AMSU-B微波资料反演对流云中冰粒子含量

微波遥感可以穿透云顶直接探测云内的冰粒子分布,NOAA系列卫星微波湿度计(AMSU-B)的3个水汽吸收波段对冰粒子含量的变化有着很好的响应,受冰粒子的强烈散射衰减作用,亮温随冰粒子的增加而降低.因此,可以利用3个水汽通道亮温变化判断云中冰粒子的含量.根据模拟实验结果,确定了对流云状态下各水汽通道对冰粒子的响应高度,冰粒...     

利用AMSU-B和GOES-9卫星资料对热带气旋“蒲公英”的分析

利用NOAA-16/AMSU-B三水汽通道微波亮温差和GOES-9红外亮温阈值对热带气旋深厚对流云进行检测,同时利用GOES-9可见光、红外、水汽多光谱通道特征对热带气旋云系进行识别,通过一次台风“蒲公英”个例,对热带气旋在微波和光学遥感图像上的深厚对流云进行分析。结果表明,微波和光学遥感资料均能对热带气旋深厚对流云进行有效识别,检测结果基本一致,但识别出的对流云,微波范围较小,光学遥感范围较大,这可能是由于光学遥感仅能获得云顶信息,将对流云顶部覆盖的卷云错判造成的;即使采用较低亮温阈值,光学遥感也很难将这部分卷云完全分离,而微波对云更具穿透性,在深厚对流云的识别方面具有独特优势;三水汽通道间微波亮温差反映了深厚对流云的发展强度,可间接揭示热带气旋的发展情况。     

一次极端短时强降水过程中FY-3微波湿度计观测特征分析

利用FY-3微波湿度计资料和常规观测资料,对2016年贵州至湖北一次强降水事件中极端短时强降水站点、一般性短时强降水站点上空对流云的微波观测特征进行了对比分析。结果表明:(1)极端短时强降水站点上空150 GHz附近窗区探测通道亮温低于一般性短时降水站点。(2)极端短时强降水站点上空水汽通道亮温垂直分布呈现漏斗状,对干侵入有一定指示作用,亮温最低值出现在183.31±7 GHz附近,主要为暖云降水;一般性短时强降水站点上空水汽通道亮温垂直分布则呈竖条形,亮温最低值出现在183.31±3 GHz和183.31±7 GHz探测通道附近,为冷云暖云混合降水。(3)极端短时强降水站点上空未出现冲顶对流,但低层对流发展旺盛;一般性短时强降水站点上空出现冲顶对流,但低层对流发展强度偏弱。     

一次锋面气旋云系中强对流云团的识别

利用NOAA-16/AMSU-B微波亮温资料和GOES-9光学遥感资料对2004年6月16日一次锋面气旋云系中的强对流云团进行识别, 尝试了NOAA-16/AM SU-B微波两窗区通道亮温、3个微波水汽通道间亮温差, GOES-9红外亮温阈值、水汽和红外通道亮温差、红外和水汽通道亮温多光谱逐个修改聚类等方法, 通过比较各种方法的识别结果, 分析各种识别技术的特点, 同时采用地面常规观测资料进行叠加, 对识别方法进行了验证。结果表明:微波对强对流云团均能较好识别, 但89 GHz通道亮温受地表影响较大, 不能很好剔除过冷水体, 150 GHz通道亮温与微波水汽通道间亮温差的识别结果较一致, 3个微波水汽通道间亮温差对阈值的依赖性相对较小; GOES-9红外亮温阈值因其随时空变化对识别结果会造成较大差别, 而水汽和红外通道亮温差对强对流云团能进行较好定位, 但识别范围较小, 多光谱逐个修改聚类方法对积雨云的识别效果较好, 且和NOAA-16/AMSU-B识别结果有较好的对应关系; 地面常规观测资料的叠加结果也说明, 多波段遥感资料对强对流云团的识别结果与当时的天气现象及积雨云状均有较好的对应关系。     

FY3极轨卫星资料在暴雨短时预报中的应用分析

利用常规观测、地面加密自动站降水资料以及FY3B极轨卫星资料,对2014年5月18日广西一次暴雨过程中暴雨云团的微波湿度计特征进行分析,得出以下结论:(1)广西中东部处受高空槽前西南气流影响,中低层水汽条件较好,低层有切变辐合,为中尺度对流系统的发生、发展提供了有利背景。(2)250m分辨率可见光通道云图上对流发展旺盛的云团有明显不均匀纹理结构,其中镶嵌着多个圆形的暗影,预示着云中伴有强降雨、雷暴大风等灾害性天气。(3)微波湿度计资料反映出暴雨云团从低层到中高层都有较高的水汽含量,50mm以上的强降雨区主要位于3个亮温低值中心的过渡区域,即对流云团合并处。高低层通道亮温差能反映云团对流的强弱程度,强降雨发生在微波亮温差的正值区,通道3与通道5的亮温差对6h强降雨落区有较好的指示意义。     

