Cloud detection from visual band of satellite image based on variance of fractal dimension

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

Cloud Detection and Centroid Extraction of Laser Footprint Image of GF-7 Satellite Laser Altimetry

The laser altimeter loaded on the GaoFen-7(GF-7)satellite is designed to record the full waveform data and footprint image,which can obtain high-precision elevation control points for stereo image.The footprint camera equipped on the GF-7 laser altimetry system can capture the energy distribution at the time of laser emission and the image of the ground object where the laser falls,which can be used to judge whether the laser is affected by the cloud.At the same time,the centroid of laser spot on the footprint image can be extracted to monitor the change of laser pointing stability.In this manuscript,a data quality analysis scheme of laser altimetry based on footprint image is presented.Firstly,the cloud detection of footprint image is realized based on deep learning.The fusion result of the model is about 5%better than that of the traditional cloud detection algorithm,which can quickly and accurately determine whether the laser spot is affected by cloud.Secondly,according to the characteristics of footprint image,a threshold constrained ellipse fitting method for extracting the centroid of laser spot is proposed to monitor the pointing stability of long-period lasers.Based on the above method,the change of laser spot centroid since GF-7 satellite was put into operation is analyzed,and the conclusions obtained have certain reference significance for the quality control of satellite laser altimetry data and the analysis of pointing angle stability.

A Method of Identifying Thunderstorm Clouds in Satellite Cloud Image Based on Clustering

In this paper,the clustering analysis is applied to the satellite image segmentation,and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power.The method firstly adopts the fuzzy C-means clustering(FCM)to obtain the satellite cloud image segmentation.Secondly,in the cloud image,we dispose the‘high-density connected’pixels in the same cloud clusters and the‘low-density connected’pixels in different cloud clusters.Therefore,we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge.Finally,using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters,thunderstorm cloud clusters are quickly and accurately identified.The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.

Discussion Measurement Models and Algorithms of the Wind Vector Field Based on Satellite Images

This article aims to discuss the strike two-dimensional wind vector on geostationary satellite imageries. The magnitude and direction of the wind vector are decided by the moving speed of the clouds. First, based on the features of the cloud map, we extract the characteristics of clouds and establish matching model for the clouds image. Maximum correlation coefficient between the target modules and tracking module is obtained by using infrared brightness temperature cross-correlation coefficient method. Then, the beginning and end of the wind vector can be ascertained. Using the spherical triangles of the law of cosines, we determine the magnitude and direction of the wind vector.

Satellite-based Observational Study of the Tibetan Plateau Vortex:Features of Deep Convective Cloud Tops

In this study, an east-moving Tibetan Plateau vortex(TPV) is analyzed by using the ERA-5 reanalysis and multi-source satellite data, including FengYun-2 E, Aqua/MODIS and CALIPSO. The objective is to demonstrate:(i) the usefulness of multi-spectral satellite observations in understanding the evolution of a TPV and the associated rainfall, and(ii) the potential significance of cloud-top quantitative information in improving Southwest China weather forecasts. Results in this study show that the heavy rainfall is caused by the coupling of an east-moving TPV and some low-level weather systems [a Plateau shear line and a Southwest Vortex(SWV)], wherein the TPV is a key component. During the TPV's life cycle, the rainfall and vortex intensity maintain a significant positive correlation with the convective cloud-top fraction and height within a 2.5?radius away from its center. Moreover, its growth is found to be quite sensitive to the cloud phases and particle sizes. In the mature stage when the TPV is coupled with an SWV, an increase of small ice crystal particles and appearance of ring-and U/V-shaped cold cloud-top structures can be seen as the signature of a stronger convection and rainfall enhancement within the TPV. A tropopause folding caused by ageostrophic flows at the upper level may be a key factor in the formation of ring-shaped and U/V-shaped cloud-top structures. Based on these results, we believe that the supplementary quantitative information of an east-moving TPV cloud top collected by multi-spectral satellite observations could help to improve Southwest China short-range/nowcasting weather forecasts.

