The Solar Dynamics Observatory (SDO) takes about a terabyte and a half of data a day, which is more data than any other satellite in the NASA Heliophysics Division. One of the data products released by the Solar Dynamics Observatory science team is called Space-weather HMI Active Region Patches, or SHARPs. SHARPs include patches of vector magnetic field data taken by the Helioseismic and Magnetic Imager (HMI) instrument aboard SDO. These patches encapsulate automatically-detected active regions. SHARP data also include spaceweather keywords describing these active regions. Bobra & Couvidat (2015), Bobra & Ilonidis (2016), and Jonas et al. (2018) used machine-learning algorithms to show that these spaceweather keywords are useful for predicting solar activity.

Users can access the SHARP data with a SunPy affiliated package called drms. If you use drms in your research, please cite The SunPy Community et al. 2020 and Glogowski et al. 2019. We released v0.1.0 of this repository and published it on Zenodo as .

This repository contains several notebooks and functions designed to interact with and understand SHARP data. The requirements.txt file lists all the packages necessary to run the notebooks and functions in this repository.

Getting Started

• The plot_swx_d3.ipynb notebook is a good place to get started. This notebook queries data using the SunPy affiliated package called drms, generates plots of keywords and images, demonstrates how to query the SHARP data, and exports data in a variety of formats.

Space-weather Keywords

• The calculate_sharpkeys.py file contains all the functions to calculate spaceweather keywords from vector magnetic field data. Sample data are included in this repository under the files directory. For an explanation of the variable cdelt1_arcsec, in the function get_data(), see cdelt1_arcsec.pdf. See SHARP_Issue_Tracker.md for a list of known issues with the SHARP data.

Coordinates

• The feature_extraction.ipynb notebook identifies which pixels in an image taken by the Atmospheric Imaging Assembly (AIA) instrument on SDO fall within the SHARP bounding box by applying coordinate transformations.
• The active_region_distances.ipynb notebook calculates the distance between two SHARP regions.

Visualizations

• The hedgehog.ipynb notebook develops an aesthetically pleasing way to visualize a vector magnetic field using SHARP data.
• The movie.ipynb notebook generates movies of SHARP data.

Disambiguation

• The disambiguation.py file contains several functions that disambiguate the azimuthal component of the vector magnetic field data and construct the field vector in spherical coordinate components on a CCD grid. This works on both the SHARP data and full-disk data. See disambiguate_data.py for some examples.

Parallelization

• See sharp-features.ipynb for a demonstration on how to efficiently calculate SHARP keywords using significant computational resources (in this case, the NASA Ames Pleiades supercomputer) and a Python package for parallelization called Dask.

If you use the Space-weather HMI Active Region Patch data in your research, please consider citing our paper and this software repository.

Here is the bibtex entry for the paper:

@ARTICLE{2014SoPh..289.3549B,
   author = {{Bobra}, M.~G. and {Sun}, X. and {Hoeksema}, J.~T. and {Turmon}, M. and 
	{Liu}, Y. and {Hayashi}, K. and {Barnes}, G. and {Leka}, K.~D.
	},
    title = "{The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs - Space-Weather HMI Active Region Patches}",
  journal = {\solphys},
archivePrefix = "arXiv",
   eprint = {1404.1879},
 primaryClass = "astro-ph.SR",
 keywords = {Active regions, magnetic fields, Flares, relation to magnetic field, Instrumentation and data management},
     year = 2014,
    month = sep,
   volume = 289,
    pages = {3549-3578},
      doi = {10.1007/s11207-014-0529-3},
   adsurl = {http://adsabs.harvard.edu/abs/2014SoPh..289.3549B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

And here is the bibtex entry for the software repository:

@misc{monica_g_bobra_2021_5131292,
  author       = {Monica G. Bobra and
                  Xudong Sun (孙旭东) and
                  Michael J. Turmon},
  title        = {mbobra/SHARPs: SHARPs 0.1.0 (2021-07-23)},
  month        = jul,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {v0.1.0},
  doi          = {10.5281/zenodo.5131292},
  url          = {https://doi.org/10.5281/zenodo.5131292}
}