Atmospheric CO2 Growth Research Articles

Scale‐Dependent Drivers of Air‐Sea CO2 Flux Variability

AbstractIn climate studies, it is crucial to distinguish between changes caused by natural variability and those resulting from external forcing. Here we use a suite of numerical experiments based on the ECCO‐Darwin ocean biogeochemistry model to separate the impact of the atmospheric carbon dioxide (CO2) growth rate and climate on the ocean carbon sink — with a goal of disentangling the space‐time variability of the dominant drivers. When globally integrated, the variable atmospheric growth rate and climate exhibit similar magnitude impacts on ocean carbon uptake. At local scales, interannual variability in air‐sea CO2 flux is dominated by climate. The implications of our study for real‐world ocean observing systems are clear: in order to detect future changes in the ocean sink due to slowing atmospheric CO2 growth rates, better observing systems and constraints on climate‐driven ocean variability are required.

The decline in tropical land carbon sink drives high atmospheric CO2 growth rate in 2023

Abstract Atmospheric CO2 growth rate (CGR), reflecting the carbon balance between anthropogenic emissions and net uptake from land and ocean, largely determines the magnitude and speed of global warming. CGR at Mauna Loa Baseline Observatory reached record high in 2023. Here we quantified major components of global carbon balance for 2023, by developing a framework which integrated fossil fuel CO2 emissions data, an atmospheric inversion from Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) with two artificial intelligence (AI) models derived from dynamic global vegetation models. We attributed the record high CGR increase in 2023 compared to 2022 primarily to the large decline in land carbon sink (1803 ± 197 TgC year−1), with minor contributions from a small reduction in ocean carbon sink (184 TgC year−1) and a slight increase in fossil fuel emissions (24 TgC year−1). At least 78% of the global decline in land carbon sink was contributed by the decline in tropical sink, with GONGGA inversion (1354 TgC year−1) and AI simulations (1578 ± 666 TgC year−1) showing similar declines in the tropics. We further linked this tropical decline to the detrimental impact of El Niño-induced anomalous warming and drying on vegetation productivity in water-limited Sahel and southern Africa. Our successful attribution of CGR increase within the framework combining atmospheric inversion with AI simulations enabled near-real-time tracking of the global carbon budget which had a one-year reporting lag.

Enhanced global carbon cycle sensitivity to tropical temperature linked to internal climate variability.

The sensitivity of atmospheric CO2 growth rate to tropical temperature (γT) has almost doubled between 1959 and 2011, a trend that has been linked to increasing drought in the tropics. However, γT has declined since then. Understanding whether these variations in γT reflect forced changes or internal climate variability in the carbon cycle is crucial for future climate projections. We show that doubling sensitivity events can arise in simulations by Earth system models with perturbed initial conditions but are likely explained by internal climate variability. We show that the doubling sensitivity event is associated with the occurrence of a few, but very strong, El Niño events, such as 1982/83 and 1997/98. Such extreme events result in concurrent carbon release by tropical and extratropical ecosystems, increasing the variance of the global land carbon sink and its apparent sensitivity to tropical temperature. Our results imply that the doubling sensitivity does not necessarily indicate a change in carbon cycle response to climate change.

Toward Low‐Latency Estimation of Atmospheric CO2 Growth Rates Using Satellite Observations: Evaluating Sampling Errors of Satellite and In Situ Observing Approaches

