Structural and statistical properties of the collocation technique for error characterization

The validation of geophysical data sets (e.g. derived from models, exploration techniques or remote sensing) presents a formidable challenge as all products are inherently different and subject to errors. The collocation technique permits the retrieval of the error variances of different data source...

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Main Authors: S. Zwieback, K. Scipal, W. Dorigo, W. Wagner
Format: Article
Language:English
Published: Copernicus Publications 2012-02-01
Series:Nonlinear Processes in Geophysics
Online Access:http://www.nonlin-processes-geophys.net/19/69/2012/npg-19-69-2012.pdf
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spelling doaj-f021523aa3494bdaafa130e6e7a9ada12020-11-25T00:12:49ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462012-02-01191698010.5194/npg-19-69-2012Structural and statistical properties of the collocation technique for error characterizationS. ZwiebackK. ScipalW. DorigoW. WagnerThe validation of geophysical data sets (e.g. derived from models, exploration techniques or remote sensing) presents a formidable challenge as all products are inherently different and subject to errors. The collocation technique permits the retrieval of the error variances of different data sources without the need to specify one data set as a reference. In addition calibration constants can be determined to account for biases and different dynamic ranges. The method is frequently applied to the study and comparison of remote sensing, in-situ and modelled data, particularly in hydrology and oceanography. Previous studies have almost exclusively focussed on the validation of three data sources; in this paper it is shown how the technique generalizes to an arbitrary number of data sets. It turns out that only parts of the covariance structure can be resolved by the collocation technique, thus emphasizing the necessity of expert knowledge for the correct validation of geophysical products. Furthermore the bias and error variance of the estimators are derived with particular emphasis on the assumptions necessary for establishing those characteristics. Important properties of the method, such as the structural deficiencies, dependence of the accuracy on the number of measurements and the impact of violated assumptions, are illustrated by application to simulated data.http://www.nonlin-processes-geophys.net/19/69/2012/npg-19-69-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author S. Zwieback
K. Scipal
W. Dorigo
W. Wagner
spellingShingle S. Zwieback
K. Scipal
W. Dorigo
W. Wagner
Structural and statistical properties of the collocation technique for error characterization
Nonlinear Processes in Geophysics
author_facet S. Zwieback
K. Scipal
W. Dorigo
W. Wagner
author_sort S. Zwieback
title Structural and statistical properties of the collocation technique for error characterization
title_short Structural and statistical properties of the collocation technique for error characterization
title_full Structural and statistical properties of the collocation technique for error characterization
title_fullStr Structural and statistical properties of the collocation technique for error characterization
title_full_unstemmed Structural and statistical properties of the collocation technique for error characterization
title_sort structural and statistical properties of the collocation technique for error characterization
publisher Copernicus Publications
series Nonlinear Processes in Geophysics
issn 1023-5809
1607-7946
publishDate 2012-02-01
description The validation of geophysical data sets (e.g. derived from models, exploration techniques or remote sensing) presents a formidable challenge as all products are inherently different and subject to errors. The collocation technique permits the retrieval of the error variances of different data sources without the need to specify one data set as a reference. In addition calibration constants can be determined to account for biases and different dynamic ranges. The method is frequently applied to the study and comparison of remote sensing, in-situ and modelled data, particularly in hydrology and oceanography. Previous studies have almost exclusively focussed on the validation of three data sources; in this paper it is shown how the technique generalizes to an arbitrary number of data sets. It turns out that only parts of the covariance structure can be resolved by the collocation technique, thus emphasizing the necessity of expert knowledge for the correct validation of geophysical products. Furthermore the bias and error variance of the estimators are derived with particular emphasis on the assumptions necessary for establishing those characteristics. Important properties of the method, such as the structural deficiencies, dependence of the accuracy on the number of measurements and the impact of violated assumptions, are illustrated by application to simulated data.
url http://www.nonlin-processes-geophys.net/19/69/2012/npg-19-69-2012.pdf
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