91 citations as recorded by crossref.

1. Biome partitioning of the global ocean based on phytoplankton biogeography U. Hofmann Elizondo et al. https://doi.org/10.1016/j.pocean.2021.102530
2. Global Carbon Budget 2021 P. Friedlingstein et al. https://doi.org/10.5194/essd-14-1917-2022
3. A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States J. Sharp et al. https://doi.org/10.1038/s41597-024-03530-7
4. Ocean carbonate system variability in the North Atlantic Subpolar surface water (1993–2017) C. Leseurre et al. https://doi.org/10.5194/bg-17-2553-2020
5. A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED M. Fourrier et al. https://doi.org/10.3389/fmars.2020.00620
6. Oceanic uptake of CO 2 enhanced by mesoscale eddies X. Li et al. https://doi.org/10.1126/sciadv.adt4195
7. Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles K. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2024.09.033
8. An assessment of the North Atlantic (25–75°N) air-sea CO2 flux in 12 CMIP6 models Y. Jing et al. https://doi.org/10.1016/j.dsr.2021.103682
9. An empirical MLR for estimating surface layer DIC and a comparative assessment to other gap-filling techniques for ocean carbon time series J. Vance et al. https://doi.org/10.5194/bg-19-241-2022
10. Observation system simulation experiments in the Atlantic Ocean for enhanced surface ocean pCO2 reconstructions A. Denvil-Sommer et al. https://doi.org/10.5194/os-17-1011-2021
11. Explicit Physical Knowledge in Machine Learning for Ocean Carbon Flux Reconstruction: The pCO2‐Residual Method V. Bennington et al. https://doi.org/10.1029/2021MS002960
12. Global Carbon Budget 2024 P. Friedlingstein et al. https://doi.org/10.5194/essd-17-965-2025
13. The impact of seasonality on the annual air-sea carbon flux and its interannual variability P. Rustogi et al. https://doi.org/10.1038/s41612-023-00378-3
14. Identifying the Most (Cost‐)Efficient Regions for CO2 Removal With Iron Fertilization in the Southern Ocean L. Bach et al. https://doi.org/10.1029/2023GB007754
15. Direct observational evidence of strong CO 2 uptake in the Southern Ocean Y. Dong et al. https://doi.org/10.1126/sciadv.adn5781
16. Global Carbon Budget 2020 P. Friedlingstein et al. https://doi.org/10.5194/essd-12-3269-2020
17. Southern Ocean phytoplankton dynamics and carbon export: insights from a seasonal cycle approach S. Thomalla et al. https://doi.org/10.1098/rsta.2022.0068
18. Decomposing tropical Pacific air-sea CO2 flux anomalies during marine heatwaves and cold spells: thermal versus non-thermal drivers Z. Meng & Y. Cai https://doi.org/10.3389/fmars.2026.1767039
19. Improved air-sea CO 2 flux estimates from sailboat measurements J. Behncke et al. https://doi.org/10.1126/sciadv.adz1502
20. Remote sensing and machine learning method to support sea surface pCO2 estimation in the Yellow Sea W. Li et al. https://doi.org/10.3389/fmars.2023.1181095
21. Synthesis of data products for ocean carbonate chemistry L. Jiang et al. https://doi.org/10.5194/essd-18-1405-2026
22. Comparison of Machine Learning Approaches for Reconstructing Sea Subsurface Salinity Using Synthetic Data T. Tian et al. https://doi.org/10.3390/rs14225650
23. Spatiotemporal reconstruction of global ocean surface pCO2 based on optimized random forest H. Wu et al. https://doi.org/10.1016/j.scitotenv.2023.169209
24. A surface ocean pCO2 product with improved representation of interannual variability using a vision transformer-based model X. Zhang et al. https://doi.org/10.5194/essd-17-6071-2025
25. Enhance seasonal amplitude of atmospheric CO 2 by the changing Southern Ocean carbon sink J. Yun et al. https://doi.org/10.1126/sciadv.abq0220
26. OceanSODA-ETHZ: a global gridded data set of the surface ocean carbonate system for seasonal to decadal studies of ocean acidification L. Gregor & N. Gruber https://doi.org/10.5194/essd-13-777-2021
27. Consistency and Challenges in the Ocean Carbon Sink Estimate for the Global Carbon Budget J. Hauck et al. https://doi.org/10.3389/fmars.2020.571720
28. Reconstruction of global surface ocean pCO2 using region-specific predictors based on a stepwise FFNN regression algorithm G. Zhong et al. https://doi.org/10.5194/bg-19-845-2022
29. Modern air-sea flux distributions reduce uncertainty in the future ocean carbon sink G. McKinley et al. https://doi.org/10.1088/1748-9326/acc195
30. The importance of adding unbiased Argo observations to the ocean carbon observing system T. Heimdal & G. McKinley https://doi.org/10.1038/s41598-024-70617-x
31. The IPCC Assessment Report Six Working Group 1 report and southern Africa: Reasons to take action F. Engelbrecht & P. Monteiro https://doi.org/10.17159/sajs.2021/12679