AbstractThe atmospheric CO2 growth rate is a fundamental measure of climate forcing. NOAA's growth rate estimates, derived from in situ observations at the marine boundary layer (MBL), serve as the benchmark in policy and science. However, NOAA's MBL‐based method encounters challenges in accurately estimating the whole‐atmosphere CO2 growth rate at sub‐annual scales. Here we introduce the Growth Rate from Satellite Observations (GRESO) method as a complementary approach to estimate the whole‐atmosphere CO2 growth rate utilizing satellite data. Satellite CO2 observations offer extensive atmospheric coverage that extends the capability of the current NOAA benchmark. We assess the sampling errors of the GRESO and NOAA methods using 10 atmospheric transport model simulations. The simulations generate synthetic OCO‐2 satellite and NOAA MBL data for calculating CO2 growth rates, which are compared against the global sum of carbon fluxes used as model inputs. We find good performance for the NOAA method (R = 0.93, RMSE = 0.12 ppm year−1 or 0.25 PgC year−1). GRESO demonstrates lower sampling errors (R = 1.00; RMSE = 0.04 ppm year−1 or 0.09 PgC year−1). Additionally, GRESO shows better performance at monthly scales than the NOAA method (R = 0.76 vs. 0.47, respectively). Due to CO2's atmospheric longevity, the NOAA method accurately captures growth rates over 5‐year intervals. GRESO's robustness across partial coverage configurations (ocean or land data) shows that satellites can be promising tools for low‐latency CO2 growth rate information, provided the systematic biases are minimized using in situ observations. Along with accurate and calibrated NOAA in situ data, satellite‐derived growth rates can provide information about the global carbon cycle at sub‐annual scales.

A global surface CO2 flux dataset (2015–2022) inferred from OCO-2 retrievals using the GONGGA inversion system

Abstract. Accurate assessment of the size and distribution of carbon dioxide (CO2) sources and sinks is important for efforts to understand the carbon cycle and support policy decisions regarding climate mitigation actions. Satellite retrievals of the column-averaged dry-air mole fractions of CO2 (XCO2) have been widely used to infer spatial and temporal variations in carbon fluxes through atmospheric inversion techniques. In this study, we present a global spatially resolved terrestrial and ocean carbon flux dataset for 2015–2022. The dataset was generated by the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) atmospheric inversion system through the assimilation of Orbiting Carbon Observatory-2 (OCO-2) XCO2 retrievals. We describe the carbon budget, interannual variability, and seasonal cycle for the global scale and a set of TransCom regions. The 8-year mean net biosphere exchange and ocean carbon fluxes were −2.22 ± 0.75 and −2.32 ± 0.18 Pg C yr−1, absorbing approximately 23 % and 24 % of contemporary fossil fuel CO2 emissions, respectively. The annual mean global atmospheric CO2 growth rate was 5.17 ± 0.68 Pg C yr−1, which is consistent with the National Oceanic and Atmospheric Administration (NOAA) measurement (5.24 ± 0.59 Pg C yr−1). Europe has the largest terrestrial sink among the 11 TransCom land regions, followed by Boreal Asia and Temperate Asia. The dataset was evaluated by comparing posterior CO2 simulations with Total Carbon Column Observing Network (TCCON) retrievals as well as Observation Package (ObsPack) surface flask observations and aircraft observations. Compared with CO2 simulations using the unoptimized fluxes, the bias and root mean square error (RMSE) in posterior CO2 simulations were largely reduced across the full range of locations, confirming that the GONGGA system improves the estimates of spatial and temporal variations in carbon fluxes by assimilating OCO-2 XCO2 data. This dataset will improve the broader understanding of global carbon cycle dynamics and their response to climate change. The dataset can be accessed at https://doi.org/10.5281/zenodo.8368846 (Jin et al., 2023a).

Ocean-driven interannual variability in atmospheric CO2 quantified using OCO-2 observations and atmospheric transport simulations

