2024-03-28T17:53:31Zhttp://doidb.wdc-terra.org/oaip/oaioai:doidb.wdc-terra.org:67102021-01-07T11:56:38ZDOIDBDOIDB.GFZ
doi:10.5880/GFZ.2.3.2019.003
eng
GFZ German Research Centre for Geosciences
http://www.gfz-potsdam.de/
information
pointOfContact
2019-09-20
urn:ogc:def:crs:EPSG:4326
ClassifyStorms - an automated classifier for geomagnetic storm drivers based on machine learning techniques
2019-04-27
creation
doi:10.5880/GFZ.2.3.2019.003
Pick, Leonie
GFZ German Research Centre for Geosciences, Potsdam, Germany
author
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/lpick/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)
Complete
Pick, Leonie
GFZ German Research Centre for Geosciences, Potsdam, Germany
Researcher
leonie.pick@gfz-potsdam.de
pointOfContact
Geomagnetic storms
Geomagnetic observatories
Machine learning
EARTH SCIENCE > SUN-EARTH INTERACTIONS > IONOSPHERE/MAGNETOSPHERE DYNAMICS > MAGNETIC FIELDS/MAGNETIC CURRENTS
EARTH SCIENCE > SUN-EARTH INTERACTIONS > IONOSPHERE/MAGNETOSPHERE DYNAMICS > MAGNETIC STORMS
EARTH SCIENCE > SUN-EARTH INTERACTIONS > IONOSPHERE/MAGNETOSPHERE DYNAMICS > SOLAR WIND
EARTH SCIENCE > SOLID EARTH > GEOMAGNETISM > MAGNETIC FIELD > MAGNETIC ANOMALIES
NASA/GCMD Earth Science Keywords
publication
Software Licence: GNU General Public License, Version 3, 29 June 2007, Copyright © 2019 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences (Leonie Pick)
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
Data Licence: CC BY 4.0
DOI of submitted paper
DOI
IsSupplementTo
10.5880/GFZ.2.3.2018.006
DOI
References
https://jupyter.org/
URL
References
http://xarray.pydata.org/en/stable
URL
References
https://www.unidata.ucar.edu/software/netcdf
URL
References
10.1007/s11214-017-0411-3
DOI
References
https://gitext.gfz-potsdam.de/lpick/ClassifyStorms
URL
References
10.1007/s11207-006-0133-2
DOI
Cites
10.1007/s11207-006-0132-3
DOI
Cites
10.1007/s11207-011-9737-2
DOI
Cites
10.1002/2017JA024100
DOI
Cites
10.1016/j.jastp.2009.02.005
DOI
Cites
http://www.wdc.bgs.ac.uk/
URL
References
http://wdc.kugi.kyoto-u.ac.jp/wdc/Sec3.html
URL
References
http://sidc.be/silso/datafiles
URL
References
eng
Coverage of input data set from the Northern hemisphere.
-157.9996
140.186
14.392
56.733
1930-01-01
2015-12-31T23:30:00
Coverage of input data set from the Southern hemisphere.
-171.775
115.95
-43.267
-13.807
1930-01-01
2015-12-31T23:30:00
http://dx.doi.org/doi:10.5880/GFZ.2.3.2019.003
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