Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-7169-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-7169-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
15 Dec 2025
Data description article |
| 15 Dec 2025
| 15 Dec 2025
Climatological fields of Southern Ocean interior carbonate system parameters and anthropogenic CO2 reconstructed and integrated from float- and ship-based observations
Wanqin Zhong
Polar and Marine Research Institute, Jimei University, Xiamen 361021, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
Xin Ma
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
Wuhan Institute of Quantum Technology, Wuhan 430079, China
Yingxu Wu
CORRESPONDING AUTHOR
Polar and Marine Research Institute, Jimei University, Xiamen 361021, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Chenglong Li
Polar and Marine Research Institute, Jimei University, Xiamen 361021, China
Tianqi Shi
Laboratoire des Sciences du Climat et de l’Environnement/IPSL, CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Wei Gong
Wuhan Institute of Quantum Technology, Wuhan 430079, China
Luojia Laboratory, Wuhan University, Wuhan 430079, China
Di Qi
CORRESPONDING AUTHOR
Polar and Marine Research Institute, Jimei University, Xiamen 361021, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Viewed
Total article views: 3,635 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 21 Aug 2025)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,256 | 1,216 | 163 | 3,635 | 120 | 146 |
- HTML: 2,256
- PDF: 1,216
- XML: 163
- Total: 3,635
- BibTeX: 120
- EndNote: 146
Total article views: 1,677 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Dec 2025)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 833 | 727 | 117 | 1,677 | 63 | 78 |
- HTML: 833
- PDF: 727
- XML: 117
- Total: 1,677
- BibTeX: 63
- EndNote: 78
Total article views: 1,958 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 21 Aug 2025)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,423 | 489 | 46 | 1,958 | 57 | 68 |
- HTML: 1,423
- PDF: 489
- XML: 46
- Total: 1,958
- BibTeX: 57
- EndNote: 68
Viewed (geographical distribution)
Total article views: 3,635 (including HTML, PDF, and XML)
Thereof 3,549 with geography defined
and 86 with unknown origin.
Total article views: 1,677 (including HTML, PDF, and XML)
Thereof 1,635 with geography defined
and 42 with unknown origin.
Total article views: 1,958 (including HTML, PDF, and XML)
Thereof 1,914 with geography defined
and 44 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
14 citations as recorded by crossref.
- From traditional observation to intelligent monitoring of estuarine, coastal, and shelf-sea environments: A review Q. Li et al. https://doi.org/10.1016/j.ecss.2026.110067
- Estimating carbon storage and flux in sea urchin barrens following kelp forest collapse L. Rogers-Bennett et al. https://doi.org/10.1016/j.marenvres.2026.108297
- Capturing carbon, creating value: unlocking carbon capture and storage and carbon capture and utilization for a net‐zero future F. Ahmad et al. https://doi.org/10.1002/bbb.70120
- Editorial: Effects of climate change on urban streams in the Anthropocene: how ready are we to tackle this looming danger? A. Edegbene et al. https://doi.org/10.3389/fenvs.2026.1915381
- Does the Circular Economy Reduce CO2 Emissions? Evidence from European Countries W. Yue & Y. Rasool https://doi.org/10.3390/su18104790
- Machine learning-augmented climate models for predicting groundwater stress zones in Sub-Saharan Africa J. Alao et al. https://doi.org/10.1007/s40328-026-00497-2
- Trait-to-landscape mapping of mangrove leaf organic carbon: a field-calibrated, species-resolved framework integrating Earth observation and machine learning in the western Sundarbans I. Mondal et al. https://doi.org/10.1016/j.pce.2026.104762
- Remote sensing and machine learning-based mapping of climatic stress impacts on vegetation and carbon sequestration K. Mehmood et al. https://doi.org/10.1080/10106049.2026.2641408
- Advancing real-time coastal data monitoring: Bio-optical property analysis (chlorophyll-a and TSM) in the Northern Bay of Bengal using Sentinel-3 OLCI, IRS Oceansat-3, and artificial neural networks A. De et al. https://doi.org/10.1016/j.marpolbul.2025.119199
- Predicting blue carbon sequestration in Sundarban coastal mangroves: A spatially explicit approach with INVEST and machine learning to advance climate resilience and UN SDG-aligned nature-based climate solutions I. Mondal et al. https://doi.org/10.1016/j.marpolbul.2026.119387
- AI-driven ocean-colour prediction of potential fishing zones for blue-economy resource sustainability in the northern Bay of Bengal I. Mondal et al. https://doi.org/10.1016/j.pce.2026.104655
- Unveiling climate transformations in the northwestern Caucasus: the Middle Holocene divergence of landscape evolution P. Kalinin et al. https://doi.org/10.1038/s41598-026-51669-7
- Predicting coastal subsidence and sea-level scenarios in the Sundarbans Delta using InSAR and artificial intelligence for sustainable coastal management I. Mondal et al. https://doi.org/10.1016/j.marpolbul.2026.119386
- Clipping-and-burning alters carbon and nitrogen cycling through bacterial fixation pathways in the key Chinese karst region A. Rebi et al. https://doi.org/10.1016/j.jenvman.2026.128721
14 citations as recorded by crossref.
