Ensemble bias correction of climate simulations: preserving internal variability

Abstract Climate simulations often need to be adjusted (i.e., corrected) before any climate change impacts studies. However usual bias correction approaches do not differentiate the bias from the different uncertainties of the climate simulations: scenario uncertainty, model uncertainty and internal...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Pradeebane Vaittinada Ayar, Mathieu Vrac, Alain Mailhot
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/51c365f6c14b4a65afa2208c0082c019
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:51c365f6c14b4a65afa2208c0082c019
record_format	dspace
spelling	oai:doaj.org-article:51c365f6c14b4a65afa2208c0082c0192021-12-02T14:06:12ZEnsemble bias correction of climate simulations: preserving internal variability10.1038/s41598-021-82715-12045-2322https://doaj.org/article/51c365f6c14b4a65afa2208c0082c0192021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82715-1https://doaj.org/toc/2045-2322Abstract Climate simulations often need to be adjusted (i.e., corrected) before any climate change impacts studies. However usual bias correction approaches do not differentiate the bias from the different uncertainties of the climate simulations: scenario uncertainty, model uncertainty and internal variability. In particular, in the case of a multi-run ensemble of simulations (i.e., multiple runs of one model), correcting, as usual, each member separately, would mix up the model biases with its internal variability. In this study, two ensemble bias correction approaches preserving the internal variability of the initial ensemble are proposed. These “Ensemble bias correction” (EnsBC) approaches are assessed and compared to the approach where each ensemble member is corrected separately, using precipitation and temperature series at two locations in North America from a multi-member regional climate ensemble. The preservation of the internal variability is assessed in terms of monthly mean and hourly quantiles. Besides, the preservation of the internal variability in a changing climate is evaluated. Results show that, contrary to the usual approach, the proposed ensemble bias correction approaches adequately preserve the internal variability even in changing climate. Moreover, the climate change signal given by the original ensemble is also conserved by both approaches.Pradeebane Vaittinada AyarMathieu VracAlain MailhotNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Pradeebane Vaittinada Ayar Mathieu Vrac Alain Mailhot Ensemble bias correction of climate simulations: preserving internal variability
description	Abstract Climate simulations often need to be adjusted (i.e., corrected) before any climate change impacts studies. However usual bias correction approaches do not differentiate the bias from the different uncertainties of the climate simulations: scenario uncertainty, model uncertainty and internal variability. In particular, in the case of a multi-run ensemble of simulations (i.e., multiple runs of one model), correcting, as usual, each member separately, would mix up the model biases with its internal variability. In this study, two ensemble bias correction approaches preserving the internal variability of the initial ensemble are proposed. These “Ensemble bias correction” (EnsBC) approaches are assessed and compared to the approach where each ensemble member is corrected separately, using precipitation and temperature series at two locations in North America from a multi-member regional climate ensemble. The preservation of the internal variability is assessed in terms of monthly mean and hourly quantiles. Besides, the preservation of the internal variability in a changing climate is evaluated. Results show that, contrary to the usual approach, the proposed ensemble bias correction approaches adequately preserve the internal variability even in changing climate. Moreover, the climate change signal given by the original ensemble is also conserved by both approaches.
format	article
author	Pradeebane Vaittinada Ayar Mathieu Vrac Alain Mailhot
author_facet	Pradeebane Vaittinada Ayar Mathieu Vrac Alain Mailhot
author_sort	Pradeebane Vaittinada Ayar
title	Ensemble bias correction of climate simulations: preserving internal variability
title_short	Ensemble bias correction of climate simulations: preserving internal variability
title_full	Ensemble bias correction of climate simulations: preserving internal variability
title_fullStr	Ensemble bias correction of climate simulations: preserving internal variability
title_full_unstemmed	Ensemble bias correction of climate simulations: preserving internal variability
title_sort	ensemble bias correction of climate simulations: preserving internal variability
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/51c365f6c14b4a65afa2208c0082c019
work_keys_str_mv	AT pradeebanevaittinadaayar ensemblebiascorrectionofclimatesimulationspreservinginternalvariability AT mathieuvrac ensemblebiascorrectionofclimatesimulationspreservinginternalvariability AT alainmailhot ensemblebiascorrectionofclimatesimulationspreservinginternalvariability
_version_	1718392020150517760

Ensemble bias correction of climate simulations: preserving internal variability

Ejemplares similares