Session 6 - Unveiling Current Challenges in Space Weather Forecasting

Anastasios Anastasiadis (National Observatory of Athens, IAASARS), Enrico Camporeale (Centre for Mathematics and Computer Science, CWI), Manolis K. Georgoulis (Academy of Athens, RCAAM), Ryan McGranaghan (Jet Propulsion Laboratory)
Wednesday 7/11, 09:00-10:30 & 11:15-12:45
MTC 00.10, Large lecture room

Predicting the conditions of our space environment is a true challenge, due to the large size of the system and the complex interplay of physical mechanisms. Nowadays, forecasting techniques range from physics-based to data-driven statistical models. Massively expanded data availability and sophisticated means to analyze voluminous and complex information open new possibilities to innovative methodologies. This session is devoted to the broad spectrum of advanced forecasting techniques, including physical models, statistical methods, data assimilation, information theory, and machine learning. The goal of this session is to provide a forum for new and ongoing efforts that connect the dots between space weather research and future operational forecasting applications. We invite abstracts covering observations, models, and their combinations. Methods that use innovative and multidisciplinary approaches are particularly welcome.

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Talks : Time schedule

Wednesday November 7, 09:00 - 10:30, MTC 00.10, Large lecture room
09:00The Solar Drivers of Space Weather: Review of the Open Issues Affecting ForecastingVourlidas, A et al.Invited Oral
09:25On the usage of Principal Components Analysis (PCA) for the Prediction of Solar Energetic Particle (SEP) events Papaioannou, A et al.Oral
09:40Challenges of space weather and space radiation predictions for human space explorations Guo, J et al.Oral
09:55Efficient photospheric flow tracking and machine learning for physics-based characterization of the solar activityAttie, R et al.Oral
10:10Forecasting Solar Wind Velocities from Coronal Hole Properties using Machine Learning Techniques.Garton, T et al.Oral

Wednesday November 7, 11:15 - 12:45, MTC 00.10, Large lecture room
11:15Applied artificial intelligence for space weather researchGuhathakurta, M et al.Invited Oral
11:40Recurrence analysis of the magnetospheric dynamicsConsolini, G et al.Oral
11:55Long-term electron radiation belt data assimilation based on multiple spacecraftCervantes villa, J et al.Oral
12:10Multiple hours ahead forecast of the Dst index using a combination of Long Short-Term Memory neural network and Gaussian ProcessGruet, M et al.Oral
12:25How predictable are the polar ionospheric equivalent currents?Freeman, M et al.Oral


1Prediction Model for Ionospheric Total Electron Content Based on Deep Learning Recurrent Neural NetworkTianjiao, Y et al.p-Poster
2Poynting flux evolution in active regionsChicrala, A et al.p-Poster
3Forecasting of a Solar Wind Classification using Convolutional Neural NetworksDepypere, G et al.p-Poster
4Deep learning approach to next-day forecast of solar wind parameters at L1.Shneider, C et al.p-Poster
5Statistical validation of an empirical model of solar proton event time profilesPaassilta, M et al.p-Poster
6Processing Solar Images to forecast Coronal Mass Ejections using Artificial IntelligenceSavvas, R et al.p-Poster
7Super-Resolution of Solar Images using Generative Adversarial NetworksShamash, Ap-Poster
8The Advanced Solar Particle Events Casting System (ASPECS) activityAnastasiadis, A et al.p-Poster
9Application of the SEPEM statistical modelling tool to the Helios 1 and 2 missionsAran, A et al.p-Poster
11Pre-flare dynamics in 3D of the Active RegionsKorsos, M et al.p-Poster
12Long-term electron radiation belt data assimilation relying on four spacecraft, the VERB code, and a sequential Kalman filter Cervantes villa, J et al.p-Poster
13Anomalies of solar activity and phase synchronization of solar magnetic field.Blanter, E et al.p-Poster
14On the use of topside RO derived electron density for model validationShaikh, M et al.p-Poster
15Predicting and now-casting Kp index using historical and real-time observationsShprits, Y et al.p-Poster
16Coronal holes detection using supervised classificationDelouille, V et al.p-Poster
17Forecast of fast solar wind using global 3D MHD simulation from the Sun to 1AU with an empirical coronal heating modelDen, M et al.p-Poster
18Solar Predict: A 4-D var method for hind- and forecasting solar activity Brun, A et al.p-Poster
19MUF(3000)F2 maps over Europe by Kriging interpolation methodSabbagh, D et al.p-Poster
20A method for MUF(3000) short-term (1-24) hour prediction over Europe.Perrone, L et al.p-Poster
21Innovative methods for the prediction of solar flares: data assimilation in sandpile models with machine learningStrugarek, A et al.p-Poster
22Precise estimation of the delayed ionospheric response to solar EUV variationsSchmölter, E et al.p-Poster
23Forecasting the Strength of Geomagnetic Storms utilizing CME-ICME characteristicsPaouris, E et al.p-Poster
24The dependence of high-speed stream peak velocities and of the Kp index on the positions of their source coronal holes on the sun Hofmeister, S et al.p-Poster
25High-speed solar wind stream forecast based on coronal hole dataPodladchikova, T et al.p-Poster
26Multi-spacecraft Prediction of Co-rotating Stream Interaction RegionsVennerstrom, S et al.p-Poster
27Inferring dynamic causal time lag: Applications to space weatherChandorkar, M et al.p-Poster
28Verification of space weather forecast models: administrative, economic, and scientificWintoft, P et al.p-Poster
30A multiscale artificial neural network approach to geomagnetic index forecastingConsolini, G et al.p-Poster
31ACE/EPAM Solar energetic electron catalog (1996-2017): Statistical Relationship with Flares and CMEsSamwel, S et al.p-Poster
32Operational Performance of the COMESEP Alert SystemDierckxsens, M et al.p-Poster
33Connecting the Sun to the Earth using Machine LearningAmaya, J et al.p-Poster
34The Self-Adjusted Solar Flux Forecasting Tool (SASFF)Podladchikova, E et al.p-Poster
35Photospheric Magnetic Field Properties of Flaring vs. Flare-quiet active regions, V: Results from HMILeka, K et al.p-Poster