The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle
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Published:2018-03-27
Issue:1
Volume:10
Page:609-626
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ISSN:1866-3516
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Container-title:Earth System Science Data
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language:en
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Short-container-title:Earth Syst. Sci. Data
Author:
Latto Rebecca, Romanou AnastasiaORCID
Abstract
Abstract. In this paper, we present a database of the basic regimes of the carbon cycle
in the ocean, the “ocean carbon states”, as obtained using a data
mining/pattern recognition technique in observation-based as well as model
data. The goal of this study is to establish a new data analysis methodology,
test it and assess its utility in providing more insights into the regional
and temporal variability of the marine carbon cycle. This is important as
advanced data mining techniques are becoming widely used in climate and Earth
sciences and in particular in studies of the global carbon cycle, where the
interaction of physical and biogeochemical drivers confounds our ability to
accurately describe, understand, and predict CO2 concentrations and
their changes in the major planetary carbon reservoirs. In this
proof-of-concept study, we focus on using well-understood data that are based
on observations, as well as model results from the NASA Goddard Institute for
Space Studies (GISS) climate model. Our analysis shows that ocean carbon
states are associated with the subtropical–subpolar gyre during the colder
months of the year and the tropics during the warmer season in the North
Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states
can be associated with the subtropical and Antarctic convergence zones in the
warmer season and the coastal Antarctic divergence zone in the colder season.
With respect to model evaluation, we find that the GISS model reproduces the
cold and warm season regimes more skillfully in the North Atlantic than in
the Southern Ocean and matches the observed seasonality better than the
spatial distribution of the regimes. Finally, the ocean carbon states provide
useful information in the model error attribution. Model air–sea CO2
flux biases in the North Atlantic stem from wind speed and salinity biases in
the subpolar region and nutrient and wind speed biases in the subtropics and
tropics. Nutrient biases are shown to be most important in the Southern Ocean
flux bias. All data and analysis scripts are available at
https://data.giss.nasa.gov/oceans/carbonstates/ (DOI:
https://doi.org/10.5281/zenodo.996891).
Funder
National Aeronautics and Space Administration
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
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