A global CO₂ flux dataset (2015–2019) inferred from OCO-2 retrievals using the Tan-Tracker inversion system

Accurate assessment of the various sources and sinks of carbon dioxide (CO2), especially terrestrial ecosystem and ocean fluxes with high uncertainties, is important for understanding of the global carbon cycle, supporting the formulation of climate policies, and projecting future climate change. Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) are being widely used to improve carbon flux estimation due to their broad spatial coverage. However, there is no consensus on the robust estimates of regional fluxes. In this study, we present a global and regional resolved terrestrial ecosystem carbon flux (NEE) and ocean carbon flux dataset for 2015–2019. The dataset was generated using the Tan-Tracker inversion system by assimilating Observing Carbon Observatory 2 (OCO-2) column CO2 retrievals. The posterior NEE and ocean carbon fluxes were comprehensively validated by comparing posterior simulated CO2 concentrations with OCO-2 independent retrievals and Total Carbon Column Observing Network (TCCON) measurements. The validation showed that posterior carbon fluxes significantly improved the modelling of atmospheric CO2 concentrations, with global mean biases of 0.33 ppm against OCO-2 retrievals and 0.12 ppm against TCCON measurements. We described the characteristics of the dataset at global, regional, and Tibetan Plateau scales in terms of the carbon budget, annual and seasonal variations, and spatial distribution. The posterior 5-year annual mean global atmospheric CO2 growth rate was 5.35 PgC yr−1, which was within the uncertainty of the Global Carbon Budget 2020 estimate (5.49 PgC yr−1). The posterior annual mean NEE and ocean carbon fluxes were −4.07 and −3.33 PgC yr−1, respectively. Regional fluxes were analysed based on TransCom partitioning. All 11 land regions acted as carbon sinks, except for Tropical South America, which was almost neutral. The strongest carbon sinks were located in Boreal Asia, followed by Temperate Asia and North Africa. The entire Tibetan Plateau ecosystem was estimated as a carbon sink, taking up −49.52 TgC yr−1 on average, with the strongest sink occurring in eastern alpine meadows. These results indicate that our dataset captures surface carbon fluxes well and provides insight into the global carbon cycle. The dataset can be accessed at https://doi.org/10.11888/Meteoro.tpdc.271317 (Jin et al., 2021).

Consistent regional fluxes of CH₄ and CO₂ inferred from GOSAT proxy XCH₄ : XCO₂ retrievals, 2010–2014

We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4 : XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. This work builds on the previously reported theory that takes into account that (1) these ratios are less prone to systematic error than either the full-physics data products or the proxy CH4 data products; and (2) the resulting CH4 and CO2 fluxes are self-consistent. We show that a posteriori fluxes inferred from the GOSAT data generally outperform the fluxes inferred only from in situ data, as expected. GOSAT CH4 and CO2 fluxes are consistent with global growth rates for CO2 and CH4 reported by NOAA and have a range of independent data including new profile measurements (0–7 km) over the Amazon Basin that were collected specifically to help validate GOSAT over this geographical region. We find that large-scale multi-year annual a posteriori CO2 fluxes inferred from GOSAT data are similar to those inferred from the in situ surface data but with smaller uncertainties, particularly over the tropics. GOSAT data are consistent with smaller peak-to-peak seasonal amplitudes of CO2 than either the a priori or in situ inversion, particularly over the tropics and the southern extratropics. Over the northern extratropics, GOSAT data show larger uptake than the a priori but less than the in situ inversion, resulting in small net emissions over the year. We also find evidence that the carbon balance of tropical South America was perturbed following the droughts of 2010 and 2012 with net annual fluxes not returning to an approximate annual balance until 2013. In contrast, GOSAT data significantly changed the a priori spatial distribution of CH4 emission with a 40 % increase over tropical South America and tropical Asia and a smaller decrease over Eurasia and temperate South America. We find no evidence from GOSAT that tropical South American CH4 fluxes were dramatically affected by the two large-scale Amazon droughts. However, we find that GOSAT data are consistent with double seasonal peaks in Amazonian fluxes that are reproduced over the 5 years we studied: a small peak from January to April and a larger peak from June to October, which are likely due to superimposed emissions from different geographical regions.

Consistent regional fluxes of CH₄ and CO₂ inferred from GOSAT proxy XCH₄:XCO₂ retrievals, 2010–2014

We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4:XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. This work builds on previously reported theory that takes advantage that: (1) these ratios are less prone to systematic error than either the full physics data products or the proxy CH4 data products; and (2) the resulting CH4 and CO2 fluxes are self-consistent. We show that a posteriori fluxes inferred from the GOSAT data generally outperform the fluxes inferred only from in situ data, as expected. GOSAT CH4 and CO2 fluxes are consistent with global growth rates for CO2 and CH4 reported by NOAA, and with a range of independent data including in particular new profile measurements (0–7 km) over the Amazon basin that were collected specifically to help validate GOSAT over this geographical region. We find that large-scale multi-year annual a posteriori CO2 fluxes inferred from GOSAT data are similar to those inferred from the in situ surface data but with smaller uncertainties, particularly over the tropics. GOSAT data are consistent with smaller peak-to-peak seasonal amplitudes of CO2 than either a priori or the in situ inversion, particularly over the tropics and the southern extra-tropics. Over the northern extra-tropics, GOSAT data show larger uptake than the a priori but less than the in situ inversion, resulting in small net emissions over the year. We also find evidence that the carbon balance of tropical South America was perturbed following the droughts of 2010 and 2012 with net annual fluxes not returning to an approximate annual balance until 2013. In contrast, GOSAT data significantly changed the a priori spatial distribution of CH4 emission with a 40 % increase over tropical South America and tropical Asia and smaller decrease over Eurasia and temperate South America. We find no evidence from GOSAT that tropical South American CH4 fluxes were dramatically affected by the two large-scale Amazon droughts. However, we find that GOSAT data are consistent with double seasonal peaks in fluxes that are reproduced over the five years we studied: a small peak in January to April and a larger peak in June to October, which is likely due to superimposed emissions from different geographical regions.

