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contributor authorLaroche, Stéphane
contributor authorGauthier, Pierre
contributor authorTanguay, Monique
contributor authorPellerin, Simon
contributor authorMorneau, Josée
date accessioned2017-06-09T17:28:34Z
date available2017-06-09T17:28:34Z
date copyright2007/06/01
date issued2007
identifier issn0027-0644
identifier otherams-85954.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4229458
description abstractA four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.
publisherAmerican Meteorological Society
titleImpact of the Different Components of 4DVAR on the Global Forecast System of the Meteorological Service of Canada
typeJournal Paper
journal volume135
journal issue6
journal titleMonthly Weather Review
identifier doi10.1175/MWR3408.1
journal fristpage2355
journal lastpage2364
treeMonthly Weather Review:;2007:;volume( 135 ):;issue: 006
contenttypeFulltext


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