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contributor authorMeehl, Gerald A.
contributor authorGoddard, Lisa
contributor authorMurphy, James
contributor authorStouffer, Ronald J.
contributor authorBoer, George
contributor authorDanabasoglu, Gokhan
contributor authorDixon, Keith
contributor authorGiorgetta, Marco A.
contributor authorGreene, Arthur M.
contributor authorHawkins, Ed
contributor authorHegerl, Gabriele
contributor authorKaroly, David
contributor authorKeenlyside, Noel
contributor authorKimoto, Masahide
contributor authorKirtman, Ben
contributor authorNavarra, Antonio
contributor authorPulwarty, Roger
contributor authorSmith, Doug
contributor authorStammer, Detlef
contributor authorStockdale, Timothy
date accessioned2017-06-09T16:27:21Z
date available2017-06-09T16:27:21Z
date copyright2009/10/01
date issued2009
identifier issn0003-0007
identifier otherams-68163.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209691
description abstractA 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.
publisherAmerican Meteorological Society
titleDecadal Prediction
typeJournal Paper
journal volume90
journal issue10
journal titleBulletin of the American Meteorological Society
identifier doi10.1175/2009BAMS2778.1
journal fristpage1467
journal lastpage1485
treeBulletin of the American Meteorological Society:;2009:;volume( 090 ):;issue: 010
contenttypeFulltext


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