Manual on Downloading Prognostic Meteorological Information from Earth System Grid Federation (ESGF) Web-sites

cg.contacticarda@CGIAR.orgen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderInternational Fund for Agricultural Development - IFADen_US
cg.contributor.projectKnowledge Management in CACILM IIen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.subject.agrovocdata processingen_US
cg.subject.agrovocmeteorological dataen_US
dc.creator(ICARDA), International Center for Agricultural Research in the Dry Areasen_US
dc.date.accessioned2020-07-21T21:22:53Z
dc.date.available2020-07-21T21:22:53Z
dc.description.abstractIn order to address this spatial scale problem various methods to downscale the GCM output have been developed. These downscaling methods can be generalized into two types: statistical and dynamical. Statistical downscaling involves deriving statistical relationships between some large-scale predictors and the local variable of interest. Dynamical downscaling uses mathematical representations of the physical processes that create the climate system, similar to GCMs, applied at a higher spatial resolution than the GCMs. In this way, they are able to capture climate phenomena not resolved by the GCMs including the influence of mountains and coastlines. Dynamical downscaling is done with a Regional Climate Model (RCM). When downscaling future climate projections RCMs assume that, the physical laws remain the same. Statistical downscaling techniques can also be applied to RCM output in order to provide information at point locations.en_US
dc.formatPDFen_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/379cc3f172939ece7249411c5958a4ba/v/08f9717be00427b72baa0bc1b2068c80en_US
dc.identifier.citationInternational Center for Agricultural Research in the Dry Areas (ICARDA). (20/6/2014). Manual on Downloading Prognostic Meteorological Information from Earth System Grid Federation (ESGF) Web-sites.en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/11304
dc.languageenen_US
dc.languageruen_US
dc.rightsCC-BY-SA-4.0en_US
dc.subjectearth system grid federation (esgf)en_US
dc.titleManual on Downloading Prognostic Meteorological Information from Earth System Grid Federation (ESGF) Web-sitesen_US
dc.typeManualen_US
dcterms.available2014-06-20en_US
mel.project.openhttp://www.cacilm.orgen_US

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