Interannual variability (IAV) in the atmospheric CO2 growth rate is caused by variation in the balance between uptake by land and ocean and accumulation of anthropogenic emissions in the atmosphere. While variations in terrestrial fluxes are thought to drive most of the observed atmospheric CO2 IAV, the ability to characterize ocean impacts has been limited by the fact that most sites in the surface CO2 monitoring network are located on coasts or islands or within the continental interior. NASA’s Orbiting Carbon-Observatory 2 (OCO-2) mission has observed the atmospheric total column carbon dioxide mole fraction (XCO2) from space since September 2014. With a near-global coverage, this dataset provides a first opportunity to directly observe IAV in atmospheric CO2 over remote ocean regions. We assess the impact of ocean flux IAV on the OCO-2 record using atmospheric transport simulations with underlying gridded air-sea CO2 fluxes from observation-based products. We use three observation-based products to bracket the likely range of ocean air-sea flux contributions to XCO2 variability (over both land and ocean) within the GEOS-Chem atmospheric transport model. We find that the magnitude of XCO2 IAV generated by the whole ocean is between 0.08-0.12 ppm throughout the world. Depending on location and flux product, between 20-80% of the IAV in the simulations is caused by IAV in air-sea CO2 fluxes, with the remainder due to IAV in atmospheric winds, which modulate the atmospheric gradients that arise from climatological ocean fluxes. The Southern Hemisphere mid-latitudes and low-latitudes are the dominant ocean regions in generating the XCO2 IAV globally. The simulation results based on all three flux products show that even within the Northern Hemisphere atmosphere, Southern Hemisphere ocean fluxes are the dominant source of variability in XCO2. Nevertheless, the small magnitude of the air-sea flux impacts on XCO2 presents a substantial challenge for detection of ocean-driven IAV from OCO-2. Although the IAV amplitude arising from ocean fluxes and transport is 20 to 50% of the total observed XCO2 IAV amplitude of 0.4 to 1.6 ppm in the Southern Hemisphere and the tropics, ocean-driven IAV represents only 10% of the observed amplitude in the Northern Hemisphere. We find that for all three products, the simulated ocean-driven XCO2 IAV is weakly anti-correlated with OCO-2 observations, although these correlations are not statistically significant (p>0.05), suggesting that even over ocean basins, terrestrial IAV obscures the ocean signal.

Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches

Abstract. While the growth rate of atmospheric CO2 mole fractions can be measured with high accuracy, there are still large uncertainties in its attribution to specific regions and diverse anthropogenic and natural sources and sinks. A major source of uncertainty is the net flux of carbon dioxide from the biosphere to the atmosphere, the net ecosystem exchange (NEE). There are two major approaches to quantifying NEE: top-down approaches that typically use atmospheric inversions and bottom-up estimates that rely on process-based or data-driven models or inventories. Both top-down and bottom-up approaches have known strengths and limitations. Atmospheric inversions (e.g., those used in global carbon budgets) produce estimates of NEE that are consistent with the atmospheric CO2 growth rate at regional and global scales but are highly uncertain at smaller scales. Bottom-up data-driven models based on eddy-covariance measurements (e.g., FLUXCOM) match local observations of NEE and their spatial variability but have difficulty in accurately upscaling to a reliable global estimate. In this study, we propose combining the two approaches to produce global NEE estimates, with the goal of capitalizing on each approach's strengths and mitigating their limitations. We do this by constraining the data-driven FLUXCOM model with regional estimates of NEE derived from an ensemble of atmospheric inversions from the Global Carbon Budget 2021. To do this, we need to overcome a series of scientific and technical challenges when combining information about diverse physical variables, which are influenced by different processes at different spatial and temporal scales. We design a modeling structure that optimizes NEE by considering both the model's performance at the in situ level, based on eddy-covariance measurements, and at the level of large regions, based on atmospheric inversion estimates of NEE and their uncertainty. This resulting “dual-constraint” data-driven flux model improves on information based on single constraints (either top down or bottom up), producing robust locally resolved and globally consistent NEE spatio-temporal fields. Compared to reference estimates of the global land sink from the literature, e.g., Global Carbon Budgets, our double-constraint inferred global NEE shows a considerably smaller bias in global and tropical NEE compared to the underlying bottom-up data-driven model estimates (i.e., single constraint). The mean seasonality of our double-constraint inferred global NEE is also more consistent with the Global Carbon Budget and atmospheric inversions. At the same time, our model allows for more robustly spatially resolved NEE. The improved performance of the double-constraint model across spatial and temporal scales demonstrates the potential for adding a top-down constraint to a bottom-up data-driven flux model.

Importance of the memory effect for assessing interannual variation in net ecosystem exchange

