Fourteenth European Space Weather Week
Nov 27 - Dec 1, 2017, Ostend, Belgium

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.






Accepted Contributions

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Invited Talks

Understanding performance of neural network models for short-term predictions applied to geomagnetic indicesWintoft, P

Talks

Global Solar Magnetic Maps and Forecasting Space Weather with ADAPTHenney, C
Variation of geomagnetic responses to the solar wind input: Half-year increase during declining phases and 2009 specialtyYamauchi, M
Evidence on second-order phase transition of the magnetosphere around magnetic stormsBalasis, G
Use of systems based models for the forecasting of space weatherWalker, S
Tracking and characterizing the evolution of active regions with SDO/HMI Attie, R
Automatically worked stages for estimation of the level of expected radiation hazards from SEP events Dorman, L
Empirical modeling of the plasmasphere dynamics using neural networksZhelavskaya, I

e-Posters

Long Term Variation of Latitudinal Distribution of Coronal HolesChargeishvili, B

p-Posters

Three-dimensional data assimilation and reanalysis of radiation belt electrons Cervantes villa, J
Increasing the horizon of the Sheffield GEO radiation belt electron flux forecasts.Walker, S
Development of MLT electron flux models Boynton, R
Hidden factors in Solar-Terrestrial Connection as reason of natural limitation on forecasting efficiency of space weather impactsPustilnik, L
Robust Nonlinear Predictive Model Identification for Kp index ForecastingWei, H
Training a new generation of Space Weather experts in Machine LearningAmaya, J
A self-consistent method for deriving polar ionospheric convection from eigenanalysis of SuperDARN radar dataShore, R
Operational control of near-Earth’s radiation conditions by space weather services at SMDC MSUBobrovnikov, S
Space radiation study based on cascades simulations in geospaceTezari, A





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