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We present improved estimates of air-sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275-1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air-sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations.

Long-term measurements at the Mauna Loa Observatory (MLO) show that the CO2 seasonal cycle amplitude (SCA) increased from 1959 to 2019 at an overall rate of 0.22  ±  0.034 ppm decade-1 while also varying on interannual to decadal time scales. These SCA changes are a signature of changes in land ecological CO2 fluxes as well as shifting winds. Simulations with the TM3 tracer transport model and CO2 fluxes from the Jena CarboScope CO2 Inversion suggest that shifting winds alone have contributed to a decrease in SCA of -0.10  ±  0.022 ppm decade-1 from 1959 to 2019, partly offsetting the observed long-term SCA increase associated with enhanced ecosystem net primary production. According to these simulations and MIROC-ACTM simulations, the shorter-term variability of MLO SCA is nearly equally driven by varying ecological CO2 fluxes (49%) and varying winds (51%). We also show that the MLO SCA is strongly correlated with the Pacific Decadal Oscillation (PDO) due to varying winds, as well as with a closely related wind index (U-PDO). Since 1980, 44% of the wind-driven SCA decrease has been tied to a secular trend in the U-PDO, which is associated with a progressive weakening of westerly winds at 700 mbar over the central Pacific from 20°N to 40°N. Similar impacts of varying winds on the SCA are seen in simulations at other low-latitude Pacific stations, illustrating the difficulty of constraining trend and variability of land CO2 fluxes using observations from low latitudes due to the complexity of circulation changes.

Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.

Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land-atmosphere CO2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4-0.7 PgC yr-1 (inversions) and by 1.0 PgC yr-1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.

Winters with higher-than-average temperatures are expected to enhance the respiratory release of CO 2 , thereby weakening the annual net terrestrial carbon sink. Using the 2010–2021 atmospheric CO 2 record from the Zotino Tall Tower Observatory (ZOTTO) located at 60°48 ′ N, 89°21 ′ E, this study analyses interannual changes in the timing and intensity of the carbon uptake and release periods (CUP and CRP, respectively) over central Siberia. We complement our CO 2 mole fraction analysis with the atmospheric inversion results to disentangle the effects of meteorological variability from the ecosystem's response to climate variability at a regional scale. From the observational data, CRP length and amplitude significantly increased between 2010 and 2021. Similarly, CUP length and amplitude have shown a positive but weaker trend since 2010, suggesting that increased CO 2 release during cold months offsets the uptake during the growing season. This suggests that during 2010–2021, climate warming did not lead to higher annual net CO 2 uptake despite the enhanced growing season uptake because cold-season respiration has also increased due to warming. The observational analysis further showed the influence of two extreme events: the 2012 wildfire and the 2020 heat wave. However, analysis of the inversion-derived net ecosystem exchange flux for the ZOTTO region did not reveal these trends or extreme events. Therefore, while ZOTTO data contain substantial information on the magnitude of the Siberian carbon balance (without further data from additional stations), we could not attribute a distinct contribution of ecosystems in the ZOTTO region of influence to the observed trends and extremes. [ABSTRACT FROM AUTHOR]

Atmospheric transport inversions are a powerful tool for independently estimating surface CO 2 fluxes from atmospheric CO 2 concentration measurements. However, additional tracers are needed to separate the fossil fuel CO 2 (ffCO 2) emissions from non-fossil CO 2 fluxes. In this study, we focus on radiocarbon (14 C), the most direct tracer of ffCO 2 , and the continuously measured surrogate tracer carbon monoxide (CO), which is co-emitted with ffCO 2 during incomplete combustion. In the companion paper by Maier et al. (2024), we determined discrete 14 C-based and continuous Δ CO-based estimates of the ffCO 2 excess concentration (Δ ffCO 2) compared with a clean-air reference for the urban Heidelberg observation site in southwestern Germany. The Δ CO-based Δ ffCO 2 concentration was calculated by dividing the continuously measured Δ CO excess concentration by an average 14 C-based ΔCO/ΔffCO2 ratio. Here, we use the CarboScope inversion framework adapted for the urban domain around Heidelberg to assess the potential of both types of Δ ffCO 2 observations to investigate ffCO 2 emissions and their seasonal cycle. We find that, although they are more precise, 14 C-based Δ ffCO 2 observations from almost 100 afternoon flask samples collected in the 2 years of 2019 and 2020 are not well suited for estimating robust ffCO 2 emissions in the main footprint of this urban area, which has a very heterogeneous distribution of sources including several point sources. The benefit of the continuous Δ CO-based Δ ffCO 2 estimates is that they can be averaged to reduce the impact of individual hours with an inadequate model performance. We show that the weekly averaged Δ CO-based Δ ffCO 2 observations allow for a robust reconstruction of the seasonal cycle of the area source ffCO 2 emissions from temporally flat a priori emissions. In particular, the distinct COVID-19 signal – with a steep drop in emissions in spring 2020 – is clearly present in these data-driven a posteriori results. Moreover, our top-down results show a shift in the seasonality of the area source ffCO 2 emissions around Heidelberg in 2019 compared with the bottom-up estimates from the Netherlands Organization for Applied Scientific Research (TNO). This highlights the huge potential of Δ CO-based Δ ffCO 2 to validate bottom-up ffCO 2 emissions at urban stations if the ΔCO/ΔffCO2 ratios can be determined without biases. [ABSTRACT FROM AUTHOR]

