The Southern Ocean has long been known to be an important region for ocean CO₂ uptake, and one which is especially sensitive to changes in the overlying climate. Here we assess the Southern Ocean CO₂ uptake (1985–2018) using data sets gathered in the REgional Carbon Cycle Assessment and Processes Project Phase 2 (RECCAP2). These include global ocean biogeochemical models (GOBMs), surface ocean pCO₂-products, data-assimilated models, and interior ocean biogeochemical observations. Over this period the Southern Ocean acted as a sink for CO₂, with magnitudes which are roughly half of those reported by RECCAP1 for the same region and timeframe. Close agreement is found between GOBMs and pCO₂-products, partly due to some compensation of seasonal and regional differences. Seasonal analyses revealed agreement in driving processes in winter (with uncertainty in the magnitude of outgassing), whereas discrepancies are more fundamental in summer, when GOBMs exhibit difficulties in simulating the balance of non-thermal processes of biology and mixing/circulation. The data sets emphasize strong latitudinal variations in the mean and seasonality of the CO₂ flux and asymmetries in the mean and amplitude of the CO₂ flux between Atlantic, Pacific and Indian sectors. The present-day net uptake is to first order a response to rising atmospheric CO₂. This drives large amounts of anthropogenic CO₂ (C_ant) into the ocean, thereby overcompensating the loss of natural CO₂ to the atmosphere driven by the changing climate. The GOBMs show, however, a 20% spread and an overall underestimate of C_ant storage in the ocean interior. An apparent knowledge gap is the increase of the sink since 2000, with pCO₂-products suggesting a growth that is more than twice as strong and uncertain as that of GOBMs. This is despite nearly identical pCO₂ trends in GOBMs and pCO₂-products when both products are compared only at the locations where pCO₂ was measured.

How to cite: Patara, L., Hauck, J., Gregor, L., Nissen, C., Hague, M., Mongwe, P., Bushinsky, S., Doney, S. C., Gruber, N., Le Quéré, C., Manizza, M., Mazloff, M., and Monteiro, P. M. S.: Mean, Seasonal Cycle, Trends, and Storage of the Southern Ocean carbon cycle in the RECCAP2 assessment (1985-2018), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16495, https://doi.org/10.5194/egusphere-egu24-16495, 2024.

Since the preindustrial era, the ocean has removed roughly 40% of fossil CO₂ from the atmosphere, and it will eventually absorb at least 80% of human CO₂ emissions. While there is no doubt that the ocean is a critical player in the global carbon cycle, many uncertainties remain and the drivers and magnitude of interannual-to-decadal timescale variability remain poorly constrained. A key question is the extent to which external forcing, specifically the variability of the atmospheric pCO₂ growth rate, or internal ocean variability is the dominant mechanism of variability. We use a suite of experiments from the ECCO-Darwin data-assimilative ocean biogeochemistry model to isolate and explore the impact of these two drivers. We demonstrate that at the global scale, external and internal variability equally drive ocean sink variability. However, as the spatial scale becomes more regional, internal variability becomes increasingly dominant. To diagnose the future evolution of the global-scale ocean carbon sink in response to a changing atmospheric growth rate, both skillful observation-based products and data-assimilative models will be required.   

How to cite: McKinley, G., Fay, A., Carroll, D., and Menemenlis, D.: Drivers of ocean carbon sink variability across spatial scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4196, https://doi.org/10.5194/egusphere-egu24-4196, 2024.

Both the tropical Pacific and Atlantic upwelling systems are modulated by their respective Ninos (ENSO and Atlantic Nino), which significantly affect the regional and global climate variability. Coincidentally, two of largest ocean carbon outgassing systems are also located in these domains. As a result, the interannual variability of ocean CO₂ fluxes in these regions have predominant imprint on the globally integrated variations (Landschutzer et al., 2016). In contrast to the effect of anomalously cold surface temperature, the upwelling of deep-water rich in dissolved inorganic carbon is understood to be the main driver for the mean CO₂ outgassing. In the tropical Pacific, El Nino (La Nina) leads to a suppressed (stronger) upwelling condition and an anomalously weaker (stronger) carbon outgassing. On the other hand, the Atlantic Nino and Nina exert considerable variability in the surface freshwater and temperature, which leads to spatially heterogeneous responses in the contemporary CO₂ fluxes. In both systems, we discover a critical role of subsurface alkalinity in regulating the observed variability, primarily through altering the surface buffering capacity (Koseki et al., 2023). We show that bias in CMIP6 Earth system models in simulating the mean contemporary alkalinity state in the tropical Pacific leads to contrasting future impacts (Vaittinada Ayar et al., 2022) and could have ramifications on the climate carbon cycle feedback. 

References

Koseki, S., J. Tjiputra, F. Fransner, L. R. Crespo, and N. S. Keenlyside (2023), Disentangling the impact of Atlantic Nino on sea-air CO₂ fluxes, Nature Communications, 14, 3649, https://doi.org/10.1038/s41467-023-38718-9.

Landschützer, P., N. Gruber, and D. C. E. Bakker (2016), Decadal variations and trends of the global ocean carbon sink, Global Bio- geochem. Cycles, 30, 1396–1417, http://doi.org/10.1002/2015GB005359.

