Sourish Basu

Understanding interannual variability (IAV) in terrestrial CO₂ fluxes is essential for constraining ecosystem responses to climatic anomalies and future carbon-climate feedbacks. A 14-year GOSAT record spanning 2009 to end of 2022 now enables a robust global assessment of regional IAV. Here, we analyse annual net land CO₂ fluxes from nine in situ-constrained inversions and three GOSAT-based inversions, and compare them with the TRENDY v13 ensemble mean of dynamic global vegetation models (DGVMs). We find that DGVMs show weaker IAV than the inversion-based flux estimates in almost all regions. In Australia, boreal and temperate North America, and Eurasian Temperate, differences in NEE anomalies between GOSAT-based inversions and TRENDY are strongly related to hydroclimatic anomalies, with soil moisture and temperature emerging as dominant drivers in different regions. These results suggest that DGVMs underestimate the sensitivity of NEE to climate variability in key regions. The extended satellite record makes it possible to use the hydroclimatic anomalies of the last 14 years to identify deficiencies in ecosystem parameterizations and thereby reduce uncertainty in the global carbon budget.

NASA's Orbiting Carbon Observatory‐2 (OCO‐2) and OCO‐3 have been observing Earth's atmosphere from space since September 2014 and August 2019, respectively. The version 11 (v11) Atmospheric Carbon Observations from Space (ACOS) Level 2 full physics (L2FP) retrieval algorithm has been used to provide estimates of the column‐averaged dry‐air mole fraction of carbon dioxide () from OCO measurements of surface reflected near‐infrared solar radiation. In this work, updates to the ACOS v11 retrieval algorithm are discussed, and the quality filtering and bias correction of the products are described. estimates from OCO‐2 and OCO‐3 are compared to Total Carbon Column Observing Network (TCCON) observations and to atmospheric inversion models, which serve as truth‐proxies for . In addition, a direct comparison of collocated soundings between OCO‐2 and OCO‐3 is performed. Variations in v11 over small areas show improvement in agreement between actual and theoretical uncertainties, suggesting a reduction in systematic errors compared to v10, especially for OCO‐3. There is reduced variance in the new v11 product relative to truth‐proxies, including less divergence in the values with time against models. The collocations of observations between OCO‐2 and OCO‐3 indicate an overall mean difference of <0.2 ppm across the overlapping time range. Furthermore, OCO‐2 and OCO‐3 agree better with each other than they do with the validation sources, suggesting a well conditioned and unified set of concentrations that can be used concurrently for carbon cycle studies to provide a benchmark record spanning September 2014 through August 2026.

Understanding interannual variability (IAV) in terrestrial CO₂ fluxes is essential for constraining ecosystem responses to climatic anomalies and future carbon-climate feedbacks. A 14-year GOSAT record spanning 2009 to end of 2022 now enables a robust global assessment of regional IAV. Here, we analyse annual net land CO₂ fluxes from nine in situ-constrained inversions and three GOSAT-based inversions, and compare them with the TRENDY v13 ensemble mean of dynamic global vegetation models (DGVMs). We find that DGVMs show weaker IAV than the inversion-based flux estimates in almost all regions. In Australia, boreal and temperate North America, and Eurasian Temperate, differences in NEE anomalies between GOSAT-based inversions and TRENDY are strongly related to hydroclimatic anomalies, with soil moisture and temperature emerging as dominant drivers in different regions. These results suggest that DGVMs underestimate the sensitivity of NEE to climate variability in key regions. The extended satellite record makes it possible to use the hydroclimatic anomalies of the last 14 years to identify deficiencies in ecosystem parameterizations and thereby reduce uncertainty in the global carbon budget.

