CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system
<p>Observation-based data reconstructions of global surface ocean carbonate system variables play an essential role in monitoring the recent status of ocean carbon uptake and ocean acidification, as well as their impacts on marine organisms and ecosystems. So far, ongoing efforts are directed...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2024-01-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/16/121/2024/essd-16-121-2024.pdf |
| _version_ | 1797359459550363648 |
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| author | T.-T.-T. Chau M. Gehlen N. Metzl F. Chevallier |
| author_facet | T.-T.-T. Chau M. Gehlen N. Metzl F. Chevallier |
| author_sort | T.-T.-T. Chau |
| collection | DOAJ |
| description | <p>Observation-based data reconstructions of global surface ocean carbonate system variables play an essential role in monitoring the recent status of ocean carbon uptake and ocean acidification, as well as their impacts on marine organisms and ecosystems. So far, ongoing efforts are directed towards exploring new approaches to describe the complete marine carbonate system and to better recover its fine-scale features. In this respect, our research activities within the Copernicus Marine Environment Monitoring Service (CMEMS) aim to develop a sustainable production chain of observation-derived global ocean carbonate system datasets at high space–time resolutions. As the start of the long-term objective, this study introduces a new global 0.25<span class="inline-formula"><sup>∘</sup></span> monthly reconstruction, namely CMEMS-LSCE (Laboratoire des Sciences du Climat et de l'Environnement) for the period 1985–2021. The CMEMS-LSCE reconstruction derives datasets of six carbonate system variables, including surface ocean partial pressure of <span class="inline-formula">CO<sub>2</sub></span> (<span class="inline-formula"><i>p</i>CO<sub>2</sub></span>), total alkalinity (<span class="inline-formula"><i>A</i><sub>T</sub></span>), total dissolved inorganic carbon (<span class="inline-formula"><i>C</i><sub>T</sub></span>), surface ocean pH, and saturation states with respect to aragonite (<span class="inline-formula">Ω<sub>ar</sub></span>) and calcite (<span class="inline-formula">Ω<sub>ca</sub></span>). Reconstructing <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> relies on an ensemble of neural network models mapping gridded observation-based data provided by the Surface Ocean <span class="inline-formula">CO<sub>2</sub></span> ATlas (SOCAT). Surface ocean <span class="inline-formula"><i>A</i><sub>T</sub></span> is estimated with a multiple-linear-regression approach, and the remaining carbonate variables are resolved by <span class="inline-formula">CO<sub>2</sub></span> system speciation given the reconstructed <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> and <span class="inline-formula"><i>A</i><sub>T</sub></span>; 1<span class="inline-formula"><i>σ</i></span> uncertainty associated with these estimates is also provided. Here, <span class="inline-formula"><i>σ</i></span> stands for either the ensemble standard deviation of <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> estimates or the total uncertainty for each of the five other variables propagated through the processing chain with input data uncertainty. We demonstrate that the 0.25<span class="inline-formula"><sup>∘</sup></span> resolution <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> product outperforms a coarser spatial resolution (1<span class="inline-formula"><sup>∘</sup></span>) thanks to higher data coverage nearshore and a better description of horizontal and temporal variations in <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> across diverse ocean basins, particularly in the coastal–open-ocean continuum. Product qualification with observation-based data confirms reliable reconstructions with root-mean-square deviation from observations of less than 8 %, 4 %, and 1 % relative to the global mean of <span class="inline-formula"><i>p</i>CO<sub>2</sub></span>, <span class="inline-formula"><i>A</i><sub>T</sub></span> (<span class="inline-formula"><i>C</i><sub>T</sub></span>), and pH. The global average 1<span class="inline-formula"><i>σ</i></span> uncertainty is below 5 % and 8 % for <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> and <span class="inline-formula">Ω<sub>ar</sub></span> (<span class="inline-formula">Ω<sub>ca</sub></span>), 2 % for <span class="inline-formula"><i>A</i><sub>T</sub></span> and <span class="inline-formula"><i>C</i><sub>T</sub></span>, and 0.4 % for pH relative to their global mean values. Both model–observation misfit and model uncertainty indicate that coastal data reproduction still needs further improvement, wherein high temporal and horizontal gradients of carbonate variables and representative uncertainty from data sampling would be taken into account as a priority. This study also presents a potential use case of the CMEMS-LSCE carbonate data product in tracking the recent state of ocean acidification. The data associated with this study are available at <a href="https://doi.org/10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982">https://doi.org/10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982</a> (Chau et al., 2023).</p> |
| first_indexed | 2024-03-08T15:25:11Z |
| format | Article |
| id | doaj.art-0f1727e2584842e5bb1c90080fb9b8a5 |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-03-08T15:25:11Z |
