How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic...

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Main Authors: L. de Mora, M. Butenschön, J. I. Allen
Format: Article
Language:English
Published: Copernicus Publications 2013-04-01
Series:Geoscientific Model Development
Online Access:http://www.geosci-model-dev.net/6/533/2013/gmd-6-533-2013.pdf
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spelling doaj-2bc2e0aaddb8494f863db708a5a235e22020-11-24T22:44:44ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032013-04-016253354810.5194/gmd-6-533-2013How should sparse marine in situ measurements be compared to a continuous model: an exampleL. de MoraM. ButenschönJ. I. AllenThis work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.http://www.geosci-model-dev.net/6/533/2013/gmd-6-533-2013.pdf
collection DOAJ
language English
format Article
sources DOAJ
author L. de Mora
M. Butenschön
J. I. Allen
spellingShingle L. de Mora
M. Butenschön
J. I. Allen
How should sparse marine in situ measurements be compared to a continuous model: an example
Geoscientific Model Development
author_facet L. de Mora
M. Butenschön
J. I. Allen
author_sort L. de Mora
title How should sparse marine in situ measurements be compared to a continuous model: an example
title_short How should sparse marine in situ measurements be compared to a continuous model: an example
title_full How should sparse marine in situ measurements be compared to a continuous model: an example
title_fullStr How should sparse marine in situ measurements be compared to a continuous model: an example
title_full_unstemmed How should sparse marine in situ measurements be compared to a continuous model: an example
title_sort how should sparse marine in situ measurements be compared to a continuous model: an example
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2013-04-01
description This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.
url http://www.geosci-model-dev.net/6/533/2013/gmd-6-533-2013.pdf
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