Issue |
J. Space Weather Space Clim.
Volume 8, 2018
Measurement, Specification and Forecasting of the Solar Energetic Particle Environment and GLEs
|
|
---|---|---|
Article Number | A31 | |
Number of page(s) | 22 | |
DOI | https://doi.org/10.1051/swsc/2018010 | |
Published online | 29 May 2018 |
Research Article
Updated Model of the Solar Energetic Proton Environment in Space
1
European Space Research and Technology Centre (ESTEC), Space Environment and Effects Section Keperlaan 1,
2200AG
Noordwijk, The Netherlands
2
DH Consultancy,
Leuven, Belgium
3
SPARC Space Applications & Research Consultancy,
Athens, Greece
4
Kallisto Consultancy,
Farnborough, United Kingdom
5
Department of Physics and Astronomy, University of Turku,
20014
Turku, Finland
* Corresponding author: piers.jiggens@esa.int
Received:
1
September
2017
Accepted:
24
January
2018
The Solar Accumulated and Peak Proton and Heavy Ion Radiation Environment (SAPPHIRE) model provides environment specification outputs for all aspects of the Solar Energetic Particle (SEP) environment. The model is based upon a thoroughly cleaned and carefully processed data set. Herein the evolution of the solar proton model is discussed with comparisons to other models and data. This paper discusses the construction of the underlying data set, the modelling methodology, optimisation of fitted flux distributions and extrapolation of model outputs to cover a range of proton energies from 0.1 MeV to 1 GeV. The model provides outputs in terms of mission cumulative fluence, maximum event fluence and peak flux for both solar maximum and solar minimum periods. A new method for describing maximum event fluence and peak flux outputs in terms of 1-in-x-year SPEs is also described. SAPPHIRE proton model outputs are compared with previous models including CREME96, ESP-PSYCHIC and the JPL model. Low energy outputs are compared to SEP data from ACE/EPAM whilst high energy outputs are compared to a new model based on GLEs detected by Neutron Monitors (NMs).
Key words: SEP / Radiation Environment / Statistics and probability / Modelling / Dose
© P. Jiggens et al., Published by EDP Sciences 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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