| publishDate | 2024-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-0f1727e2584842e5bb1c90080fb9b8a52024-01-10T10:14:12ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162024-01-011612116010.5194/essd-16-121-2024CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate systemT.-T.-T. Chau0M. Gehlen1N. Metzl2F. Chevallier3Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, FranceLaboratoire LOCEAN (IPSL), Sorbonne Université, CNRS–IRD–MNHN, Paris, 75005, FranceLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France<p>Observation-based data reconstructions of global surface ocean carbonate system variables play an essential role in monitoring the recent status of ocean carbon uptake and ocean acidification, as well as their impacts on marine organisms and ecosystems. So far, ongoing efforts are directed towards exploring new approaches to describe the complete marine carbonate system and to better recover its fine-scale features. In this respect, our research activities within the Copernicus Marine Environment Monitoring Service (CMEMS) aim to develop a sustainable production chain of observation-derived global ocean carbonate system datasets at high space–time resolutions. As the start of the long-term objective, this study introduces a new global 0.25<span class="inline-formula"><sup>∘</sup></span> monthly reconstruction, namely CMEMS-LSCE (Laboratoire des Sciences du Climat et de l'Environnement) for the period 1985–2021. The CMEMS-LSCE reconstruction derives datasets of six carbonate system variables, including surface ocean partial pressure of <span class="inline-formula">CO<sub>2</sub></span> (<span class="inline-formula"><i>p</i>CO<sub>2</sub></span>), total alkalinity (<span class="inline-formula"><i>A</i><sub>T</sub></span>), total dissolved inorganic carbon (<span class="inline-formula"><i>C</i><sub>T</sub></span>), surface ocean pH, and saturation states with respect to aragonite (<span class="inline-formula">Ω<sub>ar</sub></span>) and calcite (<span class="inline-formula">Ω<sub>ca</sub></span>). Reconstructing <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> relies on an ensemble of neural network models mapping gridded observation-based data provided by the Surface Ocean <span class="inline-formula">CO<sub>2</sub></span> ATlas (SOCAT). Surface ocean <span class="inline-formula"><i>A</i><sub>T</sub></span> is estimated with a multiple-linear-regression approach, and the remaining carbonate variables are resolved by <span class="inline-formula">CO<sub>2</sub></span> system speciation given the reconstructed <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> and <span class="inline-formula"><i>A</i><sub>T</sub></span>; 1<span class="inline-formula"><i>σ</i></span> uncertainty associated with these estimates is also provided. Here, <span class="inline-formula"><i>σ</i></span> stands for either the ensemble standard deviation of <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> estimates or the total uncertainty for each of the five other variables propagated through the processing chain with input data uncertainty. We demonstrate that the 0.25<span class="inline-formula"><sup>∘</sup></span> resolution <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> product outperforms a coarser spatial resolution (1<span class="inline-formula"><sup>∘</sup></span>) thanks to higher data coverage nearshore and a better description of horizontal and temporal variations in <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> across diverse ocean basins, particularly in the coastal–open-ocean continuum. Product qualification with observation-based data confirms reliable reconstructions with root-mean-square deviation from observations of less than 8 %, 4 %, and 1 % relative to the global mean of <span class="inline-formula"><i>p</i>CO<sub>2</sub></span>, <span class="inline-formula"><i>A</i><sub>T</sub></span> (<span class="inline-formula"><i>C</i><sub>T</sub></span>), and pH. The global average 1<span class="inline-formula"><i>σ</i></span> uncertainty is below 5 % and 8 % for <span class="inline-formula"><i>p</i>CO<sub>2</sub></span> and <span class="inline-formula">Ω<sub>ar</sub></span> (<span class="inline-formula">Ω<sub>ca</sub></span>), 2 % for <span class="inline-formula"><i>A</i><sub>T</sub></span> and <span class="inline-formula"><i>C</i><sub>T</sub></span>, and 0.4 % for pH relative to their global mean values. Both model–observation misfit and model uncertainty indicate that coastal data reproduction still needs further improvement, wherein high temporal and horizontal gradients of carbonate variables and representative uncertainty from data sampling would be taken into account as a priority. This study also presents a potential use case of the CMEMS-LSCE carbonate data product in tracking the recent state of ocean acidification. The data associated with this study are available at <a href="https://doi.org/10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982">https://doi.org/10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982</a> (Chau et al., 2023).</p>https://essd.copernicus.org/articles/16/121/2024/essd-16-121-2024.pdf |
| spellingShingle | T.-T.-T. Chau M. Gehlen N. Metzl F. Chevallier CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system Earth System Science Data |
| title | CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system |
| title_full | CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system |
| title_fullStr | CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system |
| title_full_unstemmed | CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system |
| title_short | CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system |
| title_sort | cmems lsce a global 0 25° monthly reconstruction of the surface ocean carbonate system |
| url | https://essd.copernicus.org/articles/16/121/2024/essd-16-121-2024.pdf |
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