Sustainability & AI
Climate informatics
The application of data science and machine learning to climate data and climate-science questions.
Definition
The application of data science and machine learning to climate data and climate-science questions, from detecting patterns in observations to improving models.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Established
- Last updated
- 21 August 2026
References
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Overview
What it means
The field has its own annual workshop series since 2011, bringing together climate scientists and machine-learning researchers. Work includes downscaling climate projections, detecting extremes, emulating expensive model components and mining reanalysis datasets.
How it is used
Techniques developed in climate informatics feed weather and climate services, impact assessment and risk analytics — including the machine-learning forecasters now running operationally at centres such as ECMWF.
Why it matters
Climate science sits on some of the largest structured datasets in existence. Climate informatics is how AI enters that science responsibly: grounded in physics, benchmarked against observation, and explicit about uncertainty.
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