Vaittinada Ayar, P., L. Bopp, J. R. Christian, T. Ilyina, J. P. Krasting, R. Séférian, H. Tsujino, M. Watanabe, A. Yool, and J. Tjiputra (2022), Contrasting projections of the ENSO-driven CO₂ flux variability in the equatorial Pacific under high-warming scenario, Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022.

How to cite: Tjiputra, J., Koseki, S., and Vaittinada Ayar, P.: Non-intuitive differences in Ninos-driven CO2 flux variability and long-term changes in the tropical Pacific and Atlantic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6021, https://doi.org/10.5194/egusphere-egu24-6021, 2024.

We examined the sub-seasonal to interannual variability and multi-year trend of sea surface CO₂ partial pressure (pCO₂) and air-sea CO₂ flux at a coastal site of the East China Sea (31⁰N, 122.8⁰E) based on high-frequency time-series data collected by a buoy since 2013. Seasonal average sea surface pCO₂ was highest in autumn, but the lowest value can appear in winter or spring, depending on the biological productivity in spring. The seasonal amplitude of pCO₂ was up to 123 μatm. Based on property-property relationships and a simple mass budget model, we found that temperature change, biological activity, water mixing and air-sea CO₂ exchange all made significant contributions to the seasonal variation of pCO₂. From winter to summer, seasonal warming and atmospheric CO₂ uptake elevated the pCO₂, while net biological production, weakened vertical mixing and the retreat of the Yellow Sea Coastal Water (YSCW) lowered the pCO₂. Conversely, from summer to winter, seasonal cooling and CO₂ emission lowered the pCO₂, while respiration, enhanced vertical mixing and the YSCW intrusion raised them up. Over short-term timescale, biological production and respiration frequently drew down or elevated the pCO₂ by 150-400 μatm within 5-10 days during warm months. When biological activity was suppressed during cold months, such short-term variations were dominated by water mixing with a smaller pCO₂ amplitude of 5-60 μatm within 2-6 days. This site was a sink of atmospheric CO₂ in winter and spring, but a CO₂ source in summer and autumn. Annually, it was a moderate CO₂ source in 2014 (air-sea CO₂ flux was 2.88 ± 11.02 mmol m⁻² d⁻¹), a weak CO₂ sink in 2016 (-0.21 ± 12.23 mmol m⁻² d⁻¹), and a weak CO₂ source in the combined year of the first half of 2017 and the second half of 2018 (0.40 ± 9.11 mmol m⁻² d⁻¹). The relatively high CO₂ source in 2014 was likely due to the weaker biological production in spring and more typhoon passage in autumn. From 2013 to 2019, the wintertime sea surface pCO₂ didn’t follow the increasing trend of the atmospheric pCO₂, leading to an enhancing carbon sink in winter.

How to cite: Luo, Y., Zhang, Z., Chen, J., Xu, Y., Cao, F., Huang, T., Guo, X., and Dai, M.: Sea surface pCO2 variability on different time scales in the East China Sea based on high-frequency time-series observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14038, https://doi.org/10.5194/egusphere-egu24-14038, 2024.

The ocean is a strong sink for anthropogenic CO₂, absorbing around a quarter of emissions since the industrial era. Quantifying the ocean carbon sink is necessary for constraining the global carbon budget; however, discrepancies remain between estimates of the ocean carbon sink over the last 30 years from observation-based data products and those from numerical models. Moreover, larger regional uncertainties highlight the need for a better understanding of the drivers of ocean carbon sink variability, to help improve models and to better constrain future climate projections. A comprehensive understanding of the sink must include knowledge of (1) the air-sea flux of CO₂, (2) the accumulation of carbon in the ocean interior, and (3) how it is redistributed within the ocean by changes in the physical circulation. This characterisation is typically achieved using numerical models, which are constrained by resolution and the need to parameterise processes including physical mixing at the sub-grid scale.

We present a novel method for characterising the ocean carbon sink from a combination of oceanographic datasets, and for reconciling our knowledge of the ocean’s uptake of CO₂ with that of interior carbon storage rates. Our Optimal Transformation Method (OTM) uses a water mass framework to diagnose the transport and mixing of tracers such as heat, salt, and carbon consistent with observed interior changes and estimates of boundary forcings. The water mass framework has the advantage that the transport and mixing of conservative tracers are diagnosed exactly, with no need for parameterisation. We validate OTM using outputs from a data-assimilating biogeochemical ocean model and demonstrate its ability to recover the model’s ‘true’ air-sea CO₂ fluxes when initialised with biased priors. OTM reduces root-mean-squared errors between diagnosed air-sea CO₂ fluxes and the model truth from prior to solution by up to 71%, while simultaneously estimating inter-basin transports of heat, freshwater, and carbon consistent with the model. Following successful validation, we apply OTM to a combination of observational data products to diagnose estimates of the ocean’s uptake and redistribution of carbon since 1990, utilising reanalyses of air-sea heat and freshwater fluxes, interior temperature and salinity, air-sea CO₂ fluxes, and machine-learning reconstructions of interior ocean carbon.

