82 citations as recorded by crossref.

1. The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle R. Latto & A. Romanou 10.5194/essd-10-609-2018
2. CO2 partial pressure and fluxes in the Amazon River plume using in situ and remote sensing data A. Valerio et al. 10.1016/j.csr.2021.104348
3. Remote Sensing Estimations of the Seawater Partial Pressure of CO₂ Using Sea Surface Roughness Derived From Synthetic Aperture Radar Y. Wang et al. 10.1109/TGRS.2024.3379984
4. Rapid fCO2 rise in the northern Barents Sea and Nansen Basin Y. Ericson et al. 10.1016/j.pocean.2023.103079
5. The Distribution of pCO2W and Air-Sea CO2 Fluxes Using FFNN at the Continental Shelf Areas of the Arctic Ocean I. Wrobel-Niedzwiecka et al. 10.3390/rs14020312
6. Impacts of data assimilation on the global ocean carbonate system L. Visinelli et al. 10.1016/j.jmarsys.2016.02.011
7. A statistical gap‐filling method to interpolate global monthly surface ocean carbon dioxide data S. Jones et al. 10.1002/2014MS000416
8. Dynamics of air–sea CO<sub>2</sub> fluxes in the northwestern European shelf based on voluntary observing ship and satellite observations P. Marrec et al. 10.5194/bg-12-5371-2015
9. Spatial reconstruction of long-term (2003–2020) sea surface pCO2 in the South China Sea using a machine-learning-based regression method aided by empirical orthogonal function analysis Z. Wang et al. 10.5194/essd-15-1711-2023
10. Mapping of the air–sea CO2 flux in the Arctic Ocean and its adjacent seas: Basin-wide distribution and seasonal to interannual variability S. Yasunaka et al. 10.1016/j.polar.2016.03.006
11. Climate impacts on the structures of the North Pacific air-sea CO<sub>2</sub> flux variability V. Valsala et al. 10.5194/bg-9-477-2012
12. A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink P. Landschützer et al. 10.5194/bg-10-7793-2013
13. Air–sea CO<sub>2</sub> flux in the Pacific Ocean for the period 1990–2009 M. Ishii et al. 10.5194/bg-11-709-2014
14. Hierarchical and dynamic seascapes: A quantitative framework for scaling pelagic biogeochemistry and ecology M. Kavanaugh et al. 10.1016/j.pocean.2013.10.013
15. Advancements in Carbon Dioxide Modeling: An Algorithm Incorporating In-Situ and Satellite Data for Improved Understanding of pCO Dynamics in the Bay of Bengal I. Shaik et al. 10.1109/ACCESS.2023.3338005
16. Estimating mixed layer nitrate in the North Atlantic Ocean T. Steinhoff et al. 10.5194/bg-7-795-2010
17. Estimating spatial and temporal variation in ocean surface pCO2 in the Gulf of Mexico using remote sensing and machine learning techniques Z. Fu et al. 10.1016/j.scitotenv.2020.140965
18. A comparative assessment of the uncertainties of global surface ocean CO<sub>2</sub> estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall? L. Gregor et al. 10.5194/gmd-12-5113-2019
19. Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model A. Palacz et al. 10.5194/bg-10-7553-2013
20. Technical note: Evaluation of three machine learning models for surface ocean CO<sub>2</sub> mapping J. Zeng et al. 10.5194/os-13-303-2017
21. Using satellite data to estimate partial pressure of CO2 in the Baltic Sea G. Parard et al. 10.1002/2015JG003064
22. Retrieving the vertical distribution of chlorophyll a concentration and phytoplankton community composition from in situ fluorescence profiles: A method based on a neural network with potential for global‐scale applications R. Sauzède et al. 10.1002/2014JC010355
23. Satellite estimation of coastal pCO2 and air-sea flux of carbon dioxide in the northern Gulf of Mexico S. Lohrenz et al. 10.1016/j.rse.2017.12.039
24. Annual and seasonal fCO2 and air–sea CO2 fluxes in the Barents Sea S. Lauvset et al. 10.1016/j.jmarsys.2012.12.011
25. A Multiparametric Nonlinear Regression Approach for the Estimation of Global Surface Ocean pCO2 Using Satellite Oceanographic Data K. Krishna et al. 10.1109/JSTARS.2020.3026363
26. Neural network-based estimates of Southern Ocean net community production from in situ O<sub>2</sub> / Ar and satellite observation: a methodological study C. Chang et al. 10.5194/bg-11-3279-2014
