We would like to let you know about two surface ocean CO₂ products which have recently been updated and are available online.

An updated Jena CarboScope ocean CO₂ flux product can be accessed from the website at https://www.bgc-jena.mpg.de/CarboScope/?ID=oc. CarboScope provides the temporally and spatially resolved estimates of the global sea-air CO₂ flux based on the SOCAT data set of pCO₂ observations, as presented in Rödenbeck et al., 2013. The product comprises seasonal, interannual, and day-to-day variations. This year's update involves the use of SOCATv2020 data and the additional year 2019, with further changes described in detail below.  

The latest update of the mapped surface ocean pCO₂ product (SOM-FFN) can be accessed from the NCEI OCADS website at https://www.nodc.noaa.gov/ocads/oceans/SPCO2_1982_present_ETH_SOM_FFN.html. The latest update of the product consists of monthly maps from January 1982 through December 2019 using the latest release of the SOCAT data set (SOCATv2020, Bakker et al 2016, Sabine et al 2013). In addition to previous versions of this product, air-sea fluxes are now calculated using the ERA 5 reanalysis winds (Copernicus Climate Change Service, 2017). The product will now further be updated annually.  

Jena CarboScope ocean CO₂ flux product

Besides using the new SOCATv2020 data, this year's update contains the following changes:

• the spatial resolution has been refined to 2.5 degrees longitude * 2 degrees latitude (the grid structure is also more conventional now, with a grid cell boundary at 180W; see the coordinate values in the NetCDF file)
• the time period has also been extended into the past, now starting in 1957. This has been achieved by: (i) using the decadal flux trend from the data-driven OCIM model by deVries et al as decadal prior; (ii) using a hybrid algorithm, first performing a multi-linear regression against long-term available environmental drivers, and then adding a correction from an auto-regressive interpolation similar to the algorithm used so far.

All these changes will be described in detail in a paper to be submitted soon. 

Mapped surface ocean pCO₂ product (SOM-FFN)

SOM-FFN was created using a 2-step neural network method, where in a first step the global surface ocean is clustered into a suite of 16 dynamical biogeochemical provinces and in a second step the relationship between observed pCO₂ (calculated from fCO₂) from the gridded SOCAT dataset and environmental predictor data is reconstructed for each province. Using this relationship, unobserved regions in space and time are then filled using the established relationship. These reconstructed pCO₂ maps are then used to calculate the air-sea CO₂ flux using a bulk flux parametrisation. A more detailed description can be found in Landschützer et al 2013, 2014, 2016. 

• Landschützer, P., Gruber, N. and Bakker, D. C. E.: Decadal variations and trends of the global ocean carbon sink, Global Biogeochemical Cycles, 30, 1396-1417, doi:10.1002/2015GB005359, 2016
• Landschützer, P., Gruber, N., Bakker, D. C. E. and Schuster, U.: Recent variability of the global ocean carbon sink, Global Biogeochemical Cycles, 28, 927-949, doi:10.1002/2014GB004853, 2014
• Landschützer, P., Gruber, N., Bakker, D. C. E., Schuster, U., Nakaoka, S., Payne, M. R., Sasse, T., and Zeng, J.: A neural network-based estimate of the seasonal to inter-annual variability of the Atlantic Ocean carbon sink, Biogeosciences, 10, 7793-7815, doi:10.5194/bg-10-7793-2013, 2013
• Bakker, D. C. E. et al. : A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383-413, doi:10.5194/essd-8-383-2016, 2016
• Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), date of access. https://cds.climate.copernicus.eu/cdsapp#!/home