Computing infrastructure for simulating the global and regional climate response to cumulative emissions

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The idea of measuring climate change as a function of cumulative CO2 emissions has emerged in the past five years as a simple and effective tool to understand and quantify how global temperatures respond to human emissions. In particular, the finding that climate warming responds linearly to cumulative carbon emissions is a powerful way to frame the climate problem, and opens avenues for both changing how we approach climate mitigation, as well as better predicting the climate impacts associated with a given emission pathway. This research area has focussed to date only on quantifying the globally-averaged temperature change that results from cumulative emissions of CO2. There has been relatively much less study of the climate response to cumulative emissions non-CO2 gases, which are responsibly for more than a third of historical climate warming. Furthermore, most climate impacts manifest at a local scale, in response to regional changes in temperature and precipitation. Consequently, there is a need to incorporate spatial information into the cumulative emissions framework to so as to better link human emissions to local and regional climate changes and impacts. In this proposed research, I will build a modelling framework to (a) quantify the global climate response to both CO2 and non-CO2 greenhouse gas emissions, and (b) expand the current global relationship between temperature and cumulative emissions to a regional scale, thereby linking human greenhouse gas emissions directly to local climate changes.