In this work, we trained gradient boosted trees using XGBoost to predict the SYM-H forecasting using different combinations of solar wind and interplanetary magnetic field (IMF) parameters. Data are in csv and Python pickle formats.
Iong, D., Y. Chen, G. Toth, S. Zou, T. I. Pulkkinen, J. Ren, E. Camporeale, and T. I. Gombosi, New Findings from Explainable SYM-H Forecasting using Gradient Boosting Machines, Space Weather,11, accepted, 2022. https://doi.org/10.1002/essoar.10508063.3
In this work, we perform Global Sensitivity Analysis (GSA) for the background solar wind in order to quantify contributions from uncertainty of different model parameters to the variability of in-situ solar wind speed and density at 1au, both of which have a major impact on CME propagation and strength. Scripts written in the Julia language are used to build the PCE and calculate the sensitivity results. Data is available in csv, NetCDF and JLD files. A `Project.toml` file is included to activate and install all required dependencies (See README for details).
Data used in the paper "Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations" by G. Toth, M. Velli and B. van der Holst, ApJ 2023.
The Observations directory contains the PSP observations as simple text files that can be easily read by the IDL macros in the BATSRUS/share/IDL/General/ or any other plotting software.
The Simulations directory contains BATSRUS simulations including input and output files. The runlog files show the Git references. The output files are in binary format that can be read by the IDL macros in the BATSRUS/share/IDL/General/ or with the SpacePy software.
The BATSRUS directory contains the source code that can be used to reproduce the simulations.
G. Toth, M. Velli, B. van der Holst, 2023, Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations, The Astrophysical Journal, in press
