Decadal Prediction

• DOI: 10.1175/2009bams2778.1
• Publication Date: 2009-05-28T12:45:49Z
• Authors: Gerald A. Meehl; Lisa Goddard; James Murphy; Ronald J. Stouffer; George Boer; Gokhan Danabasoglu; Keith Dixon; Marco A. Giorgetta; Arthur M. Greene; Ed Hawkins; Gabriele Hegerl; David Karoly; Noel Keenlyside; Masahide Kimoto; Ben Kirtman; Antonio Navarra; Roger Pulwarty; Doug Smith; Detlef Stammer; Timothy Stockdale
• Keywords: 550; SEA-LEVEL RISE; 551; 01 natural sciences; Climatic changes--Research; MULTIDECADAL VARIABILITY; climate models; SURFACE-TEMPERATURE TRENDS; Climatic changes--Forecasting; GLOBAL CLIMATE MODEL; GENERAL-CIRCULATION MODEL; INTERDECADAL VARIATIONS; decadal predictions; MULTIMODEL-ENSEMBLE; 0105 earth and related environmental sciences; climate science; Atmosphere; decadal prediction; 500; THERMOHALINE CIRCULATION; Climatic changes; 6. Clean water; NORTH-ATLANTIC; 13. Climate action; SOLAR-CYCLE VARIABILITY

A new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr.