This data publication includes the half-hourly Hp30 and ap30 indices as well as the hourly Hp60 and ap60 indices, collectively denoted as Hpo. This dataset is based on near real-time geomagnetic observatory data provided by 13 contributing observatories. It is derived and distributed by GFZ German Research Centre for Geosciences. When using the Hpo index, please cite this data publication as well as the accompanying publications Yamazaki et al. (2024) and Yamazaki et al. (2022), which serve as documentation of the Hpo.
The dataset is organised in yearly files, which, for the current year, are updated on a monthly basis. Typically, during the second week of a month, the data for the previous month is appended to the current year's file. The files are in ASCII files and start with header lines marked with # (hash).
The Hpo index was initially developed within the H2020 project SWAMI (grant agreement No 776287) and is produced by Geomagnetic Observatory Niemegk, GFZ German Research Centre for Geosciences. It derives from the same 13 geomagnetic observatories that also contribute to the Kp index (Matzka et al., 2021, https://doi.org/10.5880/Kp.0001). They are listed as contributors to this data publication.
With the introduction of the DOI for the Hpo index (Matzka et al, 2021, https://doi.org/10.5880/Hpo.0001), this DOI landing page and the associated HTTPS server linked to the DOI become the primary archive of Hpo (while the other established index distribution mechanisms at GFZ will be maintained in parallel). With the DOI, the dataset can grow with time, but a change of the data, once published, is not possible. If necessity arises in the future to correct already published values, then the corrected dataset will be published with a new DOI. Older DOIs and data sets will then still be available. For each DOI, an additional versioning mechanism will be available to document changes to the files such as header or format changes, which do not affect the integrity of the data. The DOI https://doi.org/10.5880/Hpo.0003 identifies the current version. A format description and a version history are provided in the data download folder.
This data publication includes the half-hourly Hp30 and ap30 indices as well as the hourly Hp60 and ap60 indices, collectively denoted as Hpo. This dataset is based on near real-time geomagnetic observatory data provided by 13 contributing observatories. It is derived and distributed by GFZ German Research Centre for Geosciences. When using the Hpo index, please cite this data publication as well as the accompanying publication Yamazaki et al. (submitted), which serves as documentation of the Hpo.
The dataset is organised in yearly files, which, for the current year, are updated on a monthly basis. Typically, during the second week of a month, the data for the previous month is appended to the current year's file. The files are in ASCII files and start with header lines marked with # (hash).
The Hpo index was developed within the H2020 project SWAMI (grant agreement No 776287) and is produced by Geomagnetic Observatory Niemegk, GFZ German Research Centre for Geosciences. It derives from the same 13 geomagnetic observatories that also contribute to the Kp index (Matzka et al., 2021, https://doi.org/10.5880/Kp.0001). They are listed as contributors to this data publication.
With the introduction of the DOI for the Hpo index (Matzka et al, 2021, https://doi.org/10.5880/Hpo.0001), this DOI landing page and the associated HTTPS server linked to the DOI become the primary archive of Hpo (while the other established index distribution mechanisms at GFZ will be maintained in parallel). With the DOI, the dataset can grow with time, but a change of the data, once published, is not possible. If necessity arises in the future to correct already published values, then the corrected dataset will be published with a new DOI. Older DOIs and data sets will then still be available. For each DOI, an additional versioning mechanism will be available to document changes to the files such as header or format changes, which do not affect the integrity of the data. The DOI https://doi.org/10.5880/Hpo.0002 identifies the current version. A format description and a version history are provided in the data download folder.
This data publication includes the half-hourly Hp30 and ap30 indices as well as the hourly Hp60 and ap60 indices. All are unitless and collectively denoted as Hpo or Hpo index family. The dataset is based on near real-time geomagnetic observatory data provided by 13 contributing observatories. It is derived and distributed by GFZ German Research Centre for Geosciences. When using the Hpo index, please cite this data publication as well as the accompanying publication Matzka et al. (in prep), which serves as documentation of the Hpo index family.
The dataset is organised in yearly files, which, for the current year, are updated on a monthly basis. Typically, during the second week of a month, the data for the previous month is appended to the current year's file. The files are in ASCII files and start with header lines marked with # (hash).
The Hpo index was developed within the H2020 project SWAMI and is produced by Geomagnetic Observatory Niemegk, GFZ German Research Centre for Geosciences. It derives from the same 13 geomagnetic observatories that also contribute to the Kp index (Matzka et al., 2021). They are listed as contributors to this data publication.
With the introduction of the DOI ‘https://doi.org/10.5880/Hpo.0001’, this DOI landing page and the associated FTP server linked to the DOI become the primary archive of Hpo (while the other established index distribution mechanisms at GFZ will be maintained in parallel). With the DOI, the dataset can grow with time, but a change of the data, once published, is not possible. If necessity arises in the future to correct already published values, then the corrected dataset will be published with a new DOI. Older DOIs and data sets will then still be available. For each DOI, an additional versioning mechanism will be available to document changes to the files such as header or format changes, which do not affect the integrity of the data. The DOI https://doi.org/10.5880/Hpo.0001 identifies the current version. A format description is provided in the data download folder.
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 contains1. 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)