Hemispheric Prediction of Solar Cycles 25 and 26 From Multivariate Sunspot Time-series Data via Informer Models

Solar activity plays an important role in influencing space weather, making it important to understand numerous aspects of spatial and temporal variations in the Sun’s radiative output. High-performance deep learning models and long-term observational records of sunspot relative numbers are essential for solar cycle forecasting. Using the multivariate time series of monthly sunspot relative numbers provided by the National Astronomical Observatory of Japan and two Informer-based models, we forecast the amplitude and timing of solar cycles 25 and 26. The main results are as follows: (i) The maximum amplitude of solar cycle 25 is higher than the previous solar cycle 24 and the following solar cycle 26, suggesting that the long-term oscillatory variation of sunspot magnetic fields is related to the roughly centennial Gleissberg cyclicity. (ii) Solar cycles 25 and 26 exhibit a pronounced Gnevyshev gap, which might be caused by two non-coincident peaks resulting from solar magnetic flux transported by meridional circulation and mid-latitude diffusion in the convection zone. (iii) Hemispheric prediction of sunspot activity reveals a significant north-south asynchrony, with activity level of the Sun being more intense in the southern hemisphere. These results are consistent with expectations derived from precursor methods and dynamo theories, and further provide evidence for internal changes in solar magnetic field during the decay of the Modern Maximum.