UCSC-SOE-11-03: Joint Projections of North Pacific Sea Surface Temperature from Different Global Climate Models

Francisco Beltran, Bruno Sanso, Ricardo T. Lemos and Roy Mendelssohn
01/26/2011 09:00 AM
Applied Mathematics & Statistics
The goal of this work is to develop a general methodology to obtain joint projections of climate indexes, based on ensembles of global climate model (GCM) output and historical records. As a case study, we consider Sea Surface Temperature (SST) in the North Pacific Ocean. We use two ensembles of 17 different GCM results, made available in the 4th Assessment Report of the Intergovernmental Panel on Climate Change: one corresponds to 20th century forcing conditions and the other corresponds to the A1B emissions scenario for the 21st century. Given a representation of the SST spatio-temporal fields based on a common set of empirical orthogonal functions (EOFs), we use a hierarchical Bayesian model for the EOF coefficients to estimate a baseline and a set of model discrepancies. These components are all time-varying. The model enables us to extract relevant temporal patterns of variability from both the observations and simulations and obtain common patterns from all eighteen series. This is used to obtain unified 21st century forecasts of relevant oceanic indexes as well as whole fields of forecast North Pacific SST. We compare the forecast index for different time scales and compare the SST reconstructions to the GCMs for the 21st century. While the coarser time resolution produces clear and faster results, we show that finer time scales produce results with structures that are similar to ones obtained at coarser scales.