27. Satellite-derived CO2fugacity in surface seawater of the tropical Atlantic Ocean using a feedforward neural network H. Moussa et al. 10.1080/01431161.2015.1131872
28. Spatiotemporal reconstruction of global ocean surface pCO2 based on optimized random forest H. Wu et al. 10.1016/j.scitotenv.2023.169209
29. Satellite-derived CO2 flux in the surface seawater of the Austral Ocean south of Australia M. Benallal et al. 10.1080/01431161.2017.1286054
30. The Gulf of Alaska coastal ocean as an atmospheric CO2 sink W. Evans & J. Mathis 10.1016/j.csr.2013.06.013
31. Reconstruction of global surface ocean <i>p</i>CO<sub>2</sub> using region-specific predictors based on a stepwise FFNN regression algorithm G. Zhong et al. 10.5194/bg-19-845-2022
32. Remote silicate supply regulates spring phytoplankton bloom magnitude in the Gulf of Maine Z. Zang et al. 10.1002/lol2.10245
33. Space-Time Sea Surface pCO2 Estimation in the North Atlantic Based on CatBoost H. Sun et al. 10.3390/rs13142805
34. Limacina retroversa's response to combined effects of ocean acidification and sea water freshening C. Manno et al. 10.1016/j.ecss.2012.07.019
35. Rapid change of the Arctic climate system and its global influences - Overview of GRENE Arctic climate change research project (2011–2016) T. Yamanouchi & K. Takata 10.1016/j.polar.2020.100548
36. Monthly dynamics of carbon dioxide exchange across the sea surface of the Arctic Ocean in response to changes in gas transfer velocity and partial pressure of CO 2 in 2010 I. Wrobel 10.1016/j.oceano.2017.05.001
37. LSCE-FFNN-v1: a two-step neural network model for the reconstruction of surface ocean <i>p</i>CO<sub>2</sub> over the global ocean A. Denvil-Sommer et al. 10.5194/gmd-12-2091-2019
38. A machine learning approach to estimate surface ocean pCO2 from satellite measurements S. Chen et al. 10.1016/j.rse.2019.04.019
39. Spatiotemporal variation in summer net community production in the Amundsen Sea Polynya: A self-organizing map analysis approach K. Park et al. 10.1016/j.csr.2019.07.001
40. Global ocean carbon uptake: magnitude, variability and trends R. Wanninkhof et al. 10.5194/bg-10-1983-2013
41. Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system P. Ciais et al. 10.5194/bg-11-3547-2014
42. Interannual sea–air CO<sub>2</sub> flux variability from an observation-driven ocean mixed-layer scheme C. Rödenbeck et al. 10.5194/bg-11-4599-2014
43. Satellite-based prediction of pCO2 in coastal waters of the eastern North Pacific B. Hales et al. 10.1016/j.pocean.2012.03.001
44. Estimating marine carbon uptake in the northeast Pacific using a neural network approach P. Duke et al. 10.5194/bg-20-3919-2023
45. Impact of sampling depth on CO$$_{2}$$ flux estimates C. Azevedo et al. 10.1038/s41598-024-69177-x
46. Global surface-ocean <i>p</i><sup>CO<sub>2</sub></sup> and sea–air CO<sub>2</sub> flux variability from an observation-driven ocean mixed-layer scheme C. Rödenbeck et al. 10.5194/os-9-193-2013
47. Reconstruction of super-resolution ocean <i>p</i>CO<sub>2</sub> and air–sea fluxes of CO<sub>2</sub> from satellite imagery in the southeastern Atlantic I. Hernández-Carrasco et al. 10.5194/bg-12-5229-2015
48. Remote sensing the sea surface CO<sub>2</sub> of the Baltic Sea using the SOMLO methodology G. Parard et al. 10.5194/bg-12-3369-2015
49. Synthetic Aperture Radar for Geosciences L. Meng et al. 10.1029/2023RG000821
50. A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks T. Sasse et al. 10.5194/bg-10-4319-2013
51. Space Observation of Carbon Dioxide Partial Pressure at Ocean Surface W. Liu & X. Xie 10.1109/JSTARS.2017.2766138
52. A Global Surface Ocean fCO2 Climatology Based on a Feed-Forward Neural Network J. Zeng et al. 10.1175/JTECH-D-13-00137.1
53. Recent variability of the global ocean carbon sink P. Landschützer et al. 10.1002/2014GB004853
54. Estimating surface pCO2 in the northern Gulf of Mexico: Which remote sensing model to use? S. Chen et al. 10.1016/j.csr.2017.10.013
55. The history of chemical concepts and field studies of CO2 in seawater: A tribute to Kurt Buch (1881–1967) B. Schneider & W. Matthäus 10.1016/j.marchem.2022.104204
56. Mapping of sea surface nutrients in the North Pacific: Basin-wide distribution and seasonal to interannual variability S. Yasunaka et al. 10.1002/2014JC010318
