Changes in Earth's climate in response to atmospheric greenhouse gas build-up impact the health of terrestrial ecosystems and the hydrologic cycle. The environmental conditions influential to plant and animal life are often mapped as ecoregions, land areas having similar combinations of environmental characteristics. We extend this idea to establish regions of similarity with respect to climatic characteristics which evolve through time using a quantitative statistical clustering technique we call Multivariate Spatio-Temporal Clustering (MSTC). MSTC was applied to the monthly time series output from a fully coupled general circulation model (GCM) called the Parallel Climate Model (PCM). Analyzed were results from an ensemble of five 99-year Business-As-Usual (BAU) transient simulations from 2000-2098. MSTC establishes an exhaustive set of recurring climate regimes which form a "skeleton" through the "observations" (model output) throughout the occupied portion of the climate phase space formed by the characteristics being considered. MSTC facilitates direct comparison of ensemble members, ensemble and temporal averages, as well as observational data since the derived climate regimes provide a basis for comparison. Moreover, by mapping all land cells to discrete climate states, one can study the dynamical behavior of any part of the system by analyzing its time-varying sequence of climate state occupancy. MSTC is a powerful tool for model developers and environmental decision-makers who wish to understand long, complex time series predictions of models. Strong predicted interannual trends were revealed in the analysis of PCM model results, including an increase in global desertification, a decrease in the cold, dry high latitude conditions typical of North American and Asian winters, and significant warming in Antarctica and western Greenland. Graphics and animations are available at http://www.climatemodeling.org/pcm/.
Hoffman, Forrest M., William W. Hargrove, David J. Erickson, and Robert J. Oglesby. August 3, 2005. "Using Clustered Climate Regimes to Analyze and Compare Predictions from Fully Coupled General Circulation Models." Earth Interactions, 9(10): 1-27, doi:10.1175/EI110.1. [ PDF ]
Research partially sponsored by the U.S. Department of Energy, Office of Science, Biological and Environmental Research Programs. This research used resources of the National Center for Computational Sciences at Oak Ridge National Laboratory which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Support was also provided by a research and development grant from the Science Directorate of NASA/MSFC.