冰雹云卫星早期识别与自动预警

利用陕西、山东、贵州和新疆等地近十年日间降雹记录和对应的极轨卫星数据,采用卫星云微物理反演技术,定量分析冰雹云微物理特征,比较不同地区间差异,并利用FY-4A静止卫星定量分析一次冰雹过程云微物理特征演变,探讨冰雹云卫星识别预警应用潜力。结果表明:（1）陕西、山东等地冰雹云微物理特征具有一致性,卫星早期识别指标为:晶化温度（T_g）较冷,均值为?33°C;全部冰晶化时T_g对应的云粒子有效半径r_e（表征为r_eg）未饱和（<40 μm）,均值36.9 μm,且r_eg 越小冰雹云越强;云顶呈现r_e随高度减小带。（2）各地冰雹云早期识别指标在数值上存在一定差异,实际应用时应针对各地进行相应调整。（3）在静止卫星上,冰雹云微物理特征与极轨卫星相一致,将早期识别指标应用于FY-4A静止卫星,跟踪云团发展演变,实现自动预警。（4）经过4次降雹过程中应用,FY-4A卫星自动预警与实况吻合22次,漏报2次,自动预警平均提前约2小时。FY-4A卫星自动预警对及时有效组织实施人工防雹作业具有重要现实意义。     

Macro- and Micro-physical Characteristics of Different Parts of Mixed Convective-stratiform Clouds and Differences in Their Responses to Seeding

This study investigates the cloud macro- and micro-physical characteristics in the convective and stratiform regions and their different responses to the seeding for mixed convective-stratiform clouds that occurred in Shandong province on 21 May 2018, based on the observations from the aircraft, the Suomi National Polar-Orbiting Partnership (NPP) satellite, and the high-resolution Himawari-8 (H8) satellite. The aircraft observations show that convection was deeper and radar echoes were significantly enhanced with higher tops in response to seeding in the convective region. This is linked with the conversion of supercooled liquid droplets to ice crystals with released latent heat, resulting in strengthened updrafts, enhanced radar echoes, higher cloud tops, and more and larger precipitation particles. In contrast, in the stratiform cloud region, after the Silver Iodide (AgI) seeding, the radar echoes become significantly weaker at heights close to the seeding layer, with the echo tops lowered by 1.4–1.7 km. In addition, a hollow structure appears at the height of 6.2–7.8 km with a depth of about 1.6 km and a diameter of about 5.5 km, and features such as icing seeding tracks appear. These suggest that the transformation between droplets and ice particles was accelerated by the seeding in the stratiform part. The NPP and H8 satellites also show that convective activity was stronger in the convective region after seeding; while in the stratiform region, a cloud seeding track with a width of 1–3 km appears 10 km downstream of the seeding layer 15 minutes after the AgI seeding, which moves along the wind direction as width increases.     

基于卫星资料的大连地区强对流天气闪电活动特征

利用FY-4卫星云顶亮温（Cloud Top Temperature,CTT）资料和雷达回波资料,分析了2019年6-9月大连地区的闪电活动特征,重点分析了该地区2019年9月4日的一次强对流天气闪电活动特征与雷达回波及CTT之间的相关性。结果表明：此次过程雷暴起始于大连东南方向。在雷暴初始阶段,以云闪为主,云闪高度主要集中在7-12 km。闪电活动主要集中在雷达回波强度>30 dBz的区域,对应的云顶高度超过了8 km。闪电活动与FY-4卫星CTT之间存在较好的相关性,闪电主要发生在CTT为240-250 K左右区域。对2019年5-8月大连地区雷达与闪电活动进行量化分析,发现闪电活动主要集中于雷达组合反射率39.38 dBz附近区域,对应的云顶高度为8.21 km。     

基于A-Train综合资料的云顶高度反演研究

提出一种适用性较强的云顶高度反演方法。利用2007年低纬地区(15°S~15°N)的A-Train综合资料反演云顶高度。首先以M0DIS通道31和通道32的亮温值为特征参数,基于SVM分类法,将云分为不透明云、半透明云和透明云三类,分类准确率达到90.6%。然后对三类云分别用核回归法反演云顶高度,将其与CloudSat的2B-GEOPROF-LIDAR产品对比,均方根误差分别为0.95、1.17和1.27 km。与未分类的核回归法结果相比,分类后三种云的反演误差都有所减小。最后分析了三个典型个例。该方法可推广至其他含有红外分裂窗通道的卫星上,发挥更多卫星资源的效用。     

