Preliminary Retrieval of Aerosol Optical Depth from All-sky Images

The relationship between the radiance ratio (radiance at wavelength 450 nm to 650 nm) and aerosol optical depth (AOD) is analyzed in this paper by numerical simulation and a "LUT" (look-up table) approach is then presented for the retrieval of AOD from the radiance ratio. In this LUT approach, the AOD retrieval error depends mainly on the assumption of aerosol types. From the preliminary simulation, a typical error of 15%–20% in AOD obtained from the radiance ratio is estimated, due to neglecting changes in...     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.     

晴空与有云大气辐射分布的数值模拟及其对全天空图像云识别的应用

全天空图像自动云识别的研究相对来说是一项较新的研究领域。当前国际上较为通用的全天空图像云识别方法主要依靠图像蓝红灰度值对比的阈值方法进行判断。然而非洁净大气中气溶胶的增多给云识别增加了难度,同时太阳高度角不同天空色度分布情况也不同。文中利用Libradtran辐射传输模式,计算了不同能见度不同太阳高度角情况下3个典型波长(450,550,650nm;蓝/绿/红)无云及有云大气的天空辐亮度分布情况,并进行了比较分析。结果表明,相同太阳高度角情况下,无云及有云大气中蓝红比值随能见度的下降呈单调下降趋势。在特定的云光学厚度和能见度情况下,天空色度彼此呈现出类似的分布状况。全天空图像阈值判断云识别自适应算法的建立需要与太阳高度角、地面能见度联系起来。当前尚无法建立一个判断阈值随太阳高度角以及能见度变化的函数关系式。较为可行的办法是建立典型能见度、典型太阳高度角情况下的辐射信息库,在具体云识别时,首先确定太阳高度角,而后根据天空辐射比情况确定天空能见度,并利用辐射信息标准库做云或非云判别。该工作为全天空云识别算法提供判别依据,同时建立云识别随能见度和太阳高度角变化的判别信息库。     

Cloud Classification and Distribution of Cloud Types in Beijing Using Ka-Band Radar Data

A cloud clustering and classification algorithm is developed for a ground-based Ka-band radar system in the vertically pointing mode. Cloud profiles are grouped based on the combination of a time–height clustering method and the k-means clustering method. The cloud classification algorithm, developed using a fuzzy logic method, uses nine physical parameters to classify clouds into nine types: cirrostratus, cirrocumulus, altocumulus, altostratus, stratus, stratocumulus, nimbostratus,cumulus or cumulonimbus. The performance of the clustering and classification algorithm is presented by comparison with all-sky images taken from January to June 2014. Overall, 92% of the cloud profiles are clustered successfully and the agreement in classification between the radar system and the all-sky imager is 87%. The distribution of cloud types in Beijing from January 2014 to December 2017 is studied based on the clustering and classification algorithm. The statistics show that cirrostratus clouds have the highest occurrence frequency(24%) among the nine cloud types. High-level clouds have the maximum occurrence frequency and low-level clouds the minimum occurrence frequency.     

Improving the Analyses and Forecasts of a Tropical Squall Line Using Upper Tropospheric Infrared Satellite Observations

The advent of modern geostationary satellite infrared radiance observations has noticeably improved numerical weather forecasts and analyses.However,compared to midlatitude weather systems and tropical cyclones,research into using infrared radiance observations for numerically predicting and analyzing tropical mesoscale convective systems remain mostly fallow.Since tropical mesoscale convective systems play a crucial role in regional and global weather,this deficit should be addressed.This study is the first of its kind to examine the potential impacts of assimilating all-sky upper tropospheric infrared radiance observations on the prediction of a tropical squall line.Even though these all-sky infrared radiance observations are not directly affected by lower-tropospheric winds,the high-frequency assimilation of these all-sky infrared radiance observations improved the analyses of the tropical squall line’s outflow position.Aside from that,the assimilation of all-sky infrared radiance observations improved the analyses and prediction of the squall line’s cloud field.Finally,reducing the frequency of assimilating these all-sky infrared radiance observations weakened these improvements to the analyzed outflow position,as well as the analyses and predictions of cloud fields.     

