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contributor authorThiébaux, H. Jean
date accessioned2017-06-09T16:01:37Z
date available2017-06-09T16:01:37Z
date copyright1977/06/01
date issued1977
identifier issn0027-0644
identifier otherams-59123.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4199647
description abstractThe possibility of improving point estimates through anisotropic interpolation is investigated. Experiments employing multivariate optimal interpolation compare rms errors for estimates based on an anisotropic geopotential correlation model with those based on three isotropic models and one using station?specific sample correlations. Heights and winds are estimated conjointly for 87 consecutive days, using winter 500 mb data of a 48?station North American network. By varying the array of stations in the observation set contributing to the estimates for a fixed location, measures of accuracy gains are established vis?à?vis observation network density and configuration. Earlier work established the simple isotropic correlation model as a significant source of error in regions of low?density data or irregular station configurations. With the representation of observed correlation behavior provided by a two?dimensional correlation function modeling the well?known anisotropy of the height field, it is shown that gains in accuracy may be substantial. Implications for specification of the shape of optimal influence regions are discussed.
publisherAmerican Meteorological Society
titleExtending Estimation Accuracy with Anisotropic Interpolation
typeJournal Paper
journal volume105
journal issue6
journal titleMonthly Weather Review
identifier doi10.1175/1520-0493(1977)105<0691:EEAWAI>2.0.CO;2
journal fristpage691
journal lastpage699
treeMonthly Weather Review:;1977:;volume( 105 ):;issue: 006
contenttypeFulltext


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