The Climate Analytics Lab aims to reduce uncertainty in the role of anthropogenic aerosol on the climate by exploiting recent advances in machine learning to enable improved projections and gain new insights from observations.

Project Highlights

Global temperature map


A benchmark dataset for the emulation of full-complexity climate models.

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Detecting ship tracks

Using machine learning to automatically detect the brightening effect that shipping can have on clouds.

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Emulator schematic

Model Emulation for Calibration

Developing climate model emulators for better parameter estimation and calibration.

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  • 23/10 - The Climate Analytics Lab held our inaugral group meeting today - with cupcakes!
  • 23/08 - Prof. Watson-Parris is quoted in a Science article describing the climate impact of recent changes in shipping fuel regulations. Read more about the project here.
  • 23/02 - After a 5400 mile move with his family, Prof. Watson-Parris takes up his position at Scripps and HDSI in UC San Diego!
  • 22/11 - Our recent Nature Climate Change paper is featured in this Wired article highlighting that “Tiny Aerosols Pose a Big Predicament in a Warming World”
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