融合光谱阈值与图像技术的静止卫星夜间云检测方法

针对夜间云检测问题,本文基于静止气象卫星Himawari-8影像数据,分析了云像元光谱特征与图像特征,提出了融合光谱阈值与图像技术的静止卫星夜间云检测方法,实现了静止卫星夜间云的快速、准确检测。利用MODIS云产品和CALIPSO雷达数据,对云检测结果进行定性分析与定量验证。结果表明:①云检测结果与MODIS的云产品MYD06分布基本一致;②算法夜间平均云检测精度达到80.3%;③不同季节夜间的云检测精度随季节变化较明显,夏季最高达到83.3%,可以区分不同季节夜间的云与非云区域。因此,融合光谱阈值与图像技术的静止卫星夜间云检测方法能有效实现夜间云检测,为夜间云检测应用提供了新思路。

滇中及以东地区一次强降雪天气过程诊断分析

2022年2月19至23日,滇中及以东地区出现强降温降雪天气,其中曲靖出现了中到大雪局部暴雪或大暴雪。利用常规观测资料、物理量场、卫星云图等数据对此次天气过程进行诊断分析。结果表明:南支槽与昆明准静止锋(冷锋)是此次强降雪天气的主要影响系统;西南气流加强、水汽通量加大以及低层水汽辐合、高层辐散为此次降雪天气过程提供了较好的水汽条件;强烈的上升运动为降雪提供了必要的动力扰动;700 hPa上-4℃等温线和地温低于0℃的温度线与雪线位置相对应;卫星云图清晰的反映了南支槽与昆明准静止锋(冷锋)的移动、交汇和发展;多普勒雷达图上也进一步证实了不断补充加强的冷空气在此次降雪过程中的重要性。此次分析从天气系统、物理量场、卫星云图和雷达回波等各个维度进行,得出了滇中及以东地区出现降雪天气的指标,对以后降雪天气的预报具有明确的指示作用。

云技术在卫星图像生成中的应用与优势

文中主要研究了云技术在卫星图像生成中的应用及优势。首先,介绍了云技术的概念、特点和发展历程,然后详细阐述了云技术的原理,并分析了云技术的优势及存在的问题,最后提出了一种基于云平台的卫星图像生成方法,以有效解决传统卫星图像生成中存在的问题。

Estimation of Cloud Motion Using Cross-Correlation

This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.

Infrared Radiance Simulation and Application under Cloudy Sky Conditions Based on HIRTM

An algorithm based on hyperspectral infrared cloudy radiative transfer model (HIRTM) is introduced and a simulation method for infrared image of the generation geostationary meteorological satellite is proposed. Based on the parameters from weather research and forecast (WRF), such as the water content, atmospheric temperature, and humidity profile, the simulation data for the advanced Himawari imager (AHI) infrared radiative (IR) channels of Himawari-8 are obtained. Simulated results based on HIRTM agree well with the observed data. Further, the movement, development, and change of the cloud are well predicated. And the simulation of IR cloud image for the weather forecast has been obtained. This paper provides an improved method for evaluation and improvement of regional numerical model for weather forecast.

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.

Identifying Sky Conditions in Iran from MODIS Terra and Aqua Cloud Products

Clouds can influence climate through many complex interactions within the hydrological cycle. Due to the important effects of cloud cover on climate, it is essential to study its variability over certain geographical areas. This study provides a spatial and temporal distribution of sky conditions, cloudy, partly cloudy, and clear days, in Iran. Cloud fraction parameters were calculated based on the cloud product(collection 6_L2) obtained from the Moderate Resolution Imaging Spectroradiometer(MODIS) sensors on board the Terra(MOD06) and Aqua(MYD06) satellites. The cloud products were collected daily from January 1, 2003 to December 31, 2014(12 years) with a spatial resolution of 5 km × 5 km. First, the cloud fraction data were converted into a regular geographic coordinate network over Iran. Then, the estimations from both sensors were analyzed. Results revealed that the maximum annual frequency of cloudy days occurs along the southern shores of the Caspian Sea, while the minimum annual frequency occurs in southeast Iran. On average, the annual number of cloudy and clear-sky days was 88 and 256 d from MODIS Terra, as compared to 96 and 244 d from MODIS Aqua. Generally, cloudy and partly cloudy days decrease from north to south, and MODIS Aqua overestimates the cloudy and partly cloudy days compared to MODIS Terra.