All emissions pathways aimed at stabilizing global temperatures at the internationally agreed target of 1.5–2 °C above pre-industrial levels require steep cuts in global CO₂ emissions. Reliable emissions tracking is therefore essential to monitoring progress towards related mitigation goals, especially for the world’s largest emitters. Here we make use of atmospheric measurements of Δ¹⁴CO₂ and the dual-tracer Δ¹⁴CO₂:CO₂ assimilation and inversion system previously developed by our group to estimate annual and monthly CO₂ emissions from fossil fuel use and cement production (FFCO₂) for the U.S. for 2010 and 2015, the first two individual years for which large numbers of atmospheric Δ¹⁴CO₂ measurements are available. Ensemble-mean national FFCO₂ totals obtained from a 9-member suite of inverse results are larger than reported by the U.S. Environmental Protection Agency (EPA), but overlap at their respective 2σ ensemble-wide model spreads (inversions) and reported 95 % confidence intervals (EPA) in both years. In contrast, the inverse results agree with both annual totals and 16 of 24 derived monthly totals from the Vulcan 3.0 emissions data product with 1σ, ensemble wide. Central estimates of the change in U.S. FFCO₂ emission between 2010 and 2015 range from -5.1 % (EPA), -5.8 % (Vulcan), and -7.8 % (this work), providing a first confirmation of an expected national FFCO₂ decline based on atmospheric observations. The development of a reliable emissions tracking system based directly on atmospheric observations, as detailed here, may take on additional scientific and policy relevance given the recent interruption of EPA reporting.

All emissions pathways aimed at stabilizing global temperatures at the internationally agreed target of 1.5–2 °C above pre-industrial levels require steep cuts in global CO₂ emissions. Reliable emissions tracking is therefore essential to monitoring progress towards related mitigation goals, especially for the world’s largest emitters. Here we make use of atmospheric measurements of Δ¹⁴CO₂ and the dual-tracer Δ¹⁴CO₂:CO₂ assimilation and inversion system previously developed by our group to estimate annual and monthly CO₂ emissions from fossil fuel use and cement production (FFCO₂) for the U.S. for 2010 and 2015, the first two individual years for which large numbers of atmospheric Δ¹⁴CO₂ measurements are available. Ensemble-mean national FFCO₂ totals obtained from a 9-member suite of inverse results are larger than reported by the U.S. Environmental Protection Agency (EPA), but overlap at their respective 2σ ensemble-wide model spreads (inversions) and reported 95 % confidence intervals (EPA) in both years. In contrast, the inverse results agree with both annual totals and 16 of 24 derived monthly totals from the Vulcan 3.0 emissions data product with 1σ, ensemble wide. Central estimates of the change in U.S. FFCO₂ emission between 2010 and 2015 range from -5.1 % (EPA), -5.8 % (Vulcan), and -7.8 % (this work), providing a first confirmation of an expected national FFCO₂ decline based on atmospheric observations. The development of a reliable emissions tracking system based directly on atmospheric observations, as detailed here, may take on additional scientific and policy relevance given the recent interruption of EPA reporting.

All emissions pathways aimed at stabilizing global temperatures at the internationally agreed target of 1.5–2 °C above pre-industrial levels require steep cuts in global CO₂ emissions. Reliable emissions tracking is therefore essential to monitoring progress towards related mitigation goals, especially for the world’s largest emitters. Here we make use of atmospheric measurements of Δ¹⁴CO₂ and the dual-tracer Δ¹⁴CO₂:CO₂ assimilation and inversion system previously developed by our group to estimate annual and monthly CO₂ emissions from fossil fuel use and cement production (FFCO₂) for the U.S. for 2010 and 2015, the first two individual years for which large numbers of atmospheric Δ¹⁴CO₂ measurements are available. Ensemble-mean national FFCO₂ totals obtained from a 9-member suite of inverse results are larger than reported by the U.S. Environmental Protection Agency (EPA), but overlap at their respective 2σ ensemble-wide model spreads (inversions) and reported 95 % confidence intervals (EPA) in both years. In contrast, the inverse results agree with both annual totals and 16 of 24 derived monthly totals from the Vulcan 3.0 emissions data product with 1σ, ensemble wide. Central estimates of the change in U.S. FFCO₂ emission between 2010 and 2015 range from -5.1 % (EPA), -5.8 % (Vulcan), and -7.8 % (this work), providing a first confirmation of an expected national FFCO₂ decline based on atmospheric observations. The development of a reliable emissions tracking system based directly on atmospheric observations, as detailed here, may take on additional scientific and policy relevance given the recent interruption of EPA reporting.

