Artificial Intelligence and Machine Learning in Climate Modeling
In one sentence. Generic overview of neural networks and deep learning for climate modeling and prediction, with no new method or quantitative result.
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) have shown immense potential in revolutionizing climate modeling by enabling more accurate predictions, real-time data processing, and better decision-making. This article explores the applications of AI and ML in climate modeling, focusing on data-driven approaches that enhance climate prediction accuracy. We delve into how neural networks, decision trees, and deep learning algorithms are utilized to simulate complex climate systems, identify patterns, and forecast climate change impacts. The integration of these technologies is a significant advancement in climate science, providing critical insights into global environmental challenges.
Labels
- Topic
- Climate emulation
- Type
- Review, survey or tutorial
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.71465/ajml3012 OpenAlex:W7143836526
- Added
- 2026-10-22
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