. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and\ntheir redistribution among the atmosphere, ocean, and terrestrial biosphere\nin a changing climate is critical to better understand the global carbon\ncycle, support the development of climate policies, and project future\nclimate change. Here we describe and synthesize datasets and methodology to\nquantify the five major components of the global carbon budget and their\nuncertainties. Fossil CO2 emissions (EFOS) are based on energy\nstatistics and cement production data, while emissions from land-use change\n(ELUC), mainly deforestation, are based on land use and land-use change\ndata and bookkeeping models. Atmospheric CO2 concentration is measured\ndirectly, and its growth rate (GATM) is computed from the annual\nchanges in concentration. The ocean CO2 sink (SOCEAN) is estimated\nwith global ocean biogeochemistry models and observation-based\ndata products. The terrestrial CO2 sink (SLAND) is estimated with\ndynamic global vegetation models. The resulting carbon budget imbalance\n(BIM), the difference between the estimated total emissions and the\nestimated changes in the atmosphere, ocean, and terrestrial biosphere, is a\nmeasure of imperfect data and understanding of the contemporary carbon\ncycle. All uncertainties are reported as ±1σ. For the first\ntime, an approach is shown to reconcile the difference in our ELUC\nestimate with the one from national greenhouse gas inventories, supporting\nthe assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with\nfossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of\n10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for\n2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLAND\nwas 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The\nglobal atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOS\nrelative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget\nare consistently estimated over the period 1959–2020, but discrepancies of\nup to 1 GtC yr−1 persist for the representation of annual to\nsemi-decadal variability in CO2 fluxes. Comparison of estimates from\nmultiple approaches and observations shows (1) a persistent large\nuncertainty in the estimate of land-use changes emissions, (2) a low\nagreement between the different methods on the magnitude of the land\nCO2 flux in the northern extra-tropics, and (3) a discrepancy between\nthe different methods on the strength of the ocean sink over the last\ndecade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understanding\nof the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; Le\nQuéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The\ndata presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).\n

. In an intensifying effort to track ocean change and distinguish between natural and anthropogenic drivers, sustained ocean time series measurements are becoming increasingly important. Advancements in the ocean carbon observation network over the last decade, such as the development and deployment of Moored Autonomous pCO2 (MAPCO2) systems, have dramatically improved our ability to characterize ocean climate, sea–air gas exchange, and biogeochemical processes. The MAPCO2 system provides high-resolution data that can measure interannual, seasonal, and sub-seasonal dynamics and constrain the impact of short-term biogeochemical variability on carbon dioxide (CO2) flux. Overall uncertainty of the MAPCO2 using in situ calibrations with certified gas standards and post-deployment standard operating procedures is < 2 μatm for seawater partial pressure of CO2 (pCO2) and < 1 μatm for air pCO2. The MAPCO2 maintains this level of uncertainty for over 400 days of autonomous operation. MAPCO2 measurements are consistent with shipboard seawater pCO2 measurements and GLOBALVIEW-CO2 boundary layer atmospheric values. Here we provide an open-ocean MAPCO2 data set including over 100 000 individual atmospheric and seawater pCO2 measurements on 14 surface buoys from 2004 through 2011 and a description of the methods and data quality control involved. The climate-quality data provided by the MAPCO2 have allowed for the establishment of open-ocean observatories to track surface ocean pCO2 changes around the globe. Data are available at doi:10.3334/CDIAC/OTG.TSM_NDP092 and http://cdiac.ornl.gov/oceans/Moorings/ndp092.\n

. Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018).

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA)-20 has been providing a large amount of global ocean color data, which are critical for monitoring and understanding of ocean optical, biological, and ecological processes and phenomena. However, VIIRS-derived daily ocean color images on either SNPP or NOAA-20 have some limitations in ocean coverage due to its swath width, high sensor-zenith angle, high sun glint, and cloud, etc. Merging VIIRS ocean color products derived from the SNPP and NOAA-20 significantly increases the spatial coverage of daily images. The two VIIRS sensors on the SNPP and NOAA-20 have similar sensor characteristics, and global ocean color products are generated using the same Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system. Therefore, the merged VIIRS ocean color data from the two sensors have high data quality with consistent statistical property and accuracy globally. Merging VIIRS SNPP and NOAA-20 ocean color data almost removes the gaps of missing pixels due to high sensor-zenith angles and high sun glint contamination, and also significantly reduces the gaps due to cloud cover. However, there are still gaps of missing pixels in the merged ocean color data. In this study, the Data Interpolating Empirical Orthogonal Functions (DINEOF) are applied on the merged VIIRS SNPP/NOAA-20 global Level-3 ocean color data to completely reconstruct the missing pixels. Specifically, DINEOF is applied to 30 days of daily merged global Level-3 chlorophyll-a (Chl-a) data of 9-km spatial resolution from 19 June to 18 July 2018. To quantitatively evaluate the accuracy of the DINEOF reconstructed data, a set of valid pixels are intentionally treated as “missing pixels”, so that reconstructed data can be compared with the original data. Results show that mean ratios of the reconstructed/original are 1.012, 1.012, 1.015, and 0.997 for global ocean, oligotrophic waters, deep waters, and coastal and inland waters, respectively. The corresponding standard deviation (SD) of the ratios are 0.200, 0.164, 0.182, and 0.287, respectively. Gap-filled daily Chl-a images reveal many large-scale and meso-scale ocean features that are invisible in the original SNPP or NOAA-20 Chl-a images. It is also demonstrated that the gap-filled data based on the merged products show more details in the dynamic ocean features than those based on SNPP or NOAA-20 alone.

. A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

The diffusion coefficients D of important gas tracers dissolved in water and seawater were measured with a modified Barrer method. The measurements include the gases He, Ne, Kr, Xe, H2, CH4, and CO2 dissolved in distilled water in the temperature range from 5 to 35°C, and He and H2 dissolved in seawater in the same temperature range. The maximum systematic error is estimated to be well below 5%. The isotopic fractionation in the diffusion coefficient, ∈D, was determined to be (−0.87 ± 0.05)‰ for 13CO2/12CO2 and (15 ± 3)% for 3He/4He.

A monthlong, high‐resolution buoy time series from the surface ocean of the Changjiang River plume in early autumn 2013 (30‐min sampling frequency) shows great variability in the partial pressure of carbon dioxide (pCO2) and other physical and biogeochemical parameters. Early in the deployment, surface pCO2 decreased by ~117 μatm in a single day (11–12 September, from an initial value of ~527 μatm); a similar decline of 62 μatm occurred five days later (to ~378 μatm). Both drawdown events were associated with strong vertical stratification, high chlorophyll a concentrations, and oxygen supersaturation. A one‐dimensional mass balance model suggests that biological production was responsible for more than half the pCO2 decrease observed during 10–23 September. Subsequently, in association with strong winds, the mixed layer rapidly deepened and surface pCO2 increased sharply (by about 108 μatm in late September and again in early October). Vertical mixing accounted for more than half of this pCO2 increase, which offset more than the earlier biologically driven CO2 drawdown. In the presence of such strong temporal variations of pCO2, sampling frequency exerts a substantial influence on air‐sea CO2 flux calculations for the Changjiang River plume and similar coastal areas. Compared to daily sampling, even weekly sampling would result in a bias of up to ±4.7 mmol C · m−2 · day−1 or ±63% error.