Solar Cycle Prediction: Challenges, Progress, and Future Perspectives

TL;DR

This paper reviews the challenges and progress in solar cycle prediction, analyzing past methods and emphasizing the importance of physical models like the polar field and dynamo models for future accuracy.

Contribution

It provides a comprehensive analysis of various prediction methods, highlights their limitations, and discusses future directions for improving solar cycle forecasts.

Findings

Most prediction methods failed to accurately predict cycle peaks.

ML models showed limited success in solar cycle prediction.

Physically supported approaches like polar field predictions are promising but have timing limitations.

Abstract

Reliable prediction of the solar cycle is a formidable challenge, yet it is increasingly vital in our technology-dependent society as solar activity drives space weather. Various methods, including precursors, nonlinear curve fitting and extrapolation, statistical and Machine Learning (ML) models, and dynamo and surface flux transport (SFT) models, were implemented to predict past cycles. Analysing about 100 predictions for Solar Cycle 24 and over 130 for Solar Cycle 25, we find that most methods largely failed to predict the peak correctly: Cycle 24 was statistically predicted to be a strong cycle, whereas Cycle 25 was predicted to be a weak cycle. By and large, predictions made only after the cycle began became closer to reality. ML-based models also produced discouraging results. The polar field and its proxy-based predictions are the most physically supported approach to prediction; however, applying them much earlier, before the solar minimum, may yield inaccurate results. Dynamo models are progressively improving both in understanding and in forecasting; however, they need to improve by accurately assimilating the observed polar field data and additional physics, such as meridional flow variations. Solar dynamo theory, complemented by the SFT model and observations, demonstrates that the prediction of a cycle before the time of its previous cycle's maximum is meaningless. The current solar cycle is declining, and the community is now preparing for the prediction of the next cycle. Thus, this review will guide future studies.