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contributor authorPincus, Robert
contributor authorPatrick Hofmann, Robert J.
contributor authorAnderson, Jeffrey L.
contributor authorRaeder, Kevin
contributor authorCollins, Nancy
contributor authorWhitaker, Jeffrey S.
date accessioned2017-06-09T16:38:13Z
date available2017-06-09T16:38:13Z
date copyright2011/03/01
date issued2010
identifier issn0027-0644
identifier otherams-71356.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213239
description abstractThis paper explores the degree to which short-term forecasts with global models might be improved if clouds were fully included in a data assimilation system, so that observations of clouds affected all parts of the model state and cloud variables were adjusted during assimilation. The question is examined using a single ensemble data assimilation system coupled to two present-generation climate models with different treatments of clouds. ?Perfect-model? experiments using synthetic observations, taken from a free run of the model used in subsequent assimilations, are used to circumvent complications associated with systematic model errors and observational challenges; these provide a rough upper bound on the utility of cloud observations with these models. A series of experiments is performed in which direct observations of the model?s cloud variables are added to the suite of observations being assimilated. In both models, observations of clouds reduce the 6-h forecast error, with much greater reductions in one model than in the other. Improvements are largest in regions where other observations are sparse. The two cloud schemes differ in their complexity and number of degrees of freedom; the model using the simpler scheme makes better use of the cloud observations because of the stronger correlations between cloud-related and dynamical variables (particularly temperature). This implies that the impact of real cloud observations will depend on both the strength of the instantaneous, linear relationships between clouds and other fields in the natural world, and how well each assimilating model?s cloud scheme represents those relationships.
publisherAmerican Meteorological Society
titleCan Fully Accounting for Clouds in Data Assimilation Improve Short-Term Forecasts by Global Models?
typeJournal Paper
journal volume139
journal issue3
journal titleMonthly Weather Review
identifier doi10.1175/2010MWR3412.1
journal fristpage946
journal lastpage957
treeMonthly Weather Review:;2010:;volume( 139 ):;issue: 003
contenttypeFulltext


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