How to cite: Mackay, N., Zika, J., Sohail, T., Ehmen, T., and Watson, A.: A water mass transformation method applied to diagnosing ocean carbon uptake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20295, https://doi.org/10.5194/egusphere-egu24-20295, 2024.

Disparities in estimates of the ocean carbon sink, whether derived from global ocean biogeochemical models or from data products based on observations of surface ocean pCO₂, question our ability to accurately assess ocean carbon uptake and its trend over recent decades. A potential factor contributing to the inconsistency between data products and model-based estimates is the pre-industrial air-sea carbon flux that is required to isolate the anthropogenic component from the total air-sea carbon flux estimated from observations. This pre-industrial air-sea carbon flux is thought to stem at the global scale from an imbalance between riverine carbon discharge to the ocean and sediment carbon burial.  Using a mass-balanced approach and comprehensive estimates of carbon inputs to the ocean by rivers and groundwater as well as carbon burial in marine sediments, Regnier et al. (2022) estimated that the pre-industrial ocean was outgassing 0.65 ± 0.30 petagrams of carbon per year. This updated estimation was used in the latest Global Carbon Budget (Friedlingstein et al., 2023) to derive an estimate of the ocean carbon sink over recent decades. In this study, we use a series of ocean biogeochemical pre-industrial simulations with varying assumptions related to carbon riverine input and burial to develop a theoretical framework to determine the ocean carbon outgassing and its spatial distribution. Building upon previous efforts, we integrate a carbon mass-balance approach with consideration of the ocean alkalinity budget. While conventionally assumed that the global alkalinity inventory was in equilibrium during the pre-industrial era — with riverine alkalinity discharge offset by CaCO₃ burial — we demonstrate that an imbalance in the pre-industrial ocean alkalinity budget could significantly affect the carbon outgassing flux. This novel conceptual framework allows us to reestimate the pre-industrial carbon flux while considering the ocean alkalinity budget. Furthermore, it provides a simple method to reevaluate this flux in light of new assessments of carbon or alkalinity sources and sinks, while also covering their uncertainty ranges.

How to cite: Planchat, A., Bopp, L., and Kwiatkowski, L.: Reassessing the pre-industrial air-sea carbon flux considering the ocean alkalinity budget, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12480, https://doi.org/10.5194/egusphere-egu24-12480, 2024.

The development of high-quality controlled databases of sea surface partial pressure of CO₂ (pCO₂) combined with robust machine learning-based mapping methods that fill pCO₂ gaps in time and space, enable us to quantify the oceanic air-sea CO₂ exchange and its spatiotemporal variability only based on in-situ observations (pCO₂-products). However, most existing pCO₂-products do not explicitly include the coastal ocean or have a spatial resolution that is too coarse (e.g., 1°) to capture the highly heterogeneous spatiotemporal dynamics of pCO₂ in these regions thus limiting our ability to resolve long-term trends and the interannual variability of the coastal air-sea CO₂ exchange (FCO₂).

To address this limitation, we updated the global coastal pCO₂-product of Laruelle et al. (2017) using a 2-step machine learning interpolation technique (relying on Self Organizing Maps and a Feed Forward neural Network) combined with the most extensive monthly time series for coastal waters from the Surface Ocean CO₂ Atlas (SOCAT), spanning from 1982 to 2020 to reconstruct monthly high spatial resolution (0.25°) continuous coastal pCO₂ maps. This updated coastal pCO₂-product is then used to reconstruct the temporal evolution of the global coastal FCO₂ based on observations.

Our results show that since 1982, the extended coastal ocean, covering an area of 77 million km² in this study, has been acting as an atmospheric CO₂ sink, removing -0.4 Pg C yr^-1 (-0.2 Pg C yr^-1 with a narrower coastal domain roughly equivalent to continental shelves) from the atmosphere. Moreover, the intensity of this CO₂ sink has been increasing over time at a rate of 0.1 Pg C yr^-1 per decade (0.03 Pg C yr^-1 decade^-1 in the narrower domain). The long-term change in the air-sea CO₂ flux is largely driven by the air-sea pCO₂ gradient, dominated by the sea surface pCO₂, however wind speed and sea-ice coverage play significant roles, regionally. This new coastal pCO₂-product provides a valuable constraint for understanding the strengthening of the global coastal ocean CO₂ sink, fill the coastal gap in synthesis studies such as the Global Carbon Budget and serves as a benchmark for evaluating emerging results of ocean biogeochemical models.

How to cite: Roobaert, A., Regnier, P., Landschützer, P., and Laruelle, G. G.: Global coastal ocean CO2 trends over the 1982–2020 period, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14775, https://doi.org/10.5194/egusphere-egu24-14775, 2024.

