# The Rise of AI in Weather and Climate Information and its Impact on Global Inequality

arXiv: https://arxiv.org/abs/2603.05710 · HTML: https://mlsanity.com/paper/2603.05710/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 26 of its 95 references that are in the map.
- First posted on arXiv 5 Mar 2026.

## Builds on (most cited first, 26 of 26)

- [Training Compute-Optimal Large Language Models](https://mlsanity.com/paper/2203.15556/) (2022)
- [FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators](https://mlsanity.com/paper/2202.11214/) (2022)
- [ClimaX: A foundation model for weather and climate](https://mlsanity.com/paper/2301.10343/) (2023)
- [WeatherBench: A benchmark dataset for data-driven weather forecasting](https://mlsanity.com/paper/2002.00469/) (2020)
- [Neural General Circulation Models for Weather and Climate](https://mlsanity.com/paper/2311.07222/) (2023)
- [Data-centric Artificial Intelligence: A Survey](https://mlsanity.com/paper/2303.10158/) (2023)
- [FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead](https://mlsanity.com/paper/2304.02948/) (2023)
- [Large Language Models are Geographically Biased](https://mlsanity.com/paper/2402.02680/) (2024)
- [FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale](https://mlsanity.com/paper/2507.12144/) (2025)
- [Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function](https://mlsanity.com/paper/2501.19374/) (2025)
- [ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning](https://mlsanity.com/paper/2311.03721/) (2023)
- [FuXi Weather: A data-to-forecast machine learning system for global weather](https://mlsanity.com/paper/2408.05472/) (2024)
- [Bias Amplification: Large Language Models as Increasingly Biased Media](https://mlsanity.com/paper/2410.15234/) (2024)
- [ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation](https://mlsanity.com/paper/2306.08754/) (2023)
- [The FLUXCOM ensemble of global land-atmosphere energy fluxes](https://mlsanity.com/paper/1812.04951/) (2018)
- [Deep Learning for predicting rate-induced tipping](https://mlsanity.com/paper/2409.07590/) (2024)
- [HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting](https://mlsanity.com/paper/2409.18885/) (2024)
- [ExEBench: Benchmarking Foundation Models on Extreme Earth Events](https://mlsanity.com/paper/2505.08529/) (2025)
- [Designing Domain-Specific Large Language Models: The Critical Role of Fine-Tuning in Public Opinion Simulation](https://mlsanity.com/paper/2409.19308/) (2024)
- [ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method](https://mlsanity.com/paper/2504.07394/) (2025)
- [Democracy of AI Numerical Weather Models: An Example of Global Forecasting with FourCastNetv2 Made by a University Research Lab Using GPU](https://mlsanity.com/paper/2504.17028/) (2025)
- [WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks](https://mlsanity.com/paper/2412.02780/) (2024)
- [Artificial Intelligence for Atmospheric Sciences: A Research Roadmap](https://mlsanity.com/paper/2506.16281/) (2025)
- [AI for a Planet Under Pressure](https://mlsanity.com/paper/2510.24373/) (2025)
- [ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution](https://mlsanity.com/paper/2408.15993/) (2024)
- [SAFE: A Novel Approach to AI Weather Evaluation through Stratified Assessments of Forecasts over Earth](https://mlsanity.com/paper/2510.26099/) (2025)

## Abstract (arXiv)

AI development's current trajectory risks automating and amplifying the North-South divide in the global climate information system. Frontier models are built almost exclusively in the Global North, and this inequality continues through inputs, processes, and outputs, from biased training data to unrepresentative validation, disproportionately affecting vulnerable regions. Addressing these disparities requires a Climate Digital Public Infrastructure, evaluation metrics centring well-being, and knowledge co-production to foster resilience rather than inequity.