物理-统计反演和云-晴空辐射特征差异检测结合的全天空高云判别能力改进算法与初步试验

在全天空红外-可见光云像观测反演方法基础上,针对已往阈值法判断高云的局限性,提出改进的算法。对可见光图像可利用以太阳-天顶为连线的主平面两边相元特性的对称性来判断云的存在,对红外成像仪可利用同一仰角扫描时所得不同方位角亮温分布的非均匀性来判断云的存在。以北京2011年1 3月观测资料为基础,选择原阈值法未能判别出来的案例进行再处理,全天空可见光成像观测仪高云判别能力最高可达73.9%,全天空扫描式红外成像仪可达70.1%。该工作为天空的高云识别提供新的复合算法。     

Assimilation of All-sky Geostationary Satellite Infrared Radiances for Convection-Permitting Initialization and Prediction of Hurricane Joaquin (2015)

Intensity forecasting is one of the most challenging aspects of tropical cyclone (TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin (2015) with an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin (2015)’s intensity, this study examines the potential in improving Joaquin’s prediction when assimilating all-sky infrared radiances from GOES-13’s water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin’s intensity, including its rapid intensification (RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane’s RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.     

A modified Becker’s split-window approach for retrieving land surface temperature from AVHRR and VIRR

In order to provide a long time-series,high spatial resolution,and high accuracy dataset of land surface temperature(LST) for climatic change research,a modified Becker and Li’s split-window approach is proposed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer(AVHRR) onboard National Oceanic and Atmospheric Administration(NOAA)-7 to-18 and the Visible and InfraRed Radiometer(VIRR) onboard FY-3A.For this purpose,the Moderate Resolution Transmittance Model(MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere(TOA) under a variety of surface and atmosphere conditions.Then,a temperature dataset consists of boundary temperature T s(which is one of the input parameters to MODTRAN),and channels 4 and 5 brightness temperatures(T 4 and T 5) were constructed.Note that channels 4 and 5 brightness temperatures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions(SRFs) of channels 4 and 5 of AVHRRs and VIRR.The coefficients of modified Becker and Li’s split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method.As an example of validation,one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li’s approach.The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88,the bias is 0.6 K,and the root mean square deviation(RMSD) is 2.1 K.Furthermore,about 70% and 37% pixels in the LST difference image,which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image,have the values within ± 2 and ± 1 K,respectively.     

A Modified Becker''s Split-Window Approach for Retrieving Land Surface Temperature from AVHRR and VIRR

In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is pro- posed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere (TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of boundary temperature Ts (which is one of the input parameters to MODTRAN), and channels 4 and 5 brightness temperatures (T4 and T5) were constructed. Note that channels 4 and 5 brightness tempera- tures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method. As an example of validation, one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li's approach. The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K. Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K, respectively.     

利用MODIS云检测产品客观确定AIRS云检测

云检测是用卫星资料研究云对气候系统作用至关重要的第一步,采用Nagle的基于扫描几何特性的共同空间匹配算法,用MODIS云检测产品客观确定了AIRS云检测,是将高空间分辨率成像仪产品与高光谱分辨率传感器观测资料结合使用的一次实际应用。合成使用高空间分辨率成像仪与高光谱分辨率传感器观测资料的关键步骤在于:①有效而精确的时间和空间上的匹配;②传感器像素内图像仪云检测产品的断定。不仅是云检测,利用AIRS视场内空间匹配的MODIS云产品,还可以判断AIRS的云相态、有效云量及云光学厚度等。     