New constraints on carbon exchanges between atmospheric, terrestrial and aquatic systems are needed to reduce uncertainty in future predictions of the global carbon cycle and climate change. Radiocarbon is a powerful tool for studying the carbon cycle due to its to its ~5700-year half-life that sheds light on processes occuring on centennial to millenial timescales, as well as the ¹⁴C “bomb spike” resulting from above-ground nuclear weapons testing in the mid-20^th Century that serves as a tracer of carbon flow among more rapidly cycling pools. The “Radiocarbon Inventories of Switzerland” (“RICH”) project is a collaborative initiative that involves undertaking a first-of-its-kind, national-scale ¹⁴C survey spanning all major carbon pools and encompassing the five different Swiss ecoregions. The project is acquiring a comprehensive “snapshot” of ¹⁴C measurements for carbon species in the atmosphere, soils and the hydrophere (e.g. ¹⁴C in atmospheric and soil-derived gas samples, ¹⁴C in bulk samples and different sub-fractions of soil, water and sediment samples), and developing historical context through ¹⁴C analysis of natural archives and of archived samples spanning the pre-bomb era to the present. The measurements are being used to study various carbon cycle processes, including turnover rates of different soil carbon fractions, budgets of riverine carbon, and anthropogenic emissions of CO₂ and CH₄. New, integrated atmospheric-terrestrial-aquatic carbon cycle models are being developed and calibrated, and existing models are being evaluated. This presentation will outline the goals and scope of the RICH project, and provide illustrations of the information that is now flowing from this collaborative undertaking. The project structure is envisioned to serve as template that can be  adapted in carbon cycle studies on regional to global scales, and the scientific outcomes will be relevant not only to Switzerland but also to the broader understanding of carbon cycle processes.

How to cite: Eglinton, T., Graven, H., Hagedorn, F., Szidat, S., Brunmayr, A., Duborgel, M., Geissbuehler, D., Laemmel, T., Minich, L., Mittelbach, B., Rhyner, T., and White, M.: Constraining atmosphere-terrestrial-aquatic carbon cycle processes at national and ecoregional scales with radiocarbon data: Introducing the Radiocarbon Inventories of Switzerland (RICH) project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11622, https://doi.org/10.5194/egusphere-egu24-11622, 2024.

As the remaining carbon budget to limit global warming in line with the Paris Agreement is rapidly shrinking, accurate estimates of the emissions from land-use and land cover change (ELUC) and the terrestrial natural CO2 sinks (SLAND) are crucial. In current carbon budgeting approaches, the ELUC and SLAND estimates are conceptually not consistent, since they stem from two different model families that differ in how CO₂ fluxes are attributed to environmental or land-use changes. Consequently, anthropogenic and natural budget terms are not fully distinguished. ELUC is estimated by bookkeeping models, which typically use time-invariant carbon densities representing contemporary environmental conditions. They thus assume a steady environmental state and neglect changes in environmental conditions preceding or succeeding a land-use change event, e.g., denser growing forests in response to rising atmospheric CO2 concentrations, which emit more when cleared for agricultural land. SLAND is estimated by dynamic global vegetation models, which account for environmental changes but assume that the land cover distribution remained at its pre-industrial state. They thus include carbon sinks in forests that in reality were cleared decades ago. Here we suggest an approach for consistent budgeting of ELUC and SLAND by integrating the response of vegetation and soil carbon to environmental changes, derived from dynamic global vegetation models, into a spatially explicit bookkeeping model (BLUE). A set of dedicated simulations allows us to disentangle and re-attribute environmental and land-use components of the land-atmosphere CO2 exchange. Our results show that land is a cumulative net source of CO₂ since 1850, which contrasts current global carbon budgets indicating a net sink. The underlying reason is both a higher estimate of ELUC than previously suggested as well as a smaller land sink: The implementation of environmental changes increases global ELUC over time (14% compared to current estimates for 2012-2021) mainly due to increased emissions from deforestation and wood harvest, which are only partly offset by increased sinks through reforestation/afforestation and other regrowing vegetation. Our SLAND estimate calculated under actual land cover amounts to 3.0 GtC yr^-1 for 2012-2021, which is substantially lower both globally and regionally compared to estimates assuming pre-industrial land cover: we find a SLAND is smaller by 0.7 GtC yr^-1 in 2012-2021, i.e., 19% lower as compared to the conventional approach using pre-industrial land cover. The overestimate of SLAND under pre-industrial land cover is particularly pronounced in regions with strong ecosystem degradation, such as Southeast Asia, Brazil, and Equatorial Africa. The consistent estimation of terrestrial carbon fluxes is thus essential not only to provide a tangible estimate to monitor the progress of net-zero emission commitments and the remaining carbon budget, but also to highlight the need to protect remaining natural ecosystems for climate regulation. Our approach provides greater consistency with atmospheric inversions and provides a finer split of anthropogenic and natural fluxes useful for a direct comparison of global carbon cycle models to national greenhouse gas inventories.

How to cite: Pongratz, J., Dorgeist, L., Schwingshackl, C., and Bultan, S.: A consistent budgeting of terrestrial carbon fluxes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15244, https://doi.org/10.5194/egusphere-egu24-15244, 2024.

CO₂ fluxes from land use and land-use change (F_LUC) are a major source of carbon to the atmosphere. They are composed of gross emissions, mainly from deforestation, peat burning, and peat drainage, and gross removals, mainly from re- and afforestation. The importance of F_LUC for climate change mitigation strategies is increasing due to the potential of storing large carbon amounts via re- and afforestation, harvested wood products, and other vegetation-based carbon dioxide removal methods, such as bioenergy with carbon capture and storage. Yet, F_LUC estimates remain largely uncertain and show substantial discrepancies between different quantification methods, which makes it challenging to provide reliable projections of their potential future evolution.

