| Method | Reference | Product |
|---|---|---|
| UEA-SI |
S. D. Jones, C. Le Quéré, C. Rödenbeck, A. C. Manning, and A. Olsen: A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data. J. Adv. Model. Earth Syst. 07, doi:10.1002/ 2014MS000416 (2015). |
Download (Pangaea) |
| Jena-MLS |
C. Rödenbeck, R.F. Keeling, D.C.E. Bakker, N. Metzl, A. Olsen, C. Sabine, and M. Heimann: Global surface-ocean pCO2 and sea-air CO2 flux variability from an observation-driven ocean mixed-layer scheme. Ocean Sci. 9, 193-216 (2013), doi:10.5194/os-9-193-2013 |
Download (Jena CarboScope) |
| JMA-MLR |
Y. Iida, A. Kojima, Y. Takatani, T. Nakano, T. Midorikawa, and M. Ishii: Trends in pCO2 and sea-air CO2 flux over the global open oceans for the last two decades. Journal of Oceanography, doi:10.1007/s10872-015-0306-4 (2015). |
Download (JMA) |
| ETH-SOMFFN |
P. Landschützer, N. Gruber, D. C. E. Bakker, and U. Schuster: Recent variability of the global ocean carbon sink. Global Biogeochemical Cycles 28, 927-949 (2014). |
Download (NOAA NODC) |
| NIES-NN |
J. Zeng, Y. Nojiri, P. Landschützer, and M. Telszewski, and S. Nakaoka: A global surface ocean fCO2 climatology based on a feed-forward neural network. Journal of Atmospheric and Ocean Technology 31, 1838-1849 (2014). |
Download (NIES) |
| CSIR-ML6 |
L. Gregor, A. D. Lebehot, S. Kok, and P. M. S. Monteiro: A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) - have we hit the wall? Geosci. Model Dev. 12, 5113-5136 (2019). |
Download (figshare) |
| CMEMS-FFNN |
A. Denvil-Sommer, M. Gehlen, M. Vrac, and C. Mejia: LSCE-FFNN-v1: a two-step neural network model for the reconstruction of surface ocean pCO2 over the global ocean. Geosci. Model Dev. 12, 2091-2105 (2019). |
Download (CMEMS) |
| LDEO-pCO2 residual method |
V. Bennington, T. Galjanic, G. A. McKinley: Explicit Physical Knowledge in Machine Learning for Ocean Carbon Flux Reconstruction: The pCO2-Residual Method. doi.org/10.1029/2021MS002960 (2022). | |
| LDEO-HPD |
L. Gloege, M. Yan, T. Zheng, G. A. McKinley: Improved Quantification of Ocean Carbon Uptake by Using Machine Learning to Merge Global Models and pCO2 Data. doi.org/10.1029/2021MS002620 (2022). |
| Method | Reference |
|---|---|
| OceanFlux-SI |
J. D. Shutler, P. E. Land, J-F. Piolle, D. K. Woolf, L. Goddijn-Murphy, F. Paul,
F. Girard-Ardhuin, B. Chapron, and C. Donlon: FluxEngine: A flexible processing system for calculating atmosphere-ocean carbon dioxide gas fluxes and climatologies. Journal of Atmospheric and Oceanic Technology 33, 741-756 (2016). |
| CU-SCSE |
A. Jacobson et al.: Trends in surface ocean pCO2. Global Biogeochemical Cycles (in preparation). |
| AOML-EMP |
G.-H. Park, R. Wanninkhof, S. C. Doney, T. Takahashi, K. Lee,
R. A. Feely, C. L. Sabine, J. Triñanes, and I. D. Lima: Variability of global net sea-air CO2 fluxes over the last three decades using empirical relationships. Tellus 62B, 352-368 (2010). |
| UEx-MLR |
U. Schuster, G. A. McKinley, N. Bates, F. Chevallier, S. C. Doney,
A. R. Fay, M. González-Dávila, N. Gruber, S. Jones, J. Krijnen,
P. Landschützer, N. Lefèvre, M. Manizza, J. Mathis, N. Metzl, A. Olsen,
A. F. Rios, C. Rödenbeck, J. M. Santana-Casiano, T. Takahashi, R. Wanninkhof, and A. J. Watson: Atlantic and Arctic sea-air CO2 fluxes, 1990-2009. Biogeosciences 10, 607-627 (2013). |
| UNSW-SOMLO |
T. P. Sasse, B. I. McNeil, and G. Abramowitz: A novel method for diagnosing seasonal to inter-annual surface ocean carbon dynamics from bottle data using neural networks. Biogeosciences 10, 4319-4340 (2013). |
| CARBONES-NN |
P. Peylin www.carbones.eu/wcmqs/ |
| NIES-SOM |
S. Nakaoka, M. Telszewski, Y. Nojiri, S. Yasunaka, C. Miyazaki, H. Mukai, and N. Usui: Estimating temporal and spatial variation of ocean surface pCO2 in the North Pacific using a self-organizing map neural network technique. Biogeosciences 10, 6093-6106 (2013). |
| PU-MCMC |
J. D. Majkut, J. L. Sarmiento, and K. B. Rodgers: A growing oceanic carbon uptake: Results from an inversion study of surface pCO2 data. Global Biogeochem. Cycles 28, 335-351 (2014). |
| NIES-OTTM |
K. V. Valsala and S. Maksyutov: Simulation and assimilation of global ocean pCO2 and air-sea CO2 fluxes using ship observations of surface ocean pCO2 in a simplified Biogeochemical offline model. Tellus 62B, 821-840 (2010). |