Abstract. Drifting snow is a widespread feature over the Antarctic ice sheet, whose climatological and hydrological significance at the continental scale have been consequently investigated through modelling and satellite approaches. While field measurements are needed to evaluate and interpret model and satellite products, most drifting-snow observation campaigns in Antarctica involved data collected at a single location and over short time periods. With the aim of acquiring new data relevant to the observation and modelling of drifting snow in Antarctic conditions, two remote locations in coastal Adélie Land (East Antarctica) that are 100 km apart were instrumented in January 2010 with meteorological and second-generation IAV Engineering acoustic FlowCapt™ sensors. The data, provided nearly continuously so far, constitute the longest dataset of autonomous near-surface (i.e. within 2 m) measurements of drifting snow currently available over the Antarctic continent. This paper presents an assessment of drifting-snow occurrences and snow mass transport from up to 9 years (2010–2018) of half-hourly observational records collected in one of the Antarctic regions most prone to snow transport by wind. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO₂ emissions (E_FOS) are based on energy statistics and cement production data, while emissions from land-use change (E_LUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO₂ concentration is measured directly and its growth rate (G_ATM) is computed from the annual changes in concentration. The ocean CO₂ sink (S_OCEAN) and terrestrial CO₂ sink (S_LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B_IM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), E_FOS was 9.6 ± 0.5 GtC yr⁻¹ excluding the cement carbonation sink (9.4 ± 0.5 GtC yr⁻¹ when the cement carbonation sink is included), and E_LUC was 1.6 ± 0.7 GtC yr⁻¹. For the same decade, G_ATM was 5.1 ± 0.02 GtC yr⁻¹ (2.4 ± 0.01 ppm yr⁻¹), S_OCEAN 2.5 ±  0.6 GtC yr⁻¹, and S_LAND 3.4 ± 0.9 GtC yr⁻¹, with a budget imbalance B_IM of −0.1 GtC yr⁻¹ indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in E_FOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr⁻¹ excluding the cement carbonation sink (9.7 ± 0.5 GtC yr⁻¹ when cement carbonation sink is included), and E_LUC was 1.8 ± 0.7 GtC yr⁻¹, for total anthropogenic CO₂ emissions of 11.5 ± 0.9 GtC yr⁻¹ (42.2 ± 3.3 GtCO₂). Also for 2019, G_ATM was 5.4 ± 0.2 GtC yr⁻¹ (2.5 ± 0.1 ppm yr⁻¹), S_OCEAN was 2.6 ± 0.6 GtC yr⁻¹, and S_LAND was 3.1 ± 1.2 GtC yr⁻¹, with a B_IM of 0.3 GtC. The global atmospheric CO₂ concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in E_FOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr⁻¹ persist for the representation of semi-decadal variability in CO₂ fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO₂ flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

Abstract. Understanding and quantifying the global methane (CH₄) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH₄ continue to increase, making CH₄ the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO₂). The relative importance of CH₄ compared to CO₂ depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH₄ sources and from the destruction of CH₄ by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).

For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH₄ yr⁻¹ (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH₄ yr⁻¹ or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH₄ yr⁻¹ or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH₄ yr⁻¹ larger than our estimate for the previous decade (2000–2009), and 24 Tg CH₄ yr⁻¹ larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH₄ emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH₄ yr⁻¹, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30^∘ N) compared to mid-latitudes (∼ 30 %, 30–60^∘ N) and high northern latitudes (∼ 4 %, 60–90^∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.

Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH₄ yr⁻¹ lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH₄ yr⁻¹ by 8 Tg CH₄ yr⁻¹, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH₄ measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.

The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

Abstract. The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797^∘ N, 63.7895^∘ W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360 m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies. The dataset is available at https://doi.org/10.17882/59892 (Massicotte et al., 2019a).