paper
2021
Climate analysis & attribution
Extremes & hazards New model or method
Classical ML (trees, GP, linear, kernels)Climate projections / centennialETH Zurich Journal
2021-09-15
022
Sep 2021
Christoph Mony, Lukas Jansing, Michael Armand Sprenger
Weather and Forecasting
ETH Zurich
XGBoost predicts Swiss foehn from synoptic fields in reanalysis and CESM simulations, projecting more spring south-foehn in Altdorf and summer north-foehn in Lugano under warming.
Climate analysis & attribution
Evaluating Foehn Occurrence in a Changing Climate Based on Reanalysis and Climate Model Data Using Machine Learning
In one sentence. XGBoost predicts Swiss foehn from synoptic fields in reanalysis and CESM simulations, projecting more spring south-foehn in Altdorf and summer north-foehn in Lugano under warming.
Labels
- Topic
- Climate analysis & attribution, Extremes & hazards
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- Climate projections / centennial
- Domain
- Local / station
- Data
- ERA5 / reanalysis, CMIP / climate model output
- Status
- Research
- Identifiers
- DOI:10.1175/waf-d-21-0036.1 OpenAlex:W3199945613
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.