The Advanced Thermosphere Modelling for Orbit Prediction project aimed to build a new thermosphere model with the potential to spawn an operational version. Accurate models enable precise air drag computation which is mandatory for precise tracking of space objects in Low Earth Orbit. My role was to validate newly developed models at various periods during the solar cycle.
Ensemble techniques combine multiple models or data sets together to produce more accurate results. Perfected by weather forecasters and data scientists, I am developing this state-of-the-art technique for use in improving solar eruption forecasts.
FLARECAST developed a fully automated solar-flare forecasting system with advanced machine learning techniques and near-real-time verification. I was a Project Management Board member and Work Package contributer to the project, with my involvement focused on verification of results for operational use, scientific exploration, and dissemination to government, industry, and the public.
Developed by the international solar flare research community and hosted by NASA's Community Coordinated Modeling Centre, the scoreboard is an automated system that allows model developers and operational space weather centres to upload their issued flare predictions. The forecasts are shown on an interactive display to allow real-time global comparison of predictions.
The Heliospheric Cataloguing, Analysis and Techniques Service provides detailed a large catalogue of coronal mass ejection (CME) events observed by heliospheric imagers onboard the two NASA/STEREO spacecraft. My role was to analyse the solar surface sources of the CMEs in the catalogue, correlating magnetic active region properties with CME kinematics.
The Solar Monitor Active Region Tracker is an automated system for detecting, tracking, and cataloguing solar active regions throughout their evolution. Originally written in the IDL programming language, I have now updated it with Python for use in operational solar eruption monitoring.