The PIs propose to test a methodology for conducting uncertainty analysis of complex, highly non-linear models with discontinuous states and apply the techniques to better characterize the likelihood that greenhouse gas forcing could cause a highly non-linear response in large-scale earth systems.
The PIs will utilize two approaches: (i) a Monte Carlo approach in which thousands of runs of a given complex model are required, and (ii) the Deterministic Equivalent Modeling Method (DEMM). DEMM will be applied to a coupled ocean-atmosphere model, viz the ocean general circulation model (OGCM) of Marshall (MIT) coupled to a two-dimensional representation of the atmosphere (the Integrated Global System Model or IGSM). The OGCM is a complex model that exhibits nonlinear behavior, including the shutdown of the thermohaline circulation (THC). The IGSM includes the Emissions Prediction and Policy Analysis (ESSA) model that predicts economic activity, energy use and resulting anthropogenic greenhouse gas emissions in response to given climatic changes; a coupled model of atmospheric composition and climate prediction that includes a two-dimensional land-ocean model based on the atmospheric GCM developed at Goddard Institute for Space Studies; and the Terrestrial Ecosystem Model that simulates the ecosystem response, i.e., carbon and nitrogen fluxes and reservoir sizes in response to changes of climate and CO2. The work is important because it will yield useful insights into the quantification of climate model uncertainties. The results will be of interest to policy makers as well as scientists involved in climate modeling.
The award is funded under NSF's Methods and Models for Integrated Assessment (MMIA) initiative.