基于2014～～2017年Ka毫米波雷达数据分析北京地区云宏观分布特征

本文利用2014年1月至2017年12月Ka毫米波雷达数据对北京地区云宏观特征进行统计分析。云出现率方面，4年平均值约36.3%；冬季最低，夏季最大；月出现率值9月最大，12月最小；出现率日变化有季节差异，春夏两季呈现中午（11:00，北京时间，下同）开始逐步升高至下午17:00后逐步下降的特点，增高幅度大于15%；冬、秋两季日变化特征不显著。高度方面，4年平均云底高约4.9 km，平均云顶高约7.2 km；云顶高和云底高的月变化特征明显，从年初1月开始逐步上升，在6月达到峰值，而后下降到12月达到低值；3～10月，高云（云底高>5 km)占约一半左右比例；厚度小于1 km的云在各月中所占比例最高；厚度1～4 km的云，厚度越大所占比例越低；特别地，厚度大于4 km的云所占比例在4～9月中仅次于厚度小于1 km云的比例。4年期间，北京地区单层云居多约占66.7%，两层云占比约25.2%，两层以上云占8.1%；冬季约80%的云为单层云，而6～9月云层分布变化最多，其中9月单层云比例最低约为40%。本文基于4年高时空分辨率雷达数据对北京地区云分布特征，特别是云垂直分布特征在数值上准确刻画，该项工作在已有云气候研究中尚未见开展，所获得的知识将对了解地区气候特征、区域模式云参数化选择提供参考。     

Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series

Fengyun-4A (FY-4A), the first of the Chinese next-generation geostationary meteorological satellites, launched in 2016, offers several advances over the FY-2: more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group (AWG). Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager (AHI), and sounder data, obtained from the Atmospheric InfraRed Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters. Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.     

Verification and Correction of Cloud Base and Top Height Retrievals from Ka–band Cloud Radar in Boseong,Korea

In this study,cloud base height(CBH) and cloud top height(CTH) observed by the Ka-band(33.44 GHz) cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013(September-November) were verified and corrected.For comparative verification,CBH and CTH were obtained using a ceilometer(CL51) and the Communication,Ocean and Meteorological Satellite(COMS).During rainfall,the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops,and this difference increased with rainfall intensity.During dry periods,however,the CBH and CTH observed by the cloud radar,ceilometer,and COMS were similar.Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS.In cases of rainfall or missing cloud radar data,the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data.These corrected cloud data were used to classify cloud types,which revealed that low clouds occurred most frequently.     

“21·7”河南暴雨环境场及云的宏微观特征

利用FY-4A静止气象卫星、FY-3D极轨气象卫星资料和ERA5再分析资料,深入分析“21·7”河南暴雨环境场及云宏微观特征,首次利用FY-4A观测研究此次事件对流云微物理特征。结果表明:“21·7”河南暴雨是一次极端强降水事件,河南省位于大陆高压和副热带高压之间的鞍型场内,有利于其上空低涡云系的发展和维持。2021年7月20日两股水汽输送交汇于河南中北部,为郑州极端降水提供了有利条件。20日14:00—16:00(北京时,下同)郑州长时间位于对流云团冷云区边界亮温梯度大值区,该时段对流发展旺盛;12:00—14:00云光学厚度跃增,且在15:00仍维持较大值,表明该时段云中液态粒子大量合并,液态水含量丰富,光学厚度峰值出现时间先于降水量峰值出现时间,FY-4A云光学厚度跃增且维持较大值对强降水出现时间及量级有重要的预警意义。对流云粒子有效半径(r_e)随温度(T)的增长曲线(T-r_e关系)表明:20日16:00河南上空的雨胚形成区最为深厚,云中不同高度的r_e整体维持在20～25μm,表明云中上升气流较强,有利于地面强降水...     

利用FY-4A卫星反演产品对飞机增雨作业的分析

本文利用FY-4A卫星反演的云降水微物理特征参数,分析了2018年10月8日的一次飞机增雨前层状云的微物理结构和特征参数变化,得到四川盆地秋季层状云增雨潜力区的分布,结果表明:①此次作业过程,四川盆地大部分地区覆盖中低云,局部有高云,中低云含有丰富的过冷水,云底粒子较小10～15μm,主要通过凝结过程增长;②此次作业过程,云系随时间的演变特征为从中午到傍晚,云层加厚,云顶升高,粒子有效半径增长,有大片过冷水区,但是缺乏大滴和冰晶,降水不充分;③在无高云配置下,中低云区产生的地面降水较小,而有高低云共同配置和粒子有效半径较大的地区,降水更为充沛;④利用统计检验中的区域对比分析、双比分析和区域历史回归分析方法对本次飞机增雨进行分析后表明,对具有丰富过冷水区的中低云进行人工引晶后,绝对增雨量分别为1.81mm (对比分析)、1.26mm (双比分析)、1.69mm (区域历史回归分析)。利用FY-4A卫星反演方法能够提供云和降水高时空分辨率的物理特征参数演变,丰富了云和降水宏微观物理信息,为人工增雨判别增雨潜力区和准确把握增雨时机提供了一种新的方法。      