面向光伏发电预测的公开数据集综述

光伏发电具有间歇性和波动性,光伏发电的精准预测是合理安排运行方式和应对措施、提高电网安全性和可靠性的重要措施。基于数据驱动方法是光伏发电预测研究中的主要技术手段,但研究人员面临实际数据难以获取、数据质量差、数据量不够等难题,光伏发电公开数据集为研究人员提供了数据资源,也提供了各种预测方法对比分析的基础。然而,研究人员在选取光伏发电公开数据集时,缺乏对各种公开数据集全面、深入的了解。文章首先阐述了光伏发电数据集中每种数据的收集方法和应用场景;其次调研总结了国内外现有面向太阳能光伏发电预测的公开数据集的现状,梳理了每个数据集的特点和优缺点;最后提出了促进公开数据集应用发展和建立高质量公开数据集的建议。

考虑云层遮挡的光伏发电功率超短期预测技术

云层对光伏电站的遮挡会导致光伏发电功率的随机波动,进而给电网稳定运行带来挑战,特别是在新能源渗透率不断提升的战略背景下,电网安全性和稳定性所面临的挑战更为严峻。为解决云遮挡下光伏功率快速波动预测精度低的难题,基于卫星云图提出一种考虑云遮挡的光伏功率超短期预测法。首先,根据场站位置信息提取目标区域具有潜在影响的云团,并通过云轨迹跟踪算法确定其移动矢量,实现超短期尺度下移动轨迹预测;然后,结合太阳-云-光伏电站的位置关系建立云遮挡评估模型,准确判断目标时刻下不同层高云团对光伏电站的遮挡情况,进而完成量化评估;最后,通过光电转换模型实现光伏发电功率超短期预测。结果显示,所提模型能准确预估未来云移动轨迹及云遮挡下的功率衰减系数,展示出较好的预测性能,具有一定的推广价值。

基于卫星云图的大区域云层预测方法

云层覆盖是影响对地观测卫星成像的一个重要问题,如果遥感图像中云层比例太高,或者特定目标不可见,则遥感图像就会失效。对地观测卫星能够根据云层预测信息,在多个观测目标之间进行选择。面向对地观测卫星任务规划的应用,设计了大区域范围的短期云层预测方法,首先通过光流法获取云运动矢量,然后依据云运动矢量外推获得预测的云层图像,同时引入拉普拉斯算子刻画云层运动过程中的扩散现象,利用风云二号卫星的真实云图序列数据,通过神经网络的反向传播算法优化扩散因子,以提升云层预测的效果。通过对结果进行分析,引入的拉普拉斯算子方法能够提高云层预测的精度,80%分位数的云层覆盖率误差约为11.7%,该精度的云层预测可以用于指导对地观测卫星任务规划。

风云三号降水卫星多角度偏振成像仪的观测特点和应用潜力

准确测量大气中云和气溶胶的辐射特性对数值天气预报和气候变化具有重要意义。搭载在风云三号降水卫星上的偏振载荷是国内首个具有短波红外通道的多角度偏振成像仪(Polarization and Multi-Angle Imager, PMAI),计划于2023年年初发射,为气溶胶-云-降水观测链条提供重要支撑。该仪器运行在非太阳同步的倾斜轨道,可提供3 km(星下点)空间分辨率和700 km幅宽的图像。PMAI的观测通道包括1030 nm、1370 nm、1640 nm的偏振通道和相应的非偏振通道,可提供14个角度的观测信息。PMAI将利用自然目标的在轨替代定标和同平台仪器的交叉定标,实现5%的辐射测量精度。观测和仿真数据表明PMAI拥有描述云和气溶胶特性的独特优势。全新的短波红外通道的多角度偏振测量可以优化云相态识别和云微物理参数反演、气溶胶的地气解耦以及地表方向反射特征的表述。处于非太阳同步轨道的PMAI具有独特观测几何,可以获得大气粒子辐射更宽的散射角分布信息。此外,PMAI可联合同平台中分辨率光谱成像仪的可见近红外和热红外通道的观测信息,进行云和气溶胶的协同反演。

