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1. Identity statement
Reference TypeConference Abstract (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Repositorysid.inpe.br/mtc-m18@80/2008/08.04.18.25   (restricted access)
Last Update2008:08.04.18.25.33 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m18@80/2008/08.04.18.25.34
Metadata Last Update2021:02.10.19.21.50 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyVanOldenborghCoel:2006:PrSeFo
TitleProbabilistic seasonal forecast verification with the climate explorer
FormatOn-line
Year2006
Secondary Date20060402
Access Date2024, Apr. 28
Secondary TypePRE CI
Number of Files1
Size424 KiB
2. Context
Author1 Van Oldenborgh, G. J.
2 Coelho, Caio Augusto dos Santos
Group1
2 DOP-INPE-MCT-BR
Affiliation1
2 Instituto Nacional de Pesquisas Espaciais (INPE/CPTEC)
e-Mail Addressdeicy@cptec.inpe.br
Conference NameEuropean Geosciences Union General Assembly 2006.
Conference LocationVienna, Austria
Date2-7 Apr.
Book TitleAbstracts
Tertiary TypePoster
OrganizationEGU
History (UTC)2008-08-04 18:35:38 :: deicy -> administrator ::
2021-02-10 19:21:50 :: administrator -> marciana :: 2006
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywords*
AbstractSeasonal climate forecasts are made using multi-model ensembles. Contrary to climate change projections, the skill of the forecasts can be verified against observations using old forecasts and hindcasts. In practice the small number of forecasts (15-45) is a severe limitation, as the skill depends strongly on the region and season. We present a web-based system to produce charts and maps of the skill of operational seasonal forecast systems using a variety of measures. It is part of the KNMI Climate Explorer (climexp.knmi.nl), and presently contains data from the ECMWF S2 and NCEP CFS operational forecast systems, as well as the Demeter research experiment. The verification measures have been developed in the RCLIM project, and include deterministic measures such as the ensemble mean correlation, RMSE and MAE, as well as probabilistic measures such as the Brier Score, its decomposition into resolution, reliability and uncertainty, and the ROC curve. These are available both for time series (area-averaged or all grid points in a region) and as spatial maps. More measures, and estimates of the uncertainties of the skill scores, are planned. The verification system allows seasonal forecasters and climate researchers to quickly explore the predictability of the short-term climate with current state-of-the-art models.
AreaMET
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDOP > Probabilistic seasonal forecast...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
Languageen
Target Fileegu06_climexp.pdf
User Groupadministrator
deicy
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Visibilityshown
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Next Higher Units8JMKD3MGPCW/43SQKNE
Host Collectionsid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notes
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7. Description control
e-Mail (login)marciana
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