Session 13 - System Science: Application to space weather analysis, modelling and forecasting

Richard Boynton (Univ of Sheffield); Homayon Aryan (Goddard Space Flight Center); George Balasis (IAASARS, NOA); Enrico Camporeale (CWI)
Friday 01/12, 9:45 - 13:00

KEYWORDS - System science, machine learning, data assimilation, information theory, signal processing

The construction of accurate dynamical models is fundamental to forecasting the many aspects of space weather. The process of deducing models for forecasting traditionally involved breaking the system into component parts and applying the laws of physics to each part to build up a description of that system. However, for complex space weather systems, we do not have enough knowledge about some of the processes involved to build an accurate model solely from first principles. Alternatively, complex systems science based methods have been developed to deduce dynamical models from input-output data. The techniques developed from system science, such as system identification, machine learning, data assimilation, information theory, signal processing, among others, are applicable to any system that has large amounts of data availability. With the increasing amount of space weather data, we are able to make use of these tools and techniques to analyse, model and forecast the complex systems of space weather. As such, this session is for contributions that employ these state of the art tools that have been developed in system science.

Poster Viewing
From Thursday morning to Friday noon

Friday December 1, 09:45 - 11:00, Delvaux
Friday December 1, 11:45 - 13:00, Delvaux

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Talks : Time schedule

Friday December 1, 09:45 - 11:00, Delvaux
09:45Understanding performance of neural network models for short-term predictions applied to geomagnetic indicesWintoft, P et al.Invited Oral
10:10Automatically worked stages for estimation of the level of expected radiation hazards from SEP events Dorman, L et al.Oral
10:30Empirical modeling of the plasmasphere dynamics using neural networksZhelavskaya, I et al.Oral
10:45Variation of geomagnetic responses to the solar wind input: Half-year increase during declining phases and 2009 specialtyYamauchi, M et al.Oral

Friday December 1, 11:45 - 13:00, Delvaux
11:45Global Solar Magnetic Maps and Forecasting Space Weather with ADAPTHenney, C et al.Oral
12:05Use of systems based models for the forecasting of space weatherWalker, S et al.Oral
12:25Evidence on second-order phase transition of the magnetosphere around magnetic stormsBalasis, G et al.Oral
12:45Tracking and characterizing the evolution of active regions with SDO/HMI Attie, R et al.Oral


1Long Term Variation of Latitudinal Distribution of Coronal HolesChargeishvili, B et al.e-Poster
2Three-dimensional data assimilation and reanalysis of radiation belt electrons Cervantes villa, J et al.p-Poster
3Proton Prediction using Deep learningYang, S et al.p-Poster
4Solar Demon flare and dimming statistics from AIA observations 2010-2017Kraaikamp, E et al.p-Poster
5Forecasting the AE indices using machine learningWik, M et al.p-Poster
6A Comparative Performance Study of Machine Learning Algorithms for Space Weather ForecastingNanouris, N et al.p-Poster
7Using the Local Ensemble Transform Kalman Filter (LETKF) For Upper Atmosphere ModellingAngling, M et al.p-Poster
8Space radiation study based on cascades simulations in geospaceTezari, A et al.p-Poster
9Operational control of near-Earth’s radiation conditions by space weather services at SMDC MSUBobrovnikov, S et al.p-Poster
10A self-consistent method for deriving polar ionospheric convection from eigenanalysis of SuperDARN radar dataShore, R et al.p-Poster
11Training a new generation of Space Weather experts in Machine LearningAmaya, J et al.p-Poster
12Robust Nonlinear Predictive Model Identification for Kp index ForecastingWei, H et al.p-Poster
13Hidden factors in Solar-Terrestrial Connection as reason of natural limitation on forecasting efficiency of space weather impactsPustilnik, L et al.p-Poster
14Development of MLT electron flux models Boynton, R et al.p-Poster
15Increasing the horizon of the Sheffield GEO radiation belt electron flux forecasts.Walker, S et al.p-Poster
16Forecasting the photospheric magnetic field using machine learningNikolic, L et al.p-Poster