Himawari-8气溶胶光学厚度产品的验证分析

Himawari-8是由日本气象局发射的新一代静止气象卫星，其搭载的传感器AHI（Advanced Himawari Imager）可实现10 min/次的高时间分辨率对地观测。本文将2015年9月至2017年12月Himawari-8卫星Level-2气溶胶光学厚度（AOD）产品与AERONET（AErosol RObotic NETwork）70个站点的地基观测数据进行对比验证分析，结果表明Himawari-8卫星反演的气溶胶光学厚度产品的精度存在很大的空间上的差异性，其中有48个站点Himawari-8 AOD与AERONET AOD之间存在较好的相关性（R>0.5），有22个站点Himawari-8卫星反演气溶胶光学厚度产品存在明显的低估现象。在American_Samoa、Bandung、Birdsville、Bukit_Kototabang、Canberra、Fowlers_Gap、Jabiru以及QOMS_CAS等站点出现地基观测值很小而卫星反演的气溶胶光学厚度较大的情况。对绝对误差（Himawari-8 AOD与AERONET AOD的差）进行分析发现Himawari-8 AOD存在低估现象时绝对误差与AERONET AOD之间存在较好的相关性；在地基观测值很小而Himawari-8卫星反演AOD较大的地区绝对误差与Himawari-8 AOD之间存在较好的线性关系，这为Himawari-8 AOD反演算法的改进与完善提供了有用的研究发现。     

Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies

In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.     

Observational Characteristics of Cloud Vertical Profiles over the Continent of East Asia from the CloudSat Data

The CloudSat satellite data from June 2006 to April 2011 are used to investigate the characteristics of cloud vertical profiles over East Asia(20°-50°N,80°-120°E),with particular emphasis on the profiles of precipitative clouds in comparison with those of nonprecipitative clouds,as well as the seasonal variations of these profiles.There are some obvious differences between the precipitative and nonprecipitative cloud profiles.Generally,precipitative clouds mainly locate below 8 km with radar reflectivity in the range of-20 to 15 dBZ and maximum values appearing within 2-4-km height,and the clouds usually reach the ground;while nonprecipitative clouds locate in the layers of 4-12 km with radar reflectivity between-28 and 0 dBZ and maximum values within 8-10-km height.There are also some differences among the liquid precipitative,solid precipitative,and possible drizzle precipitative cloud profiles.In precipitative clouds,radar reflectivity increases rapidly from 11 to 7 km in vertical,implying that condensation and collision-coalescence processes play a crucial role in the formation of large-size drops.The frequency distribution of temperature at-15℃ is consistent with the highest frequency of radar reflectivity in solid precipitative clouds,which suggests that the temperatures near-15℃ are conductive to deposition and accretion processes.The vertical profiles of liquid precipitative clouds show almost the same distributions in spring,summer,and autumn but with differences in winter at mainly lower levels.In contrast,the vertical profiles of solid precipitative clouds change from spring to winter with an alternate double and single high-frequency core,which is consistent with variations of the frequency distribution of temperature at-15℃.The vertical profiles of nonprecipitative clouds show a little change with season.The observations also show that the precipitation events over East Asia are mostly related to deep convective clouds and nimbostratus clouds.These results are expected to be useful for evaluation of weather and climate models and for improvement of microphysical parameterizations in numerical models.     

