Hα全日面太阳图像云污染的去除

Hα全日面太阳图像对太阳物理研究有着重要的意义,但其观测过程中可能受天气的影响,导致观测图像含有云层覆盖的污染。主要通过对这种Hα全日面太阳图像的云污染进行处理,从而得到较为清晰的太阳活动细节。具体算法为:首先将含云污染的图像扣除模板图像的标准临边昏暗轮廓,然后对其进行中值滤波获得云层图像,最后在原始图像上扣除云层图像得到修复后的全日面图像。实验证明此方法可以有效地去除Hα全日面太阳图像上的云污染,并对太阳活动区域影响较小。     

1993年5月日面AR7500中暗条的动力学特征

本文利用光球磁场、色球Hα单色像和Hβ速度场等观测资料，分析了1993年5月日面AR7500中3个暗条的演化和动力学行为，得出4个结论(1)3个暗条中两个是右旋暗条，一个是左旋暗条。(2)暗条附近两侧的色球纤维和光球横场几乎平行于暗条长轴，暗条端点处的黑子没有呈现明显的涡旋结构。(3)尖角处因为轴向场取向不同，一直没有发生暗条合并，即使其中一个右旋暗条消失后又重新形成也如此。(4)几天持续存在的左旋暗条，在两天的观测中未出现扰动激活，其中部为杂乱而不明显的运动图案。本文还讨论了可以用暗条的扭曲磁流绳模型来解释暗条的这些动力学行为，以及一些尚待进一步澄清的问题。     

1993年5月日面AR7500中暗条的动力学特征

本文利用光球磁场、色球Hα单色像和Hβ速度场等观测资料，分析了1993年5月日面AR7500中3个暗条的演化和动力学行为，得出4个结论：（1）3个暗条中两人是右旋暗条，一个是左旋暗条。（2）暗条附近两侧的色球纤维和光球横场几乎平行于暗条长轴，暗条端点处的黑子没有呈现明显的涡旋结构。（3）尖角处因为轴向场取向不同，一直没有发生暗条合并，即使其中一个右旋暗条消失后又重新形成也如此。（4）几天持续存在的左旋暗条，在两天的观测中未出现扰动激活，其中部为杂乱而不明显的运动因素。本文还讨论了可以用暗条的扭曲磁流绳模型来解释暗条的这些动力学行为，以及一些尚待进一步澄清的问题。     

2004年4月11日AR0588中环形暗条爆发与CME的研究

利用云南天文台色球Hα单色像、SOHO/EITEUV单色像、SOHO/LASCO白光日冕观测、SOHO/MDI光球磁图及Nobeyama17GHz微波射电观测资料对2004年4月11日AR0588中的环形暗条爆发进行了初步的分析。主要结论如下:(1)爆发的暗条呈现封闭的环形。在Hα观测上爆发前有明显的激活态,表现为西半环变粗变厚,断裂出现缺口并缓慢向西南方向上升。在EIT195 观测上,此暗条爆发表现出两条扎根于爆发源区的亮带,其顶部可能是爆发中的暗条,而这两条亮带是暗条的两条腿。该暗条爆发是动力学爆发,但暗条等离子体在爆发过程中也受到明显的加热。(2)该暗条爆发伴随有一个明显的双带耀斑。一个带位于暗条爆发的中心,几乎不动,而另一个带呈环状包围爆发的暗条,展示明显的分离运动。这两个带之间,在耀斑后期出现明显的耀斑后环。(3)这一暗条爆发及耀斑与LASCO观测到的一个快速的、具有典型三部分结构的partialHaloCME在时间和空间上是密切相关的。     

基于支持向量机的太阳磁场活动区极性反转线位置的探测

太阳磁场的极性反转线(Polarity Inversion Line, PIL)是研究太阳活动、分析太阳磁场结构演变和预测太阳耀斑最重要的日面特征之一.磁场极性反转的位置是太阳耀斑和暗条可能出现的位置."先进天基太阳天文台(ASO-S)"是中国首颗空间太阳专用观测卫星,其搭载的"全日面矢量磁像仪(Full-Disk Vector Magnetograph, FMG)"主要任务是探测高空间、高时间分辨率的全日面矢量磁场.为了提高观测数据使用效率、快速监测太阳活动水平、提高太阳耀斑与日冕物质抛射的预报水平以及更好地服务于FMG数据处理与分析系统,采用了图像自动识别与处理技术,更加精确有效地检测极性反转线.从支持向量机(Support Vector Machine, SVM)的模型出发,将极性反转线位置的探测问题转化为一个模式识别中的二分类问题,提出了一种基于支持向量机的极性反转线检测算法,自动探测与识别太阳动力学天文台(Solar Dynamics Observatory, SDO)日震和磁成像仪(Helioseismic and Magnetic Imager, HMI)磁图的极性反转线位置.与现有算法的对比结果表明,此算法可以精确直观地检测太阳活动区的极性反转线.     

