PRIME (Probabilistic Regressor for Input to the Magnetosphere Estimation) is a probabilistic algorithm that uses solar wind time history from L1 monitors to generate predictions of near-Earth solar wind with uncertainties. For codes used to create the figures in the paper, see the 'paper' subdirectory. Python implementation can be found in prime_bin subdirectory. CDFs of PRIME's outputs are being compiled and will be included in a future release.
For information on PRIME, including results from its validation and caveats on its use, please see the paper.
If you make use of PRIME, please cite it:
@article{obrien_prime_2023,
title = {{PRIME}: a probabilistic neural network approach to solar wind propagation from {L1}},
volume = {10},
issn = {2296-987X},
shorttitle = {{PRIME}},
url = {https://www.frontiersin.org/articles/10.3389/fspas.2023.1250779/full},
doi = {10.3389/fspas.2023.1250779},
urldate = {2023-11-13},
journal = {Frontiers in Astronomy and Space Sciences},
author = {O’Brien, Connor and Walsh, Brian M. and Zou, Ying and Tasnim, Samira and Zhang, Huaming and Sibeck, David Gary},
month = sep,
year = {2023},
pages = {1250779},
}