论文标题
空间天气应用的自动检测冠状质量喷射起源（Almanac）
Automated detection of coronaL MAss ejecta origiNs for space weather AppliCations (ALMANAC)
论文作者
论文摘要
潜在的危险冠状质量弹出（CME）的警报是基于检测太阳大气远程观察结果的快速变化。本文提出了一种检测和估算极端紫外线（EUV）数据中CME喷发的中心坐标的方法，其双重目的是提供早期警报，并对CME几何模型的CME传播方向进行初步估计。特别是，我们计划将年鉴方法与太空天气经验合奏包（SWEEP）的CME检测和表征模块联系起来，该模块是一个完全自动化的模块化软件包，用于目前正在为英国流星局开发的操作空间天气能力。在这项工作中，天文学应用于太阳动力学天文台（SDO）上的大气成像组件（AIA）。除了介绍该方法外，还对与协调数据分析研讨会（CDAW）记录的二十个Halo CME相关的有限数据进行了概念证明，附近是太阳能周期的活动最大的活动。每个事件的SDO/AIA数据在6分钟内处理，以6分钟的速度处理，以确定每个CME的现场位置和时间。年鉴和CDAW源事件坐标之间的绝对平均偏差在37.05 +-29.71分钟内，11.01 +-10.39度。这些有希望的结果为将来的工作奠定了坚实的基础，并将为自动CME警报和预测系统提供初始限制。
Alerts of potentially hazardous coronal mass ejections (CME) are based on the detection of rapid changes in remote observations of the solar atmosphere. This paper presents a method that detects and estimates the central coordinates of CME eruptions in Extreme Ultraviolet (EUV) data, with the dual aim of providing an early alert, and giving an initial estimate of the CME direction of propagation to a CME geometrical model. In particular, we plan to link the ALMANAC method to the CME detection and characterisation module of the Space Weather Empirical Ensemble Package (SWEEP), which is a fully automated modular software package for operational space weather capability currently being developed for the UK Meteorological Office. In this work, ALMANAC is applied to observations by the Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamics Observatory (SDO). As well as presenting the method, a proof of concept test is made on a limited set of data associated with twenty halo CMEs recorded by the Coordinated Data Analysis Workshop (CDAW) catalogue near the activity maximum of solar cycle 24. SDO/AIA data for each event is processed at 6 minute cadence to identify the on-disk location and time of each CME. The absolute mean deviance between the ALMANAC and CDAW source event coordinates are within 37.05 +- 29.71 minutes and 11.01 +- 10.39 degrees. These promising results give a solid foundation for future work, and will provide initial constraints to an automated CME alert and forecasting system.