利用多角度POLDER偏振资料实现陆地上空大气气溶胶光学厚度和地表反照率的同时反演 II. 实例分析

由于陆地地表反照率的复杂性,陆地上空气溶胶的反演一直是卫星对地观测的一个难点,针对这个难点,作者提出联合利用偏振反射率和总反射率提取陆地上空大气气溶胶光学厚度和地表反照率及其区域分布的反演方案,提出了利用NCEP资料订正由海拔高度引起的Rayleigh散射变化的具体方法,并利用POLDER（POLarization and Directionality of Earth's Reflectance）的LEVEL-1B资料进行实际反演计算,给出中国华北地区气溶胶光学厚度和地表反照率的区域分布。反演结果与地基观测进行了对比验证分析,结果表明,综合利用标量辐射和偏振信息的可以实现区域乃至全球尺度的大气气溶胶和地表反照率的定量反演。     

Satellite All-sky Infrared Radiance Assimilation: Recent Progress and Future Perspectives

Satellite infrared(IR)sounder and imager measurements have become one of the main sources of data used by data assimilation systems to generate initial conditions for numerical weather prediction(NWP)models and atmospheric analysis/reanalysis.This paper reviews the development of satellite IR data assimilation in NWP in recent years,especially the assimilation of all-sky satellite IR observations.The major challenges and future directions are outlined and discussed.     

Fog detection using geostationary satellite data: Temporally continuous algorithm

A fog detection algorithm that uses geostationary satellite data has been developed and tested. This algorithm focuses on continuous fog detection since temporal discontinuities, especially at dawn and dusk, are a major problem with current fog detection algorithms that use satellite imagery data. This is because the spectral radiance at 3.7 μm contains overlapping emissive and reflectance components. In order to determine the radiance at 3.7 μm under fog conditions, radiative transfer model simulations were performed. The results showed that the radiance at 3.7 μm obviously varies with the solar zenith angle, and the brightness temperature differences between 3.7 μm and 10.8 μm are completely dissimilar between day and night (positive and varying with the angle during the daytime, but negative and constant at night). In this algorithm, a dynamic threshold is used as a function of the solar zenith angle. Moreover, additional criteria such as infrared, split-window channels, and a water vapor channel are used to remove high-level clouds. Also, the visible reflectance (0.67 μm) channel is used in the daytime algorithm because visible channel images are very practical for confirming a fog area with the high reflectivity and the smooth texture. The clear-sky visible reflectance for the previous 15 days was also employed to eliminate the surface effect that appeared during dawn and dusk. As the results, fog areas were estimated continuously, allowing the lifecycle of the fog system, from its development to decline, to appear obviously in the resulting images. Moreover, the estimated fog areas matched well with surface observations, except in a high latitude region that was covered by thin cirrus clouds.     

FY-4A GIIRS高时间分辨率温湿度廓线反演及其在台风中的应用

针对2020年第9号台风"美莎克"期间FY-4A 高光谱红外干涉式大气垂直探测仪GIIRS每15 min一次的目标区跟踪加密观测资料,用三维卷积神经网络算法反演的全天空大气温度、湿度廓线分析了台风处于生命史不同阶段时暖心结构和湿度场结构的演变特征。结果表明:卷积神经网络的深度机器学习算法可以用来反演全天空的三维大气温度和湿度垂直廓线,不光适用范围广(晴空和有云视场)、反演精度高,而且反演速度快。利用静止卫星平台高时间分辨率的特性,反演得到的温度、湿度廓线可以细致追踪台风处于发展、成熟和登陆等阶段时暖心结构和湿度场的时空演变特征。台风从发展阶段(热带风暴和强热带风暴)到成熟阶段至登陆消亡时,暖心首先出现在对流层中高层较薄的区域,随着台风强度的加强,深厚的暖心结构明显、强度增加,水平面积增大且垂直往下延伸。由于对流云中强上升气流的输送水汽正距平区逐渐上传至300 hPa,台风最强时密闭云区与四周下沉气流区比湿差高到8 K·kg^-1。暖心结构和高湿度中心随着台风登陆而逐渐消失。     

Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors. The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally, without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the a...     

