AniMAIRE -- A New Openly Available Tool for Calculating Atmospheric Ionising Radiation Dose Rates and Single Event Effects During Anisotropic Conditions

TL;DR

AniMAIRE is an open-source Python toolkit that models atmospheric ionising radiation dose rates during anisotropic solar energetic particle events, incorporating complex physics to improve accuracy over existing models.

Contribution

It introduces a new physics-based model and Python toolkit for calculating radiation dose rates during anisotropic solar energetic particle events, expanding on previous models.

Findings

AniMAIRE's dose rate estimates fall between WASAVIES and CRAC:DOMO models.

Dose rate hotspots correspond to peaks in pitch angle distribution.

The model effectively analyzes time-dependent spectra and pitch angle distributions.

Abstract

AniMAIRE (Anisotropic Model for Atmospheric Ionising Radiation Effects) is a new model and Python toolkit for calculating radiation dose rates experienced by aircraft during anisotropic solar energetic particle events. AniMAIRE expands the physics of the MAIRE+ model such that dose rate calculations can be performed for anisotropic solar energetic particle conditions by supplying a proton or alpha particle rigidity spectrum, a pitch angle distribution, and the conditions of Earth's magnetosphere. In this paper, we describe the algorithm and top-level structure of AniMAIRE and showcase AniMAIRE's capabilities by analysing the dose rate maps that AniMAIRE produces when the time-dependent spectra and pitch angle distribution for GLE71 are inputted. We find that the dose rates AniMAIRE produces for the event fall between the dose rates produced by the WASAVIES and CRAC:DOMO models. Dose rate maps that evolve throughout the event are also shown, and it is found that each peak in the inputted pitch angle distribution generates a dose rate hotspot in each of the polar regions. AniMAIRE has been made available openly online so that it can be downloaded and run freely on local machines and so that the space weather community can easily contribute to it using Github forking.