Terrestrial carbon flux shows greater interannual variation (IAV) than the ocean and drives most temporal changes in the atmospheric CO2 growth rate. Accurate estimation of the interannual variation in the terrestrial carbon budget is crucial for predicting changes in the carbon balance of ecosystems and atmospheric CO2 concentrations in the context of climate change. However, the interannual variation simulation of the terrestrial carbon budget has considerable uncertainty. One of the important reasons is the neglect of the memory effect of the ecosystem on climate change, namely the potential lagged impact of climate change. In the present work, we integrated meteorological and remote sensing vegetation data and introduced the memory effect into a deep learning model to simulate the global terrestrial net ecosystem exchange (NEE). The conclusions were as follows: (a) Considering the memory effect not only improved the simulation accuracy of the global terrestrial NEE, R2 increased by 0.37–0.55, RMSE decreased by 38.97%–52.42%, and MAE decreased by 39.77%–52.38%, but also improved the simulation accuracy of the interannual variation of NEE, R2 increased by 0.50–0.84, RMSE decreased by 37.13%–72.07%, and MAE decreased by 40.72%–66.49%. (b) The memory effect of NEE varied by ecosystem type, environmental factors, and plant development phase. The response of NEE to precipitation in most ecosystems was slower than that to temperature and radiation. The length of the comprehensive memory effect of NEE on antecedent environmental variables in the non-growth season was longer than that in the growth season. (c) NEE in the tropics has shown greater interannual variation than that in the high latitudes and dominated interannual variation in global terrestrial NEE. The tropical savanna exceeded tropical forest and contributed the largest fraction of the interannual variation of NEE in the tropics.

Increasingly negative tropical water–interannual CO2 growth rate coupling

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon–climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land–atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon–climate interactions3–6. It is thought that variations in CGR are largely controlled by temperature7–10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989–2018 compared to 1960–1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water–carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon–climate feedbacks.

Elevated atmospheric CO2 suppresses silicon accumulation and exacerbates endophyte reductions in plant phosphorus

Abstract Many temperate grasses are both hyper‐accumulators of silicon (Si) and hosts of Epichloë fungal endophytes, functional traits which may alleviate environmental stresses such as herbivore attack. Si accumulation and endophyte infection may operate synergistically, but this has not been tested in a field setting, nor in the context of changing environmental conditions. Predicted increases in atmospheric CO2 concentrations can affect both Si accumulation and endophyte function, but these have not been studied in combination. We investigated how elevated atmospheric CO2 (eCO2), Si supplementation, endophyte‐presence and insect herbivory impacted plant growth, stoichiometry (C, N, P and Si), leaf gas exchange (rates of photosynthesis, stomatal conductance, transpiration rates) and endophyte production of anti‐herbivore defences (alkaloids) of an important pasture grass (tall fescue; Lolium arundinaceum) in the field. eCO2 and Si supplementation increased shoot biomass (+52% and +31%, respectively), whereas herbivory reduced shoot biomass by at least 35% and induced Si accumulation by 24%. Shoot Si concentrations, in contrast, decreased by 17%–21% under eCO2. Si supplementation and herbivory reduced shoot C concentrations. eCO2 reduced shoot N concentrations which led to increased shoot C:N ratios. Overall, shoot P concentrations were 26% lower in endophytic plants compared to non‐endophytic plants, potentially due to decreased mass flow (i.e. observed reductions in stomatal conductance and transpiration). Alkaloid production was not discernibly affected by any experimental treatment. The negative impacts of endophytes on P uptake were particularly strong under eCO2. We show that eCO2 and insect herbivory reduce and promote Si accumulation, respectively, incorporating some field conditions for the first time. This indicates that these drivers operate in a more realistic ecological context than previously demonstrated. Reduced uptake of P in endophytic plants may adversely affect plant productivity in the future, particularly if increased demand for P due to improved plant growth under eCO2 cannot be met. Read the free Plain Language Summary for this article on the Journal blog.

Recent decrease of the impact of tropical temperature on the carbon cycle linked to increased precipitation

The atmospheric CO2 growth rate (CGR) variability is largely controlled by tropical temperature fluctuations. The sensitivity of CGR to tropical temperature left({{{{rm{gamma }}}}}_{{{{rm{CGR}}}}}^{{{{rm{T}}}}}right) has strongly increased since 1960, but here we show that this trend has ceased. Here, we use the long-term CO2 records from Mauna Loa and the South Pole to compute CGR, and show that {{{{rm{gamma }}}}}_{{{{rm{CGR}}}}}^{{{{rm{T}}}}} increased by 200% from 1960–1979 to 1979–2000 but then decreased by 117% from 1980–2001 to 2001–2020, almost returning back to the level of the 1960s. Variations in {{{{rm{gamma }}}}}_{{{{rm{CGR}}}}}^{{{{rm{T}}}}} are significantly correlated with changes in precipitation at a bi-decadal scale. These findings are further corroborated by results from a dynamic vegetation model, collectively suggesting that increases in precipitation control the decreased {{{{rm{gamma }}}}}_{{{{rm{CGR}}}}}^{{{{rm{T}}}}} during recent decades. Our results indicate that wetter conditions have led to a decoupling of the impact of the tropical temperature variation on the carbon cycle.