Here, we review the main characteristics, uncertainties, and discrepancies of individual methods used to estimate F_LUC, and we highlight promising steps to reduce F_LUC uncertainties and to harmonize the various F_LUC estimates. Differences between the approaches are mainly due to differing definitions and assumptions, such as the definition of anthropogenic fluxes and managed land (leading to a gap in F_LUC of ~1.8 GtC/yr in 2000-2020 between F_LUC estimates by bookkeeping models used in the Global Carbon Project and inventory-based estimates reported by countries to the United Nations Framework Convention on Climate Change) and the inclusion of environmental effects on carbon stocks (leading to a gap of ~0.4 GtC/yr in 2000-2020 between F_LUC estimates from dynamic global vegetation models and bookkeeping models). Furthermore, the individual estimation methods have large uncertainties, mainly arising from the usage of differing land-use forcing data, missing observational constraints, differences in how models implement individual processes, and the degree of implementation of land use practices in models.

To improve the confidence in the individual F_LUC estimates, we argue for a systematic model evaluation and an improved parametrization of models, in particular regarding land-use forcing data, carbon densities of vegetation and soils, and the represented processes. Alongside, remaining framework inconsistencies, such as a precise and consistent definition of F_LUC and the consideration of transient C densities need to be resolved. This undertaking requires developments in several directions. Earth observations may provide data on carbon densities in vegetation and soil at high spatial resolution, improved estimates of forest regrowth rates as well as impacts of forest management. Models need to be further improved to consider all relevant land-use processes and provide more fine-granular output to guarantee that the different estimates are comparable and/or translatable into each other.

Providing harmonized and more accurate F_LUC estimates is essential to improve the stocktake of countries' land use-related CO₂ emissions, to provide an accurate budget of the global carbon cycle, and to effectively plan and monitor land-based carbon dioxide removal methods.

How to cite: Obermeier, W., Schwingshackl, C., Ganzenmüller, R., Bastos, A., Ciais, P., Grassi, G., Luijkx, I., Sitch, S., and Pongratz, J.: Reviewing differences and uncertainties in land-use CO2 flux estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18116, https://doi.org/10.5194/egusphere-egu24-18116, 2024.

As one of the world’s economic engine and the largest greenhouse gases (GHGs) emitter of fossil fuel in the past two decades, China has expressed the recent ambition to reduce GHG emissions by mid-century. The status of GHG balance over terrestrial ecosystems in China, however, remains elusive. Here, we present a synthesis of the three most important long-lived greenhouse gases (CO₂, CH₄ and N₂O) budgets over China during the 2000s and 2010s, following a dual constraint bottom-up and top-down approach. We estimate that China’s terrestrial ecosystems act as a small GHG sink (-29.0 ± 207.5 Tg CO₂-eq yr^-1 with the bottom-up estimate and -75.3 ± 496.8 Tg CO₂-eq yr^-1 with the top-down estimate). This net GHG sink includes an appreciable land CO₂ sink, which is being largely offset by CH₄ and N₂O emissions, predominantly coming from the agricultural sector. Emerging data sources and modelling capacities have helped achieve agreement between the top-down and bottom-up approaches to within 25% for all three GHGs, but sizeable uncertainties remain. 

How to cite: Gao, Y., Wang, X., Wang, K., Sang, Y., Wang, Y., Zhang, Y., Hong, S., Zhang, Y., Yuan, W., and Piao, S.: The greenhouse gas budget of terrestrial ecosystems in China since 2000, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5576, https://doi.org/10.5194/egusphere-egu24-5576, 2024.

Miombo woodlands are the world’s largest savanna, covering 2-3 M km², and are the dominant land cover in the dry tropics of southern Africa. Here we quantify the dynamics of the miombo region carbon cycle, diagnosing stocks and fluxes and their interactions with climate and disturbance, and evaluate their representation in Trendy land surface models (LSMs). We produce a constrained multi-year analysis (2006-2017) using earth observation time series of total wood C (C_wood) and leaf area index to calibrate an intermediate complexity ecosystem model forced with observed climate, deforestation and burned area. Statistical analyses determine the relationships between carbon cycling, environmental and disturbance variables, and evaluate LSMs. The analysis suggests that the regional net biome production is neutral, 0.0 Mg C ha^-1 yr^-1 (95% Confidence Interval -1.7 - 1.6), with fire emissions contributing ~1.0 Mg C ha^-1 yr^-1 (95% CI 0.4-2.5). Spatial variation in biogenic fluxes and C pools is strongly correlated with mean annual precipitation. Burned area is also positively correlated with these pools and fluxes. Areas that are more frequently burned tend to have greater precipitation, and shorter residence time of C_wood. Fire-related mortality from C_wood to dead organic matter likely exceeds fire-related emissions from C_wood to atmosphere, and likely exceeds natural rates of C_wood mortality. LSMs match the biogenic fluxes of the analysis, but diverge on C stocks, timings of heterotrophic respiration and magnitude of fire emissions. The analysis suggests that climate, through precipitation, drives spatial variability in C_wood and GPP across the region. Fire disturbance is the major driver of losses from C_wood. Larger annual precipitation is correlated with both greater GPP and greater fire disturbance. These factors have opposing but unbalanced impacts on Cwood, but the precipitation-GPP effect dominates. Patterns of C cycling across the region are a complex outcome of climate controls on production, and vegetation-fire interactions.

