Process‐Based Machine Learning Observationally Constrains Future Regional Warming Projections
Abstract We present the results of a novel process‐based machine learning method to constrain climate model uncertainty in future regional temperature projections. Ridge‐ERA5—a ridge regression model—learns coefficients to represent observed relationships between daily near‐surface temperature anoma...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
|
| Series: | Journal of Geophysical Research: Machine Learning and Computation |
| Online Access: | https://doi.org/10.1029/2025JH000698 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!