云南天文台Hα全日面观测数据服务系统

云南天文台Hα全日面望远镜是云南天文台太阳观测的主要仪器之一。经过十几年的运行,望远镜积累了大量的观测数据,并且这些数据还在以每天1～2Gbyte的速度增长。为了保存这些数据,便于进行数据共享,建立了Hα全日面观测数据服务系统。硬件方面,采用DAS+NAS的存储方案;软件方面采用PHP+MySQL的方案。本系统的基本功能包括数据存储、数据备份、数据查询和数据下载,并已经正常运行了半年左右。介绍了这一系统的设计方案和基本结构。由于这一系统更多的是为澄江1m红外太阳塔的有关系统的设计提供经验和参照,因此在文中相关部分初步讨论了某些针对澄江1m红外太阳塔有关系统的考虑。     

一个大暗条激活的Hα观测及其电流模型解释

本文利用赣榆站获得的精细Ｈα资料，分析了同ＮＯＡＡ６３２７和６３３１活动区相关的一个大暗条的活动情况，这是一个部分宁静和部分活动的复合暗条，伴有频繁的分裂和重现。特别是在１０月２９日附近活动区的耀斑活动后将它激活，暗条在耀斑的ＭＨＤ长波的激发下，呈现出强烈的红移特征－向下沉降，本文利用ＶａｎＴｅｄｅｔａｌ所发展的暗条电流模型来解释暗条的活动，针对不同的背景场形式和参数，计算了暗条的不稳定（向上或向     

面向ONSET实时数据处理的图像选帧GPU技术实现

光学和近红外太阳爆发监测望远镜每天可以获得大量的太阳图像数据,对这些观测数据进行实时选帧处理,一方面可以减轻存储压力,另一方面也可以提高后续图像重建的质量。针对观测过程中的选帧要求,设计并实现了一套基于图形处理器的图像选帧实时处理模块,当前的模块已经实现了平均梯度法和谱比法选帧两种算法的高速并行处理。对模块的实现进行了细致的讨论,并比较了两种选帧方法的加速比。实验表明,该模块运行稳定可靠;从执行效率来看,针对近全日面图像的选帧总体执行时间最快为1.2 s,比原有串行实现提升了7倍;局部面图最快为0.7 s,平均提升了5倍。整体模块的实现与当前性能已经可以满足实时观测与处理的要求。     

1966年3月24日耀斑的分析研究

本文用数据方法分析了紫金山天文台色球望远镜观测的１９９６年３月２４日３Ｂ级双带主资料，结果表明：由于新浮磁流改变背景磁场，光球剪切运动引起暗条圆柱轴向磁力线扭转而使暗条电流增加，致使暗条整体力学平衡破坏，驱动暗条向上运动。并对暗条上升运动与耀斑爆发的物理关系进行了分析讨论。     

云南天文台Hα全日面望远镜4K×4K CCD性能测试

天文观测采用的CCD一般都要进行性能测试,然后再投入常规观测。针对云南天文台Hα全日面望远镜新引入的4K×4K大尺寸QHYl6803CCD已投入实际观测的情况,对其进行了较为全面的测试,检测内容包括有效尺寸、本底情况、读出噪声、增益、暗流、热像素等等。从检测结果来看,该CCD是适用于太阳全日面观测的。同时提出的检测方案是一种在非实验室条件下的测试方案,较为方便和快捷。从检测结果来看,参数的测量可信度高。     

Automatic Detection and Classification of Coronal Holes and Filaments Based on EUV and Magnetogram Observations of the Solar Disk