How to cite: Williams, M., Milodowski, D., Luke, S., McNicol, I., Dexter, K., Ryan, C., O'Sullivan, M., Valade, A., Hegerl, G., and Sitch, S.: Fire-precipitation interactions control biomass carbon and net biome production across the world’s largest savanna, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20466, https://doi.org/10.5194/egusphere-egu24-20466, 2024.

Fires in the Amazon are of great concern because they threaten the integrity of the tropical forest biome, the carbon cycle, and air quality. Fire emissions depend on the burning behaviour of vegetation biomass, woody debris, and litter. However, the effects of fuels on the combustion process and on the composition of fire emissions are simplified in current fire emission inventories and models. Several new fire emission approaches have recently been developed to better quantify fire emissions by either making use the improved spatial resolution of modern satellite observations or by developing new modelling approaches. 

Here we compare several current and novel approaches to quantify fuel consumption and fire emissions for the Amazon and Cerrado for the fire season in 2020. The approaches include the widely used GFAS, a top-down approach based on Sentinel-5p observations (KNMI.S5p), a bottom-up approach based on active fire observations from VIIRS (GFA.S4F), two bottom-up approaches based on MODIS burned area data (500-m version of GFED, REFIT.AC), a data-model fusion approach with dynamic emission factors that integrates several Earth observation products (TUD.S4F), and three dynamic global vegetation models in diagnostic mode with prescribed burned area. The different approaches to estimate fire emission show that forest and deforestation fires dominate the regional total fire emissions. However, large differences exist in the very high emissions of individual fires that mainly contribute to the regional total fire emissions. We found a higher agreement in estimated CO and NOx emissions between approaches for savannah fires (normalised RMSE < 20%) than for forest and deforestation fires (nRMSE 30%). We estimate that only 10% of all fire events contribute between 85% and 97% of the regional total fire emissions. By using the TUD.S4F data-model fusion approach with dynamic emission factors, we show that most fire CO emissions originate from the burning of woody debris, which burns with low combustion efficiency and hence has higher emission factors for CO. Comparisons with regional field-based investigations show, however, large differences in estimates of surface fuel loads and fuel consumption. Our results demonstrate the advantage of exploring several complementary fire emission approaches to better understand the underlying processes and to account for regional to global fire emissions and their uncertainties.

How to cite: Forkel, M., Wessollek, C., Andela, N., de Laat, J., Huijnen, V., Kinalczyk, D., Marrs, C., van Wees, D., Bastos, A., Ciais, P., Fawcett, D., Kaiser, J. W., Kutchartt, E., Klauberg, C., Leite, R. V., Li, W., Silva, C., Sitch, S., Goncalves De Souza, J., and Plummer, S.: Multiple approaches for quantifying fuels, combustion dynamics, and regional fire emissions in the Amazon and Cerrado, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14672, https://doi.org/10.5194/egusphere-egu24-14672, 2024.

Peatlands are the world’s largest storage of soil organic carbon. While natural peatlands act as sinks of atmospheric carbon, drainage and disturbance (e.g., due to land use and climate change) turn peatlands into net carbon sources. Greenhouse gas (GHG) emissions from drained peatlands are therefore part of national GHG-emission reports, guided by the IPCC wetlands supplement. Herein, default emission factors (EF) are defined both for drained and rewetted peatlands, the former split into tropical and boreal/temperate wetlands, the latter further sub-categorized into nutrient poor and rich peatlands. These default emission factors are to date largely based on a limited number of static chamber-based studies, many measured over relatively short periods of time (1-3 years). As carbon flux measurements on peatlands have gained more attention, recent publications have added several new datasets to the EF calculations, significantly reducing the EF and narrowing confidence intervals. However, the final values are still almost entirely derived from chamber-based measurements with inherent limitations and uncertainties.

The Eddy-Covariance (EC) method is an alternative, established method to quantify carbon fluxes from ecosystems, spatially and temporally integrated (typically every 30 min throughout the year, representing a “flux-footprint” covering a whole ecosystem). As EC-based measurements are increasingly applied and such data are now available from several disturbed peatlands over several years, it is plausible to revise the default EFs. In this study we compile global EC time series for CO₂ fluxes from disturbed peatlands of different land use categories with a focus on drained and rewetted peatlands affected by no or by  minor extensive management practices.  We investigate the diurnal, seasonal and annual variability of the fluxes. The net carbon emissions are compared to the EFs currently in use. With available ancillary data such as climate, water table depths, nutrients, ecosystem type and (succession-) state of the ecosystem we asses controlling factors for carbon fluxes. This investigation yields important context to evaluate the uncertainty and reliability of default emission factors for disturbed peatlands. Additionally, we apply a process-based model (CoupModel) to an own study-site to generate a higher-tier emission factor, including seasonality and climate variations.

