paper
2022
Downscaling & super-resolution
Application study
CNN / U-NetClimate projections / centennialPrinceton University Journal
2022-09-30
018
Sep 2022
Firas Gerges, Michel C. Boufadel, Elie R. Bou-Zeid et al.
World Scientific Annual Review of Artificial Intelligence
Princeton University
An overview of ML downscaling of GCM output, with a deep-learning case study producing local weekly temperature projections for a New Jersey watershed.
Downscaling & super-resolution
Deep Learning-Based Downscaling of Temperatures for Monitoring Local Climate Change Using Global Climate Simulation Data
In one sentence. An overview of ML downscaling of GCM output, with a deep-learning case study producing local weekly temperature projections for a New Jersey watershed.
Labels
- Topic
- Downscaling & super-resolution
- Type
- Application study
- Method
- CNN / U-Net
- Time scale
- Climate projections / centennial
- Domain
- Local / station
- Data
- CMIP / climate model output, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1142/s2811032322500011 OpenAlex:W4298145914
- Added
- 2026-10-22
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