Abstract
SUMMARY: This paper describes the development of a multiparametric interpolation method and its application to anthropogenic carbon (CANT) in the Atlantic, calculated by two estimation methods using the CARINA database. The multiparametric interpolation proposed uses potential temperature (θ), salinity, conservative ‘NO’ and ‘PO’ as conservative parameters for the gridding, and the World Ocean Atlas (WOA05) as a reference for the grid structure and the indicated parameters. We thus complement CARINA data with WOA05 database in an attempt to obtain better gridded values by keeping the physical-biogeochemical sea structures. The algorithms developed here also have the prerequisite of being simple and easy to implement. To test the improvements achieved, a comparison between the proposed multiparametric method and a pure spatial interpolation for an independent parameter (O2) was made. As an application case study, CANT estimations by two methods (jC T o and TrOCA) were performed on the CARINA database and then gridded by both interpolation methods (spatial and multiparametric). Finally, a calculation of CANT inventories for the whole Atlantic Ocean was performed with the gridded values and using ETOPO2v2 as the sea bottom. Thus, the inventories were between 55.1 and 55.2 Pg-C with the jCTo method and between 57.9 and 57.6 Pg-C with the TrOCA method.
Highlights
This work began as a contribution to the CARINA (Carbon in the Atlantic Ocean) Project, with the aim of developing an interpolation algorithm that would enhance the gridding in low coverage areas, but with the premise of being easy to apply
SUMMARY: This paper describes the development of a multiparametric interpolation method and its application to anthropogenic carbon (CANT) in the Atlantic, calculated by two estimation methods using the CARINA database
To assess the quality of both types of interpolation, their results were evaluated against the World Ocean Atlas 2005 (WOA05) data, i.e. the interpolated potential temperature, salinity, ‘NO’ and ‘PO’ obtained from equation (1) were compared with the corresponding original values from WOA05 variables
Summary
This work began as a contribution to the CARINA (Carbon in the Atlantic Ocean) Project, with the aim of developing an interpolation algorithm that would enhance the gridding in low coverage areas, but with the premise of being easy to apply. The present study uses a multiparametric inverse distance algorithm that was applied to the CARINA data (see the Material and Methods section) and took the WOA05 objective interpolated data as a reference to calculate the multiparametric distances. This approach provides a simple interpolation algorithm that is easy to use and to quality assess
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