一次雨转暴雪天气过程卫星云图中尺度特征分析

基于NCEP逐日再分析资料、常规地面高空观测资料、FY-2卫星云图资料,从大尺度环流背景、多尺度影响系统相互作用、卫星云图演变特征等方面,分析2016年10月26至27日宁夏秋末雨转暴雪天气过程的卫星云图特征.结果表明,该次过程的主要影响系统为地面冷锋、850 hPa切变线、700,500 hPa高空槽和200 hPa西风急流;过程中可见光、红外和水汽图上各云团的特征明显.在对应近地面天气尺度和中尺度系统的移动发展中,β尺度云团以类似“列车效应”的现象先后过境,它是造成该次暴雪过程的主要原因.云顶亮度温度TBB值的变化在雨雪转化过程中无明显特征,但在相态转为降雪后,其变化与降雪强度的关系较为明显.

基于生成对抗网络和卫星数据的云图临近预报

利用风云四号气象卫星A星(FY-4A)红外云图,基于生成对抗网络方法,提出了红外云图外推预报模型,实现了华东区域未来3 h的云图预报,预报的时空分辨率分别为1 h和4 km。结果表明:该外推模型预报的云图可较好描述云团移动、发展和减弱趋势,对研究区域内云团的强度、位置和形态得到较为理想的预报效果。为了验证提出的云图外推模型的有效性,将其与光流法和轨迹门控循环单元模型进行比较。对比试验结果表明:该云图外推模型具有最优的预报效果,说明使用生成对抗网络进行云图外推具有较好的可行性,能有效应用于气象业务中监测云团的生消和移动并提前预警灾害性天气的发生,为天气预报提供重要的参考依据。

广东2022年一次强降水的FY-4A观测及闪电特征

利用FY-4A卫星闪电成像仪LMI、TBB、地基闪电ADTD数据和NCEP-FNL再分析资料等,以2022年5月10日广东一次暴雨过程为例,对两个不同强降水区域对流云团发展演变的观测特征进行了分析。结果表明:中北部清远至九连山南侧的强降水1区属于典型的锋面低槽型暴雨,发生在低槽前部冷暖交汇区,珠江口西侧沿海附近的强降水2区则是暖区西南和偏南气流辐合作用的结果。此个例强降水发生前TBB迅速下降,强降水主要位于对流云团TBB低值中心梯度大值区。对流发展初期TBB逐渐下降到230 K以下,TBB变率较前1 h下降幅度可达-15℃以上,局部可达-30℃,对流云团移动前方的闪电对下一时刻对流的发展移动有很好的指示意义,锋面降水中ADTD较LMI提前出现;成熟阶段TBB大范围下降到220 K以下,局部200 K以下,TBB变率减小,维持在0~-10℃,闪电达到峰值,密集闪电随着TBB≤220 K低值区移动。

基于静止卫星探测的夏季青藏高原云分布及其日变化分析

我国新一代静止气象卫星首颗卫星风云四号先进成像仪AGRI(Advanced Geosynchronous Radiation Imager)具有更多的观测波段、更高的光谱分辨率和更高的时空分辨率,能够以较小的卫星天顶角获取完整的青藏高原观测图像,但尚未开发利用青藏高原地区的风云四号卫星云产品开展相关研究。本文基于FY-4A/AGRI提供的青藏高原地区像元级云图像,研究分析夏季青藏高原地区云分布及其日变化的特征和规律。研究发现高原南部和东南部区域云出现频率远高于高原其他地区;高原地区云频具有明显的昼夜变化,最高云频发生在12:00(当地时间,下同),最低云频出现在04:00;高原南部地区云频具有日出后增长速度最快、增长幅度最大、最先达到最高值的特征;当高原云频在当地正午达到最大值时,极高云频沿主要山脉分布,具有明显的地形依赖特征;云顶最大频率高度超过12 km的区域集中在雅鲁藏布江河谷及其北侧,念青唐古拉山脉附近,以及横断山脉东界以西地区;云顶最大频率高度日变化与云频的日变化存在显著不同。本文同时就青藏高原复杂地形对云分布和日变化的强烈影响进行了讨论。