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Land surface model parameter optimisation using in situ flux data : Comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

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dc.contributor.authorBastrikov, Vladislav
dc.contributor.authorMacbean, Natasha
dc.contributor.authorBacour, Cédric
dc.contributor.authorSantaren, Diego
dc.contributor.authorKuppel, Sylvain
dc.contributor.authorPeylin, Philippe
dc.contributor.institutionUniversity of Aberdeen.Northern Rivers Institute (NRI)en
dc.contributor.institutionUniversity of Aberdeen.Geology and Geophysicsen
dc.date.accessioned2019-01-09T10:20:07Z
dc.date.available2019-01-09T10:20:07Z
dc.date.issued2018-11-30
dc.descriptionThis work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia and USCCC. We acknowledge the financial support to the eddy covariance data harmonisation provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Universiteì Laval, Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California – Berkeley and the University of Virginia.en
dc.description.statusPeer revieweden
dc.format.extent16
dc.format.extent1439100
dc.identifier141592892
dc.identifier03123766-d1bc-42aa-86d7-e67d79a2c318
dc.identifier85039871600
dc.identifier.citationBastrikov, V, Macbean, N, Bacour, C, Santaren, D, Kuppel, S & Peylin, P 2018, 'Land surface model parameter optimisation using in situ flux data : Comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)', Geoscientific Model Development, vol. 11, no. 12, pp. 4739-4754. https://doi.org/10.5194/gmd-11-4739-2018en
dc.identifier.doi10.5194/gmd-11-4739-2018
dc.identifier.iss12en
dc.identifier.issn1991-959X
dc.identifier.urihttp://hdl.handle.net/2164/11749
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85039871600&partnerID=8YFLogxKen
dc.identifier.vol11en
dc.language.isoeng
dc.relation.ispartofGeoscientific Model Developmenten
dc.subjectSDG 13 - Climate Actionen
dc.subjectSDG 15 - Life on Landen
dc.subjectQE Geologyen
dc.subjectModelling and Simulationen
dc.subjectGeneral Earth and Planetary Sciencesen
dc.subject.lccQEen
dc.titleLand surface model parameter optimisation using in situ flux data : Comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)en
dc.typeJournal articleen

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