The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle
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...
Published in: | Earth System Science Data |
---|---|
Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2018
|
Subjects: | |
Online Access: | https://doi.org/10.5194/essd-10-609-2018 https://www.earth-syst-sci-data.net/10/609/2018/essd-10-609-2018.pdf https://doaj.org/article/245249aaf90c4bcabb6d12b0cd603d5e |
id |
fttriple:oai:gotriple.eu:oai:doaj.org/article:245249aaf90c4bcabb6d12b0cd603d5e |
---|---|
record_format |
openpolar |
spelling |
fttriple:oai:gotriple.eu:oai:doaj.org/article:245249aaf90c4bcabb6d12b0cd603d5e 2023-05-15T14:03:53+02:00 The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle R. Latto A. Romanou 2018-03-01 https://doi.org/10.5194/essd-10-609-2018 https://www.earth-syst-sci-data.net/10/609/2018/essd-10-609-2018.pdf https://doaj.org/article/245249aaf90c4bcabb6d12b0cd603d5e en eng Copernicus Publications doi:10.5194/essd-10-609-2018 1866-3508 1866-3516 https://www.earth-syst-sci-data.net/10/609/2018/essd-10-609-2018.pdf https://doaj.org/article/245249aaf90c4bcabb6d12b0cd603d5e undefined Earth System Science Data, Vol 10, Pp 609-626 (2018) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2018 fttriple https://doi.org/10.5194/essd-10-609-2018 2023-01-22T17:53:14Z 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 ... Article in Journal/Newspaper Antarc* Antarctic North Atlantic Southern Ocean Unknown Antarctic Southern Ocean Earth System Science Data 10 1 609 626 |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
geo envir |
spellingShingle |
geo envir R. Latto A. Romanou The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
topic_facet |
geo envir |
description |
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 ... |
format |
Article in Journal/Newspaper |
author |
R. Latto A. Romanou |
author_facet |
R. Latto A. Romanou |
author_sort |
R. Latto |
title |
The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
title_short |
The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
title_full |
The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
title_fullStr |
The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
title_full_unstemmed |
The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
title_sort |
ocean carbon states database: a proof-of-concept application of cluster analysis in the ocean carbon cycle |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/essd-10-609-2018 https://www.earth-syst-sci-data.net/10/609/2018/essd-10-609-2018.pdf https://doaj.org/article/245249aaf90c4bcabb6d12b0cd603d5e |
geographic |
Antarctic Southern Ocean |
geographic_facet |
Antarctic Southern Ocean |
genre |
Antarc* Antarctic North Atlantic Southern Ocean |
genre_facet |
Antarc* Antarctic North Atlantic Southern Ocean |
op_source |
Earth System Science Data, Vol 10, Pp 609-626 (2018) |
op_relation |
doi:10.5194/essd-10-609-2018 1866-3508 1866-3516 https://www.earth-syst-sci-data.net/10/609/2018/essd-10-609-2018.pdf https://doaj.org/article/245249aaf90c4bcabb6d12b0cd603d5e |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/essd-10-609-2018 |
container_title |
Earth System Science Data |
container_volume |
10 |
container_issue |
1 |
container_start_page |
609 |
op_container_end_page |
626 |
_version_ |
1766274744814927872 |