫米波雷达更好地应用于云探测提供参考。通过获取位于北京南郊观象台的毫米波雷达2014年10月28日至2015年2月17日长达113天连续观测的反射率因子以及探空温、压、湿数据,设计或选取合适的方法对二者进行云边界的计算,并进行云高（包括云底高和云顶高）以及云层数的一致性比对分析。结果认为,除对于高层云的云顶高度毫米波雷达由于探测限制不能探测到10 km以上的云顶,某些时刻与探空产生较大差异外,在云底高度以及中低云的云顶高度上可以与探空观测取得很好的匹配效果,对于云的垂直分层上二者也有较强的一致性。该毫米波雷达具有较为准确并连续刻画10 km以下云垂直结构的能力。     

基于毫米波雷达观测及探空反演的云垂直结构对比分析

针对北京南郊观象台的Ka波段毫米波雷达以及L波段探空设备的观测原理和特点,提出了适用于各设备的云垂直结构判定方法,并基于二者2016年12月13日至2017年3月13日长达91 d的时空同步观测数据,结合激光云高仪、葵花8卫星、全天空成像仪等多源辅助数据,对探空与毫米波雷达观测结果（包括云底高、云顶高、云层数等）进行了对比,并对云高偏差的原因进行了分析,结论如下:毫米波雷达与探空判定的云垂直结构普遍具有较好的一致性,统计时段探空观测云顶高度比毫米波雷达平均高422 m,而云底高度则平均偏低350.7 m,导致二者观测云高差异主要包括二者观测原理不同、探空仪湿延迟、气球漂移引起的时空匹配偏差、探空判识云高算法的局限性、降雨时毫米波雷达的衰减等多方面。     

稳定性层状云降雨量的估算研究

利用5 a 711雷达观测的稳定性层状云降雨回波,结合雨滴谱和地面雨量自计资料,使用统计方法,分析了引起稳定性层状云降雨量大小改变的因子,得出稳定性层状云降雨量大小除与雷达回波强度关系最为密切外,还和云顶高度、暖云厚度等因素有关。分析了产生误差的原因,建立了多元回归方程,为利用雷达回波对降雨量的估算提供了一种方法。     

河北冬季一次冷锋降雪云系微物理演变特征综合观测分析研究

利用河北省中南部地区皇寺国家观测站布设的毫米波云雷达、微雨雷达结合飞机等联合观测数据，对2019年2 月14日河北中南部地区一次冷锋降雪云系微物理演变特征进行分析，探讨雷达回波与冰雪晶粒子微结构的关系，以便更好地认识该地区自然降雪的宏微观结构特征。研究结果表明：降雪初生阶段表现为双层云结构，中云云顶高约4100 m，云底高约3600 m，低云云顶高约3100 m，云底高约200 m，中间存在一干层，3000 m以下高度粒子增长以凇附过程为主。降雪发展阶段上下两层云相接，雷达回波强度较强的时段地面降水量也较大，该时段降雪过程主要以凝华〖CD*2〗聚并增长为主。降雪后期回波强度最大值减小，云顶高降低，3000 m以下高度范围内回波强度、多普勒速度、谱宽随高度降低呈增大趋势；飞机观测结果显示，降雪消散阶段逆温层底部由于水云云层较薄，催化潜力较小,冰雪晶粒子主要位于云的中上部，随着高度降低，冰雪晶粒子在下落过程中增大，与雷达观测结果一致，毫米波云雷达和微雨雷达反射率因子随高度变化与降水粒子有效粒径之间相关系数分别为0.89和0.83, 雷达反射率因子主要受冰雪晶等大尺度粒子主导。     

稳定性层状云降雨量的估算研究

利用2000-2004年711雷达观测的稳定性层状云降雨回波资料，结合雨滴谱和地面雨量自记资料，使用统计方法，分析了引起稳定性层状云降雨量大小改变的因子，得出稳定性层状云降雨量大小除与雷达回波强度关系最为密切外，还和云顶高度、暖云厚度等因素有关，分析了产生误差的原因，建立了多元回归方程，为使用雷达回波对降雨量的估算提供了一种方法。     

固态毫米波雷达探测模式的对比评估与分析

利用2014年广东阳江和青藏高原外场观测中多种探测仪器的观测资料,对比了灾害天气国家重点实验室与航天科工23所联合研制的固态毫米波雷达三种探测模式最小可测回波强度、可测液态水(冰水)含量、观测同一目标时回波强度的差异以及与K波段微降水雷达回波强度的差异等。结果表明:(1)毫米波雷达不同模式最小可测回波强度差异与理论差异一致,边界层模式和降水模式能观测近地面全部层云和积云,卷云能观测5km高度冰水含量在0.0007 g·m~(-3)以上的卷云,随着高度上升探测能力有所下降;(2)毫米波雷达使用不同模式观测同一目标时,不同观测模式宏观回波强度一致,大部分差异不超过3.5 dB;(3)K波段微降水雷达和Pasivel2激光雨滴谱仪的近地面回波强度一致,毫米波雷达与K波段微降水雷达存在系统差异。     

毫米波云雷达及探空反演的云垂直结构对比分析

利用2021年9月9日—2022年1月31日泾河国家基本气象站毫米波云雷达（简称云雷达）的反射率因子及L波段探空雷达的温度、相对湿度数据,根据时空匹配方法,对比分析了二者探测和识别云的垂直结构特征（包括云底高度、云顶高度、云层数）的一致性。结果表明：云雷达和探空数据对低、中、高的单层云、双层云及临近降水云的垂直结构的识别结果基本一致;二者对于单层云的云底高度以及双、多层云的云顶高度识别一致性更好,探空识别的云底高度整体略高于云雷达的。引起二者识别云层数不一致的原因：一是因为低层相对湿度较大以及探空识别云算法的敏感性;二是当云体的结构松散时,加上探空漂移作用导致二者识别的云体不一致。在二者识别云层一致的情况下,识别单层云的垂直结构的差异是由于探空仪在低温条件的低敏感以及云雷达对高层薄云的探测能力引起;对于双层和多层云,主要是由于时空匹配方法对于短时间内垂直结构显著变化的云的识别还需要进一步改进。     

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