Artificial intelligence and downscaling global climate model future projections

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Authors: Rasmus Eduard Benestad
Cited by: 0

Abstract

A critical review of artificial intelligence and deep machine learning (AI/ML) applied to downscaling of global climate model simulations provides some words of caution, based on past experiences and well-established principles. Recent papers tend to ignore more subtle successes with statistics and mathematical based downscaling, and there are examples of inappropriate evaluation strategies and incomplete accounts of the scientific progress when it comes to climate downscaling. An incomplete description state-of-the-art and a dogmatic approach to evaluation may give a deceiving impression that AI/ML is superior to more statistics and mathematics based methods.

Fields of Study & Subjects

Climate variability and models Climate Change Policy and Economics Climate Change and Environmental Impact

Publication details

Journal / source
arXiv (Cornell University)
Publication date
2 January 2026
Document type
Preprint