Abstract
This dataset includes the monthly distributions of CO2 fugacity in the world surface oceans reconstructed using a feed‐forward neural network model and the CO2 measurements of the Surface Ocean CO2 Atlas version 2.0. It has a spatial resolution of 1 × 1° and spans a period of 22 years, from January 1990 to December 2011. The dataset also includes necessary parameters for the reconstruction and an estimate of the CO2 fluxes between the ocean and the atmosphere. The aim of this work is to provide a dataset for estimating the oceans' contribution to the global carbon budget.
Highlights
Understanding the global distribution of the surface ocean CO2 (SOC) fugacity plays an important role in accurately estimating the oceans’ contribution to the global carbon budget, as indicated in Le Quere et al (2013) and Wanninkhof et al (2013)
Recent studies showed that the amplitude of the seasonal SOC changes can be 100 latm or more (Wanninkhof et al, 2013), which is about 10 times of what has been observed for atmospheric CO2 (e.g. Bacastow et al, 1985); and that the spatial decorrelation length scales are on the order of 100 km (Li et al, 2005) to 400 km (Jones et al, 2012), which is smaller than that of the marine atmosphere
Many works on modelling SOC focused on a mesoscale (e.g. Zeng et al, 2002; Lefevre et al, 2005; Sarma et al, 2006; Jamet et al, 2007; Friedrich and Oschlies, 2009; Telszewski et al, 2009; Takamura et al, 2010; Landschu€tzer et al, 2013; Nakaoka et al, 2013; Schuster et al, 2013); and on the global scale, mapping SOC was confined to the climatology in a given year (e.g. Takahashi et al, 2009; Zeng et al, 2014)
Summary
Understanding the global distribution of the surface ocean CO2 (SOC) fugacity plays an important role in accurately estimating the oceans’ contribution to the global carbon budget, as indicated in Le Quere et al (2013) and Wanninkhof et al (2013). The composite map of SOC measurements from 1990 to 2011, shown in Zeng et al (2014), indicates that about 60% of the oceanic areas were sampled, the area ratio is only about 7–25% when divided by the same months of all years (Figure 1(a)) and is even smaller, between 0% and 4% (Figure 1(b)), when calculated for individual months. Insufficient measurements demand using models to estimate the global SOC in multiple years. Climatology of Takahashi et al (2009) (4° 9 5°), which is currently the most frequently used product, and provides global SOC maps in multiple years. While the SOC climatology of Zeng et al (2014) does not cover areas where chlorophyll data were not available, this dataset filled those gaps
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
