Modelling cosmic radiation events in the tree-ring radiocarbon recordZhang, Q. ORCID: https://orcid.org/0000-0002-0906-8533, Sharma, U. ORCID: https://orcid.org/0000-0002-0771-8109, Dennis, J. A. ORCID: https://orcid.org/0000-0001-8125-6494, Scifo, A. ORCID: https://orcid.org/0000-0002-7174-3966, Kuitems, M. ORCID: https://orcid.org/0000-0002-8803-2650, Büntgen, U. ORCID: https://orcid.org/0000-0002-3821-0818, Owens, M. J. ORCID: https://orcid.org/0000-0003-2061-2453, Dee, M. W. ORCID: https://orcid.org/0000-0002-3116-453X and Pope, B. J. S. ORCID: https://orcid.org/0000-0003-2595-9114 (2022) Modelling cosmic radiation events in the tree-ring radiocarbon record. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 478 (2266). ISSN 1471-2946
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1098/rspa.2022.0497 Abstract/SummaryAnnually resolved measurements of the radiocarbon content in tree-rings have revealed rare sharp rises in carbon-14 production. These ‘Miyake events’ are likely produced by rare increases in cosmic radiation from the Sun or other energetic astrophysical sources. The radiocarbon produced is not only circulated through the Earth’s atmosphere and oceans, but also absorbed by the biosphere and locked in the annual growth rings of trees. To interpret high-resolution tree-ring radiocarbon measurements therefore necessitates modelling the entire global carbon cycle. Here, we introduce ‘ticktack’ (https://github.com/SharmaLlama/ticktack/), the first open-source Python package that connects box models of the carbon cycle with modern Bayesian inference tools. We use this to analyse all public annual 14C tree data, and infer posterior parameters for all six known Miyake events. They do not show a consistent relationship to the solar cycle, and several display extended durations that challenge either astrophysical or geophysical models.
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