青藏高原那曲地区一次深对流云垂直结构的多源卫星和地基雷达观测对比分析

为了加强对青藏高原深对流云垂直结构的深入认识,利用TRMM、CloudSat和Aqua多源卫星观测资料及地基垂直指向雷达（C波段调频连续波雷达和KA波段毫米波云雷达）资料,对第三次青藏高原大气科学试验期间2014年7月9日13-16时（北京时）发生在那曲气象站附近的深厚强对流云和那曲气象站以西100 km左右的深厚弱对流云的垂直结构特征进行了分析,得到的结果如下:（1）深厚强对流云和深厚弱对流云的水平尺度均较小（10-20 km）,垂直发展高度较高（15-16 km,均指海拔高度）;深厚强对流云在0℃层以下雷达反射率因子递增非常快,表明对流云内固态降水粒子下落至0℃层以下后融化过程有很重要的作用;在对流减弱阶段有明显的0℃层亮带出现,亮带位于5.5 km左右（距地1 km）;（2）对比TRMM测雨雷达和C波段调频连续波雷达观测到的雷达反射率因子,发现TRMM测雨雷达在11 km以下存在高估;（3）深对流云主要为冰相云,云内10 km以上主要是丰富小冰粒子,而10 km以下是较少的大冰晶粒子;深厚强对流云和深厚弱对流云的微物理过程都主要包括混合相过程和冰化过程,混合相过程分为两种:一种是-25℃（深厚强对流云）或-29℃（深厚弱对流云）高度以下以凇附增长为主,另一种是该高度以上主要以冰晶聚合、凝华增长为主,该过程冰晶粒子有效半径增长较快。这些空基和地基的观测证据进一步揭示了青藏高原深对流云的垂直结构特征,为模式模拟青藏高原深对流云的检验提供了依据。      

Comparison of cloud-top height retrievals from ground-based 35 GHz MMCR and GMS-5 satellite observations at ARM TWP Manus site

Retrievals of cloud-top heights from the ARM 35 GHz Millimeter Wave Cloud Radar (MMCR) located on Manus Island are compared to those from the GMS-5 satellite as a means to evaluate the accuracy of both MMCR and GMS-5 retrievals, as well as to ascertain their limitations. Comparisons are carried out for retrievals of both single-layer and multilayer clouds as seen by radar, but only for satellite-detected clouds with 100% amount within a 0.3×0.3° domain centered at the ARM site of one cloud type (i.e., low, middle, or high). Mean differences, with 95% confidence limits, between radar- and satellite-retrieved cloud-top heights (i.e., radar-retrieved cloud-top heights−satellite-retrieved cloud-top heights) are 0.3±0.3 km for single-layer clouds and −0.7±0.3 km for multilayer clouds. The study reveals that for thick clouds (i.e., cloud base ≤1 km and cloud thickness ≥10 km), which are representative of convective towers with no/light precipitation as well as thick anvil clouds, retrievals from the MMCR agree well with those from satellite with mean differences of 0.0±0.4 and −0.2±0.3 km for single-layer and multilayer clouds, respectively. For clouds of lesser thickness, mean cloud-top heights derived from satellite are lower than those derived from radar by as much as 2.0 km. It is also shown that for convective clouds with heavy precipitation, MMCR retrievals underestimate the cloud-top heights significantly.     

2014年青藏高原云和降水多种雷达综合观测试验及云特征初步分析结果

加密外场试验可提供云降水物理过程新的数据。2014年7月1日—8月31日,第3次青藏高原大气科学试验项目组在那曲开展了水汽、云和降水的综合观测,使用了中国最先进的Ka波段毫米波云雷达、Ku波段微降水雷达、C波段连续波雷达和激光雷达,并配以微波辐射计、雨滴谱仪等设备,获取了高时空分辨率的云和降水宏微观垂直结构特征数据;利用C波段双线偏振雷达与新一代天气雷达配对,进行双多普勒雷达观测,获取青藏高原对流云三维风场和降水粒子相态的结构和演变数据。文中简单介绍了本次试验的情况,并利用这次观测的云雷达数据对那曲地区夏季云的云顶和云底高度、云厚、云量、云层数等特征的日变化进行了初步统计分析,对不同类型云的宏观特征进行了讨论。结果表明:本次外场试验首次成功获取到了多种雷达的云观测数据。那曲地区夏季云主要集中在6 km(距地面高度,下同)以上和4 km以下;总云量、高云的云顶、云量和云厚等云的统计参数有明显的日变化,10时(北京时)为云发展最弱的时段,20时云发展最为旺盛;初生的积云和层云常常出现在3 km高度上,这一高度上常常存在明显的上升气流;深对流系统高度可达16.5 km,同时存在上升气流和下沉气流,对流中可能存在过冷水。这些数据和初步结果为进一步开展高原云和降水机理、云和降水物理过程参数化方案研究及卫星反演结果的订正提供了基础。     

A Comparison of Cloud Layers from Ground and Satellite Active Remote Sensing at the Southern Great Plains ARM Site

