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Quantifying and reducing uncertainty in global carbon cycle predictions: lessons and perspectives from 15 years of data assimilation studies with the ORCHIDEE Terrestrial Biosphere Model

hal.structure.identifierIndiana University [Bloomington]
dc.contributor.authorMACBEAN, N.
hal.structure.identifierNOVELTIS [Sté]
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorBACOUR, C.
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorRAOULT, N.
hal.structure.identifierScience and Technology Research Partners Ltd.
dc.contributor.authorBASTRIKOV, V.
hal.structure.identifierEuropean Commission - Joint Research Centre [Ispra] [JRC]
dc.contributor.authorKOFFI, E.
hal.structure.identifierGéosciences Environnement Toulouse [GET]
dc.contributor.authorKUPPEL, S.
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorMAIGNAN, F.
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorOTTLE, Catherine
hal.structure.identifierUniversiteit Gent = Ghent University [UGENT]
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorPEAUCELLE, M.
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation INVerse pour les mesures atmosphériques et SATellitaires [SATINV]
dc.contributor.authorSANTAREN, D.
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
hal.structure.identifierModélisation des Surfaces et Interfaces Continentales [MOSAIC]
dc.contributor.authorPEYLIN, P.
dc.date.accessioned2024-04-08T11:46:34Z
dc.date.available2024-04-08T11:46:34Z
dc.date.issued2022
dc.identifier.issn0886-6236
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195238
dc.description.abstractEnPredicting terrestrial carbon, C, budgets and carbon-climate feedbacks strongly relies on our ability to accurately model interactions between vegetation, C and water cycles, and the atmosphere. However, C fluxes simulated by global, process-based terrestrial biosphere models (TBMs) remain subject to large uncertainties, partly due to unknown or poorly calibrated parameters. This is because TBMs have not routinely been confronted against C cycle related datasets within a statistical data assimilation (DA) system. In this review, we present 15 years' development of a C cycle DA system for optimizing C cycle parameters of the ORCHIDEE TBM. We analyze the impact of assimilating multiple different C cycle related datasets on regional to global-scale gross and net CO2 fluxes. We find that assimilating atmospheric CO2 data is crucial for improving (increasing) ORCHIDEE predictions of the terrestrial land C sink. The improvement is predominantly due to the global-scale constraint these data provide for optimizing initial soil C stocks, which are likely in error due to inaccurate assumptions about steady state spin-up and incomplete knowledge of land use change histories. When comparing the data-constrained ORCHIDEE land C sink estimates to the CAMS atmospheric inversion, we show that while the two approaches agree on the global C sink magnitude, they continue to differ in how the global C sink is partitioned between the northern hemisphere and tropics. We also discuss technical challenges faced in our C cycle DA studies, in particular the difficulty in characterizing the error covariance matrix due to unknown observation biases and/or model-data inconsistencies. We offer our perspectives on how to tackle these challenges that we hope can serve as a roadmap for other TBM groups wishing to develop C cycle DA systems.
dc.language.isoen
dc.publisherAmerican Geophysical Union
dc.title.enQuantifying and reducing uncertainty in global carbon cycle predictions: lessons and perspectives from 15 years of data assimilation studies with the ORCHIDEE Terrestrial Biosphere Model
dc.typeArticle de revue
dc.identifier.doi10.1029/2021GB007177
dc.subject.halPlanète et Univers [physics]/Océan, Atmosphère
dc.subject.halPlanète et Univers [physics]/Interfaces continentales, environnement
dc.description.sponsorshipEurope30-year re-analysis of CARBON fluxES and pools over Europe and the Globe
dc.description.sponsorshipEuropeMULTIscale SENTINEL land surface information retrieval PLatform
dc.description.sponsorshipEuropeObservation - based system for monitoring and verification of greenhouse gases
bordeaux.journalGlobal Biogeochemical Cycles
bordeaux.pagee2021GB007177
bordeaux.volume36
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue7
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-03693760
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03693760v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Global%20Biogeochemical%20Cycles&rft.date=2022&rft.volume=36&rft.issue=7&rft.spage=e2021GB007177&rft.epage=e2021GB007177&rft.eissn=0886-6236&rft.issn=0886-6236&rft.au=MACBEAN,%20N.&BACOUR,%20C.&RAOULT,%20N.&BASTRIKOV,%20V.&KOFFI,%20E.&rft.genre=article


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