Exploring spatial patterns of GCM projection bias via model based geostatistics.

MAIA, A. de H. N.; HAMADA, E.; GONDIM, R. S.

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Campo DC	Valor	Idioma
dc.contributor.author	MAIA, A. de H. N.	pt_BR
dc.contributor.author	HAMADA, E.	pt_BR
dc.contributor.author	GONDIM, R. S.	pt_BR
dc.date.accessioned	2013-10-10T11:11:11Z	pt_BR
dc.date.available	2013-10-10T11:11:11Z	pt_BR
dc.date.created	2013-10-10	pt_BR
dc.date.issued	2013	pt_BR
dc.identifier.citation	In: REUNIÃO ANUAL DA REGIÃO BRASILEIRA DA SOCIEDADE INTERNACIONAL DE BIOMETRIA, 58.; SIMPÓSIO DE ESTATÍSTICA APLICADA À EXPERIMENTAÇÃO AGRONÔMICA, 15., 2013, Campina Grande. Modelagem estatística em áreas multidisciplinares: impactos causados pelas mudanças climáticas na Região Nordeste: [anais]. Campina Grande: Sociedade Internacional de Biometria, 2013. 5 p.	pt_BR
dc.identifier.uri	http://www.alice.cnptia.embrapa.br/alice/handle/doc/968325	pt_BR
dc.description	General Circulation Models (GCMs) are numerical models developed to represent physical processes in the atmosphere, ocean, cryosphere and land surface. They constitute the most advanced tool currently available for simulating future climate scenarios as a response to increasing greenhouse gas concentrations. GCMs, possibly in conjunction with nested regional climate models (RCMs), have the potential to provide consistent estimates of regional climate change which are required in climate impact assessments. The characterization of model bias in terms of magnitude and spatial patterns is part of the process of evaluating the model performance via hindcast skill analysis, an important preliminary step in climate change impact assessments. In this paper, we discuss how Model Based Geostatistics can be applied for exploring bias patterns, key information for performing bias correction of GCM or RCM projections in future time slices. As example, we present an assessment of annual rainfall projection bias for three GCMs across the Northeast Brazil.	pt_BR
dc.language.iso	eng	eng
dc.rights	openAccess	eng
dc.subject	Gestatistics	pt_BR
dc.title	Exploring spatial patterns of GCM projection bias via model based geostatistics.	pt_BR
dc.type	Artigo em anais e proceedings	pt_BR
dc.date.updated	2013-10-10T11:11:11Z	pt_BR
dc.subject.thesagro	Modelo de simulação	pt_BR
dc.subject.thesagro	Clima	pt_BR
dc.subject.nalthesaurus	General Circulation Models	pt_BR
dc.subject.nalthesaurus	Climate change	pt_BR
riaa.ainfo.id	968325	pt_BR
riaa.ainfo.lastupdate	2013-10-10	pt_BR
dc.contributor.institution	ALINE DE HOLANDA NUNES MAIA, CNPMA; EMILIA HAMADA, CNPMA; RUBENS SONSOL GONDIM, CNPAT.	pt_BR
Aparece nas coleções:	Artigo em anais de congresso (CNPMA)

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