High Spatiotemporal Resolution Data-Driven Hindcasting and Forecasting of Daily Snow Dynamics from Climate Data
Date:
Location:
Hörsaal Davos
Organised by:
SLF Davos
Speakers:
Fatemeh Zakeri, Geostatistical Algorithms & Image Analysis research group, University of Lausanne
Languages:
English
Type of event:
Presentations and colloquia
Audience:
Everyone who is interested in this topic
Mountain snowpacks are essential for water supply, ecosystems, and hydropower. But as climate change alters when and how snow accumulates and melts, predicting future snow dynamics has become increasingly complex.
In this talk, I’ll present a data-driven approach developed during my PhD at UNIL and UC Berkeley, under the supervision of Prof. Mariéthoz and Prof. Girotto. This work addresses the challenge by transforming large-scale climate and satellite data into high-resolution maps of snow cover and Snow Water Equivalent (SWE).
Focusing on the Swiss Alps, I’ll show how we use analog-based methods, drawing on patterns from past and present climate conditions, to reconstruct historical snow dynamics and project future ones. This approach has produced daily SWE projections at 500 m resolution from
1980 to 2100 across the Swiss Alps.
These datasets provide valuable insights for water resource planning, flood risk management, and climate impact studies in alpine regions. If you're interested in the future of snow in a warming world, I’d love for you to join.