🚨Postdoc in Climate Dynamics at ETH Zurich🚨 We are hiring a postdoc to work on understanding projected future changes in the atmospheric circulation and climate. The scope is broad, with flexibility to work on questions aligned with your interests/experience. jobs.ethz.ch/job/view/JOP...
Great new paper by Gordon Bonan and others on the deep historical legacies that limit how we think about the biosphere within the climate system, and the need to more fully represent diverse ways of understanding nature in the face of climate change. agupubs.onlinelibrary.wiley.com/doi/10.1029/...
A preprint I’ve been working on together with Olivier Pasche, Zhongwei Zhang, @zscheischlerjak.bsky.socialarxiv.org/abs/2404.17652. We compared ML-based weather models and ECMWF’s HRES in case studies on 3 recent high-impact extreme events! Summary & a few thoughts 🧵👇
I have a commentary in Nature on our disquieting inability to work out why 2023 was so warm. www.nature.com/articles/d41...
Taking into account all known factors, the planet warmed 0.2 °C more last year than climate scientists expected. More and better data are urgently needed. Taking into account all known factors, the pl...
The Compound Event Network is on bsky! Give them a follow to keep up with the most recent research on compound and cascading climate hazards and risks. ➡️ @compoundnet.bsky.social
Researchers often use interpretable machine learning tools like feature importances to identify drivers, but cross-validation strategy used can affect these results: Our open access study in AIES doi.org/10.1175/AIES... (with co-authors Jakob Zscheischler, Christoph Müller, Mohit Anand)
Abstract Machine learning algorithms are able to capture complex, nonlinear, interacting relationships and are increasingly used to predict agricultural yield variability at regional and national scal...