A new method for the automated detection of coronal holes and filaments on the solar disk is presented. The starting point is coronal images taken by the Extreme Ultraviolet Telescope on the Solar and Heliospheric Observatory (SOHO/EIT) in the Fe ix/x 171 Å, Fe xii 195 Å, and He ii 304 Å extreme ultraviolet (EUV) lines and the corresponding full-disk magnetograms from the Michelson Doppler Imager (SOHO/MDI) from different phases of the solar cycle. The images are processed to enhance their contrast and to enable the automatic detection of the two candidate features, which are visually indistinguishable in these images. Comparisons are made with existing databases, such as the He i 10830 Å NSO/Kitt Peak coronal-hole maps and the Solar Feature Catalog (SFC) from the European Grid of Solar Observations (EGSO), to discriminate between the two features. By mapping the features onto the corresponding magnetograms, distinct magnetic signatures are then derived. Coronal holes are found to have a skewed distribution of magnetic-field intensities, with values often reaching 100?–?200 gauss, and a relative magnetic-flux imbalance. Filaments, in contrast, have a symmetric distribution of field intensity values around zero, have smaller magnetic-field intensity than coronal holes, and lie along a magnetic-field reversal line. The identification of candidate features from the processed images and the determination of their distinct magnetic signatures are then combined to achieve the automated detection of coronal holes and filaments from EUV images of the solar disk. Application of this technique to all three wavelengths does not yield identical results. Furthermore, the best agreement among all three wavelengths and NSO/Kitt Peak coronal-hole maps occurs during the declining phase of solar activity. The He ii data mostly fail to yield the location of filaments at solar minimum and provide only a subset at the declining phase or peak of the solar cycle. However, the Fe ix/x 171 Å and Fe xii 195 Å data yield a larger number of filaments than the Hα data of the SFC.     

A Comparative Evaluation of Automated Solar Filament Detection

We present a comparative evaluation for automated filament detection in Hα solar images. By using metadata produced by the Advanced Automated Filament Detection and Characterization Code (AAFDCC) module, we adapted our trainable feature recognition (TFR) module to accurately detect regions in solar images containing filaments. We first analyze the AAFDCC module’s metadata and then transform it into labeled datasets for machine-learning classification. Visualizations of data transformations and classification results are presented and accompanied by statistical findings. Our results confirm the reliable event reporting of the AAFDCC module and establishes our TFR module’s ability to effectively detect solar filaments in Hα solar images.     

A Comparison Between Nonlinear Force-Free Field and Potential Field Models Using Full-Disk SDO/HMI Magnetogram

Measurements of magnetic fields and electric currents in the pre-eruptive corona are crucial to the study of solar eruptive phenomena, like flares and coronal mass ejections (CMEs). However, spectro-polarimetric measurements of certain photospheric lines permit a determination of the vector magnetic field only at the photosphere. Therefore, there is considerable interest in accurate modeling of the solar coronal magnetic field using photospheric vector magnetograms as boundary data. In this work, we model the coronal magnetic field above multiple active regions with the help of a potential field and a nonlinear force-free field (NLFFF) extrapolation code over the full solar disk using Helioseismic and Magnetic Imager (SDO/HMI) data as boundary conditions. We compare projections of the resulting magnetic field lines with full-disk coronal images from the Atmospheric Imaging Assembly (SDO/AIA) for both models. This study has found that the NLFFF model reconstructs the magnetic configuration closer to observation than the potential field model for full-disk magnetic field extrapolation. We conclude that many of the trans-equatorial loops connecting the two solar hemispheres are current-free.     

Processing Photometric Full-Disk Solar Images

Daily, photometric, full-disk digital solar images have been taken at the San Fernando Observatory (SFO) at two resolutions and in several wavelengths for more than eleven years. We describe the standard data processing techniques used for these images, including: calibration, limb fitting, geometric correction, and production of a solar contrast map by limb-darkening removal. The resulting contrast maps have a photometric accuracy which is often a few tenths of a percent. We show that the geometric accuracy of our images, as measured by the reproducibility of disk and sunspot areas, is very high as well. The techniques described in this paper should be applicable to any instrument producing full-disk photometric images.     

A Method of Resolving the 180-Degree Ambiguity by Employing the Chirality of Solar Features

