Fifteenth European Space Weather Week
November 5 - 9, 2018, Leuven, Belgium

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


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.


Accepted Contributions

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Invited Talks

The Solar Drivers of Space Weather: Review of the Open Issues Affecting ForecastingVourlidas, A

Talks

Multiple hours ahead forecast of the Dst index using a combination of Long Short-Term Memory neural network and Gaussian ProcessGruet, M
Long-term electron radiation belt data assimilation based on multiple spacecraftPelivan, I
How predictable are the polar ionospheric equivalent currents?Meredith, N
Efficient photospheric flow tracking and machine learning for physics-based characterization of the solar activityAttie, R
On the usage of Principal Components Analysis (PCA) for the Prediction of Solar Energetic Particle (SEP) events Papaioannou, A
Recurrence analysis of the magnetospheric dynamicsAlberti, T
Forecasting Solar Wind Velocities from Coronal Hole Properties using Machine Learning Techniques.Garton, T
Challenges of space weather and space radiation predictions for human space explorations Guo, J

p-Posters

Prediction Model for Ionospheric Total Electron Content Based on Deep Learning Recurrent Neural NetworkTianjiao, Y
Poynting flux evolution in active regionsChicrala, A
Forecasting of a Solar Wind Classification using Convolutional Neural NetworksDepypere, G
Deep learning approach to next-day forecast of solar wind parameters at L1.Shneider, C
Statistical validation of an empirical model of solar proton event time profilesPaassilta, M
Processing Solar Images to forecast Coronal Mass Ejections using Artificial IntelligenceSavvas, R
Super-Resolution of Solar Images using Generative Adversarial NetworksShamash, A
The Advanced Solar Particle Events Casting System (ASPECS) activityAnastasiadis, A
Application of the SEPEM statistical modelling tool to the Helios 1 and 2 missionsAran, A
Case Studies of Combining Expertise for Groundbreaking, Integrated Space Weather ForecastingGeorgoulis, M
Pre-flare dynamics in 3D of the Active RegionsKorsos, M
Long-term electron radiation belt data assimilation relying on four spacecraft, the VERB code, and a sequential Kalman filter Cervantes villa, J
Anomalies of solar activity and phase synchronization of solar magnetic field.Blanter, E
On the use of topside RO derived electron density for model validationShaikh, M
Predicting and now-casting Kp index using historical and real-time observationsShprits, Y
Coronal holes detection using supervised classificationDelouille, V
Forecast of fast solar wind using global 3D MHD simulation from the Sun to 1AU with an empirical coronal heating modelDen, M
Solar Predict: A 4-D var method for hind- and forecasting solar activity Brun, A
MUF(3000)F2 maps over Europe by Kriging interpolation methodSabbagh, D
A method for MUF(3000) short-term (1-24) hour prediction over Europe.Perrone, L
Innovative methods for the prediction of solar flares: data assimilation in sandpile models with machine learningStrugarek, A
Precise estimation of the delayed ionospheric response to solar EUV variationsSchmölter, E
Forecasting the Strength of Geomagnetic Storms utilizing CME-ICME characteristicsPaouris, E
THE 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
High-speed solar wind stream forecast based on coronal hole dataPodladchikova, T
Multi-spacecraft Prediction of Co-rotating Stream Interaction RegionsVennerstrom, S
Inferring dynamic causal time lag: Applications to space weatherChandorkar, M
Verification of space weather forecast models: administrative, economic, and scientificWintoft, P
Operational Flare Forecasting -- Performance ComparisonsLeka, K
Characterizing the Dynamics Highly Energetic Coronal Mass EjectionsThompson, B
A multiscale artificial neural network approach to geomagnetic index forecastingConsolini, G
ACE/EPAM Solar energetic electron catalog (1996-2017): Statistical Relationship with Flares and CMEsSamwel, S
Operational Performance of the COMESEP Alert SystemDierckxsens, M
Connecting the Sun to the Earth using Machine LearningAmaya, J