“5·6”四川盆地对流云团特征及触发机制

利用FY-2卫星资料、NCEP再分析资料和常规观测资料,分析研究了2016年5月6日四川盆地暴雨对流云团的特征及其形成机制。结果表明:四川盆地对流云团易发生在青藏高原东侧边坡陡峭地形带,初生对流云团的云顶亮温低于-45℃,边缘最大温度梯度为15~20℃,水汽-红外通道亮温差值介于-5~0℃,分裂窗-红外亮温差值介于0~2℃。强降水出现在红外和水汽亮温快速下降到最低值、水汽-红外通道差值达0℃附近、分裂窗-红外亮温差为正值和温度梯度达0℃后的几小时内,最大雨强出现在强对流云团成熟后开始迅速减弱的初始阶段(即云顶亮温开始回升的阶段)。较大范围的强降水由发展成熟的云顶最低亮温约为-70℃的对流云团产生,主要出现在红外亮温低于-50℃的区域,集中在红外亮温-65℃~-60℃、水汽亮温为-65℃~-60℃的云顶较为平滑的次低值中心区域内,并不与云顶最低亮温中心相吻合。机制分析表明,对流云团生成区域均受偏东风影响,且形成于高的对流不稳定能量条件下,发展于高湿区,近地层冷空气扩散南下与气旋式流场中的辐合共同触发对流在辐合线以北生成,而中层垂直风切变的加强、中低层暖平流和高层冷平流的发展促使对流云团发展旺盛。     

对流性降水云微波辐射特性

结合MM5模式和三维微波辐射传输模式, 对2003年7月9日宜昌地区一次典型的中尺度降水中心的对流性降水云微波辐射特性进行研究。结果表明:MM5模式模拟的降水量和落区与实况一致,模拟的水凝物廓线也与TMI反演值接近,85.5 GHz通道辐射亮温与TMI实测情况相近。85.5 GHz通道亮温与地面雨强相关性很弱, 受云中云冰和雪花的散射降温作用显著, 由于其他粒子的综合作用以及斜角观测造成的位置偏移, 霰粒子对该通道亮温散射作用不明显。19.35 GHz通道亮温随雨强增加先升温后降温; 与霰粒子含量表现出明显的负相关关系。37.0 GHz通道亮温随雨强的增加而降温, 雨强大于20 mm/h后达到饱和, 主要受雨水降温作用影响。倾斜观测比天顶垂直观测产生更低的亮温低值中心, 且频率越高, 低值中心的偏移越严重。     

利用TRMM卫星资料对青藏高原地区强对流天气特征分析

利用热带测雨卫星TRMM(Tropical Rainfall Measure Mission)多种探测结果,结合NCEP再分析资料,研究了发生在青藏高原地区的一次强对流天气特征,综合分析了高原地区对流云特殊的水平、垂直结构特征。结果表明:(1)该强对流降水系统由几个孤立、零散的块状降水云团组成,以深厚弱对流降水为主,微波亮温的低值区也呈孤立、零散的块状分布,并且整个对流系统的云顶高度一致偏高,深厚强对流降水的雨谱主要集中在1～20mm.h-1的范围内,90%以上的深厚弱对流降水样本数和降水量都集中在0～5mm.h-1范围内,在垂直方向上呈被"挤压"状态。除云冰粒子集中在6～18km高度外,可降冰、可降水和云水粒子都集中在低层8km以下,冰雹天气表现为可降冰粒子在低层含量偏高。(2)高原地区强对流天气的特征与其他地方的不同,表现为雨强较小,比平原地区明显偏弱,且对流云降雨样本在不同降雨率范围内分布不均匀,降水云团雨顶高度也远低于平原地区的对流云,地表降水率大值区与微波辐射亮温低值区呈不完全对称分布,潜热释放呈单峰型。(3)高原地区强对流系统发生时,垂直上升运动在400hPa达到最大,水汽主要集中在400hPa高度以下的范围内。     

青海高原短时强降水天气的葵花-8卫星监测预警特征对比分析

为获得青海高原（以下简称高原）对流云团的强降水监测预警特征和预警方法,使用葵花-8卫星数据跟踪识别高原典型强降水天气过程的对流云团,计算并分析具有提前预警意义的云团特征参数。结果表明：（1）本文提出的对流云团识别的改进多通道法,经与传统多通道法对比检验,证明所得云团更接近对流主体,该方法适用于高原对流云团识别。（2）对流形成到成熟阶段,特征参数起伏变化,但红外与水汽通道亮温差（DTB13）和云顶亮温（Tmin）整体下降,云顶亮温梯度（GTmax）整体上升;在对流发展阶段仅红外1和2通道亮温差（DTB12）平均可达预警极值,在成熟阶段则是Tmin、DTB13、GTmax、深对流指数（DCI）等平均可达预警极值。高原上强降水天气的对流云多发展成深对流,降水发生在云团特征参数极值附近,短时强降水发生在深对流云区内特定云顶（上冲云顶或近似上冲云顶）所在特征参数极值区内或边缘附近。（3）特征参数极值对一般降水和强降水的开始时间分别提前0～1 h和0.5～4.5 h出现,在西风型流场下对强降水开始的提前时间相对较长。降水开始前,副高型流场下对流云团向深对流发展变化最剧烈,表现为DCI和GTmax平...     

西南低涡对流云团及其降水的一些特征

基于FY-2C静止卫星红外和水汽通道资料,简单分析了发生在四川盆地的西南低涡暴雨云团生消过程,给出了一些有意义的云团生命特征。同时,结合相应的地面自动站降水资料,详细分析了卫星红外和水汽通道云顶亮温与对流云团降水之间的关系特征,结果表明:对于一完整对流降水过程,1小时内最低水汽亮温和水汽亮温增量能很好地描述地面1小时累计降水特征。然而,用静止卫星红外或水汽通道亮温来表征的云团降水特征是非常复杂的。尽管具有相同的最低云顶红外或水汽亮温,但对不同的对流过程其总体降水量级趋势不一样。而且,对于同一对流过程的不同发展阶段,即使出现云顶红外或水汽亮温一样,但其地面降水特征也是不一致的。甚至是对于同一时刻具有相同最低红外或最低水汽亮温特征的云,其降水落区与量级都不尽相同。正是这些复杂的降水特征,使得西南低涡对流云团的降水估算具有很大的难度。      

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.     

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     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;