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dc.contributor.authorHaarsma, Reindert J.
dc.contributor.authorRoberts, Malcolm J.
dc.contributor.authorVidale, Pier L.
dc.contributor.authorSenior, Catherine A.
dc.contributor.authorBellucci, Alessio
dc.contributor.authorBao, Qing
dc.contributor.authorChang, Ping
dc.contributor.authorCorti, Susanna
dc.contributor.authorFuckar, Neven S.
dc.contributor.authorGuemas, Virginie
dc.contributor.authorHardenberg, Jost von
dc.contributor.authorHazeleger, Wilco
dc.contributor.authorKodama, Chihiro
dc.contributor.authorKoenigk, Torben
dc.contributor.authorLeung, L. Ruby
dc.contributor.authorLu, Jian
dc.contributor.authorLuo, Jing-Jia
dc.contributor.authorMao, Jiafu
dc.contributor.authorMizielinski, Matthew S.
dc.contributor.authorMizuta, Ryo
dc.contributor.authorNobre, Paulo
dc.contributor.authorSatoh, Masaki
dc.contributor.authorScoccimarro, Enrico
dc.contributor.authorSemmler, Tido
dc.contributor.authorSmall, Justin
dc.contributor.authorvon Storch, Jing-Song
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2016-11-29T15:38:49Z
dc.date.available2016-11-29T15:38:49Z
dc.date.issued2016-11-22
dc.identifier.citationHaarsma, Reindert J. [et al.]. High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6. "Geoscientific Model Development", 22 Novembre 2016, vol. 9, p. 4185-4208.
dc.identifier.issn1991-959X
dc.identifier.urihttp://hdl.handle.net/2117/97450
dc.description.abstractRobust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.
dc.description.sponsorshipPRIMAVERA project members (Malcolm J. Roberts, Reindert J. Haarsma, Pier Luigi Vidale, Torben Koenigk, Virginie Guemas, Susanna Corti, Jost von Hardenberg, Jin-Song von Storch,Wilco Hazeleger, Catherine A. Senior, Matthew S. Mizielinsky, Tido Semmler, Alessio Bellucci, Enrico Scoccimarro, Neven S. Fuckar) acknowledge funding received from the European Commission under grant agreement 641727 of the Horizon 2020 research programme. Chihiro Kodama acknowledges Y. Yamada, M. Nakano, T. Nasuno, T. Miyakawa, and H. Miura for analysis ideas. Neven S. Fuckar acknowledges support of the Juan de la Ciervaincorporación postdoctoral fellowship from the Ministry of Economy and Competitiveness of Spain. L. Ruby Leung and Jian Lu acknowledge support from the U.S. Department of Energy Office of Science Biological and Environmental Research as part of the Regional and Global Climate Modeling Program. The Pacific Northwest National Laboratory is operated for the DOE by Battelle Memorial Institute under contract DE-AC05-76RLO1830. Jiafu Mao is supported by the Biogeochemistry-Climate Feedbacks Scientific Focus Area project funded through the Regional and Global Climate Modeling Program in Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the U.S. Department of Energy Office of Science. Oak Ridge National Laboratory is managed by UTBATTELLE for the DOE under contract DE-AC05-00OR22725. Paulo Nobre acknowledges support from CNPq grant nos. 573797/2008-0 and 490237/2011-8, and FAPESP grant no. 2008/57719-9. Chihiro Kodama and Masaki Satoh are supported by the Program for Risk Information on Climate Change (SOSEI) and the FLAGSHIP2020 within the priority study4 (Advancement of meteorological and global environmental predictions utilizing observational “Big Data”), which are promoted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. Ping Chang is supported by US National Science Foundation grants AGS-1462127 and AGS-1067937, and National Oceanic and Atmospheric Administration grant NA11OAR4310154, as well as by China’s National Basic Research Priorities Programme (2013CB956204 and 2014CB745000). We thank Martin Juckes and his team for all their work on the HighResMIP and CMIP6 data request. Nick Rayner and John Kennedy for allowing early access to the HadISST2 daily, 1/4º SST and sea-ice dataset. Mark Ringer and Mark Webb for ideas for the targeted CFMIP-style experiment. Francois Massonnet for discussions on high-resolution modelling and sea ice.
dc.format.extent24 p.
dc.language.isoeng
dc.publisherEuropean Geosciences Union (EGU)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica
dc.subject.lcshAtmospheric circulation
dc.subject.lcshClimate change
dc.subject.otherHigh-performance computing (HPC)
dc.subject.otherCoupled Model Intercomparison Project 6 (CMIP6)
dc.subject.otherHigh Resolution Model Intercomparison Project (HighResMIP)
dc.subject.otherWorld Climate Research Program (WCRP)
dc.titleHigh Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6
dc.typeArticle
dc.subject.lemacCirculació atmosfèrica
dc.subject.lemacCanvis climàtics
dc.identifier.doi10.5194/gmd-9-4185-2016
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.geosci-model-dev.net/9/4185/2016/
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/641727/EU/PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment/PRIMAVERA
local.citation.publicationNameGeoscientific Model Development
local.citation.volume9
local.citation.startingPage4185
local.citation.endingPage4208


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