The concentration of carbon dioxide (CO₂) in Earth's atmosphere is increasing due to human activities and the resulting effects on the global climate system have initiated several policy‐driven approaches to reduce emissions of this greenhouse gas. Quantifying the effectiveness of such policies requires both bottom‐up and top‐down approaches to estimate CO₂ emissions. This work investigates, for the first time, the potential of using Snapshot Area Map observations from NASA's OCO‐3 instrument to disaggregate sector‐specific emissions from instrument observations. Optimized sector‐specific timeseries were produced using Bayesian inversion techniques and compared to proxy activity data from transportation, commercial maritime, and industrial sectors in the Los Angeles Basin. Results demonstrate that dense space‐based observations of atmospheric CO₂ are capable of disentangling sector‐specific CO₂ fluxes, paving the way for accurate monitoring of the effects of carbon‐reduction policies and operational carbon monitoring systems.

The Orbiting Carbon Observatory 2 (OCO‐2) is NASA's first Earth observation satellite mission dedicated to studying the sources and sinks of carbon dioxide (CO₂) on a global scale. The observations of reflected sunlight are inverted in a retrieval algorithm to produce estimates of the dry air mole‐fractions of CO₂ (X_CO2). The OCO‐2 Level 2 data release, version 11.1 (v11.1) retrievals from the Atmospheric Carbon Observations from Space (ACOS) algorithm, includes significant improvements in the X_CO2 data product compared to older OCO‐2 data versions. This work compares the v11.1 X_CO2 from OCO‐2 against X_CO2 estimates collected from a global ground‐based network known as the Total Carbon Column Observing Network (TCCON), OCO‐2's primary validation source. The OCO‐2 project provides a version of the Level 2 data product, called “lite” files that include calibrated and bias‐corrected X_CO2 values, accessible together with all OCO‐2 data products through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). This work shows that OCO‐2 X_CO2 observations made between September 2014 and December 2023, after quality filtering and the application of an averaging kernel correction, agree well with coincident TCCON data for all OCO‐2 observational modes of land (nadir, glint, target) and ocean (glint). The aggregated, bias‐corrected, and quality‐filtered absolute average bias values are less than or equal to 0.20 parts per million (ppm) globally for all OCO‐2 observation modes, where the biases do not indicate a statistically significant time dependence. The land nadir/glint mode has the lowest bias value of −0.03 ± 0.85 ppm.

The COllaborative Carbon Column Observing Network has become a reliable source of high-quality ground-based remote sensing network data that provide column-averaged dry-air mole fractions of carbon dioxide (XCO₂), methane (XCH₄), and carbon monoxide (XCO). The fiducial reference measurements of these gases from the COCCON complement the TCCON and NDACC-IRWG data. This study shows the application of COCCON data for the validation of existing greenhouse gas satellite products. This study includes the validation of XCH₄ and XCO products from the European Copernicus Sentinel-5 Precursor (S5P) mission, XCO₂ products from the American Orbiting Carbon Observatory-2 (OCO-2) mission, and XCO₂ and XCH₄ products from the Japanese Greenhouse gases Observing SATellite (GOSAT). A total of 27 datasets contributed to this study; some of these were collected in the framework of campaign activities and covered only a short time period. In addition, several permanent stations provided long-term observations. The random uncertainties in the validation results, specifically for S5P with a lot of coincidences pairs, are found to be similar to the comparison with the TCCON. The comparison results of OCO-2 land nadir and land glint observation modes to the COCCON on a global scale, despite limited coincidences, are very promising. The stations can, therefore, expand on the coverage of the already existing ground-based reference remote sensing sites from the TCCON and the NDACC network. The COCCON data can be used for future satellite and model validation studies and carbon cycle studies.

