Show simple item record

dc.contributor.authorVannitsem, S.
dc.coverage.temporal21st century
dc.date2009
dc.date.accessioned2016-03-07T16:17:00Z
dc.date.accessioned2021-12-09T09:54:03Z
dc.date.available2016-03-07T16:17:00Z
dc.date.available2021-12-09T09:54:03Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/8815
dc.descriptionAn extension of the classical linear Model Output Statistics (MOS) technique is proposed allowing for the post-processing of ensemble forecasts. In this new approach, the cost function on which the least square parameter estimation is based takes into account the presence of errors in both observations and model observables (referred to as Error-in-Variables MOS, EVMOS), unldike the classical linear MOS cost function whose implicit assumption is the absence of errors in the model observables. It allows for the maintenance of an appropriate variability for the corrected forecasts, even for long lead times and for providing a framework in which both deterministic and probabilistic forecasts can be corrected. The scheme is successfully tested for ensemble correction in the context of an idealized low-order chaotic system, the Lorenz atmospheric model, in the presence of model errors, and compared with a classical technique, known as the non-homogeneous Gaussian regression (NGR) method. The potential use of this approach is also briefly discussed. Copyright © 2009 Royal Meteorological Society
dc.languageeng
dc.publisherIRM
dc.publisherKMI
dc.publisherRMI
dc.titleA unified linear Model Output Statistics scheme for both deterministic and ensemble forecasts
dc.typeArticle
dc.subject.frascatiEarth and related Environmental sciences
dc.audienceGeneral Public
dc.audienceScientific
dc.subject.freeEVMOS
dc.subject.freeNGR
dc.subject.freepost-processing
dc.source.issue0
dc.source.page1/15/2015
Orfeo.peerreviewedNot pertinent


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record