Aurora borealis visibility, or ABV

• Running it
  • Setup
  • Plot the aurora events, this is it!
    • Notes and caveats
  • Tips
• Know more
• Cached data
• Sources and credits

ABV will graph aurora borealis visibility throughout years, with the planetary K_p-index plotted and with decent thresholds. It should also show the trend line of sunspots visible, which correlates with a better chance of seeing auroras in the upcoming year (or not). If the year is not over yet it will even try to be smart enough and pull forecast data and plot it for your convenience.

Basically this was created to show my wife the best time of the year and annual average occurrences of auroras in the northern hemisphere, because she didn't believe me when I told her about the K_p-index and multi year cycles of correlated sunspots etc. She wanted to see an aurora but nobody could tell her the best time nor place to go with minimal guarantee to see one.

There you have it: pay attention to the roughly 7-years or 11-years long solar cycles suggested by the sunspots trend, plus streak of geomagnetic storms confirmed by K_p-index above certain thresholds. Just you wait, the current 3 years period is looking fantastic...

All that said: I'm a complete ignorant and armchair nerd about such things, so take it all with a sol-sized grain of salt. This is all informative and nice and cool, but that's about it.

Running it

Setup

Prep step... install Python's virtualenv on your system, which on macOS can be done with brew install pyenv pyenv-virtualenv and you'll need to adapt that for your system like Linux.

Local shell config in ~/.profile:

export PYENV_ROOT="$HOME/.pyenv"
export PATH="$PYENV_ROOT/bin:$PATH"

eval "$(pyenv init --path)"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"

Python stuff:

git clone https://github.com/caiobegotti/aurora-borealis-visibility.git
cd aurora-borealis-visibility/

pyenv install 3.8.10
pyenv virtualenv 3.8.10 myenv
pyenv activate myenv

pyenv local myenv
pip install --upgrade pip
pip install matplotlib

Plot the aurora events, this is it!

$ ./ABV.py 2024
$ open kp_index_2024.png

$ ./ABV.py --help

    Usage: python script.py <YEAR> [--quiet] [--simplified] [--refresh] [--help]

    Options:
    <YEAR>         The year for which the Kp index data should be plotted.
    --quiet        Suppress all logs and outputs.
    --simplified   Hide the legend box on the plot, makes graphs bigger.
    --refresh      Force fetching the remote data (refreshing local cache).
    --help         Show this help message.

Notes and caveats

• the green trend line of sunspots doesn't match the scale of the rest of the graph, it's just informative
• the red aurora events are just the meaningful geomagnetic storms recorded, it doesn't mean you can't see auroras below those dots, you definitely can but they won't be as spectacular
• the solar cycles don't have peaks necessarily, their peak looks more like the M letter being that a 3 years cycle can have a "bad" year in between with much less sunspots
• once again, there is some correlation between sunspots and geomagnetic storms leading to auroras but such correlation is not strong enough to guarantee sights
• right after the equinox dates in the northern hemisphere is when auroras start to look really beautiful so the period is shown as a reminder
• forecasted data may show up wrong, be incomplete and might not respect visibility thresholds

Tips

1. Download all available years at once, updates local cache:

   for y in $(seq 1932 2024); do ./ABV.py ${y} --quiet --refresh; done
   

2. Combine multiple years locally so you can visualize them together, say, using the data between 2010 and today. You will need the montage command from ImageMagick, likely via brew install imagemagick on macOS:

   montage kp_index_201* kp_index_202* -tile 5x5 -geometry +2+2 combined_image.png
   

   Just note that 5x5 makes a pretty big image already hard to view in small monitors. You can also combine montage with running ABV using --simplified for clarity.

Know more

1. Kalman-filtered sunspots optimized forecasts, the best place to figure out whether your vacations are going to be ruined or not after generating graphs with ABV: https://www.sidc.be/SILSO/ssngraphics and https://www.sidc.be/SILSO/predikfsc specifically.

2. Solar cycle progressions from NOAA can be helpful when planning your vacations to places like Island or Norway too: https://www.swpc.noaa.gov/products/solar-cycle-progression will make it clearer the relation between sunspots numbers and geomagnetic storms.

3. I can also recommend checking out UAF's aurora forecasts for short-term predictions which may be quicker to grasp.

Cached data

The cache directory holds all available data since 1932 until the end of Q3 2024. If you're not online it will simply process the data from the cache, otherwise it pulls the data via the API client but that may break over time if the service changes format etc.

Sources and credits

The file getKpindex.py and respective data come from the GFZ German Research Centre for Geosciences (under CC BY 4.0).

Sunspots data like cache/SN_y_tot_V2.0.csv is under CC BY-NC 4.0 license and comes from WDC-SILSO, Royal Observatory of Belgium, Brussels.