32. A monthly surface pCO2 product for the California Current Large Marine Ecosystem J. Sharp et al. https://doi.org/10.5194/essd-14-2081-2022
33. Emergence of an oceanic CO2 uptake hole under global warming H. Lee et al. https://doi.org/10.1038/s41467-025-57724-7
34. Marine particles and their remineralization buffer future ocean biogeochemistry response to climate warming J. Maerz et al. https://doi.org/10.5194/bg-23-1897-2026
35. Storms drive outgassing of CO2 in the subpolar Southern Ocean S. Nicholson et al. https://doi.org/10.1038/s41467-021-27780-w
36. Global Carbon Budget 2025 P. Friedlingstein et al. https://doi.org/10.5194/essd-18-3211-2026
37. BIOPERIANT12: a mesoscale-resolving coupled physics–biogeochemical model for the Southern Ocean N. Chang et al. https://doi.org/10.5194/gmd-18-6415-2025
38. Reconstruction and spatiotemporal analysis of global surface ocean pCO2 considering sea area characteristics H. Wu et al. https://doi.org/10.5194/bg-23-967-2026
39. Improved Quantification of Ocean Carbon Uptake by Using Machine Learning to Merge Global Models and pCO2 Data L. Gloege et al. https://doi.org/10.1029/2021MS002620
40. The Southern Ocean Carbon Cycle 1985–2018: Mean, Seasonal Cycle, Trends, and Storage J. Hauck et al. https://doi.org/10.1029/2023GB007848
41. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake B. Byrne et al. https://doi.org/10.5194/essd-15-963-2023
42. External Forcing Explains Recent Decadal Variability of the Ocean Carbon Sink G. McKinley et al. https://doi.org/10.1029/2019AV000149
43. Carbon Sinks and Variations of pCO2 in the Southern Ocean From 1998 to 2018 Based on a Deep Learning Approach Y. Wang et al. https://doi.org/10.1109/JSTARS.2021.3066552
44. Quantifying the Atmospheric CO2 Forcing Effect on Surface Ocean pCO2 in the North Pacific Subtropical Gyre in the Past Two Decades S. Chen et al. https://doi.org/10.3389/fmars.2021.636881
45. Alternate Histories: Synthetic Large Ensembles of Sea‐Air CO2 Flux H. Olivarez et al. https://doi.org/10.1029/2021GB007174
46. Trends and variability in the ocean carbon sink N. Gruber et al. https://doi.org/10.1038/s43017-022-00381-x
47. How statistical modeling and machine learning could help in the calibration of numerical simulation and fluid mechanics models? Application to the calibration of models reproducing the vibratory behavior of an overhead line conductor H. Amroun et al. https://doi.org/10.1016/j.array.2022.100187
48. Seamless Integration of the Coastal Ocean in Global Marine Carbon Cycle Modeling M. Mathis et al. https://doi.org/10.1029/2021MS002789
49. CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system T. Chau et al. https://doi.org/10.5194/essd-16-121-2024
50. Seasonality of pCO2 and air-sea CO2 fluxes in the Central Labrador Sea R. Arruda et al. https://doi.org/10.3389/fmars.2024.1472697
51. Substantially underestimated winter CO 2 sources of the Southern Ocean S. Zhang et al. https://doi.org/10.1126/sciadv.aea0024
52. Global air-sea CO2 flux inversion based on multi-source data fusion and machine learning Y. Chen et al. https://doi.org/10.1016/j.chaos.2024.115963
53. Widespread changes in Southern Ocean phytoplankton blooms linked to climate drivers S. Thomalla et al. https://doi.org/10.1038/s41558-023-01768-4
54. Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling T. Heimdal et al. https://doi.org/10.5194/bg-21-2159-2024
55. The Southern Ocean mixed layer and its boundary fluxes: fine-scale observational progress and future research priorities S. Swart et al. https://doi.org/10.1098/rsta.2022.0058
56. A systematic bias in float pH leads to overestimation of derived pCO2 and underestimation of carbon uptake by the Southern Ocean C. Zhang et al. https://doi.org/10.1038/s41598-026-43863-4
57. SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach A. Fay et al. https://doi.org/10.5194/essd-13-4693-2021
58. Surface ocean CO2 concentration and air-sea flux estimate by machine learning with modelled variable trends J. Zeng et al. https://doi.org/10.3389/fmars.2022.989233
59. A global monthly 3D field of seawater pH over 3 decades: a machine learning approach G. Zhong et al. https://doi.org/10.5194/essd-17-719-2025
60. Decrease in air-sea CO2 fluxes caused by persistent marine heatwaves A. Mignot et al. https://doi.org/10.1038/s41467-022-31983-0
61. Phytoplankton bloom distribution and succession driven by sea-ice melt in the Kong Håkon VII Hav M. Lenss et al. https://doi.org/10.1525/elementa.2023.00122
