Community Research and Development Information Service - CORDIS


ACRCC Report Summary

Project ID: 339390
Funded under: FP7-IDEAS-ERC
Country: United Kingdom

Mid-Term Report Summary - ACRCC (Understanding the atmospheric circulation response to climate change)

My project aims to better understand the response of the atmospheric circulation to climate change, including how to best characterize the uncertainties associated with that response. The latter are considerably greater than the uncertainties associated with the thermodynamic aspects of climate change such as surface warming and sea-level rise, because of the smaller signal-to-noise ratio of the climate-change response, and the impact of model uncertainty. This research is highly relevant to regional aspects of climate change and the associated climate-related risk.

A team of four PhD students and four post-doctoral research associates has been recruited and is using both theoretical and computational methods to tackle this challenge from a number of different directions. A number of external collaborators are also involved.

One line of attack is to improve climate models by diagnosing errors within them. We have extensively examined the sensitivity of key features of atmospheric circulation simulated by the models, such as the strength and location of tropical rain belts and midlatitude storm tracks, to poorly constrained aspects of surface drag processes that need to be represented through parameterizations of unresolved (or subgridscale) processes. This is a comparatively unexplored aspect of climate model error. We have overcome previous methodological limitations by developing new ways of constructing model hierarchies and of suppressing dynamical feedbacks in order to isolate key interactions between processes.

A second line of attack is to make better use of existing model projections of climate change, notably the CMIP5 multi-model archive of projections produced for the last IPCC Assessment Report. The traditional approach to quantifying uncertainty in these projections, e.g. in the IPCC Assessment Reports, is to take the ensemble mean as the central estimate, and the spread as a measure of uncertainty. This is widely admitted to be unfounded but is still the standard practice. We have developed new ways to improve the signal-to-noise ratio of the atmospheric circulation response to climate change, and to identify its role in crucial climate-change impacts such as cold-season Mediterranean drying. We are actively pursuing the hypothesis that given the very different nature of the uncertainties associated with thermodynamic and circulation-related aspects of climate change, those uncertainties ought to be treated differently.

A third line of attack is to better understand the physical processes and mechanisms behind atmospheric variability. This is challenging because climate noise is highly structured in space and time, with long-memory effects that can be difficult to separate from climate change. We are questioning the efficacy of standard statistical approaches using correlations of climate anomalies, which rely on an assumption of statistical stationarity. This assumption is not generally valid for the climate system. As an alternative we are developing new physically based ways to diagnose causal inference, taking proper account of interannual variations in the seasonal cycle.

In addition to the achievements described above, the project involves inter-disciplinary developments. These have raised the awareness of the importance of atmospheric circulation as a source of uncertainty in climate change risk, within the wider climate-change community. A notable application is the attribution of extreme weather and climate events in the context of climate change, which is a rapidly growing research area with considerable public interest. We have helped make the case for a paradigm shift towards a ‘storyline’ approach to unquantifiable aspects of climate risk.

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United Kingdom
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