The Sailor diagram – A new diagram for the verification of two-dimensional vector data from multiple models
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Published:2020-07-15
Issue:7
Volume:13
Page:3221-3240
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Sáenz JonORCID, Carreno-Madinabeitia SheilaORCID, Esnaola Ganix, González-Rojí Santos J., Ibarra-Berastegi Gabriel, Ulazia Alain
Abstract
Abstract. A new diagram is proposed for the verification of vector quantities
generated by multiple models against a set of observations. It has
been designed with the objective, as in the Taylor diagram, of
providing a visual diagnostic tool which allows an easy comparison of
simulations by multiple models against a reference dataset. However,
the Sailor diagram extends this ability to two-dimensional quantities
such as currents, wind, horizontal fluxes of water vapour and other
geophysical variables by adding features which allow us to evaluate
directional properties of the data as well. The diagram is based on
the analysis of the two-dimensional structure of the mean squared
error matrix between model and observations. This matrix is separated
in a part corresponding to the bias and the relative rotation of the
two orthogonal directions (empirical orthogonal functions; EOFs) which
best describe the vector data. Since there is no truncation of the
retained EOFs, these orthogonal directions explain the total
variability of the original dataset. We test the performance of this
new diagram to identify the differences amongst the reference dataset
and a series of model outputs by using some synthetic datasets and
real-world examples with time series of variables such as wind,
current and vertically integrated moisture transport. An alternative
setup for spatially varying time-fixed fields is shown in the last
examples, in which the spatial average of surface wind in the Northern
and Southern Hemisphere according to different reanalyses and
realizations from ensembles of CMIP5 models are compared. The Sailor
diagrams presented here show that it is a tool which helps in
identifying errors due to the bias or the orientation of the simulated
vector time series or fields. The R implementation of the diagram
presented together with this paper allows us also to easily retrieve the
individual diagnostics of the different components of the mean squared
error and additional diagnostics which can be presented in tabular
form.
Publisher
Copernicus GmbH
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