Reconstruction of Solar EUV Irradiance Using CaII K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification

TL;DR

This paper introduces SEMNet, a Bayesian deep learning model that reconstructs long-term solar EUV irradiance from CaII K images, filling data gaps and quantifying uncertainty to improve understanding of solar impacts on Earth's climate.

Contribution

The study presents SEMNet, a novel Bayesian deep learning approach that uses CaII K images to reconstruct and extend solar EUV flux measurements over multiple solar cycles with uncertainty quantification.

Findings

SEMNet accurately reconstructs EUV flux with reliable uncertainty bounds.

CaII K images serve as effective proxies for long-term EUV flux estimation.

The method extends EUV flux data back to the 1950s, filling historical gaps.

Abstract

Solar extreme ultraviolet (EUV) irradiance plays a crucial role in heating the Earth's ionosphere, thermosphere, and mesosphere, affecting atmospheric dynamics over varying time scales. Although significant effort has been spent studying short-term EUV variations from solar transient events, there is little work to explore the long-term evolution of the EUV flux over multiple solar cycles. Continuous EUV flux measurements have only been available since 1995, leaving significant gaps in earlier data. In this study, we propose a Bayesian deep learning model, named SEMNet, to fill the gaps. We validate our approach by applying SEMNet to construct SOHO/SEM EUV flux measurements in the period between 1998 and 2014 using CaII K images from the Precision Solar Photometric Telescope. We then extend SEMNet through transfer learning to reconstruct solar EUV irradiance in the period between 1950 and 1960 using CaII K images from the Kodaikanal Solar Observatory. Experimental results show that SEMNet provides reliable predictions along with uncertainty bounds, demonstrating the feasibility of CaII K images as a robust proxy for long-term EUV fluxes. These findings contribute to a better understanding of solar influences on Earth's climate over extended periods.