Long-lived atmospheric trace gases measurements in flask samples from three stations in India

With the rapid growth in population and economic development, emissions of greenhouse gases (GHGs) from the Indian subcontinent have sharply increased during recent decades. However, evaluation of regional fluxes of GHGs and characterization of their spatial and temporal variations by atmospheric inversions remain uncertain due to a sparse regional atmospheric observation network. As a result of an Indo-French collaboration, three new atmospheric stations were established in India at Hanle (HLE), Pondicherry (PON) and Port Blair (PBL), with the objective of monitoring the atmospheric concentrations of GHGs and other trace gases. Here we present the results of the measurements of CO2, CH4, N2O, SF6, CO, and H2 from regular flask sampling at these three stations over the period 2007–2011. For each species, annual means, seasonal cycles and gradients between stations were calculated and related to variations in natural GHG fluxes, anthropogenic emissions, and monsoon circulations. Covariances between species at the synoptic scale were analyzed to investigate the likely source(s) of emissions. The flask measurements of various trace gases at the three stations have the potential to constrain the inversions of fluxes over southern and northeastern India. However, this network of ground stations needs further extension to other parts of India to better constrain the GHG budgets at regional and continental scales.

Five-year flask measurements of long-lived trace gases in India

With the rapid growth in population and economic development, emissions of greenhouse gases (GHGs) from the Indian subcontinent have sharply increased during recent decades. However, evaluation of regional fluxes of GHGs and characterization of their spatial and temporal variations by atmospheric inversions remain uncertain due to a sparse regional atmospheric observation network. As a result of Indo-French collaboration, three new atmospheric stations were established in India at Hanle (HLE), Pondicherry (PON) and Port Blair (PBL), with the objective of monitoring the atmospheric concentrations of GHGs and other trace gases. Here we present the results of five-year measurements (2007–2011) of CO2, CH4, N2O, SF6, CO, and H2 from regular flask sampling at these three stations. For each species, annual means, seasonal cycles and gradients between stations were calculated and related to variations in the natural GHG fluxes, anthropogenic emissions, and the monsoon circulations. Covariances between species at the synoptic scale were analyzed to investigate the dominant source(s) of emissions. The flask measurements of various trace gases at the three stations show potential to constrain the inversions of fluxes over Southern and Northeastern India. However, this network of ground stations needs further extension to other parts of India to allow a better understanding of, and constraints on the GHG budgets at regional and continental scales.

Estimating regional fluxes of CO2 and CH4 using space-borne observations of XCH4 : XCO2

We use the GEOS-Chem global 3-D atmospheric chemistry transport model to interpret XCH4:XCO2 column ratios retrieved using a proxy method from the Japanese Greenhouse gases Observing SATellite (GOSAT). The advantage of these data over CO2 and CH4 columns retrieved independently using a full physics optimal estimation algorithm is that they suffer less from scattering-related regional bias. We show the model is able to reproduce observed global and regional spatial (mean bias =0.7%) and temporal variations (global r2=0.92) of this ratio with model bias <2.5%. We also show these variations are driven by emissions of CO2 and CH4 that are typically six months out of phase which may reduce the sensitivity of the ratio to changes in either gas. To simultaneously estimate fluxes of CO2 and CH4 we use a formal Bayesian inverse model infrastructure. We use two approaches to independently resolve flux estimates of these two gases using GOSAT observations of XCH4:XCO2: (1) the a priori error covariance between CO2 and CH4 describing common source from biomass burning; and (2) also fitting independent surface atmospheric measurements of CH4 and CO2 mole fraction that provide additional constraints, improving the effectiveness of the observed GOSAT ratio to constrain fluxes. We demonstrate the impact of these two approaches using Observing System Simulation Experiments. A posteriori flux estimates inferred using only the GOSAT ratios and taking advantage of the error covariance due to biomass burning are not consistent with the true fluxes in our experiments, as the inversion system cannot judge which species' fluxes to adjust. This can result in a posteriori fluxes that are further from the truth than the a priori fluxes. We find that adding the surface data to the inversion dramatically improves the ability of the GOSAT ratios to infer both CH4 and CO2 fluxes. We show that using real GOSAT XCH4:XCO2 ratios together with the surface data during 2010 outcompetes inversions using the individual XCH4 or the full-physics XCO2 data products. Regional fluxes that show the greatest improvements have model minus observation differences with a large seasonal cycle such as Tropical South America for which we report a small but significant annual source of CO2 compared to a small annual sink inferred from the XCO2 data. Based on our analysis we argue that using the ratios we may be reaching the limitations on the precision of these data.