paper
2024
Climate analysis & attribution
Extremes & hazards New model or method
CNN / U-NetClimate projections / centennialColorado State University (incl. CIRA)Stanford University Journal
2024-08-23
046
Aug 2024
Jared T. Trok, Elizabeth A. Barnes, Frances V. Davenport et al.
Science Advances
Colorado State University (incl. CIRA), Stanford University
A CNN generates dynamically consistent counterfactual extreme heat events, estimating the 2023 southcentral North America heat was 1.18–1.42°C warmer due to warming.
Climate analysis & attribution
Machine learning–based extreme event attribution
In one sentence. A CNN generates dynamically consistent counterfactual extreme heat events, estimating the 2023 southcentral North America heat was 1.18–1.42°C warmer due to warming.
Labels
- Topic
- Climate analysis & attribution, Extremes & hazards
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- Climate projections / centennial
- Domain
- Regional
- Data
- ERA5 / reanalysis, CMIP / climate model output
- Status
- Research
- Identifiers
- DOI:10.1126/sciadv.adl3242 OpenAlex:W4401724841
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.