sunspots

End-to-end time series analysis and forecasting of monthly sunspot numbers using classical machine learning and deep learning models, including linear regression, tree-based methods, and advanced PyTorch architectures.

Surface Flux Transport modelling in one dimension (latitude).

Reproducible pipeline that fetches and aligns NAO, ENSO, and sunspot time series into monthly/yearly panels for climate-driver correlation and predictive modeling.

SWATNet - School1: Introduction to Space Weather, November 8-12, 2021

SunspotsYoloDataset: annotated solar images captured with smart telescopes (January 2023 - May 2024) - for sunspots detection

Python toolkit correlating a GitHub user's commit history with solar and geomagnetic activity — sunspot numbers (SILSO), F10.7 flux, Dst and ap indices from OMNI2/NOAA SWPC. Computes lagged Pearson/Spearman correlations, Lomb-Scargle periodograms, and bootstrap CIs with heatmaps and multi-user comparison.

Use FFT to analyse sunspot activity

R interface for fetching selected astronomical time series available in free access.

This project predicts sunspot activity using an LSTM model for time series data. Built with TensorFlow and Keras, it uses Huber loss for outlier handling and MAE for performance evaluation. The dataset, sourced from Kaggle or SIDC, spans over 270 years of monthly sunspot data.

A spatially-resolved, multi-wavelength analysis framework for studying sunspot Center-to-Limb Variations (CLV) using SDO/HMI and SDO/AIA data.

Exploration of time series forecasting concepts and techniques

Project aims at modeling the size distribution of sunspots greater than 60 millionths of a solar hemisphere (MSH) using a truncated log-normal distribution.

The Solar Benchmark: Rotational Modulation of the Sun Reconstructed from Archival Sunspot Records