Extending Estimation Accuracy with Anisotropic InterpolationSource: Monthly Weather Review:;1977:;volume( 105 ):;issue: 006::page 691Author:Thiébaux, H. Jean
DOI: 10.1175/1520-0493(1977)105<0691:EEAWAI>2.0.CO;2Publisher: American Meteorological Society
Abstract: The 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.
|
Collections
Show full item record
contributor author | Thiébaux, H. Jean | |
date accessioned | 2017-06-09T16:01:37Z | |
date available | 2017-06-09T16:01:37Z | |
date copyright | 1977/06/01 | |
date issued | 1977 | |
identifier issn | 0027-0644 | |
identifier other | ams-59123.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4199647 | |
description abstract | The 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. | |
publisher | American Meteorological Society | |
title | Extending Estimation Accuracy with Anisotropic Interpolation | |
type | Journal Paper | |
journal volume | 105 | |
journal issue | 6 | |
journal title | Monthly Weather Review | |
identifier doi | 10.1175/1520-0493(1977)105<0691:EEAWAI>2.0.CO;2 | |
journal fristpage | 691 | |
journal lastpage | 699 | |
tree | Monthly Weather Review:;1977:;volume( 105 ):;issue: 006 | |
contenttype | Fulltext |