- From traditional observation to intelligent monitoring of estuarine, coastal, and shelf-sea environments: A review Q. Li et al. https://doi.org/10.1016/j.ecss.2026.110067
- Estimating carbon storage and flux in sea urchin barrens following kelp forest collapse L. Rogers-Bennett et al. https://doi.org/10.1016/j.marenvres.2026.108297
- Capturing carbon, creating value: unlocking carbon capture and storage and carbon capture and utilization for a net‐zero future F. Ahmad et al. https://doi.org/10.1002/bbb.70120
- Editorial: Effects of climate change on urban streams in the Anthropocene: how ready are we to tackle this looming danger? A. Edegbene et al. https://doi.org/10.3389/fenvs.2026.1915381
- Does the Circular Economy Reduce CO2 Emissions? Evidence from European Countries W. Yue & Y. Rasool https://doi.org/10.3390/su18104790
- Machine learning-augmented climate models for predicting groundwater stress zones in Sub-Saharan Africa J. Alao et al. https://doi.org/10.1007/s40328-026-00497-2
- Trait-to-landscape mapping of mangrove leaf organic carbon: a field-calibrated, species-resolved framework integrating Earth observation and machine learning in the western Sundarbans I. Mondal et al. https://doi.org/10.1016/j.pce.2026.104762
- Remote sensing and machine learning-based mapping of climatic stress impacts on vegetation and carbon sequestration K. Mehmood et al. https://doi.org/10.1080/10106049.2026.2641408
- Advancing real-time coastal data monitoring: Bio-optical property analysis (chlorophyll-a and TSM) in the Northern Bay of Bengal using Sentinel-3 OLCI, IRS Oceansat-3, and artificial neural networks A. De et al. https://doi.org/10.1016/j.marpolbul.2025.119199
- Predicting blue carbon sequestration in Sundarban coastal mangroves: A spatially explicit approach with INVEST and machine learning to advance climate resilience and UN SDG-aligned nature-based climate solutions I. Mondal et al. https://doi.org/10.1016/j.marpolbul.2026.119387
- AI-driven ocean-colour prediction of potential fishing zones for blue-economy resource sustainability in the northern Bay of Bengal I. Mondal et al. https://doi.org/10.1016/j.pce.2026.104655
- Unveiling climate transformations in the northwestern Caucasus: the Middle Holocene divergence of landscape evolution P. Kalinin et al. https://doi.org/10.1038/s41598-026-51669-7
- Predicting coastal subsidence and sea-level scenarios in the Sundarbans Delta using InSAR and artificial intelligence for sustainable coastal management I. Mondal et al. https://doi.org/10.1016/j.marpolbul.2026.119386
- Clipping-and-burning alters carbon and nitrogen cycling through bacterial fixation pathways in the key Chinese karst region A. Rebi et al. https://doi.org/10.1016/j.jenvman.2026.128721
Saved (final revised paper)
Latest update: 23 Aug 2026
Short summary
This work addresses a critical observational gap in the Southern Ocean — one of the most important regions for carbon uptake — by integrating comprehensive Argo float observations with historical ship-based measurements. Our findings demonstrate the feasibility of using machine learning models to integrate observations, and support in-depth analyses of carbon transport and storage mechanisms. This can foster broader utilization of Argo floats data in ocean carbon research.
This work addresses a critical observational gap in the Southern Ocean — one of the most...
Altmetrics
Final-revised paper
Preprint