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Source code for ARGUS (AI-based Reconstruction of the Geospace Unified System). The principal part is the FORTRAN source code for the Stephens et al. (2019) empirical geomagnetic field model, termed SST19, (https://doi.org/10.1029/2018JA025843).
GIC Forecasting & Analysis — A data-driven framework for modeling Geomagnetically Induced Currents using solar wind data, SuperMAG observations, and advanced ML techniques. Integrates domain physics, feature engineering, and imputation strategies to tackle real-world space weather challenges.
🚀 CosmoPredict is an AI-powered Space Weather & Rocket Simulation platform that uses real-time NASA/NOAA data, Machine Learning, and 3D visualization to predict geomagnetic storms and analyze their impact on rocket trajectories and satellite systems.
In this challenge, your task is to develop models for forecasting Dst that push the boundary of predictive performance, under operationally viable constraints, using the real-time solar-wind (RTSW) data feeds from NOAA’s DSCOVR and NASA’s ACE satellites. Improved models can provide more advanced warning of geomagnetic storms and reduce errors in…
connects to NASA’s DONKI (Database Of Notifications, Knowledge and Information) API to retrieve and display information about space weather events, especially Coronal Mass Ejections (CMEs).
Research-grade space weather simulation dashboard using real NOAA and NASA data for CME propagation, Kp estimation, impact assessment, synchronized playback, and optional 3D visualization — fully client-side.
Archivos relacionado con mi proyecto de TFG de Física en la UCM, Tormentas Geomagnéticas y su Impacto en la Biosfera (Geomagnetic Storms and Their Impact on the Geomagnetic Field)
🌎 Прогнозирование геомагнитных индексов Dst и AE на основе временных рядов параметров солнечного ветра для предсказания магнитных бурь и авроральной активности