Ignoring the diurnal cycle in surface-to-atmosphere CO2 fluxes leads to a systematic bias in CO2 mole fraction simulations sampled at daytime, because the daily mean flux systematically misses the CO2 uptake during the daytime hours. In an atmospheric inversion using daytime-selected CO2 measurements at most continental sites and not resolving diurnal cycles in the flux, this leads to systematic biases in the estimates of the annual sources and sinks of atmospheric CO2. This study focuses on quantifying the impact of this diurnal cycle effect on the annual carbon fluxes estimated with the CarboScope (CS) atmospheric inversion at regional, continental, and global scales for the period of time 2010-2020. Biogenic fluxes of hourly Net Ecosystem Exchange (NEE) obtained from the data-driven FLUXCOM estimates are used in the inversion together with global and regional atmospheric transport models. Differences between CO2 mixing ratios simulated with daily averaged and hourly NEE range between around -2.5 and 7 ppm averaged annually throughout a site network across the world. As a consequence, these differences lead to systematic biases in CO2 flux estimates when ignoring the diurnal variations of the CO2 flux in the atmospheric inversions. Although the impact on the global average of estimated annual flux is negligible (around 2% of the overall land flux of -1.79 Pg C yr-1), we find significant biases in the annual flux budgets at continental and regional scales. For Europe, the annual mean difference in the fluxes arising from the diurnal cycle of CO2 represents around 48% of the annual posterior fluxes (0.31 Pg C yr-1) estimated with CarboScope-Regional (CSR). Furthermore, the differences in NEE estimates calculated with CS increase the magnitude of the flux budgets for some regions such as northern American temperate and northern Africa by a factor of about 1.5. To the extent that FLUXOM diurnal cycles are realistic at all latitudes and for the station set used in our inversions here, we conclude that ignoring the diurnal variations in the land CO2 flux leads to overestimation of both CO2 sources in the tropical lands and CO2 sinks in the temperate zones. [ABSTRACT FROM AUTHOR]

We investigate the use of atmospheric oxygen (O 2) and carbon dioxide (CO 2) measurements for the estimation of the fossil fuel component of atmospheric CO 2 in the UK. Atmospheric potential oxygen (APO) – a tracer that combines O 2 and CO 2 , minimizing the influence of terrestrial biosphere fluxes – is simulated at three sites in the UK, two of which make APO measurements. We present a set of model experiments that estimate the sensitivity of APO simulations to key inputs: fluxes from the ocean, fossil fuel flux magnitude and distribution, the APO baseline, and the exchange ratio of O 2 to CO 2 fluxes from fossil fuel combustion and the terrestrial biosphere. To estimate the influence of uncertainties in ocean fluxes, we compare three ocean O 2 flux estimates from the NEMO–ERSEM, the ECCO–Darwin ocean model, and the Jena CarboScope (JC) APO inversion. The sensitivity of APO to fossil fuel emission magnitudes and to terrestrial biosphere and fossil fuel exchange ratios is investigated through Monte Carlo sampling within literature uncertainty ranges and by comparing different inventory estimates. We focus our model–data analysis on the year 2015 as ocean fluxes are not available for later years. As APO measurements are only available for one UK site at this time, our analysis focuses on the Weybourne station. Model–data comparisons for two additional UK sites (Heathfield and Ridge Hill) in 2021, using ocean flux climatologies, are presented in the Supplement. Of the factors that could potentially compromise simulated APO-derived fossil fuel CO 2 (ffCO 2) estimates, we find that the ocean O 2 flux estimate has the largest overall influence at the three sites in the UK. At times, this influence is comparable in magnitude to the contribution of simulated fossil fuel CO 2 to simulated APO. We find that simulations using different ocean fluxes differ from each other substantially. No single model estimate, or a model estimate that assumed zero ocean flux, provided a significantly closer fit than any other. Furthermore, the uncertainty in the ocean contribution to APO could lead to uncertainty in defining an appropriate regional background from the data. Our findings suggest that the contribution of non-terrestrial sources needs to be better accounted for in model simulations of APO in the UK to reduce the potential influence on inferred fossil fuel CO 2 using APO. [ABSTRACT FROM AUTHOR]

