2026-08-04T21:52:25Zhttp://doidb.wdc-terra.org/oaip/oai
oai:doidb.wdc-terra.org:80152026-06-10T10:27:51ZDOIDBDOIDB.GFZ
false4DOIDB.GFZ 10.5880/GFZ.2.7.2024.001 Collin, Daniel Daniel Collin 0000-0001-5426-3242 GFZ German Research Centre for Geosciences, Potsdam, Germany Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany Shprits, Yuri Yuri Shprits 0000-0002-9625-0834 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany Department of Earth, Planetary, and Space Sciences, University of California Los Angeles, Los Angeles, USA Hofmeister, Stefan J. Stefan J. Hofmeister 0000-0001-7662-1960 Columbia Astrophysics Laboratory, Columbia University, New York, USA Bianco, Stefano Stefano Bianco GFZ German Research Centre for Geosciences, Potsdam, Germany Gallego, Guillermo Guillermo Gallego Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany Einstein Center Digital Future, Berlin, Germany Solar Wind Speed Prediction from Coronal Holes GFZ Data Services 2024 Coronal hole solar wind speed high-speed stream machine learning EARTH SCIENCE > SUN-EARTH INTERACTIONS > SOLAR ACTIVITY > CORONA HOLES EARTH SCIENCE > SUN-EARTH INTERACTIONS > SOLAR ACTIVITY > CORONAL MASS EJECTIONS EARTH SCIENCE > SUN-EARTH INTERACTIONS > SOLAR ACTIVITY > SOLAR IMAGERY EARTH SCIENCE > SUN-EARTH INTERACTIONS > SOLAR ENERGETIC PARTICLE PROPERTIES > PARTICLE SPEED Collin, Daniel Daniel Collin 0000-0001-5426-3242 GFZ German Research Centre for Geosciences, Potsdam, Germany Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany Collin, Daniel Daniel Collin 0000-0001-5426-3242 GFZ German Research Centre for Geosciences, Potsdam, Germany Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany Shprits, Yuri Yuri Shprits 0000-0002-9625-0834 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany Department of Earth, Planetary, and Space Sciences, University of California Los Angeles, Los Angeles, USA Hofmeister, Stefan J. Stefan J. Hofmeister 0000-0001-7662-1960 Columbia Astrophysics Laboratory, Columbia University, New York, USA Bianco, Stefano Stefano Bianco GFZ German Research Centre for Geosciences, Potsdam, Germany Gallego, Guillermo Guillermo Gallego Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany Einstein Center Digital Future, Berlin, Germany Collin, Daniel GFZ German Research Centre for Geosciences, Potsdam, Germany, Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany 2024-07-10 Dataset 10.1029/2024SW004125 10.7910/DVN/C2MHTH 10.3847/1538-4357/ac5f43 2.0 CC BY 4.0 The solar wind, a stream of charged particles originating from the Sun and transcending interplanetary space, poses risks to technology and astronauts. In particular geomagnetic storm, can lead to severe damage. One major cause of geomagnetic storms are high-speed solar wind streams (HSSs), emitted by coronal holes on the solar surface.

This data set provides (1) coronal hole segmentation maps, extracted from solar EUV images, (2) the heliospheric latitude of Earth, needed to compute coronal hole area features, and (3) a machine learn-ing data set, consisting of input features related to coronal holes and the solar wind speed at Earth as the target output, used to predict the solar wind speed with a lead time of four days. Additionally, we provide (4) a list of high-speed solar wind streams (HSSs) and coronal mass ejections (CMEs) which can be used for investigating the effectiveness of a prediction model with regards to HSSs and CMEs, and (5) the predicted time series from the article. All data are provided as used in the publication Collin et al. (2025). For all details on the data preparation and usage, we refer to the original article.
Version history:
28 February 2025: release of version 2.0 (all files of version 1.0 are in the “previous-versions” folder. Changes in version 2.0:
• Replacement of most pickle files with csv files
• Addition of a new zip folder with predictions used in the related article (2024-001_Collin-et-al_predicted_time_series_v2.0)
• Updated data description
• The file 2024-001_Collin-et-al_1_segmentation_maps_v1.0.zip remains unchanged