Speaker
Description
Long-term solar magnetic variability governs the space climate conditions. These variations also modulate the galactic cosmic ray influx reaching Earth and subsequently regulate the production of cosmogenic isotopes in the Earth's atmosphere. By harnessing the multi-millennial records of these radio-isotope proxies archived in various natural terrestrial reservoirs, such as tree rings and ice cores, it is possible to reconstruct past solar magnetic activity predating the telescopic era.
However, existing regression-based reconstruction methods often yield negative sunspot numbers during low solar activity phases, which are unphysical.
To address this, we have recently developed a Monte‑Carlo inversion framework consisting of a sequence of physics‑based forward models, supplemented by an approximate Bayesian computation-based posterior selection, to infer the most plausible temporal evolution of solar magnetic parameters, including solar modulation potential, open solar flux, and sunspot numbers. Our approach produces physically consistent, uncertainty‑quantified multi-millennial reconstructions of annually resolved sunspot numbers.
The reconstruction shows excellent agreement with direct observations during the telescopic era. We further identify epochs of extreme solar activity, such as grand solar minima, and examine their statistical properties.
These results offer valuable insights into long-term solar variability and provide improved constraints for long-term solar dynamo modelling. The annual-scale reconstructions are also directly usable for solar irradiance estimation, terrestrial climate modelling, and studies of long‑term Sun-Earth coupling.