We present improved estimates of air–sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275–1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air–sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations. [ABSTRACT FROM AUTHOR]

Atmospheric measurements of the O2/N2 ratio and the CO2 mole fraction (combined into the conceptual tracer "Atmospheric Potential Oxygen", APO) over continents have been proposed as a constraint on CO2 emissions from fossil-fuel burning. Here we assess the suitability of such APO data to constrain anthropogenic CO2 emissions in western Europe, with particular focus on their decadal trends. We use an inversion of atmospheric transport to estimate spatially and temporally explicit scaling factors on a bottom-up fossil-fuel emissions inventory. Based on the small number of currently available observational records, our CO2 emissions estimates show relatively large apparent year-to-year variations, exceeding the expected uncertainty of the bottom-up inventory and precluding the calculation of statistically significant trends. We were not able to trace the apparent year-to-year variations back to particular properties of the APO data. Inversion of synthetic APO data, however, confirms that data information content and degrees of freedom are sufficient to successfully correct a counterfactual prior. Larger sets of measurement stations, such as the recently started APO observations from the Integrated Carbon Observation System (ICOS) European research infrastructure, improve the constraint and may ameliorate possible problems with local signals or with measurement or model errors at the stations. We further tested the impact of uncertainties in the O2:CO2 stoichiometries of fossil-fuel burning and land biospheric exchange and found they are not fundamental obstacles to estimating decadal trends in fossil-fuel CO2 emissions, though further work on fossil-fuel O2:CO2 stoichiometries seems necessary. [ABSTRACT FROM AUTHOR]

The direct way to estimate the regional fossil fuel CO2 surplus (ΔffCO2) at a station is by measuring the Δ14CO2 depletion compared with a respective background. However, this approach has several challenges, which are (i) the choice of an appropriate Δ14CO2 background, (ii) potential contaminations through nuclear 14CO2 emissions and (iii) masking of ΔffCO2 by 14C-enriched biosphere respiration. Here we evaluate these challenges and estimate potential biases and typical uncertainties of 14C-based ΔffCO2 estimates in Europe. We show that Mace Head (MHD), Ireland, is a representative background station for the Integrated Carbon Observation System (ICOS) atmosphere station network. The mean ΔffCO2 representativeness bias when using the MHD Δ14CO2 background for the whole observation network is of order 0.1 ± 0.3 ppm. At ICOS sites, the median nuclear contamination leads to 25% low-biased ΔffCO2 estimates if not corrected for. The ΔffCO2 masking due to 14C-enriched heterotrophic CO2 respiration can lead to similar ΔffCO2 biases as the nuclear contaminations, especially in summer. Our evaluation of all components contributing to the uncertainty of ΔffCO2 estimates reveals that, due to the small ffCO2 signals at ICOS stations, almost half of the 14C-based ΔffCO2 estimates from integrated samples have an uncertainty that is larger than 50%. This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'. [ABSTRACT FROM AUTHOR]

