Global Space-Time Models for Climate Ensembles

• Activity Number: 602
• Type: Contributed
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Stefano Castruccio*+ and Michael L Stein
• Companies: University of Chicago and The University of Chicago
• Keywords: space-time models ; emulation ; process on a sphere

Abstract

Climate sensitivity to anthropogenic forcing can be investigated by the use of global climate models which reproduce physical processes on a global scale and predict variables such as temperature. A collection of different runs (model ensemble) can be obtained setting different initial conditions and greenhouse gas concentrations. The purpose of this work is to show how the runs of a precomputed ensemble can be reproduced (emulated) with a global space/time statistical model that addresses the issue of capturing nonstationarities in latitude more effectively than current alternatives in the literature. Exploiting the gridded geometry of the data, the proposed algorithm is able to fit massive datasets with millions of observations within a few hours. In the last part of the talk, an application to the recent CMIP5 multi model ensemble will be introduced and compared with reanalysis data.