Examination of the quality of GOSAT/CAI cloud flag data over Beijing using ground-based cloud data

It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.     

多普勒雷达图像逆风区的自动监测识别

在多普勒雷达降水回波径向速度场中及时准确地发现逆风区,对灾害天气预报预警具有重要意义.根据逆风区在雷达径向速度图中的物理图像特征,采用数字图像处理和分析方法实现了逆风区自动监测识别.首先,以雷达图像色标为依据,采用阈值法分别获取正、负速度区域二值图像,再对2幅图像分别进行形态学运算,然后将上述4幅图像做交叉逻辑运算,得到逆风区监测识别结果和相关参数.通过在2005-2011年长沙雷达站47幅根据实况进行人工标注后的多普勒雷达径向速度图像上进行实验,表明该方法对逆风区可以进行快速准确识别,与人工标注结果比较准确率可达89%,满足实际应用需要.     

Assimilation of GPM Microwave Imager Radiance for Track Prediction of Typhoon Cases with the WRF Hybrid En3DVAR System

The impact of assimilating radiance data from the advanced satellite sensor GMI(GPM microwave imager) for typhoon analyses and forecasts was investigated using both a three-dimensional variational(3DVAR) and a hybrid ensemble-3DVAR method. The interface of assimilating the radiance for the sensor GMI was established in the Weather Research and Forecasting(WRF) model. The GMI radiance data are assimilated for Typhoon Matmo(2014), Typhoon Chan-hom(2015), Typhoon Meranti(2016), and Typhoon Mangkhut(2018) in the Pacific before their landing. The results show that after assimilating the GMI radiance data under clear sky condition with the 3DVAR method, the wind,temperature, and humidity fields are effectively adjusted, leading to improved forecast skills of the typhoon track with GMI radiance assimilation. The hybrid DA method is able to further adjust the location of the typhoon systematically. The improvement of the track forecast is even more obvious for later forecast periods. In addition, water vapor and hydrometeors are enhanced to some extent, especially with the hybrid method.     

高性能机载云粒子成像仪研制及应用

机载云粒子成像仪是目前直接观测云中粒子谱分布和形状特征的关键设备,在云物理结构探测、遥感反演验证、数值模式云物理过程改进和人工影响天气等领域具有十分重要的作用。因此,针对现有进口仪器性能和应用方面的不足,开发更高性能的云粒子探测仪器十分必要。通过2011年启动的国家重大科学仪器设备开发专项—机载云粒子谱仪与成像仪研制项目,研制出国产高性能机载云粒子测量系统。经过多年的研制和反复测试,解决和显著改进了激光光束均匀化、弱信号探测、多路并行处理及微粒消衍射等关键技术,从而提高了探测器像元的光功率均匀性和一致性,使光斑区域内平均光功率密度提高约3倍,从而改进了粒子成像能力。采用更高分辨率国产光电线阵探测器,测量响应时间明显缩短,对小云粒子的探测能力明显提高。研制的仪器通过一系列基础参数测试、系统优化、环境适应性实验和累计60多架次的飞行测试。对2018年11月5日进行的两架次对比探测结果的初步分析表明,新研制的云粒子成像仪对小粒子浓度的测量精度较进口仪器提高一个量级左右,测量数据起伏更小,稳定性更高,并且可正确获得更清晰可靠的云粒子形态特征。      

基于方向特征显著性计算的MRI脑图像肿瘤检测

本文提出了一种利用方向性特征进行显著性建模的MRI脑图像肿瘤自动检测算法.该模型首先将MRI脑图像进行预处理,去除掉图像中头骨区域的干扰;然后使用基于方向特征的显著性检测增加病变区域的对比度,实现更准确地提取肿瘤图像区域.本文算法在脑图像数据集上进行了大量的实验,并且与主流的肿瘤自动检测方法进行了对比,证明了本文算法的有效性,并为医生提供可靠的辅助诊断和临床参考.