Research
Back to researchResearch sweep · deep · 2015 – 2026
AI in Weather and Climate Prediction
AI in weather and climate prediction across the 2015 to June 2026 machine-learning era, with historical context from mid-twentieth-century numerical weather prediction and Lorenz's chaos theory: the shift from physics-based NWP and statistical post-processing (MOS) to data-driven models (GraphCast, GenCast, Pangu-Weather, FourCastNet, Aurora, NeuralGCM, ECMWF AIFS), how forecasters at ECMWF, NOAA, and the Met Office have operationalised them, measured accuracy versus the IFS, and the predictability limits imposed by chaos, the Lorenz attractor, and the butterfly effect.
- Claude Opus 4.8
- financial
- frontier
- academic
- vc
- blogs
Synthesised 2026-06-26
Full brief
Read the synthesised summary→
Weather forecasting has just lived through its biggest methodological break since ensemble prediction arrived in 1992. Between November 2023 and mid-2026, data-driven models trained on decades of reanalysis went from research curiosities to operational systems running alongside the physics-based engines they were…
Research lanes
5 lanes
academic
25 sources
Academic & arXiv
The academic literature on machine learning for weather prediction spans roughly three phases. The foundational period, culminating in Rasp et al.'s WeatherBench (JAMES, 2020) and its ERA5-based benchmark, established reanalysis data as the common training…
Read lane →
blogs
25 sources
Blogs & Independent Thinkers
The dominant Substack voice for technically fluent independent commentary on AI weather prediction is Karolina Stanisławska's AI Weather Hub, which bridges the gap between ML engineers and practising meteorologists. Her January 2025 piece on GenCast explains…
Read lane →
financial
25 sources
Financial Press
The commercial appetite for AI-driven weather data has grown sharply. Bloomberg reported in September 2025 that the number of commercial firms licensing data from ECMWF rose almost 20% in 2024 to over 800, with nearly half owned by energy companies including…
Read lane →
frontier
25 sources
Frontier Lab & Model News
The wave of deep-learning weather models that emerged from 2022 onwards represents the most consequential shift in meteorology since ensemble numerical weather prediction. The first significant contact between big-tech AI methods and operational meteorology…
Read lane →
vc
25 sources
VC & Analyst Reports
Market sizing estimates for AI-driven weather and climate modelling vary sharply across research houses, but directional agreement points to rapid growth from a still-modest base. Grand View Research put the global AI-based climate modelling market at USD 343…
Read lane →