Please use this identifier to cite or link to this item: https://physrep.ff.bg.ac.rs/handle/123456789/1156
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dc.contributor.authorRajkovic, B.en
dc.contributor.authorVeljović, Katarinaen
dc.contributor.authorDjurdjevic, V.en
dc.date.accessioned2022-07-12T18:29:04Z-
dc.date.available2022-07-12T18:29:04Z-
dc.date.issued2012-12-01en
dc.identifier.isbn9781619425224en
dc.identifier.urihttps://physrep.ff.bg.ac.rs/handle/123456789/1156-
dc.description.abstractAt the present state of modeling skills and computer resources, monthly forecasts are the shortest integrations falling in the long-term integrations category. What are the possible applications and the general meanings of such results relative to standard 5 to 10 day forecasts? Another issue is the ability to conduct forecasts without resorting to the nudging of large scales during integration. Finally, we discuss the quantitative scores for such forecasts. The other types of integrations/simulations are climate time scale integrations. The need for the assessment of their quality is paramount. The first step in that direction involves downscaling the ERA-interim data set, which can be achieved by performing integrations in both the non-coupled and coupled modes. © 2012 by Nova Science Publishers, Inc. All rights reserved.en
dc.relation.ispartofEssays on Fundamental and Applied Environmental Topicsen
dc.titleDynamical downscaling: Monthly, seasonal and climate case studiesen
dc.typeBook Chapteren
dc.identifier.scopus2-s2.0-84883444373en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84883444373en
dc.relation.firstpage135en
dc.relation.lastpage157en
item.grantfulltextnone-
item.openairetypeBook Chapter-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
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