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Updated: Aug 9, 2026
13:27
Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
Published on: June 8, 2015
Modelling climate change: the role of unresolved processes
1Centre for Global Atmospheric Modelling, University of Reading Department of Meteorology PO Box 243, Earley Gate, Reading RG6 6BB, UK. p.d.williams@reading.ac.uk
Summary
Sophisticated climate models guide global warming policies. A novel approach suggests adding random noise to represent unresolved processes may improve climate model performance.
Area of Science:
- Climate Science
- Computational Modeling
Background:
- Climate models are crucial for predicting global warming and informing policy.
- Current models simplify reality by omitting small or fast physical processes.
- Unresolved scales in climate models present a significant challenge to accuracy.
Purpose of the Study:
- To provide a personal perspective on the state of knowledge regarding unresolved scales in climate models.
- To discuss a novel solution for addressing the problem of unresolved scales.
Main Methods:
- Review of current understanding of unresolved scales in climate modeling.
- Discussion of a novel method involving the addition of random noise.
Main Results:
- The paper explores the challenges posed by unresolved physical processes in climate models.
- A counter-intuitive solution is proposed: incorporating random noise to represent these processes.
Conclusions:
- Addressing unresolved scales is critical for improving climate model accuracy.
- The proposed method of adding random noise offers a potential pathway to enhance model performance.
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