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| Titel |
Reconstruction of super-resolution ocean pCO2 and air–sea fluxes of CO2 from satellite imagery in the southeastern Atlantic |
| VerfasserIn |
I. Hernández-Carrasco, J. Sudre, V. Garçon, H. Yahia, C. Garbe, A. Paulmier, B. Dewitte, S. Illig, I. Dadou, M. González-Dávila, J. M. Santana-Casiano |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 12, no. 17 ; Nr. 12, no. 17 (2015-09-11), S.5229-5245 |
| Datensatznummer |
250118086
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| Publikation (Nr.) |
 copernicus.org/bg-12-5229-2015.pdf |
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| Zusammenfassung |
| An accurate quantification of the role of the ocean as source/sink of
greenhouse gases (GHGs) requires to access the high-resolution of the GHG
air–sea flux at the interface. In this paper we present a novel method to
reconstruct maps of surface ocean partial pressure of CO2 ( pCO2) and
air–sea CO2 fluxes at super resolution (4 km, i.e.,
1/32° at these latitudes) using sea
surface temperature (SST) and ocean color (OC) data at this resolution, and
CarbonTracker CO2 fluxes data at low resolution (110 km). Inference of
super-resolution pCO2 and air–sea CO2 fluxes is performed using
novel nonlinear signal processing methodologies that prove efficient in the
context of oceanography. The theoretical background comes from the
microcanonical multifractal formalism which unlocks the geometrical
determination of cascading properties of physical intensive variables. As a
consequence, a multi-resolution analysis performed on the signal of the
so-called singularity exponents allows for the correct and near optimal
cross-scale inference of GHG fluxes, as the inference suits the geometric
realization of the cascade. We apply such a methodology to the study offshore
of the Benguela area. The inferred representation of oceanic partial pressure
of CO2 improves and enhances the description provided by CarbonTracker,
capturing the small-scale variability. We examine different combinations of
ocean color and sea surface temperature products in order to increase the
number of valid points and the quality of the inferred pCO2 field. The
methodology is validated using in situ measurements by means of statistical
errors. We find that mean absolute and relative errors in the inferred values
of pCO2 with respect to in situ measurements are smaller than for
CarbonTracker. |
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