How to cite: Behrens, N., Knorr, K.-H., and Gharun, M.: Peatland IPCC emission factors in the light of new EC carbon flux time series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5271, https://doi.org/10.5194/egusphere-egu24-5271, 2024.

The Arctic-boreal zone and its permafrost regions have historically been sparsely measured for carbon dioxide and methane fluxes. This data sparsity has created significant uncertainties in Arctic-boreal carbon budget estimates. However, over the past decade, the availability of Arctic-boreal carbon flux data has increased substantially. Yet, it remains scattered across different repositories, papers, and unpublished sources, making it hard to estimate more accurate Arctic-boreal carbon budgets. To address this research gap, we have compiled a database of Arctic-boreal carbon fluxes (ABCFlux v2) from flux repositories, literature, and site principal investigators, which will be openly distributed. The database includes carbon dioxide fluxes of gross primary production, ecosystem respiration, and net ecosystem exchange, and plant-mediated, diffusive, ebullitive, and storage methane fluxes measured with eddy covariance and chamber techniques with supporting methodological and environmental metadata from terrestrial (including wetland) and freshwater ecosystems. It has in total over 12,000 site-months and 30,000 unique monthly flux values, therefore almost doubling earlier synthesis efforts in the region. Here, we present preliminary results on carbon flux magnitudes across key land cover types and multidecadal trends based on the in-situ data and machine-learning based upscaling. These indicate, for example, that the Arctic-boreal region has been an increasing annual terrestrial net ecosystem CO₂ sink with the boreal biome primarily driving this trend. This collaborative initiative, involving contributions from over 100 researchers, serves as an important step in reducing uncertainties in Arctic-boreal carbon budgets and enhancing our understanding of climate feedbacks.

How to cite: Virkkala, A., Wargowsky, I., Vogt, J., Kuhn, M., Natali, S., Rogers, B., Goeckede, M., Arndt, K., Watts, J., Windholz, T., and Madaan, S.: A new synthesis of Arctic-boreal carbon fluxes for improved carbon budget estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10840, https://doi.org/10.5194/egusphere-egu24-10840, 2024.

Globally permafrost soils store huge quantities of carbon (C) in dead organic matter (DOM). Currently, the permafrost region is estimated to be a small net C sink. However, as the climate warms permafrost soils have begun to thaw, making a massive quantity of DOM available for potential decomposition and likely shifting the region to a net source of C. Process-models of terrestrial ecosystems are a vital tool in evaluating our understanding of ecosystem function, but also in generating forecasts of C emissions under varied climate change scenarios in support of decision support. But different models contain competing hypothesise of ecosystem functioning, leading to divergent forecasts despite convergent estimates of contemporary net C emissions. These process-models also result in contrasting estimates of the internal C-cycling. We currently lack a consistent, rigorous observational constraint on ecosystem C-stocks and dynamics (particularly below ground) due to varied challenges across both in-situ and satellite-based Earth Observation (EO). Here, we present a Bayesian model-data fusion approach (CARDAMOM) which combines diverse observations of terrestrial ecosystems (e.g. leaf area, soil C, biomass, net C exchange) to calibrate an intermediate complexity model (DALEC). CARDAMOM generates a probabilistic estimates of DALEC parameters at pixel scale based on local information. Using these local calibrations, DALEC offers a probabilistic, data-constrained estimate of current ecosystem C-cycling including its internal dynamics, which can be used to evaluate large scale process-models. We evaluate process-model estimates of key ecosystem properties, e.g. DOM residence time, and their climate sensitivity. Through this process we can identify and exclude process-models which are inconsistent with data from forecast analyses.

How to cite: Smallman, L. and Burke, E.: Quantifying permafrost C-cycling by fusing process-models and observations , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7366, https://doi.org/10.5194/egusphere-egu24-7366, 2024.

Atmospheric methane levels (the second largest contributor to climate change) have more than doubled over the last 200 years, though with highly variable trends over time. The relative contribution of different sources and sinks to the global CH₄ budget remains uncertain despite ongoing efforts to improve the estimates based on various approaches, and particularly the causes for an accelerated increase in recent years remain unclear. Therefore, understanding and quantifying methane sources at global to regional scales is essential to reduce uncertainties in the global methane budget and its feedback with the climate system.

Within the Arctic region, wetlands and lakes constitute a major natural source of methane. With temperatures rising at rates at least twice the global average over the last decades, Arctic permafrost is increasingly thawing. Associated disturbance processes hold the potential to increase methane emissions, and as a consequence result in a positive feedback to climate change. However, until now neither observations nor model estimates could provide clear evidence of such a trend in emissions. As a consequence, current and possible future contributions of Arctic ecosystems to the accelerated increase in the global atmospheric methane levels remain highly uncertain.