62. Global Surface Ocean Acidification Indicators From 1750 to 2100 L. Jiang et al. https://doi.org/10.1029/2022MS003563
63. GOBAI-O2: temporally and spatially resolved fields of ocean interior dissolved oxygen over nearly 2 decades J. Sharp et al. https://doi.org/10.5194/essd-15-4481-2023
64. Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3 Ö. Gürses et al. https://doi.org/10.5194/gmd-16-4883-2023
65. Air‐Sea Fluxes of CO2 in the Indian Ocean Between 1985 and 2018: A Synthesis Based on Observation‐Based Surface CO2, Hindcast and Atmospheric Inversion Models V. Sarma et al. https://doi.org/10.1029/2023GB007694
66. Sparse observations induce large biases in estimates of the global ocean CO 2 sink: an ocean model subsampling experiment J. Hauck et al. https://doi.org/10.1098/rsta.2022.0063
67. Composite model-based estimate of the ocean carbon sink from 1959 to 2022 J. Terhaar https://doi.org/10.5194/bg-22-1631-2025
68. Magnitude, Trends, and Variability of the Global Ocean Carbon Sink From 1985 to 2018 T. DeVries et al. https://doi.org/10.1029/2023GB007780
69. Contrasting high-latitude mixed layer depth trends in Earth System Models and data products and their impact on temporal pCO2 variability C. Danek & J. Hauck https://doi.org/10.1007/s00382-026-08109-z
70. The sensitivity of pCO2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach L. Djeutchouang et al. https://doi.org/10.5194/bg-19-4171-2022
71. Observed Regional Fluxes to Constrain Modeled Estimates of the Ocean Carbon Sink A. Fay & G. McKinley https://doi.org/10.1029/2021GL095325
72. Sailing through the southern seas of air–sea CO 2 flux uncertainty P. Landschützer et al. https://doi.org/10.1098/rsta.2022.0064
73. Research ReportDiurnal global ocean surface pCO2 and air–sea CO2 flux reconstructed from spaceborne LiDAR data S. Zhang et al. https://doi.org/10.1093/pnasnexus/pgad432
74. Variability in the Global Ocean Carbon Sink From 1959 to 2020 by Correcting Models With Observations V. Bennington et al. https://doi.org/10.1029/2022GL098632
75. The Four-Dimensional Carbon Cycle of the Southern Ocean A. Gray https://doi.org/10.1146/annurev-marine-041923-104057
76. Early winter barium excess in the southern Indian Ocean as an annual remineralisation proxy (GEOTRACES GIPr07 cruise) N. van Horsten et al. https://doi.org/10.5194/bg-19-3209-2022
77. Identifying the biological control of the annual and multi-year variations in South Atlantic air–sea CO2 flux D. Ford et al. https://doi.org/10.5194/bg-19-4287-2022
78. Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis K. Rodgers et al. https://doi.org/10.1029/2023GB007798
79. Targeting bias in algorithm optimization improves reconstructions of surface ocean pCO2 T. Heimdal et al. https://doi.org/10.1088/3049-4753/adddc3
80. The Ocean Carbon Cycle T. DeVries https://doi.org/10.1146/annurev-environ-120920-111307
81. Sea-surface pCO2 maps for the Bay of Bengal based on advanced machine learning algorithms A. Joshi et al. https://doi.org/10.1038/s41597-024-03236-w
82. A seamless ensemble-based reconstruction of surface ocean pCO2 and air–sea CO2 fluxes over the global coastal and open oceans T. Chau et al. https://doi.org/10.5194/bg-19-1087-2022
83. pH trends and seasonal cycle in the coastal Balearic Sea reconstructed through machine learning S. Flecha et al. https://doi.org/10.1038/s41598-022-17253-5
84. The Southern Ocean carbon sink has been overestimated in the past three decades G. Zhong et al. https://doi.org/10.1038/s43247-024-01566-6
85. Projected poleward migration of the Southern Ocean CO2 sink region under high emissions P. Mongwe et al. https://doi.org/10.1038/s43247-024-01382-y
86. Atmospheric CO2 and Sea Surface Temperature Variability Cannot Explain Recent Decadal Variability of the Ocean CO2 Sink T. DeVries https://doi.org/10.1029/2021GL096018
87. Variability of North Atlantic CO2 fluxes for the 2000–2017 period estimated from atmospheric inverse analyses Z. Chen et al. https://doi.org/10.5194/bg-18-4549-2021
88. Data-based estimates of interannual sea–air CO2 flux variations 1957–2020 and their relation to environmental drivers C. Rödenbeck et al. https://doi.org/10.5194/bg-19-2627-2022
89. How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle? D. Crisp et al. https://doi.org/10.1029/2021RG000736
90. Large spread in interannual variance of atmospheric CO2 concentration across CMIP6 Earth System Models V. Martín-Gómez et al. https://doi.org/10.1038/s41612-023-00532-x
91. Observation-constrained estimates of the global ocean carbon sink from Earth system models J. Terhaar et al. https://doi.org/10.5194/bg-19-4431-2022