Released
Software

ClassifyStorms - an automated classifier for geomagnetic storm drivers based on machine learning techniques

Cite as:

Pick, Leonie (2019): ClassifyStorms - an automated classifier for geomagnetic storm drivers based on machine learning techniques. V. 1.0.1. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2019.003

Status

I   N       R   E   V   I   E   W : Pick, Leonie (2019): ClassifyStorms - an automated classifier for geomagnetic storm drivers based on machine learning techniques. V. 1.0.1. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2019.003

Abstract

The software package “ClassifyStorms” version 1.0.1 performs a classification of geomagnetic storms according to their interplanetary driving mechanisms based exclusively on magnetometer measurements from ground. In this version two such driver classes are considered for storms dating back to 1930. Class 0 contains storms driven by Corotating or Stream Interaction Regions (C/SIRs) and class 1 contains storms driven by Interplanetary Coronal Mass Ejections (ICMEs). The properties and geomagnetic responses of these two solar wind structures are reviewed, e.g., by Kilpua et al. (2017, http://doi.org/10.1007/s11214-017-0411-3). The classification task is executed by a supervised binary logistic regression model in the framework of python's scikit-learn library. The model is validated mathematically and physically by checking the driver occurrence statistics in dependence on the solar cycle phase and storm intensity. A detailed description of the classification model is given in Pick et al. (2019) to which this software is supplementary material.

Under “Files” you can download ClassifyStorms-V1.0.1.zip, which contains the jupyter notebook “ClassifyStorms.ipynb” (https://jupyter.org/) and the python modules “Imports.py”, “Modules.py” and “Plots.py”. Check for an up-to-date release of the software on GitLab via https://gitext.gfz-potsdam.de/pick/public/ClassifyStorms (under Project, Releases). The “Readme.md” file provides all information needed to run or modify “ClassifyStorms” from the GitLab source.

The software depends on the input data set “Input.nc”, an xarray Dataset (http://xarray.pydata.org/en/stable) saved in NetCDF format (https://www.unidata.ucar.edu/software/netcdf), which you can also download under “Files”. It contains

1. the HMC index: a three-hour running mean with weights [0.25,0.5,0.25] of the original Hourly Magnetospheric Currents index (HMC index, http://doi.org/10.5880/GFZ.2.3.2018.006).

2. the geomagnetic observatory data: vector geomagnetic disturbances from 34 mid-latitude observatories during 1900-2015 in the Cartesian Centered Dipole coordinate system. The original observatory data was downloaded from the WDC for Geomagnetism, Edinburgh (http://www.wdc.bgs.ac.uk/) and processed as described in section 2.1 of Pick et al. (2019).

3. the “reference” geomagnetic storms: universal time hours of 868 geomagnetic storm peaks together with their interplanetary drivers (class labels 0 or 1, see above) as described in section 2.2 of Pick et al., 2019. These events are taken from published lists (Jian et al., 2006a, 2006b, 2011; Shen et al., 2017; Turner et al., 2009), which are gathered in the separate ASCII file “ReferenceEvents.txt” (under “Files”) for a quick overview.

4. additional quantities for plotting: time series of Kp (since 1932) and Dst (since 1957) geomagnetic indices from the WDC for Geomagnetism, Kyoto (http://wdc.kugi.kyoto-u.ac.jp/wdc/Sec3.html) as well as the yearly mean total sunspot number from WDC-SILSO, Royal Observatory of Belgium, Brussels (http://sidc.be/silso/datafiles).

The output of ClassifyStorms is "StormsClassified.csv" (under “Files”). This table lists the Date (Year-Month-Day) and Time (Hour:Minutes:Seconds) of 7546 classified geomagnetic storms together with the predicted interplanetary driver class label (0 or 1) and the corresponding probability (between 0 and 1).


Version history:
20 Sep 2019: Version 1.0.1: Correction of plotting mistake in Figure m / Figure S4 (see gitlab repository for details)

Authors

  • Pick, Leonie;GFZ German Research Centre for Geosciences, Potsdam, Germany

Contact

  • Pick, Leonie (Researcher) ; German Aerospace Center (DLR), Neustrelitz, Germany;

Keywords

Geomagnetic storms, Geomagnetic observatories, Machine learning

GCMD Science Keywords

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    Files

    License: Software Licence: GNU General Public License, Version 3, 29 June 2007, Copyright © 2019 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences (Leonie Pick)
    Data Licence: CC BY 4.0

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