In space weather prediction, it is difficult to infer geomagnetic indices such as Dst or Kp from knowledge of the solar wind at the Sun-Earth L1 point. This package provides 3 methods for achieving this for Dst (Kp will be added in the future), namely: Temerin and Li (2002), O'Brien and McPherron (2000), and Burton et al. (1975).
Status: work in progress, November 2018 / issue with offsets needs to be resolved (fit_offset.py)
If you plan to use this code for generating results for peer-reviewed scientific publications, please contact me (see bio).
- python 3 anaconda, non-standard packages: sunpy, seaborn
- I use python 3.5.2 / IPython 4.2.0 on MacOSX Mojave
- After cloning the repository, run on the command line:
$ python solar_wind_to_dst.py
- or in ipython
$ run solar_wind_to_dst
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The code will download OMNI2 hourly data (158 MB currently) into the main folder, convert the time to the matplotlib time format, and save the data as a numpy recarray in a python pickle file, so when the structure 'omni' contains the data, the variables can be used as 'omni.time','omni.btot', 'omni.speed' etc.
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The main function to convert a given solar wind to dst is 'make_dst_from_wind' in the dst_module.py file
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The main program solar_wind_to_dst.py creates a plot of the solar wind, the observed Dst and a Dst calculated from the solar wind for a time interval selected in solar_wind_to_dst.py