Effective energy of cosmogenic isotope (¹⁰Be, ¹⁴C and ³⁶Cl) production by solar energetic particles and galactic cosmic rays
Koldobskiy, Sergey; Usoskin, Ilya; Kovaltsov, Gennady A. (2021-01-23)
Koldobskiy, S., Usoskin, I., & Kovaltsov, G. A. (2022). Effective energy of cosmogenic isotope (¹⁰Be, ¹⁴C and ³⁶Cl) production by solar energetic particles and galactic cosmic rays. Journal of Geophysical Research: Space Physics, 127, e2021JA029919. https://doi.org/10.1029/2021JA029919
© 2022. The Authors.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2022041929429
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Abstract
Cosmogenic isotopes ¹⁴C, ¹⁰Be and ³⁶Cl measured in datable natural archives provide the only known quantitative proxy for cosmic-ray (CR) and solar-activity variability before the era of direct measurements. Studies of relations between the measured isotope concentrations and CR variability require complicated modeling including the isotope production and transport in the terrestrial system. Here we propose a rough “effective energy” method to make quick estimates of the CR variability directly from the cosmogenic data using an approximate linear scaling between the measured isotope concentrations and the energy-integrated flux of CR above the effective energy. The method is based on the thoroughly computed effective yield function presented here. A simple way to account for the variable geomagnetic field is also provided. The method was developed for both solar energetic particles (SEPs) and galactic cosmic ray (GCR) variability and is shown to provide a robust result within 20% and 1% accuracy, respectively, without an assumption of the specific spectral shape. Applications of the effective-energy method to the known extreme SEP events and the secular GCR variability are discussed. The new method provides a simple and quick tool to assess the CR variability in the past. On the other hand, it does not supersede the full detailed modeling required for precise results.
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