A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

Steve D. Jones; Corinne Le Quere; Christian Rodenbeck; Andrew Manning; Are Olsen

doi:10.1002/2014MS000416

A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

Steve D. Jones, Corinne Le Quere, Christian Rodenbeck, Andrew Manning, Are Olsen

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Abstract

We have developed a statistical gap-ﬁlling method adapted to the speciﬁc coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a ‘‘radius of inﬂuence’’ to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-ﬁtting, and also ﬁts long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe ﬁtted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage.

Original language	English
Pages (from-to)	1554-1575
Number of pages	22
Journal	Journal of Advances in Modeling Earth Systems
Volume	7
Issue number	4
Early online date	24 Oct 2015
DOIs	https://doi.org/10.1002/2014MS000416
Publication status	Published - Dec 2015

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10.1002/2014MS000416

Jones_et_al-2015-Journal_of_Advances_in_Modeling_Earth_Systems
VC2015. The Authors.This is an open access article under theterms of the Creativ e CommonsAttribution License, which permits use,distribution and reproduction in anymedium, provide d the original work isproperly cited
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Cite this

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title = "A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data",

abstract = "We have developed a statistical gap-ﬁlling method adapted to the speciﬁc coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a {\textquoteleft}{\textquoteleft}radius of inﬂuence{\textquoteright}{\textquoteright} to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-ﬁtting, and also ﬁts long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe ﬁtted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage. ",

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AU - Jones, Steve D.

AU - Le Quere, Corinne

AU - Rodenbeck, Christian

AU - Manning, Andrew

AU - Olsen, Are

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N2 - We have developed a statistical gap-ﬁlling method adapted to the speciﬁc coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a ‘‘radius of inﬂuence’’ to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-ﬁtting, and also ﬁts long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe ﬁtted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage.

AB - We have developed a statistical gap-ﬁlling method adapted to the speciﬁc coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a ‘‘radius of inﬂuence’’ to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-ﬁtting, and also ﬁts long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe ﬁtted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage.

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