Modelling Cosmic Radiation Events in the Tree-ring Radiocarbon Record

TL;DR

This paper introduces 'ticktack', an open-source Python tool for modeling the global carbon cycle to analyze high-resolution tree-ring radiocarbon data, revealing insights into rare cosmic radiation events called Miyake events.

Contribution

The paper presents 'ticktack', the first open-source Python package that integrates carbon cycle models with Bayesian inference to analyze Miyake events in radiocarbon data.

Findings

Miyake events do not show a consistent link to the solar cycle.

Several Miyake events have extended durations challenging existing models.

Posterior analysis of all six known Miyake events was performed.

Abstract

Annually-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', 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.