Please use this identifier to cite or link to this item: https://oar.tib.eu/jspui/handle/123456789/5110
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dc.rights.licenseCC BY 4.0 Unportedger
dc.contributor.authorSchaphoff, S.-
dc.contributor.authorForkel, M.-
dc.contributor.authorMüller, C.-
dc.contributor.authorKnauer, J.-
dc.contributor.authorVon, Bloh, W.-
dc.contributor.authorGerten, D.-
dc.contributor.authorJägermeyr, J.-
dc.contributor.authorLucht, W.-
dc.contributor.authorRammig, A.-
dc.contributor.authorThonicke, K.-
dc.contributor.authorWaha, K.-
dc.date.accessioned2020-07-27T12:26:29Z-
dc.date.available2020-07-27T12:26:29Z-
dc.date.issued2018-
dc.identifier.urihttp://dx.doi.org/10.34657/3739-
dc.identifier.urihttps://oar.tib.eu/jspui/handle/123456789/5110
dc.description.abstractThe dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through <a hrefCombining double low line"https://gitlab.pik-potsdam.de/lpjml/LPJmL" targetCombining double low linehttps://gitlab.pik-potsdam.de/lpjml/LPJmL</a>. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.eng
dc.language.isoeng-
dc.publisherGöttingen : Copernicus GmbH-
dc.relation.ispartofseriesGeoscientific Model Development Vol. 11 (2018), No. 4-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/ger
dc.subjectagricultural modelingeng
dc.subjectagrometeorologyeng
dc.subjectenvironmental changeeng
dc.subjectglobal perspectiveeng
dc.subjectin situ measurementeng
dc.subjectland use changeeng
dc.subjectmodel validationeng
dc.subjectpermafrosteng
dc.subjectphenologyeng
dc.subjectsatellite dataeng
dc.subjectseasonal variationeng
dc.subjectspatiotemporal analysiseng
dc.subjectvegetation dynamicseng
dc.subject.ddc550-
dc.titleLPJmL4 - A dynamic global vegetation model with managed land - Part 2: Model evaluationeng
dc.typearticle-
dc.typeText-
dc.description.versionpublishedVersioneng
local.accessRightsopenAccess-
wgl.contributorPIKger
wgl.subjectGeowissenschaftenger
wgl.typeZeitschriftenartikelger
dc.bibliographicCitation.firstPage1377-
dc.bibliographicCitation.lastPage1403-
dc.bibliographicCitation.volume11-
dc.bibliographicCitation.issue4-
dc.relation.doihttps://doi.org/10.5194/gmd-11-1377-2018-
dcterms.bibliographicCitation.journalTitleGeoscientific Model Development-
local.identifier.doihttp://dx.doi.org/10.34657/3739-
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