Assessment of vapor pressure deficit variability and trends in Spain and possible connections with soil moisture

The Vapor Pressure Deficit (VPD) is one of the most relevant surface meteorological variables; with important implications in ecology, hydrology, and atmosphere. By understanding the processes involved in the variability and trend of the VPD, it is possible to assess the possible impacts and implications related to both physical and human environments, like plant function, water use efficiency, net ecosystem production, atmospheric CO2 growth rate, etc. This study analysed recent temporal variability and trends in VPD in Spain between 1980 and 2020 using a recently developed high-quality dataset. Also, the connection between VPD and soil moisture and other key climate variables (e.g. air temperature, precipitation, and relative humidity) was assessed on different time scales varying from weekly to annual. The objective was to determine if changes in land-atmosphere feedbacks connected with soil moisture and evapotranspiration anomalies have been relevant to assess the interannual variability and trends in VPD. Results demonstrate that VPD exhibited a clear seasonality and dominant positive trends on both the seasonal (mainly spring and summer) and annual scales. Rather, trends were statistically non-significant (p > 0.05) during winter and autumn. Spatially, VPD positive trends were more pronounced in southern and eastern of Spain. Also, results suggest that recent trends of VPD shows low contribution of variables that drive land-atmosphere feedbacks (e.g. evapotranspiration, and soil moisture) in comparison to the role of global warming processes. Notably, the variability of VPD seems to be less coupled with soil moisture variability during summertime, while it is better interrelated during winter, indicating that VPD variability would be mostly related to climate variability mechanisms that control temperature and relative humidity than to land-atmosohere feedbacks. Overall, our findings highlight the importance of assessing driving forces and physical mechanisms that control VPD variability using high-quality climate datasets, especially, in semiarid and sub-humid regions of the world.

Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model

Abstract. The global carbon budget (GCB) – including fluxes of CO2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO2 growth, air–land CO2 fluxes, and air–sea CO2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO2 fluxes, and 2 years for the air–land CO2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.

Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale

Due to the substantial gross exchange fluxes with the atmosphere, the terrestrial carbon cycle plays a significant role in the global carbon budget. Drought commonly affects terrestrial carbon absorption negatively. Terrestrial biosphere models exhibit significant uncertainties in capturing the carbon flux response to drought, which have an impact on estimates of the global carbon budget. Through plant physiological processes, soil moisture tightly regulates the carbon cycle in the environment. Therefore, accurate observations of soil moisture may enhance the modeling of carbon fluxes in a model–data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36-year satellite-derived surface soil moisture observations in combination with flask samples of atmospheric CO2 concentrations. We find that, compared to the default model, the performance of optimized net ecosystem productivity (NEP) and gross primary productivity (GPP) has increased with the RMSEs reduced by 1.62 gC/m2/month and 10.84 gC/m2/month, which indicates the added value of the ESA-CCI soil moisture observations as a constraint on the terrestrial carbon cycle. Additionally, the combination of soil moisture and CO2 concentration in this study improves the representation of inter-annual variability of terrestrial carbon fluxes as well as the atmospheric CO2 growth rate. We thereby investigate the ability of the optimized GPP in responding to drought by comparing continentally aggregated GPP with the drought index. The assimilation of surface soil moisture has been shown to efficiently capture the influences of the sub-annual (≤9 months drought durations) and large-scale (e.g., regional to continental scales) droughts on GPP. This study highlights the significant potential of satellite soil moisture for constraining inter-annual models of the terrestrial biosphere’s carbon cycle and for illustrating how GPP responds to drought at a continental scale.

Isotopic evidence for increased carbon and nitrogen exchanges between peatland plants and their symbiotic microbes with rising atmospheric CO2 concentrations since 15,000 cal. year BP.