The 180-degree ambiguity in magnetic field direction along polarity reversal boundaries can be resolved often and reliably by the chiral method. The chiral method requires (1) identification of the chirality of at least one solar feature related to a polarity reversal boundary along which the field direction is sought and (2) knowledge of the polarity of the network magnetic field on at least one side of the polarity reversal boundary. In the context of the Sun, chirality is an observable signature of the handedness of the magnetic field of a solar feature. We concentrate on how to determine magnetic field direction from chirality definitions and illustrate the technique in eight examples. The examples cover the spectrum of polarity boundaries associated with filament channels and filaments ranging from those connected with active regions to those on the quiet Sun. The applicability of the chiral method to all categories of filaments supports the view that active region filaments and quiescent filaments are the extreme ends in a continuous spectrum of filaments. The chiral method is almost universally applicable because many types of solar features that reveal chirality are now readily seen in solar images accessible over the World Wide Web; also there are clear differences between left-handed and right-handed solar structures that can be identified in both high- and low-resolution data although high-resolution images are almost always preferable. In addition to filaments and filament channels, chirality is identifiable in coronal loop systems, flare loop systems, sigmoids, some sunspots, and some erupting prominences. Features other than filament channels and filaments can be used to resolve the 180-degree ambiguity because there is a one-to-one relationship between the chiralities of all features associated with a given polarity reversal boundary. Y. Lin is now at the Institute of Theoretical Astrophysics, University of Oslo.     

Motions and magnetic fields in filaments

Based on the developed method of jointly using data on the magnetic fields and brightness of filaments and coronal holes (CHs) at various heights in the solar atmosphere as well as on the velocities in the photosphere, we have obtained the following results:

The upward motion of matter is typical of filament channels in the form of bright stripes that often surround the filaments when observed in the HeI 1083 nm line.

The filament channels observed simultaneously in Hα and HeI 1083 nm differ in size, emission characteristics, and other parameters. We conclude that by simultaneously investigating the filament channels in two spectral ranges, we can make progress in understanding the physics of their formation and evolution.

Most of the filaments observed in the HeI 1083 nm line consist of dark knots with different velocity distributions in them. A possible interpretation of these knots is offered.

The height of the small-scale magnetic field distribution near the individual dark knots of filaments in the solar atmosphere varies between 3000 and 20000 km.

The zero surface separating the large-scale magnetic field structures in the corona and calculated in the potential approximation changes the inclination to the solar surface with height and is displaced in one or two days.

The observed formation of a filament in a CH was accompanied by a significant magnetic field variation in the CH region at heights from 0 to 30000 km up to the change of the predominant field sign over the entire CH area. We assume that this occurs at the stage of CH disappearance.

     

Developing an Advanced Automated Method for Solar Filament Recognition and Its Scientific Application to a Solar Cycle of MLSO Hα Data

We developed a method to automatically detect and trace solar filaments in Hα full-disk images. The program is able not only to recognize filaments and determine their properties, such as the position, the area, the spine, and other relevant parameters, but also to trace the daily evolution of the filaments. The program consists of three steps: First, preprocessing is applied to correct the original images; second, the Canny edge-detection method is used to detect filaments; third, filament properties are recognized through morphological operators. To test the algorithm, we successfully applied it to observations from the Mauna Loa Solar Observatory (MLSO). We analyzed Hα images obtained by the MLSO from 1998 to 2009 and obtained a butterfly diagram of filaments. This shows that the latitudinal migration of solar filaments has three trends in Solar Cycle 23: The drift velocity was fast from 1998 to the solar maximum, after which it became relatively slow. After 2006, the migration became divergent, signifying the solar minimum. About 60 % of the filaments with latitudes higher than 50^° migrate toward the polar regions with relatively high velocities, and the latitudinal migrating speeds in the northern and the southern hemispheres do not differ significantly in Solar Cycle 23.     

Filament Recognition and Image Cleaning on Meudon Hα Spectroheliograms

This paper presents the techniques developed for the automated detection of filaments on Meudon H spectroheliograms, and, by extension, on any full-disk H Sun observations. Some cleaning processes are first applied to the images to correct them from defects characteristic of the instrument. Indeed, these defects may lead to spurious detections. From the cleaned images, filament areas are then segmented using a region growing method which efficiently returns the full extent of these dark areas. The filaments are finally described by means of their pruned skeleton. This representation allows one to compare the automatically segmented filaments with those manually recorded for Meudon Synoptic Maps. The very good agreement observed on a representative set of images confirms that this method can effectively be used in the frame of the EGSO (European Grid of Solar Observations) project in order to produce a reliable catalog dedicated to solar features.     

Development of an Automatic Filament Disappearance Detection System

This paper presents an efficient and automatic method for detecting filament disappearances. This method was applied to the Big Bear Solar Observatory's (BBSO) full-disk H images. The initial step is to detect the filaments in the solar image, then determine if they are growing, stable or disappearing. If a disappearing filament is found, the solar community can be automatically alerted in near real time. This system is proven to be accurate and fast. In addition, three statistical studies of the appearance and disappearance of all filaments in 1999 are presented.