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Space Weather Prediction System providing forecasts and alerts on solar flares and SEP events

机译：空间天气预报系统提供有关太阳耀斑和sEp事件的预报和警报

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A web-based prototype system for predicting Solar Flares and Solar Energetic Particle (SEP) events for its use by space launcher operators or any interested user has been implemented. The main goal of this system, called SEPsFLAREs, is to provide warnings/predictions with forecast horizons from 48 hours before to a few hours before to the SEP peak flux, and duration predictions. The module responsible for predicting solar flares, the SF_PMod, is based on the well-known ASAP flare predictor [T. Colak & R. Qahwaji, Automated solar activity prediction: A hybrid computer platform using machine learning and solar imaging for automated prediction of solar flares, Space Weather, 7 (S06001), 2009], which learns rules by using machine learning techniques on SDO/SOHO solar images to automatically detect sunspots, classify them based on the McIntosh classification system, and predict C-, M-, and X-class flares with forecast horizon from 6 h to 48 h. Regarding the performance of the flare predictor, the 24-hour forecast horizon was found to provide the best performance: the Probability of Detection (POD), False Alarm Ratio (FAR) and True Skill Statistics estimations were 63.8%, 99.0% and 0.5 respectively for predicting X-class flares; and 88.7%, 87.0% and 0.59 respectively, for predicting M-class flares. The module responsible for predicting the SEP onset and occurrence, the SEP_OO_PMod, is based on the well-known UMASEP predictor [M. Núñez, Predicting solar energetic proton events (E > 10 MeV), Space Weather, 9 (S07003), 2011], which performs X-ray and proton flux correlations to find the first symptoms of future well- and poorly-connected SEP events. The SEP_OO_PMod also provides a Warning Tool which is able to warn about potential proton enhancements (including SEP events) from flare predictions. Regarding the performance of the SEP_OO_PMod, it was validated taking into account all 129 SEP events from January 1994 to June 2014 and obtained a POD of 86.82%, a FAR of 25.83%, and an Average Warning Time (AWT) of 3.93 h. Regarding the evaluation of the Warning Tool, the best performance, obtained with a set of user-defined parameters, were a POD of 58.3%, FAR of 90.1%, and AWT of 23.1 h. The module responsible for predicting SEP peak and duration, the SEP_FID_PMod, identifies the parent solar flare associated to an observed/predicted SEP, simulates the radial propagation of the predicted shock on a representative IMF structure (i.e. a static Parker Spiral), and predicts the SEP peak and duration. The SEP_FID_PMod, validated taking into account all 129 SEP events from January 1994 to June 2014, obtained a Mean Absolute Error (MAE) of SEP peak time predictions of 11.3 h, a MAE of peak intensity predictions of 0.53 in log10 units of pfu, and a MAE of SEP end time predictions of 28.8 h. The SEPsFLAREs system also acquires data for solar flares nowcasting (including GSFLAD proxy and SISTED detector from MONITOR’s ESA-funded project; [Hernández-Pajares, M., A. García-Rigo, J.M. Juan, J. Sanz, E. Monte and A. Aragón-Ángel (2012), GNSS measurement of EUV photons flux rate during strong and mid solar flares. Space Weather, Volume 10, Issue 12, doi:10.1029/2012SW000826] and [García-Rigo, A. (2012), Contributions to ionospheric determination with Global Positioning System: solar flare detection and prediction of global maps of Total Electron Content, Ph.D. dissertation. Doctoral Program in Aerospace Science & Technology, Technical University of Catalonia, Barcelona, Spain]).
机译：已经实现了一个基于网络的原型系统，该系统可以预测空间发射器操作员或任何感兴趣的用户使用的太阳耀斑和太阳高能粒子（SEP）事件。该系统称为SEPsFLARE，其主要目标是为预警/预测提供预测范围，从48小时到SEP峰值通量的前几个小时，以及持续时间预测。负责预测太阳耀斑的模块SF_PMod基于著名的ASAP耀斑预测器[T. Colak＆R. Qahwaji，“自动太阳活动预测：使用机器学习和太阳成像的混合计算机平台，用于太阳耀斑的自动预测，《太空天气》，第7期（S06001），2009年]，该平台通过在SDO /上使用机器学习技术来学习规则SOHO太阳图像可自动检测黑子，根据McIntosh分类系统对黑子进行分类，并预测6h至48h的C级，M级和X级耀斑。关于耀斑预报器的性能，发现24小时预报范围提供了最佳性能：检测概率（POD），错误警报率（FAR）和真实技能统计估计分别为63.8％，99.0％和0.5。用于预测X级耀斑；预测M级耀斑的分别为88.7％，87.0％和0.59。负责预测SEP发生和发生的模块SEP_OO_PMod基于众所周知的UMASEP预测器[M. Núñez，《预测太阳高能质子事件（E> 10 MeV）》，《太空天气》，第9期（S07003），2011年]，该函数执行X射线和质子通量的相关性，以发现未来良好连接和连接不良的SEP事件的最初症状。 SEP_OO_PMod还提供了一个警告工具，该工具能够警告耀斑预测中潜在的质子增强（包括SEP事件）。关于SEP_OO_PMod的性能，已对1994年1月至2014年6月的所有129次SEP事件进行了验证，得出的POD为86.82％，FAR为25.83％，平均警告时间（AWT）为3.93 h。关于警告工具的评估，通过一组用户定义的参数获得的最佳性能是POD为58.3％，FAR为90.1％和AWT为23.1小时。负责预测SEP峰值和持续时间的模块SEP_FID_PMod，标识与观察到/预测的SEP相关的母体太阳耀斑，模拟预测的冲击在代表性IMF结构（即静态Parker螺旋）上的径向传播，并预测SEP峰值和持续时间。经过验证的SEP_FID_PMod已考虑到1994年1月至2014年6月的所有129次SEP事件，得出SEP峰值时间预测的平均绝对误差（MAE）为11.3 h，峰值强度预测的MAE为log10单位pfu为0.53，并且SEP结束时间预测的MAE为28.8小时。 SEPsFLAREs系统还从MONITOR的ESA资助项目中获取临近预报的太阳耀斑数据（包括GSFLAD代理和SISTED探测器； [Hernández-Pajares，M.，A。García-Rigo，JM Juan，J。Sanz，E。Monte和A 。Aragón-Ángel（2012），强和中太阳耀斑期间EUV光子通量率的GNSS测量。空间天气，第10卷，第12期，doi：10.1029 / 2012SW000826]和[García-Rigo，A.（2012），贡献全球定位系统确定电离层的方法：太阳耀斑的探测和总电子含量全球图的预测，博士学位论文，西班牙巴塞罗那加泰罗尼亚技术大学航空航天科学与技术博士学位]）。

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