Atmospheric measurements of the O2/N2 ratio and the CO2 mole fraction (combined into the conceptual tracer 'Atmospheric Potential Oxygen', APO) over continents have been proposed as a constraint on CO2 emissions from fossil-fuel burning. Here we assess the suitability of such APO data to constrain anthropogenic CO2 emissions in Western Europe, with particular focus on their decadal trends. We use an inversion of atmospheric transport to estimate spatially and temporally explicit scaling factors on a bottom-up fossil-fuel emissions inventory. Based on the small number of currently available observational records, our CO2 emissions estimates show relatively large apparent year-to-year variations, exceeding the expected uncertainty of the bottom-up inventory and precluding the calculation of statistically significant trends. We were not able to trace the apparent year-to-year variations back to particular properties of the APO data. Inversion of synthetic APO data, however, confirms that data information content and degrees of freedom are sufficient to successfully correct a counterfactual prior. Larger sets of measurement stations, such as the recently started APO observations from the Integrated Carbon Observation System (ICOS) European research infrastructure, improve the constraint and may ameliorate possible problems with local signals or with measurement or model errors at the stations. We further tested the impact of uncertainties in the O2:CO2 stoichiometries of fossil-fuel burning and land biospheric exchange and found they are not fundamental obstacles to estimating decadal trends in fossil-fuel CO2 emissions, though further work on fossil-fuel O2:CO2 stoichiometries seems necessary. [ABSTRACT FROM AUTHOR]

Atmospheric transport inversions are a powerful tool for independently estimating surface CO2 fluxes from atmospheric CO2 concentration measurements. However, additional tracers are needed to separate the fossil fuel CO2 (ffCO2) emissions from natural CO2 fluxes. In this study we focus on radiocarbon (14C), the most direct tracer for ffCO2, and the continuously measured surrogate tracer carbon monoxide (CO), which is co-emitted with ffCO2 during incomplete combustion. In the companion paper by Maier et al. (2023a) we determined for the urban Heidelberg observation site in Southwestern Germany discrete 14C-based and continuous ∆CO-based estimates of the ffCO2 excess concentration (∆ffCO2) compared to a clean-air reference. Here, we use the CarboScope inversion framework adapted for the urban domain around Heidelberg to assess the potential of both types of ∆ffCO2 observations to investigate ffCO2 emissions and their seasonal cycle. We find that discrete 14C-based ∆ffCO2 observations from almost 100 afternoon flask samples collected in the two years 2019 and 2020 are not well suited for estimating robust ffCO2 emissions in the main footprint of this urban area with a very heterogeneous distribution of sources including several point sources. The benefit of the continuous ∆CO-based ∆ffCO2 estimates is that they can be averaged to reduce the impact of individual hours with an inadequate model performance. We show that the weekly averaged ∆CO-based ∆ffCO2 observations allow for a robust reconstruction of the seasonal cycle of the area source ffCO2 emissions from temporally flat a-priori emissions. In particular, the distinct COVID-19 signal with a steep drop in emissions in spring 2020 is clearly present in these data-driven a-posteriori results. Moreover, our top-down results show a shift in the seasonality of the area source ffCO2 emissions around Heidelberg in 2019 compared to the bottom-up estimates from TNO. This highlights the huge potential of ∆CO-based ∆ffCO2 to verify bottom-up ffCO2 emissions at urban stations if the ∆CO / ∆ffCO2 ratios can be determined without biases. [ABSTRACT FROM AUTHOR]

Estimates of ocean CO2 uptake from global ocean biogeochemistry models and pCO2 -based data products differ substantially, especially in high latitudes and in the trend of the CO2 uptake since 2000. Here, we assess the effect of data sparsity on two pCO2 -based estimates by subsampling output from a global ocean biogeochemistry model. The estimates of the ocean CO2 uptake are improved from a sampling scheme that mimics present-day sampling to an ideal sampling scheme with 1000 evenly distributed sites. In particular, insufficient sampling has given rise to strong biases in the trend of the ocean carbon sink in the pCO2 products. The overestimation of the CO2 flux trend by 20–35% globally and 50–130% in the Southern Ocean with the present-day sampling is reduced to less than 15% with the ideal sampling scheme. A substantial overestimation of the decadal variability of the Southern Ocean carbon sink occurs in one product and appears related to a skewed data distribution in pCO2 space. With the ideal sampling, the bias in the mean CO2 flux is reduced from 9–12% to 2–9% globally and from 14–26% to 5–17% in the Southern Ocean. On top of that, discrepancies of about 0.4 PgC yr−1 (15%) persist due to uncertainties in the gas-exchange calculation. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'. [ABSTRACT FROM AUTHOR]