Methane (CH ₄ ) oxidation by microbes is the largest biological sink of global methane, yet its magnitude and long‐term variability remain uncertain. Here, we combined process‐based (PB), machine‐learning (ML), and atmospheric inversion approaches to evaluate the global methane soil sinks and its implication for the atmospheric CH ₄ budget in this study. Both PB and ML approaches estimated annual global methane soil sink to be 40–45 Tg CH ₄ yr ⁻¹ , 30%–50% larger than conventional estimates. Although the two approaches agreed on total magnitude, they differ in their representation of variability. PB models simulate stronger spatial heterogeneity, seasonality, and long‐term increases in CH ₄ uptake because environmental sensitivities are explicitly represented through mechanistic equations. In contrast, ML models reproduce site‐level observations more closely but exhibit muted spatial and temporal variability due to their limited environmental sensitivities from sparse and discrete observations used for model training. Atmospheric inversions further indicate that incorporating the larger soil sink improves agreement with observed atmospheric CH ₄ and its stable carbon isotope changes and requires larger microbial CH ₄ emissions. Together, these results suggest that the global methane soil sink may have been underestimated and demonstrate the value of integrating PB and ML modeling, and atmospheric constraints to improve understanding of global methane cycling.

Understanding interannual variability (IAV) in terrestrial CO₂ fluxes is essential for constraining ecosystem responses to climatic anomalies and future carbon-climate feedbacks. A 14-year GOSAT record spanning 2009 to end of 2022 now enables a robust global assessment of regional IAV. Here, we analyse annual net land CO₂ fluxes from nine in situ-constrained inversions and three GOSAT-based inversions, and compare them with the TRENDY v13 ensemble mean of dynamic global vegetation models (DGVMs). We find that DGVMs show weaker IAV than the inversion-based flux estimates in almost all regions. In Australia, boreal and temperate North America, and Eurasian Temperate, differences in NEE anomalies between GOSAT-based inversions and TRENDY are strongly related to hydroclimatic anomalies, with soil moisture and temperature emerging as dominant drivers in different regions. These results suggest that DGVMs underestimate the sensitivity of NEE to climate variability in key regions. The extended satellite record makes it possible to use the hydroclimatic anomalies of the last 14 years to identify deficiencies in ecosystem parameterizations and thereby reduce uncertainty in the global carbon budget.

All emissions pathways aimed at stabilizing global temperatures at the internationally agreed target of 1.5–2 °C above pre-industrial levels require steep cuts in global CO2 emissions. Reliable emissions tracking is therefore essential to monitoring progress towards related mitigation goals, especially for the world’s largest emitters. Here we make use of atmospheric measurements of Δ14CO2 and the dual-tracer Δ14CO2:CO2 assimilation and inversion system previously developed by our group to estimate annual and monthly CO2 emissions from fossil fuel use and cement production (FFCO2) for the U.S. for 2010 and 2015, the first two individual years for which large numbers of atmospheric Δ14CO2 measurements are available. Ensemble-mean national FFCO2 totals obtained from a 9-member suite of inverse results are larger than reported by the U.S. Environmental Protection Agency (EPA), but overlap at their respective 2σ ensemble-wide model spreads (inversions) and reported 95 % confidence intervals (EPA) in both years. In contrast, the inverse results agree with both annual totals and 16 of 24 derived monthly totals from the Vulcan 3.0 emissions data product with 1σ, ensemble wide. Central estimates of the change in U.S. FFCO2 emission between 2010 and 2015 range from -5.1 % (EPA), -5.8 % (Vulcan), and -7.8 % (this work), providing a first confirmation of an expected national FFCO2 decline based on atmospheric observations. The development of a reliable emissions tracking system based directly on atmospheric observations, as detailed here, may take on additional scientific and policy relevance given the recent interruption of EPA reporting.