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dc.contributor.authorIvanov, Leonid M.
dc.contributor.authorFan, Chenwu
dc.contributor.authorChu, Peter C.
dc.date2002
dc.date.accessioned2013-09-11T23:03:03Z
dc.date.available2013-09-11T23:03:03Z
dc.date.issued2002
dc.identifier.citationChu, P.C., L.M. Ivanov, C.W. Fan, 2002: Backward Fokker-Planck equation for determining model valid prediction period (paper download). Journal of Geophysical Research, American Geophysical Union, 107, C6, 10.1029/2001JC000879.
dc.identifier.urihttps://hdl.handle.net/10945/36156
dc.descriptionJournal of Geophysical Research, American Geophysical Union, 107, C6, 10.1029/2001JC000879.en_US
dc.description.abstractnew concept, valid prediction period (VPP), is presented here to evaluate ocean (or atmospheric) model predictability. VPP is defined as the time period when the prediction error first exceeds a predetermined criterion (i.e., the tolerance level). It depends not only on the instantaneous error growth but also on the noise level, the initial error, and the tolerance level. The model predictability skill is then represented by a single scalar, VPP. The longer the VPP, the higher the model predictability skill is. A theoretical framework on the basis of the backward Fokker-Planck equation is developed to determine the mean and variance of VPP. A one-dimensional stochastic dynamical system [Nicolis, 1992] is taken as an example to illustrate the benefits of using VPP for model evaluation.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleBackward Fokker-Planck equation for determining model valid prediction perioden_US
dc.typeArticleen_US
dc.contributor.departmentOceanographyen_US
dc.subject.authorbackward Fokker-Planck equationen_US
dc.subject.authorinstantaneous erroren_US
dc.subject.authorLorenz systemen_US
dc.subject.authorpredictabilityen_US
dc.subject.authortolerance levelen_US
dc.subject.authorvalid prediction perioden_US


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