Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters
The dataset contains interpolated fields of surface ocean partial pressure of carbon dioxide (pCO2sw) for the South Atlantic Ocean (10N – 60S; 25E-70W) on a monthly time and 1 degree latitude and longitude grid, between July 2002 and December 2018. The pCO2sw is interpolated using SOCATv2020 observa...
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ftdatacite:10.1594/pangaea.935936 2023-05-15T18:20:42+02:00 Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters Ford, Daniel J Tilstone, Gavin H Shutler, Jamie D Kitidis, Vassilis 2021 text/tab-separated-values https://dx.doi.org/10.1594/pangaea.935936 https://doi.pangaea.de/10.1594/PANGAEA.935936 en eng PANGAEA - Data Publisher for Earth & Environmental Science https://dx.doi.org/10.5194/bg-19-93-2022 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY chlorophyll-a Net community production net primary production pCO2 South Atlantic Ocean File content Binary Object File Size Binary Object interpolated Dataset dataset 2021 ftdatacite https://doi.org/10.1594/pangaea.935936 https://doi.org/10.5194/bg-19-93-2022 2022-03-10T10:53:10Z The dataset contains interpolated fields of surface ocean partial pressure of carbon dioxide (pCO2sw) for the South Atlantic Ocean (10N – 60S; 25E-70W) on a monthly time and 1 degree latitude and longitude grid, between July 2002 and December 2018. The pCO2sw is interpolated using SOCATv2020 observational data, that have been corrected to the surface sub skin temperature, using a neural network interpolation scheme described in Ford et al. (2022).Five separate pCO2sw estimates are provided using different biological parameters as input to the interpolation scheme. These consist of net community production (NCP), net primary production, chlorophyll-a, and two variants with no biological parameters as input. Full details are given in the article published in Biogeosciences. This article highlights that the NCP variant is the most accurate and therefore is the recommended version. : The data submission contains five netCDF files. The files contain the pCO2sw estimates for the South Atlantic Ocean from five neural network interpolation schemes, using different biological parameters as input, as described in Ford et al. (2022). These biological parameters are net community production (FULL_PCO2_SAFNN_NCP_072002_122018.nc), net primary production (FULL_PCO2_SAFNN_NPP_072002_122018.nc) and chlorophyll-a (FULL_PCO2_SAFNN_CHL_072002_122018.nc). Two variants of the neural network without biological parameters are also presented: one trained with SST (FULL_PCO2_SAFNN_NO_BIO_1_072002_122018.nc) and the second with SST, salinity, and mixed layer depth (FULL_PCO2_SAFNN_NO_BIO_2_072002_122018.nc). Inputs parameters for all the variants are shown in Table 2 of the accompanying manuscript (Ford et al., 2022).Within each netCDF, five variables are present:latitude – The latitude grid in degrees north (10N to -60N).longitude – The longitude grid in degrees east (25E to -75E).time – MATLAB date number for the 1st day of each month. This is 198 months spanning July 2002 to December 2018pCO2sw – The interpolated partial pressure of CO2 in seawater corrected to the surface sub skin in μatm.pCO2sw_unc – The propagated uncertainty on the partial pressure of CO2 in seawater in μatm. Dataset South Atlantic Ocean DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
language |
English |
topic |
chlorophyll-a Net community production net primary production pCO2 South Atlantic Ocean File content Binary Object File Size Binary Object interpolated |
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chlorophyll-a Net community production net primary production pCO2 South Atlantic Ocean File content Binary Object File Size Binary Object interpolated Ford, Daniel J Tilstone, Gavin H Shutler, Jamie D Kitidis, Vassilis Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
topic_facet |
chlorophyll-a Net community production net primary production pCO2 South Atlantic Ocean File content Binary Object File Size Binary Object interpolated |
description |
The dataset contains interpolated fields of surface ocean partial pressure of carbon dioxide (pCO2sw) for the South Atlantic Ocean (10N – 60S; 25E-70W) on a monthly time and 1 degree latitude and longitude grid, between July 2002 and December 2018. The pCO2sw is interpolated using SOCATv2020 observational data, that have been corrected to the surface sub skin temperature, using a neural network interpolation scheme described in Ford et al. (2022).Five separate pCO2sw estimates are provided using different biological parameters as input to the interpolation scheme. These consist of net community production (NCP), net primary production, chlorophyll-a, and two variants with no biological parameters as input. Full details are given in the article published in Biogeosciences. This article highlights that the NCP variant is the most accurate and therefore is the recommended version. : The data submission contains five netCDF files. The files contain the pCO2sw estimates for the South Atlantic Ocean from five neural network interpolation schemes, using different biological parameters as input, as described in Ford et al. (2022). These biological parameters are net community production (FULL_PCO2_SAFNN_NCP_072002_122018.nc), net primary production (FULL_PCO2_SAFNN_NPP_072002_122018.nc) and chlorophyll-a (FULL_PCO2_SAFNN_CHL_072002_122018.nc). Two variants of the neural network without biological parameters are also presented: one trained with SST (FULL_PCO2_SAFNN_NO_BIO_1_072002_122018.nc) and the second with SST, salinity, and mixed layer depth (FULL_PCO2_SAFNN_NO_BIO_2_072002_122018.nc). Inputs parameters for all the variants are shown in Table 2 of the accompanying manuscript (Ford et al., 2022).Within each netCDF, five variables are present:latitude – The latitude grid in degrees north (10N to -60N).longitude – The longitude grid in degrees east (25E to -75E).time – MATLAB date number for the 1st day of each month. This is 198 months spanning July 2002 to December 2018pCO2sw – The interpolated partial pressure of CO2 in seawater corrected to the surface sub skin in μatm.pCO2sw_unc – The propagated uncertainty on the partial pressure of CO2 in seawater in μatm. |
format |
Dataset |
author |
Ford, Daniel J Tilstone, Gavin H Shutler, Jamie D Kitidis, Vassilis |
author_facet |
Ford, Daniel J Tilstone, Gavin H Shutler, Jamie D Kitidis, Vassilis |
author_sort |
Ford, Daniel J |
title |
Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
title_short |
Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
title_full |
Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
title_fullStr |
Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
title_full_unstemmed |
Interpolated surface ocean carbon dioxide partial pressure for the South Atlantic Ocean (2002-2018) using different biological parameters |
title_sort |
interpolated surface ocean carbon dioxide partial pressure for the south atlantic ocean (2002-2018) using different biological parameters |
publisher |
PANGAEA - Data Publisher for Earth & Environmental Science |
publishDate |
2021 |
url |
https://dx.doi.org/10.1594/pangaea.935936 https://doi.pangaea.de/10.1594/PANGAEA.935936 |
genre |
South Atlantic Ocean |
genre_facet |
South Atlantic Ocean |
op_relation |
https://dx.doi.org/10.5194/bg-19-93-2022 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1594/pangaea.935936 https://doi.org/10.5194/bg-19-93-2022 |
_version_ |
1766198469391810560 |