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contributor authorCharron, Martin
contributor authorPellerin, Gérard
contributor authorSpacek, Lubos
contributor authorHoutekamer, P. L.
contributor authorGagnon, Normand
contributor authorMitchell, Herschel L.
contributor authorMichelin, Laurent
date accessioned2017-06-09T16:32:33Z
date available2017-06-09T16:32:33Z
date copyright2010/05/01
date issued2009
identifier issn0027-0644
identifier otherams-69686.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4211382
description abstractAn updated global ensemble prediction system became operational at the Meteorological Service of Canada in July 2007. The new elements of the system include the use of 20 members instead of 16, a single dynamical core [the Global Environmental Multiscale (GEM) model], stochastic physical tendency perturbations and a kinetic energy backscatter algorithm, an ensemble Kalman filter with four-dimensional data handling, and a decrease from 1.2° to 0.9° in horizontal grid spacing. This system is compared with the former operational one using a variety of probabilistic measures. For global upper-air dynamical fields, the improvement in predictive skill for equivalent forecast quality is from 9 to 16 h around day 6. Precipitation forecasts, verified over Canada, are also significantly improved. The impact of each of the abovementioned new elements of the ensemble prediction system is also evaluated separately in a series of sensitivity experiments for which one given element is removed from the system.
publisherAmerican Meteorological Society
titleToward Random Sampling of Model Error in the Canadian Ensemble Prediction System
typeJournal Paper
journal volume138
journal issue5
journal titleMonthly Weather Review
identifier doi10.1175/2009MWR3187.1
journal fristpage1877
journal lastpage1901
treeMonthly Weather Review:;2009:;volume( 138 ):;issue: 005
contenttypeFulltext


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