CMG: Non-stationary Spherical Processes to Synthesize Multimodel Climate Change Simulations

Colorado School Of Mines, Golden CO

Investigators

Abstract

The objective of this project is the assessment of the inherent uncertainty of global and regional climate change projections based on model output obtained from about twenty different state-of-the-art atmosphere-ocean general circulation models using advanced and specifically tailored statistical methodologies. The proposed approach concerns the development of a Bayesian statistical framework for quantifying uncertainty and attributing it to different factors. Spatial statistical models that borrow strength across adjacent spatial regions of the globe will be used in order to provide a statistically accurate assessment of climate model bias and inter-model variability. An additional feature of the methodology is the ability to synthesize climate change projections across the different models and then to down-scale to almost arbitrary regions providing a coherent uncertainty estimate. Questions to be addressed include: How large are the uncertainties in future climate change on different time and spatial scales? How are changes in the mean related to changes in variability and extreme events? By how much can predictive skill be improved when using joint climate variables? To what degree does agreement with observations imply predictive skill for the future? How can one efficiently model the evident non-stationarity of climate variability on the globe? The proposed project combines recent research efforts in statistics and climate science and promotes the use of advanced statistical methodology in climate science. It is also applicable to many other scientific areas, such as cosmic background radiation modeling, pollutant mapping, and disease spreading. The proposed work will also contribute to the training of graduate students. The interdisciplinary nature of the project and the close collaboration between statisticians and climate scientists will be an extraordinary educational experience and a source of intellectual networks for students and all participants. The results of this project will provide important tools for the assessment of climate change to scientists, policy makers and the general public.