University of Cambridge > Talks.cam > Centre for Atmospheric Science seminars, Chemistry Dept. > How can we reduce the uncertainty in estimates of aerosol cloud forcing?

How can we reduce the uncertainty in estimates of aerosol cloud forcing?

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Dr Amanda Maycock.

Aerosol cloud forcing is the least well constrained climate forcing and has remained so throughout successive IPCC reports. This uncertainty has remained despite considerable advances in our understanding of atmospheric aerosols, and in spite of the development of increasingly sophisticated models. Identifying sources of uncertainty is the first step towards reducing uncertainty, and will help us produce more robust estimates of aerosol cloud forcing.

In this talk I use results from the AeroCom model inter-comparison project to examine the role of model diversity in contributing to uncertainty. I also use output from a single global model (GLOMAP) and the technique of Gaussian process emulation to perform a perturbed physics experiment to explore the extent to which uncertainties within the model control the simulated aerosol distribution. In this step we move from examining diversity to understanding and quantifying model uncertainty.

This talk is part of the Centre for Atmospheric Science seminars, Chemistry Dept. series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2021 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity