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Understanding uncertainty via statistical analysis of a global aerosol model

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If you have a question about this talk, please contact Dr Gillian Young .

If external to BAS, please email the organiser in advance to gain access to the building

Huge investment in observations and more complex models of atmospheric aerosol have improved understanding of aerosol-cloud processes but the uncertainty in aerosol radiative forcing has not been reduced. We have used a statistical analysis of a single global aerosol GLOMAP to better understand its sources of uncertainty. We can use this uncertainty information to target research in the right places and to quantify the value of observations with respect to reducing model uncertainty. I will allow some time to focus on what we learn about the polar regions and how we can use observations to help reduce model uncertainty. This talk will show how statistical methods applied to this problem, including expert elicitation, Gaussian Process emulation and sensitivity analysis have helped to understand why uncertainty in aerosol radiative is not being reduced.

This talk is part of the British Antarctic Survey series.

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