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- Creator:
- Gergely Koban, Judit Szente, Bart van der Holst, Gabor Toth, and Enrico Landi
- Description:
- This study aims to assess the performance of coronal models across multiple solar cycles and to analyze long-term variations in solar coronal structures observed in multiple EUV channels. To achieve this, we developed a comprehensive database of solar corona (data cubes) and inner heliosphere simulation outputs using the Alfvén Wave Solar atmosphere Model (AWSoM) within the Space Weather Modeling Framework (SWMF) for Solar Cycles 24 and 25 (SC24 and SC25). This database enables us to investigate the temporal evolution of solar wind source regions—Coronal Holes (CH) and Active Regions (AR). Model accuracy was assessed by comparing synthetic images with concurrent AIA observations in six EUV channels (94, 131, 171, 193, 211, and 335 Å). Additionally, we evaluated the reliability of AWSoM’s solar wind plasma outputs at 1 AU by comparing them with OMNI data for each Carrington Rotation (CR).
- Keyword:
- Solar Corona, SWMF, Solar Physics, Solar Cycle, and MHD Modelling
- Citation to related publication:
- Koban et al. (2025). Validation of Long-Term Solar Coronal Modeling Using FORWARD (Under review).
- Discipline:
- Science
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- Creator:
- Mukhopadhyay, Agnit, Daniel T Welling, Michael W Liemohn, Aaron J Ridley, Shibaji Chakrabarty, and Brian J Anderson
- Description:
- An updated auroral conductance module is built for global models, using nonlinear regression & empirical adjustments to span extreme events., Expanded dataset raises the ceiling of conductance values, impacting the ionospheric potential dB/dt & dB predictions during extreme events., and Application of the expanded model with empirical adjustments refines the conductance pattern, and improves dB/dt predictions significantly.
- Keyword:
- Space Weather Forecasting, Extreme Weather, Ionosphere, Magnetosphere, MI Coupling, Ionospheric Conductance, Auroral Conductance, Aurora, SWMF, SWPC, Nonlinear Regression, and dB/dt
- Citation to related publication:
- Mukhopadhyay, A., Welling, D. T., Liemohn, M. W., Ridley, A. J., Chakraborty, S., & Anderson, B. J. (2020). Conductance Model for Extreme Events: Impact of Auroral Conductance on Space Weather Forecasts. Space Weather, 18(11), e2020SW002551. https://doi.org/10.1029/2020SW002551
- Discipline:
- Engineering and Science