We present new calculations of radiative forcing at very high concentrations of CO2, CH4, and N2O, relevant to extreme anthropogenic climate change and paleoclimate studies. CO2 forcing is calculated over the range 100 ppmv to 50,000 ppmv, and the maximum forcing is 38.1 W m−2. CH4 and N2O forcings are calculated over the range 100 ppbv to 100 ppmv and give maximum forcings of 6.66 W m−2 and 22.3 W m−2. The sensitivity of our calculations to spatial averaging and tropopause definition is examined. We compare our results with the “simplified expressions” reported by Intergovernmental Panel on Climate Change (IPCC) and find significant differences at high greenhouse gas concentrations. We provide new simplified expressions which agree much better with the calculated forcings and suggest that these expressions be used in place of the IPCC expressions. Additionally, we provide meridionally resolved forcings which may be used to force simple and intermediate complexity climate models.

While large‐scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO2 offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration. Widespread flooding during spring and early summer 2019 induced conditions that delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar‐induced chlorophyll fluorescence from TROPOspheric Monitoring Instrument and Orbiting Carbon Observatory reveal a 16‐day shift in the seasonal cycle of photosynthesis relative to 2018, along with a 15% lower peak value. We estimate a reduction of 0.21 PgC in cropland gross primary productivity in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late‐season temperature. Ultimately, this change is predicted to reduce the crop productivity in the Midwest Corn/Soy belt by ~15% compared to 2018. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO2 enhancements of up to 10 ppm in the midday boundary layer from Atmospheric Carbon and Transport‐America aircraft and over 3 ppm in column‐averaged dry‐air mole fractions from Orbiting Carbon Observatory. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining solar‐induced chlorophyll fluorescence with atmospheric CO2 observations to monitor regional carbon flux anomalies.

Abstract. We use optimal estimation (OE) to quantify methane fluxes based on total column CH4 data from the Greenhouse Gases Observing Satellite (GOSAT) and the GEOS-Chem global chemistry transport model. We then project these fluxes to emissions by sector at 1∘ resolution and then to each country using a new Bayesian algorithm that accounts for prior and posterior uncertainties in the methane emissions. These estimates are intended as a pilot dataset for the global stock take in support of the Paris Agreement. However, differences between the emissions reported here and widely used bottom-up inventories should be used as a starting point for further research because of potential systematic errors of these satellite-based emissions estimates. We find that agricultural and waste emissions are ∼ 263 ± 24 Tg CH4 yr−1, anthropogenic fossil emissions are 82 ± 12 Tg CH4 yr−1, and natural wetland/aquatic emissions are 180 ± 10 Tg CH4 yr−1. These estimates are consistent with previous inversions based on GOSAT data and the GEOS-Chem model. In addition, anthropogenic fossil estimates are consistent with those reported to the United Nations Framework Convention on Climate Change (80.4 Tg CH4 yr−1 for 2019). Alternative priors can be easily tested with our new Bayesian approach (also known as prior swapping) to determine their impact on posterior emissions estimates. We use this approach by swapping to priors that include much larger aquatic emissions and fossil emissions (based on isotopic evidence) and find little impact on our posterior fluxes. This indicates that these alternative inventories are inconsistent with our remote sensing estimates and also that the posteriors reported here are due to the observing and flux inversion system and not uncertainties in the prior inventories. We find that total emissions for approximately 57 countries can be resolved with this observing system based on the degrees-of-freedom for signal metric (DOFS > 1.0) that can be calculated with our Bayesian flux estimation approach. Below a DOFS of 0.5, estimates for country total emissions are more weighted to our choice of prior inventories. The top five emitting countries (Brazil, China, India, Russia, USA) emit about half of the global anthropogenic budget, similar to our choice of prior emissions but with the posterior emissions shifted towards the agricultural sector and less towards fossil emissions, consistent with our global posterior results. Our results suggest remote-sensing-based estimates of methane emissions can be substantially different (although within uncertainty) than bottom-up inventories, isotopic evidence, or estimates based on sparse in situ data, indicating a need for further studies reconciling these different approaches for quantifying the methane budget. Higher-resolution fluxes calculated from upcoming satellite or aircraft data such as the Tropospheric Monitoring Instrument (TROPOMI) and those in formulation such as the Copernicus CO2M, MethaneSat, or Carbon Mapper can be incorporated into our Bayesian estimation framework for the purpose of reducing uncertainty and improving the spatial resolution and sectoral attribution of subsequent methane emissions estimates.