Whether nitrogen (N) availability will limit plant growth and removal of atmospheric CO2 by the terrestrial biosphere this century is controversial. Studies have suggested that N could progressively limit plant growth, as trees and soils accumulate N in slowly cycling biomass pools in response to increases in carbon sequestration. However, a question remains over whether longer-term (decadal to century) feedbacks between climate, CO2 and plant N uptake could emerge to reduce ecosystem-level N limitations. The symbioses between plants and microbes can help plants to acquire N from the soil or from the atmosphere via biological N2 fixation-the pathway through which N can be rapidly brought into ecosystems and thereby partially or completely alleviate N limitation on plant productivity. Here we present measurements of plant N isotope composition (δ15 N) in a peat core that dates to 15,000 cal. year BP to ascertain ecosystem-level N cycling responses to rising atmospheric CO2 concentrations. We find that pre-industrial increases in global atmospheric CO2 concentrations corresponded with a decrease in the δ15 N of both Sphagnum moss and Ericaceae when constrained for climatic factors. A modern experiment demonstrates that the δ15 N of Sphagnum decreases with increasing N2 -fixation rates. These findings suggest that plant-microbe symbioses that facilitate N acquisition are, over the long term, enhanced under rising atmospheric CO2 concentrations, highlighting an ecosystem-level feedback mechanism whereby N constraints on terrestrial carbon storage can be overcome.

An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019

The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO2 concentrations to invert carbon sources and sinks; however, many global carbon inversion models are not publicly available. In addition, our regional assimilation inversion system, CCMVS-R (China Carbon Monitoring, Verification and Supporting for Regional), needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions. Here, an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter (EnSRF) algorithm is constructed and used to infer global and China's carbon fluxes in 2019. Atmospheric CO2 concentrations from ObsPack sites and five additional CO2 observational sites from China's Greenhouse Gas Observation Network (CGHGNET) were used for data assimilation to improve the estimate. The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year, respectively, accounting for 21.1% and 25.1% of global fossil fuel CO2 emissions. The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO2 growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration (NOAA), showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks. The inverted terrestrial carbon sink of China is 0.37 Pg C per year, accounting for approximately 13% of China's fossil CO2 emissions.

Interannual global carbon cycle variations linked to atmospheric circulation variability

Abstract. One of the least understood temporal scales of global carbon cycle (C-cycle) dynamics is its interannual variability (IAV). This variability is mainly driven by variations in the local climatic drivers of terrestrial ecosystem activity, which in turn are controlled by large-scale modes of atmospheric variability. Here, we quantify the fraction of global C-cycle IAV that is explained by large-scale atmospheric circulation variability, which is quantified by spatiotemporal sea level pressure (SLP) fields. C-cycle variability is diagnosed from the global detrended atmospheric CO2 growth rate and the land CO2 sink from 16 dynamic global vegetation models and two atmospheric inversions in the Global Carbon Budget 2018. We use a regularized linear regression model, which represents a statistical learning technique apt to deal with the large number of atmospheric circulation predictors (p≥800, each representing one pixel-based time series of SLP anomalies) in a relatively short observed record (n<60 years). We show that boreal winter and spring SLP anomalies allow predicting IAV in the atmospheric CO2 growth rate and the global land sink, with Pearson correlations between reference and predicted values between 0.70 and 0.84 for boreal winter SLP anomalies. This is comparable to or higher than that of a similar model using 15 traditional teleconnection indices as predictors. The spatial patterns of regression coefficients of the model based on SLP fields show a predominant role of the tropical Pacific and over Southeast Asia extending to Australia, corresponding to the regions associated with the El Niño–Southern Oscillation variability. We also identify another important region in the western Pacific, roughly corresponding to the West Pacific pattern. We further evaluate the influence of the time series length on the predictability of IAV and find that reliable estimates of global C-cycle IAV can be obtained from records of 30–54 years. For shorter time series (n<30 years), however, our results show that conclusions about CO2 IAV patterns and drivers need to be evaluated with caution. Overall, our study illustrates a new data-driven and flexible approach to model the relationship between large-scale atmospheric circulation variations and C-cycle variability at global and regional scales, complementing the traditional use of teleconnection indices.

