Adverse (and extreme) Weather and the renewable energy system – across the time scales from definition to detection to prediction and return periods

Join us for the sixth session of the IIASA-wide seminar series, AI for Climate Science!

We are pleased to announce the next talk in the series, featuring Irene Schicker from GeoSphere. Austria.

Irene Schicker is a senior scientist at GeoSphere Austria, where she leads research on renewable energy meteorology and extreme weather and the intersection with deep learning methods, including AIWP models. Her work focuses on bridging weather and climate science with applications in the energy system, including wind and solar forecasting, AI-enhanced prediction, and extreme-event detection. She is actively involved in international collaborations such as the IEA Wind Task 51 “Forecasting for the Weather-Driven Energy System”, the Destination Earth on-demand Extremes Digital Twin, and several Austrian and European research initiatives. With a strong background in applied meteorology and stakeholder engagement, she develops methods and tools that translate atmospheric information into actionable insights for grid operators, energy planners, and policymakers.

For online participation, a registration is necessary.

Please register here.

Please note that the seminar is going to be recorded.

Title:
Adverse (and extreme) Weather and the renewable energy system – across the time scales from definition to detection to prediction and return periods

Abstract:
Adverse and extreme weather events pose growing challenges to renewable-based power systems, as variability and system stress increasingly coincide with climate-driven extremes across the different time scales. This presentation explores the full chain from definition to detection, prediction, and possible use of weather-related coding to calculationg of return periods of extreme events, highlighting their impacts on energy generation, grid stability, and system resilience. Case studies such as storm-driven wind cut-outs, prolonged Dunkelflauten, and heat- or cold-induced demand peaks illustrate how meteorological extremes translate into critical power system events. We discuss how definitions of extremes differ between meteorology and the power sector, and why multi-disciplinary approaches are essential. Advances in physics-informed detection methods, probabilistic forecasting, and digital-twin-based scenario simulations (e.g. Destination Earth Extremes) are presented as pathways to anticipate and mitigate adverse impacts. By bridging weather and climate timescales, the talk emphasizes the importance of consistent definitions, robust indices, and uncertainty-aware forecasts to support decision-making and enhance the resilience of renewable energy systems under a changing climate.