A monthly surface pCO2 product for the California Current Large Marine Ecosystem
A common strategy for calculating the direction and rate of carbon dioxide gas (CO 2 ) exchange between the ocean and atmosphere relies on knowledge of the partial pressure of CO 2 in surface seawater ( p CO 2(sw) ), a quantity that is frequently observed by autonomous sensors on ships and moored bu...
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ftcopernicus:oai:publications.copernicus.org:essd98091 2023-05-15T17:52:09+02:00 A monthly surface pCO2 product for the California Current Large Marine Ecosystem Sharp, Jonathan D. Fassbender, Andrea J. Carter, Brendan R. Lavin, Paige D. Sutton, Adrienne J. 2022-04-29 application/pdf https://doi.org/10.5194/essd-14-2081-2022 https://essd.copernicus.org/articles/14/2081/2022/ eng eng doi:10.5194/essd-14-2081-2022 https://essd.copernicus.org/articles/14/2081/2022/ eISSN: 1866-3516 Text 2022 ftcopernicus https://doi.org/10.5194/essd-14-2081-2022 2022-05-02T16:22:29Z A common strategy for calculating the direction and rate of carbon dioxide gas (CO 2 ) exchange between the ocean and atmosphere relies on knowledge of the partial pressure of CO 2 in surface seawater ( p CO 2(sw) ), a quantity that is frequently observed by autonomous sensors on ships and moored buoys, albeit with significant spatial and temporal gaps. Here we present a monthly gridded data product of p CO 2(sw) at 0.25 ∘ latitude by 0.25 ∘ longitude resolution in the northeastern Pacific Ocean, centered on the California Current System (CCS) and spanning all months from January 1998 to December 2020. The data product (RFR-CCS; Sharp et al., 2022; https://doi.org/10.5281/zenodo.5523389 ) was created using observations from the most recent (2021) version of the Surface Ocean CO 2 Atlas (Bakker et al., 2016). These observations were fit against a variety of collocated and contemporaneous satellite- and model-derived surface variables using a random forest regression (RFR) model. We validate RFR-CCS in multiple ways, including direct comparisons with observations from sensors on moored buoys, and find that the data product effectively captures seasonal p CO 2(sw) cycles at nearshore sites. This result is notable because global gridded p CO 2(sw) products do not capture local variability effectively in this region, suggesting that RFR-CCS is a better option than regional extractions from global products to represent p CO 2(sw) in the CCS over the last 2 decades. Lessons learned from the construction of RFR-CCS provide insight into how global p CO 2(sw) products could effectively characterize seasonal variability in nearshore coastal environments. We briefly review the physical and biological processes – acting across a variety of spatial and temporal scales – that are responsible for the latitudinal and nearshore-to-offshore p CO 2(sw) gradients seen in the RFR-CCS reconstruction of p CO 2(sw) . RFR-CCS will be valuable for the validation of high-resolution models, the attribution of spatiotemporal carbonate system variability to physical and biological drivers, and the quantification of multiyear trends and interannual variability of ocean acidification. Text Ocean acidification Copernicus Publications: E-Journals Bakker ENVELOPE(64.588,64.588,-70.326,-70.326) Pacific Earth System Science Data 14 4 2081 2108 |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
language |
English |
description |
A common strategy for calculating the direction and rate of carbon dioxide gas (CO 2 ) exchange between the ocean and atmosphere relies on knowledge of the partial pressure of CO 2 in surface seawater ( p CO 2(sw) ), a quantity that is frequently observed by autonomous sensors on ships and moored buoys, albeit with significant spatial and temporal gaps. Here we present a monthly gridded data product of p CO 2(sw) at 0.25 ∘ latitude by 0.25 ∘ longitude resolution in the northeastern Pacific Ocean, centered on the California Current System (CCS) and spanning all months from January 1998 to December 2020. The data product (RFR-CCS; Sharp et al., 2022; https://doi.org/10.5281/zenodo.5523389 ) was created using observations from the most recent (2021) version of the Surface Ocean CO 2 Atlas (Bakker et al., 2016). These observations were fit against a variety of collocated and contemporaneous satellite- and model-derived surface variables using a random forest regression (RFR) model. We validate RFR-CCS in multiple ways, including direct comparisons with observations from sensors on moored buoys, and find that the data product effectively captures seasonal p CO 2(sw) cycles at nearshore sites. This result is notable because global gridded p CO 2(sw) products do not capture local variability effectively in this region, suggesting that RFR-CCS is a better option than regional extractions from global products to represent p CO 2(sw) in the CCS over the last 2 decades. Lessons learned from the construction of RFR-CCS provide insight into how global p CO 2(sw) products could effectively characterize seasonal variability in nearshore coastal environments. We briefly review the physical and biological processes – acting across a variety of spatial and temporal scales – that are responsible for the latitudinal and nearshore-to-offshore p CO 2(sw) gradients seen in the RFR-CCS reconstruction of p CO 2(sw) . RFR-CCS will be valuable for the validation of high-resolution models, the attribution of spatiotemporal carbonate system variability to physical and biological drivers, and the quantification of multiyear trends and interannual variability of ocean acidification. |
format |
Text |
author |
Sharp, Jonathan D. Fassbender, Andrea J. Carter, Brendan R. Lavin, Paige D. Sutton, Adrienne J. |
spellingShingle |
Sharp, Jonathan D. Fassbender, Andrea J. Carter, Brendan R. Lavin, Paige D. Sutton, Adrienne J. A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
author_facet |
Sharp, Jonathan D. Fassbender, Andrea J. Carter, Brendan R. Lavin, Paige D. Sutton, Adrienne J. |
author_sort |
Sharp, Jonathan D. |
title |
A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
title_short |
A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
title_full |
A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
title_fullStr |
A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
title_full_unstemmed |
A monthly surface pCO2 product for the California Current Large Marine Ecosystem |
title_sort |
monthly surface pco2 product for the california current large marine ecosystem |
publishDate |
2022 |
url |
https://doi.org/10.5194/essd-14-2081-2022 https://essd.copernicus.org/articles/14/2081/2022/ |
long_lat |
ENVELOPE(64.588,64.588,-70.326,-70.326) |
geographic |
Bakker Pacific |
geographic_facet |
Bakker Pacific |
genre |
Ocean acidification |
genre_facet |
Ocean acidification |
op_source |
eISSN: 1866-3516 |
op_relation |
doi:10.5194/essd-14-2081-2022 https://essd.copernicus.org/articles/14/2081/2022/ |
op_doi |
https://doi.org/10.5194/essd-14-2081-2022 |
container_title |
Earth System Science Data |
container_volume |
14 |
container_issue |
4 |
container_start_page |
2081 |
op_container_end_page |
2108 |
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1766159499786190848 |