Using the atmospheric CO2 growth rate to constrain the CO2 flux from land use and land cover change since 1900.

We explore the ability of the atmospheric CO2 record since 1900 to constrain the source of CO2 from land use and land cover change (hereafter "land use"), taking account of uncertainties in other terms in the global carbon budget. We find that the atmospheric constraint favors land use CO2 flux estimates with lower decadal variability and can identify potentially erroneous features, such as emission peaks around 1960 and after 2000, in some published estimates. Furthermore, we resolve an offset in the global carbon budget that is most plausibly attributed to the land use flux. This correction shifts the mean land use flux since 1900 across 20 published estimates down by 0.35 PgC year-1 to 1.04 ± 0.57 PgC year-1 , which is within the range but at the low end of these estimates. We show that the atmospheric CO2 record can provide insights into the time history of the land use flux that may reduce uncertainty in this term and improve current understanding and projections of the global carbon cycle.

Soil carbon and microbes in the warming tropics

Abstract Climate warming could destabilise the Earth's largest terrestrial store of reactive carbon (C), by accelerating the decomposition of soil organic matter. A third of that C store resides in the tropics. The potential for tropical soils to sequester C, or to act as an additional source of CO2, will depend on the balance of C inputs and outputs, mediated by the response of soil microbial communities and their activity to perturbation. We review the impact of warming on microbial communities and C storage in humid tropical forest soils over multiple time‐scales. Recent in situ experiments indicate high sensitivity of tropical forest soil C mineralisation to warming in the short term. However, whether this will translate into long‐term soil C decline remains unclear. At decadal time‐scales, high sensitivity of soil C mineralisation to warming is consistent with the correlation between the inter‐annual variation in the tropical land surface temperature and atmospheric CO2 growth rate, and with simulations using the Carnegie‐Ames‐Stanford Approach biosphere model. This observed sensitivity may further contribute to climatic change over millennial time‐scales, suggested by radiocarbon dating of organic matter in river basins showing a twofold acceleration in tropical soil C release during the late‐glacial warming period. However, counter to this evidence, long‐term stability of tropical soil C is suggested by observed steady‐state soil C turnover across temperature gradients with elevation, and by the presence of C in tropical soils that pre‐dates the Holocene Thermal Maximum and late‐glacial warming periods. To help reconcile these recent experimental findings and long‐term observations, we propose mechanisms to explain tropical soil C and microbial responses to warming across multiple time‐scales. Combined in situ experimental and monitoring approaches—large‐scale and cross‐site—are urgently needed to resolve the interplay of these mechanisms across spatial and temporal scales, to shape a better understanding of the relationship between soil microbes and C storage in tropical soils. Read the free Plain Language Summary for this article on the Journal blog.

How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle?

AbstractFossil fuel combustion, land use change and other human activities have increased the atmospheric carbon dioxide (CO2) abundance by about 50% since the beginning of the industrial age. The atmospheric CO2 growth rates would have been much larger if natural sinks in the land biosphere and ocean had not removed over half of this anthropogenic CO2. As these CO2 emissions grew, uptake by the ocean increased in response to increases in atmospheric CO2 partial pressure (pCO2). On land, gross primary production also increased, but the dynamics of other key aspects of the land carbon cycle varied regionally. Over the past three decades, CO2 uptake by intact tropical humid forests declined, but these changes are offset by increased uptake across mid‐ and high‐latitudes. While there have been substantial improvements in our ability to study the carbon cycle, measurement and modeling gaps still limit our understanding of the processes driving its evolution. Continued ship‐based observations combined with expanded deployments of autonomous platforms are needed to quantify ocean‐atmosphere fluxes and interior ocean carbon storage on policy‐relevant spatial and temporal scales. There is also an urgent need for more comprehensive measurements of stocks, fluxes and atmospheric CO2 in humid tropical forests and across the Arctic and boreal regions, which are experiencing rapid change. Here, we review our understanding of the atmosphere, ocean, and land carbon cycles and their interactions, identify emerging measurement and modeling capabilities and gaps and the need for a sustainable, operational framework to ensure a scientific basis for carbon management.