Using the data collected over the Southern Great Plains ARM site from 2006 to 2010, the surface Active Remote Sensing of Cloud(ARSCL) and Cloud Sat-CALIPSO satellite(CC) retrievals of total cloud and six specified cloud types [low, mid–low(ML), high–mid–low(HML), mid, high–mid(HM) and high] were compared in terms of cloud fraction(CF), cloud-base height(CBH), cloud-top height(CTH) and cloud thickness(CT), on different temporal scales, to identify their respective advantages and limitations. Good agreement between the two methods was exhibited in the total CF. However, large discrepancies were found between the cloud distributions of the two methods at a high(240-m) vertical grid spacing. Compared to the satellites, ARSCL retrievals detected more boundary layer clouds, while they underestimated high clouds. In terms of the six specific cloud types, more low- and mid-level clouds but less HML- and high-level clouds were detected by ARSCL than by CC. In contrast, the ARSCL retrievals of ML- and HM-level clouds agreed more closely with the estimations from the CC product. Lower CBHs tended to be reported by the surface data for low-, ML- and HML-level clouds; however, higher CTHs were often recorded by the satellite product for HML-, HM- and high-level clouds. The mean CTs for low- and ML-level cloud were similar between the two products; however, the mean CTs for HML-, mid-, HM- and high-level clouds from ARSCL were smaller than those from CC.     

一次典型降水层状云的结构特征和增雨潜势分析

利用FY-2C卫星资料、雷达资料和逐时降水资料及NCAR/NCEP(1°×1°)再分析资料,对2005年9月24-25日河南省出现的层状云降水过程进行了分析。结果表明:影响降水过程的是低槽—切变云系,切变线云系为暖云云系,结构较均匀,低槽云系主体为冷云,云顶亮温不均匀,有低亮温带结构,当东移的低槽云系与北抬的切变线云系叠加后,叠加区上有中小尺度云团活动,促使降水加强。强降水出现在700 hPa、850 hPa切变线之间及500 hPa低槽前部,并与云顶亮温的发展变化趋势表现出相似性;500 hPa槽前、700 hPa切变线北侧的降水,雨强与亮温值的对应关系不确定。这主要是由于低槽云系和切变线云系的叠加部位不仅具有深厚的湿层,而且具有较强的动力抬升和水汽辐合条件;切变线北侧处于低空辐散区且水汽条件较差,自然降水产生的条件不是很好。最后借助于FY-2C卫星资料反演的云物理参数,对低槽—切变云系的增雨潜势进行了简要分析,认为低槽—切变云系上云顶温度较高的部位符合“播云窗”概念,具有很好的增雨潜势,切变线北侧的低槽云系由于云顶温度低、低空水汽不充分,“播撒—供应”机制不能很好地建立,其增雨潜势条件也弱。     

DETECTION OF MULTILAYER CIRRUS CLOUD USING FY-1C DATA

There are ten channels in the FY-1C polar-orbiting meteorological satellite of China.Thesechannels cover visible,near-infrared and infrared spectral bands.Based on simulating analysis ofsingle layer and multilayer clouds that cirrus clouds possibly overlap low water clouds,the casestudy using FY-1C data is performed.Results show that FY-1C data can be used to analyzemultilayer clouds,especially for the ease of low water cloud overlaid by cirrus.     

DETECTION OF MULTILAYER CIRRUS CLOUD USING FY-1C DATA*

There are ten channels in the FY-1C polar-orbiting meteorological satellite of China.These channels cover visible,near-infrared and infrared spectral bands.Based on simulating analysis of single layer and multilayer clouds that cirrus clouds possibly overlap low water clouds,the case study using FY-1C data is performed.Results show that FY-1C data can be used to analyze multilayer clouds,especially for the ease of low water cloud overlaid by cirrus.     

半透明云风矢量高度算法中云下背景辐射的估计

半透明云风矢量高度指定是卫星风矢量算法的重要部分,需要来自半透明云体的辐射和云下背景辐射两个变量。云下背景辐射发生在云层下面,未被卫星直接观测到,为了在半透明云风矢量高度指定算法中更精确地获得云下背景辐射,使用风矢量附近无云区的红外/水汽散点图,估计云下背景辐射。分析表明:在追踪区域里存在无云区的情况下,追踪区的最高红外亮温可代表红外通道的背景辐射;而水汽通道的背景辐射,却在红外亮温高值区段内水汽亮温相对较低区段。追踪区内找不到无云区时应扩大搜索范围,找到无云区后可估计云下背景辐射。在半透明云风矢量高度指定算法中使用云下背景辐射估计的改进算法前后,计算FY-2气象卫星进行风矢量,并将结果与欧洲中期天气预报中心（ECMWF）分析场进行对比表明,在半透明风矢量高度指定算法中使用云下背景辐射估计,FY-2气象卫星风矢量误差明显降低。