Show simple item record

dc.contributor.authorChu, Peter C.
dc.contributor.authorIvanov, Leonid, M.
dc.date.accessioned2013-09-30T19:52:46Z
dc.date.available2013-09-30T19:52:46Z
dc.date.issued2003-09-05
dc.identifier.urihttp://hdl.handle.net/10945/36781
dc.descriptionVarious numerical atmospheric and oceanic models have been developed in the past several decades. a fundamental questions arises: Can we determine which model prpovides "the best prediction"? To answer this question, full knowledge of the prediction error statistics of each model is needed. Due to high structural complexity and high dimensionality of the error phase space, establishment of such statistics is difficult. Usually the Gaussian distribution is assumed for the error statistics for simplicity. However, it might not be true for regional ocean models.en_US
dc.publisherInternational Conference on Earth System Modeling: Development and Evaluation of Comprehensive Earth System Models; Atmospheres, Oceans and Sea Icesen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titlePrediction-skill variability in atmospheric and oceanic modelsen_US
dc.typeArticleen_US
dc.contributor.departmentOceanographyen_US
dc.subject.authorprediction-skill variabilityen_US
dc.subject.authoratmospheric modelsen_US
dc.subject.authoroceanic modelingen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record