To help reduce methane emission uncertainties in the high northern latitudes, we estimated global CH₄ fluxes to the atmosphere using the Jena CarboScope Global Inversion System, with a strong focus of our analysis on the Arctic region. We used wetland flux from JSBACH model as prior and assimilated atmospheric observations from regional networks available over the last years for the region above 60°N latitude (a total of 23 towers) to quantify the methane emissions over this region between 2010 to 2020. We found a clear seasonal pattern with emission peaks during July and August. As a sensitivity test to evaluate the improvement to constrain the Arctic methane fluxes with the assimilation of the regional data, we also conducted an inversion using just the global background surface stations (a total of 30 global stations). We found higher mean annual methane flux to the atmosphere when assimilating the regional data, with the largest difference between May to August. These estimates were finally evaluated against an ensemble of inverse model estimates from Global Methane Project available for the period between 2010 to 2017.

How to cite: Basso, L., Rödenbeck, C., Brovkin, V., Georgievski, G., and Göckede, M.: Estimating methane emissions at high northern latitudes using regional data and global inverse modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8175, https://doi.org/10.5194/egusphere-egu24-8175, 2024.

From 2020, the atmospheric methane burden has grown at the fastest rate in the detailed observational record. This rise has been accompanied by an unprecedented plunge in d¹³C(CH₄). The causes of recent accelerated growth are as yet uncertain but the geographic spread of growth and the rapid isotopic plunge suggest strong rises in isotopically light emissions from both Tropical and Boreal wetlands. These emissions may be due to rising precipitation and temperatures in parts of the tropics, and by rising temperatures in northern Canada, Siberia, and Europe. Over the longer period since 2007, methane’s actual growth is comparable to methane’s growth in the ‘worst case’ very high baseline emission scenario RCP8.5 (8.5 W/m² forcing increase relative to pre-industrial). If the recent trend were to continue for more than another decade it could make the 2°C target as hard to achieve as the 1.5°C target is now. Natural feedbacks to climate warming in wetlands need to be included in future modelling and should be incorporated in climate modelling projects such as CMIP7. Methane’s recent accelerated growth also has wide implications for climate negotiations as it reduces the permissible total anthropogenic greenhouse gas emissions if the Paris Agreement is to be achieved. Strong growth in non-anthropogenic methane emissions, driven by feedback impacts on natural and quasi-natural sources, was not expected in modelling at the time of the Paris Agreement and shows the urgency of improving our understanding of the feedback impacts of climate change. The simplest way to limit methane’s growth is for all nations,  including non-signatory countries, to cut anthropogenic emissions urgently and sharply, meeting or exceeding the targets of the Global Methane Pledge.

How to cite: Manning, M. R., Nisbet, E. G., Michel, S. E., Lan, X., Dlugokencky, E., Lowry, D., Fisher, R. E., and France, J. L.: Methane’s record rise 2020-2023: likely causes, impacts and consequences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12481, https://doi.org/10.5194/egusphere-egu24-12481, 2024.

We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios. GISS-E2.1 is one of the few ESMs that can be driven by anthropogenic CH4 emissions, as well as interactive natural sources such as wetlands, and can simulate the tropospheric CH4 chemistry. In frame of the recent short-lived climate forcers (SLCFs) assessment by the Arctic Monitoring and Assessment Programme (AMAP), we used the GISS-E2.1 model with prescribed long-lived greenhouse gas (GHG) concentrations. In the present study, we have supplemented these simulations using the interactive CH4 sources and sinks in order to quantify the model performance and the sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) emission scenarios from the Eclipse V6b emission database to simulate the future chemical composition and climate impacts from 2015 to 2050. We have also simulated 1995-2014 in order to evaluate the model performance following the AMAP-SLCF protocol.

The prescribed GHG version underestimates the Global Atmospheric Watch (GAW) surface CH4 observations during the period between 1995 and 2023 by 1% [-8.4%-2.0%], with a correlation (r) of 0.71 [-0.41 0.99]. The largest underestimations are over the continental emission regions such as North America, Europe, and Asia, while biases are smallest over oceans. On the other hand, the simulation with interactive sources and sinks underestimates the GAW observations more than the prescribed simulation, by 18.5% [-25% -10.4%], with a lower r of 0.36 [-0.82 0.93]. Opposite to the prescribed simulation, the biases are largest over oceans and smaller over the continents, however they are still larger over land than the prescribed simulation. The interactive simulation, with large sources virtually over land and strong sink over oceans, has a land/ocean ratio larger than 1 while the prescribed simulation has this ratio equal to 1 as it distributes the global prescribed CH4 concentration equally in longitude over a given latitude. This clearly shows that the interactive sources and sinks should be represented in models in order to realistically simulate the chemical composition and the oxidative capacity of the atmosphere.

As expected, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day.  In the CLE scenario, increases are largest over the equatorial belt, in particular over India and East China, while the MFR scenario shows increases over the whole Southern Hemisphere, however much smaller compared to CLE. Finally, the interactive simulation shows that the chemical CH4 sink increases in the CLE scenario, while it slightly decreases in the MFR, leading to a larger CH4 lifetime in the MFR scenario compared to in the CLE scenario.

How to cite: Im, U., Tsigaridis, K., Bauer, S., Eckhardt, S., Shindell, D., Sørensen, L. L., and Wilson, S.: Future CH4 budgets as modelled by a fully coupled Earth system model using prescribed GHG concentrations vs. interactive CH4 sources and sinks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2492, https://doi.org/10.5194/egusphere-egu24-2492, 2024.