57. A neural network‐based method for merging ocean color and Argo data to extend surface bio‐optical properties to depth: Retrieval of the particulate backscattering coefficient R. Sauzède et al. 10.1002/2015JC011408
58. Arctic Ocean CO<sub>2</sub> uptake: an improved multiyear estimate of the air–sea CO<sub>2</sub> flux incorporating chlorophyll <i>a</i> concentrations S. Yasunaka et al. 10.5194/bg-15-1643-2018
59. Water clarity monitoring in complex coastal environments: Leveraging seagrass light requirement toward more functional satellite ocean color algorithms M. Xu et al. 10.1016/j.rse.2022.113418
60. Remote estimation of surface pCO2 on the West Florida Shelf S. Chen et al. 10.1016/j.csr.2016.09.004
61. Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning A. Denvil-Sommer et al. 10.5194/gmd-16-2995-2023
62. The use of machine learning algorithms to design a generalized simplified denitrification model F. Oehler et al. 10.5194/bg-7-3311-2010
63. Estimation of Fugacity of Carbon Dioxide in the East Sea Using In Situ Measurements and Geostationary Ocean Color Imager Satellite Data E. Jang et al. 10.3390/rs9080821
64. A Machine Learning Approach to Estimate Surface Chlorophyll a Concentrations in Global Oceans From Satellite Measurements C. Hu et al. 10.1109/TGRS.2020.3016473
65. The quiet crossing of ocean tipping points C. Heinze et al. 10.1073/pnas.2008478118
66. Estimating summer sea surface pCO2 on a river-dominated continental shelf using a satellite-based semi-mechanistic model C. Le et al. 10.1016/j.rse.2019.02.023
67. Applications of Machine Learning in Chemical and Biological Oceanography B. Sadaiappan et al. 10.1021/acsomega.2c06441
68. A uniform, quality controlled Surface Ocean CO<sub>2</sub> Atlas (SOCAT) B. Pfeil et al. 10.5194/essd-5-125-2013
69. Surface ocean p CO2 seasonality and sea-air CO2 flux estimates for the North American east coast S. Signorini et al. 10.1002/jgrc.20369
70. Estimation of Subsurface Temperature Anomaly in the North Atlantic Using a Self-Organizing Map Neural Network X. Wu et al. 10.1175/JTECH-D-12-00013.1
71. Research ReportDiurnal global ocean surface pCO2 and air–sea CO2 flux reconstructed from spaceborne LiDAR data S. Zhang et al. 10.1093/pnasnexus/pgad432
72. Sea Surface pCO₂ and Its Variability in the Ulleung Basin, East Sea Constrained by a Neural Network Model S. PARK et al. 10.7850/jkso.2016.21.1.1
73. Surface water fCO2 algorithms for the high-latitude Pacific sector of the Southern Ocean M. Chierici et al. 10.1016/j.rse.2011.12.020
74. Po River plume pattern variability investigated from model data F. Falcieri et al. 10.1016/j.csr.2013.11.001
75. Variations in the summer oceanic <i>p</i>CO<sub>2</sub> and carbon sink in Prydz Bay using the self-organizing map analysis approach S. Xu et al. 10.5194/bg-16-797-2019
76. Estimating temporal and spatial variation of ocean surface <i>p</i>CO<sub>2</sub> in the North Pacific using a self-organizing map neural network technique S. Nakaoka et al. 10.5194/bg-10-6093-2013
77. Ocean-Atmosphere CO2 Fluxes in the North Atlantic Subtropical Gyre: Association with Biochemical and Physical Factors during Spring M. Burgos et al. 10.3390/jmse3030891
78. Determination and uncertainty of spring net community production estimated from O2/Ar measurements in the northern East China Sea and southern Yellow Sea I. Lee et al. 10.1016/j.csr.2021.104570
79. Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea S. Zhang et al. 10.3390/rs13020259
80. Investigating the complex relationship between in situ Southern Ocean $$pCO_{2}$$ p C O 2 and its ocean physics and biogeochemical drivers using a nonparametric regression approach W. Pretorius et al. 10.1007/s10651-014-0276-5
81. A performance evaluation of remotely sensed sea surface salinity products in combination with other surface measurements in reconstructing three-dimensional salinity fields J. Chen et al. 10.1007/s13131-017-1079-y
82. Temporal evolution of near‐surface chlorophyll over cyclonic eddy lifecycles in the southeastern Pacific J. Huang et al. 10.1002/2017JC012915