{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1390001205221351296.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.2151/sola.2009-031"}},{"identifier":{"@type":"HDL","@value":"http://hdl.handle.net/2241/104812"}},{"identifier":{"@type":"URI","@value":"https://tsukuba.repo.nii.ac.jp/records/19040"}},{"identifier":{"@type":"URI","@value":"http://www.jstage.jst.go.jp/article/sola/5/0/5_0_121/_pdf"}},{"identifier":{"@type":"NAID","@value":"130004940906"}}],"resourceType":"学術雑誌論文(journal article)","dc:title":[{"@language":"en","@value":"Applying the Local Ensemble Transform Kalman Filter to the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)"}],"dc:language":"en","description":[{"type":"abstract","notation":[{"@language":"en","@value":"In this study, we apply the local ensemble transform Kalman filter (LETKF) to the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) to develop the NICAM-LETKF. In addition, an algorithm to adaptively estimate the inflation parameter and the observational errors is introduced to the LETKF. The feasibility and stability of the NICAM-LETKF are investigated under the perfect model scenario. <br>According to the results, we confirm that the converged analysis errors of the NICAM-LETKF are smaller than the observational errors, and the magnitude and distribution of the root mean square errors (RMSEs) are comparable to those of the ensemble spreads. In our experiments, we find that the inflation parameter is optimally tuned and the observational errors are close to the true value. <br>It is concluded that the NICAM-LETKF works appropriately and stably under the perfect model scenario even if the inflation parameter and the observational errors are adaptively estimated within the LETKF."}],"abstractLicenseFlag":"disallow"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1030848083883669377","@type":"Researcher","personIdentifier":[{"@type":"KAKEN_RESEARCHERS","@value":"70644805"},{"@type":"NRID","@value":"1000070644805"},{"@type":"NRID","@value":"9000363504580"},{"@type":"NRID","@value":"9000267809650"},{"@type":"NRID","@value":"9000258631480"},{"@type":"NRID","@value":"9000242877891"},{"@type":"NRID","@value":"9000283593584"},{"@type":"NRID","@value":"9000241868461"},{"@type":"NRID","@value":"9000376553255"},{"@type":"NRID","@value":"9000401716555"},{"@type":"NRID","@value":"9000017893783"},{"@type":"NRID","@value":"9000401862887"},{"@type":"NRID","@value":"9000020828365"},{"@type":"NRID","@value":"9000004647953"},{"@type":"NRID","@value":"9000258149153"},{"@type":"NRID","@value":"9000018112922"},{"@type":"NRID","@value":"9000401692170"},{"@type":"NRID","@value":"9000017893654"},{"@type":"NRID","@value":"9000258167626"},{"@type":"NRID","@value":"9000254567663"},{"@type":"NRID","@value":"9000009548652"},{"@type":"NRID","@value":"9000292882697"},{"@type":"NRID","@value":"9000283593939"},{"@type":"NRID","@value":"9000288831482"},{"@type":"NRID","@value":"9000257828207"},{"@type":"NRID","@value":"9000311489204"},{"@type":"NRID","@value":"9000292882701"},{"@type":"RESEARCHMAP","@value":"https://researchmap.jp/-kkonodo-"}],"foaf:name":[{"@language":"en","@value":"Kondo Keiichi"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Graduate School of Life and Environmental Sciences, University of Tsukuba"}]},{"@id":"https://cir.nii.ac.jp/crid/1410001205221351296","@type":"Researcher","personIdentifier":[{"@type":"NRID","@value":"9000283593585"}],"foaf:name":[{"@language":"en","@value":"Tanaka H. L."}],"jpcoar:affiliationName":[{"@language":"en","@value":"Center for Computational Sciences, University of Tsukuba"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"13496476"},{"@type":"NCID","@value":"AA12022899"}],"prism:publicationName":[{"@language":"en","@value":"SOLA"},{"@language":"en","@value":"SOLA"}],"dc:publisher":[{"@language":"en","@value":"Meteorological Society of Japan"},{"@language":"ja","@value":"公益社団法人 日本気象学会"}],"prism:publicationDate":"2009","prism:volume":"5","prism:startingPage":"121","prism:endingPage":"124"},"reviewed":"false","dcterms:accessRights":"http://purl.org/coar/access_right/c_abf2","url":[{"@id":"https://tsukuba.repo.nii.ac.jp/records/19040"},{"@id":"http://www.jstage.jst.go.jp/article/sola/5/0/5_0_121/_pdf"},{"@id":"http://hdl.handle.net/2241/104812"}],"availableAt":"2009","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360574095675173888","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Diagnosis of observation, background and analysis‐error statistics in observation space"}]},{"@id":"https://cir.nii.ac.jp/crid/1360855567863731200","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Nonhydrostatic icosahedral atmospheric model (NICAM) for global cloud resolving simulations"}]},{"@id":"https://cir.nii.ac.jp/crid/1360855570047666048","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A New Approach to Linear Filtering and Prediction Problems"}]},{"@id":"https://cir.nii.ac.jp/crid/1361981470355540352","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics"}]},{"@id":"https://cir.nii.ac.jp/crid/1362825894222426496","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Atmospheric simulations using a GCM with simplified physical parametrizations. I: model climatology and variability in multi-decadal experiments"}]},{"@id":"https://cir.nii.ac.jp/crid/1363388845204651776","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter"}]},{"@id":"https://cir.nii.ac.jp/crid/1363670319839467520","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Construction of correlation functions in two and three dimensions"}]},{"@id":"https://cir.nii.ac.jp/crid/1363670320946583040","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Tests of an Ensemble Kalman Filter for Mesoscale and Regional-Scale Data Assimilation. 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