Top‐down estimates of CO2 fluxes are typically constrained by either surface‐based or space‐based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface‐based and space‐based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6‐year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface‐based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space‐based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root‐mean‐square differences between posterior flux‐simulated CO2 and aircraft‐based CO2 over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface‐based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space‐based and surface‐based flux constraints.

Abstract. Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1∘ × 1∘ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr−1 (0.90–1.25 Pg C yr−1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

Inverse modeling of regional CO2 fluxes using atmospheric CO2 data is sensitive to the observational coverage of the observing network. Here we use the GEOS‐Chem adjoint model to examine the sensitivity to CO2 fluxes of observations from the in situ surface network, the Total Carbon Column Observing Network (TCCON), the Greenhouse Gases Observing Satellite (GOSAT), and the Orbiting Carbon Observatory (OCO‐2). We find that OCO‐2 has high sensitivity to fluxes throughout the tropics and Southern Hemisphere, while surface observations have high sensitivity to fluxes in the northern extratropics throughout the year. For GOSAT viewing modes, ocean glint data provide the strongest constraints on fluxes in the tropics and Southern Hemisphere during Northern Hemisphere fall and winter relative to other viewing modes. In contrast, GOSAT nadir land data offer the greater sensitivity to fluxes in these regions during Northern Hemisphere spring and summer. For OCO‐2 viewing modes, ocean glint data provided the dominant sensitivity to the surface fluxes in the northern subtropics, tropics, and Southern Hemisphere. We performed a series of inversion analyses using pseudodata and found that the varying sensitivities can result in large differences in regional flux estimates. However, combining measurements from different observing systems to exploit their complementarity may lead to a posteriori flux estimates with improved accuracy.

On regional to global scales, few constraints exist on gross primary productivity (GPP) and ecosystem respiration (R e ) fluxes. Yet constraints on these fluxes are critical for evaluating and improving terrestrial biosphere models. In this study, we evaluate the seasonal cycle of GPP, R e , and net ecosystem exchange (NEE) produced by four terrestrial biosphere models and FLUXCOM, a data-driven model, over northern midlatitude ecosystems. We evaluate the seasonal cycle of GPP and NEE using solar-induced fluorescence retrieved from the Global Ozone Monitoring Experiment-2 and column-averaged dry-air mole fractions of CO 2 (X CO 2 ) from the Total Carbon Column Observing Network, respectively. We then infer R e by combining constraints on GPP with constraints on NEE from two flux inversions. An ensemble of optimized R e seasonal cycles is generated using five GPP estimates and two NEE estimates. The optimized R e curves generally show high consistency with each other, with the largest differences due to the magnitude of GPP. We find optimized R e exhibits a systematically broader summer maximum than modeled R e , with values lower during June-July and higher during the fall than R e . Further analysis suggests that the differences could be due to seasonal variations in the carbon use efficiency (possibly due to an ecosystem-scale Kok effect) and to seasonal variations in the leaf litter and fine root carbon pool. The results suggest that the inclusion of variable carbon use efficiency for autotrophic respiration and carbon pool dependence for heterotrophic respiration is important for accurately simulating R e .

Despite reduced insolation in the late Archean, evidence suggests a warm climate which was likely sustained by a stronger greenhouse effect, the so-called Faint Young Sun Problem (FYSP). CO 2 and CH 4 are generally thought to be the mainstays of this enhanced greenhouse, though many other gases have been proposed. We present high accuracy radiative forcings for CO 2 , CH 4 and 26 other gases, performing the radiative transfer calculations at line-by-line resolution and using HITRAN 2012 line data for background pressures of 0.5, 1, and 2 bar of atmospheric N 2 . For CO 2 to resolve the FYSP alone at 2.8 Gyr BP (80 % of present solar luminosity), 0.32 bar is needed with 0.5 bar of atmospheric N 2 , 0.20 bar with 1 bar of atmospheric N 2 , or 0.11 bar with 2 bar of atmospheric N 2 . For CH 4 , we find that near-infrared absorption is much stronger than previously thought, arising from updates to the HITRAN database. CH 4 radiative forcing peaks at 10.3, 9, or 8.3 W m −2 for background pressures of 0.5, 1 or 2 bar, likely limiting the utility of CH 4 for warming the Archean. For the other 26 HITRAN gases, radiative forcings of up to a few to 10 W m −2 are obtained from concentrations of 0.1-1 ppmv for many gases. For the 20 strongest gases, we calculate the reduction in radiative forcing due to overlap. We also tabulate the modern sources, sinks, concentrations and lifetimes of these gases and summaries the literature on Archean sources and concentrations. We recommend the forcings provided here be used both as a first reference for which gases are likely good greenhouse gases, and as a standard set of calculations for validation of radiative forcing calculations for the Archean.