The Solar Occultation for Ice Experiment (SOFIE) has operated aboard the Aeronomy of Ice in the Mesosphere (AIM) satellite since 2007. SOFIE uses solar occultation to retrieve ozone (O ₃ ) profiles from ∼20 to 100 km altitude, typically at polar latitudes. This study validates SOFIE O ₃ profiles, including error analysis and comparisons with independent observations. Comparisons are made to the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE‐FTS) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. SOFIE shows qualitative and quantitative agreement with both data sets between 30 and 70 km and better overall agreement in the northern hemisphere. SOFIE and ACE mean differences are typically within 20% in the 30–70 km altitude range. SOFIE and MIPAS exhibit mean difference values within 30% in the winter and 20% for all other seasons averaged, between ∼30 and 60 km. Seasonal comparisons indicate similar variations in both hemispheres and through all seasons. The comparisons indicate that SOFIE is biased 5%–10% low at 30–70 km altitudes, with greater differences at higher and lower altitudes. The comparisons are challenging due to the low O ₃ concentrations at high altitudes, the limited number of coincidences, and the large diurnal variation in mesospheric O ₃ during twilight hours.

The Orbiting Carbon Observatory-2 (OCO-2), launched in 2014, is NASA’s first satellite dedicated to measure sources and sinks of carbon dioxide (CO2) in Earth’s atmosphere on regional scales. Since 2019, measurements from the Orbiting Carbon Observatory-3 (OCO-3) have complemented OCO-2’s data record. In addition, OCO-3’s Snapshot Area Mapping (SAM) mode observations over emission hotspots like cities, power plants, and volcanoes provide a novel data set for carbon cycle studies on local scales. Data from both instruments are analyzed with the Atmospheric Carbon Observations from Space (ACOS) retrieval algorithm to estimate column-average dry-air mole fractions of carbon dioxide (XCO2) in Earth’s atmosphere. Evaluating these space-based estimates of XCO2 against independent validation data sets provides information about the quality, potential biases, and errors in the OCO-2/3 data record. Here, we present comparisons of the ACOS V10 XCO2 from OCO-3 and the new and improved ACOS V11 XCO2 from OCO-2 against ground-based measurements from the Total Carbon Column Observing Network (TCCON).For both instruments, the root-mean-square error (RMSE) is below 1 ppm for all observational modes when compared to collocated TCCON observations. The OCO-3 V10.4 data version, an improvement over the initial vEarly data version, reduces an XCO2 time-dependent bias that was present in the previous OCO-3 data record. Consequently, data from both instruments does not indicate any significant time-dependent bias over the span of several years. Further, we evaluate differences between OCO-3 and TCCON related to different local overpass times. On average, OCO-3’s equator crossing time occurs about 20 minutes earlier every day. Comparisons against TCCON indicate no significant local time of day bias in the OCO-3 XCO2 data, however, comparisons over individual TCCON sites indicate a dependence which provides insight into potential airmass and viewing geometry related biases. The improved OCO-2 V11 data version reduces the mean bias against TCCON to ~0.15ppm from previously ~0.4ppm in V10. We find the largest reduction in RMSE over ocean due to an improved ocean glint surface treatment in V11. Both OCO data products are of comparable quality and are an improvement over earlier OCO data versions. Finally, we analyze how well OCO-2 captures the mean seasonal cycle amplitudes and growth rates over selected TCCON sites.

Carbon dioxide (CO2) is the primary greenhouse gas emitted from anthropogenic activities. Although it is naturally present as a part of Earth’s carbon-cycle, human activities influence the ability of natural sinks to reduce CO2 from the atmosphere, thus altering the carbon-cycle and necessitating the long-term monitoring of atmospheric CO2. Precise, accurate and continuous measurements of CO2 are important to this end.The Orbiting Carbon Observatory-2 (OCO-2) was launched in 2014. It is NASA’s first Earth-orbiting satellite dedicated to making observations of CO2 in the atmosphere and measuring its column-averaged dry-air mole fraction (XCO2). The primary goal of the OCO-2 mission is to provide XCO2 measurements with sufficient precision and accuracy alongside quantifying its seasonal and interannual variability. In this study, we use the new and improved OCO-2 B11 data set.In the past, the space-based XCO2 measurements from OCO-2 data have been validated against independent data sets such as the Total Carbon Column Observing Network (TCCON). In this study, we use independent measurements from the COllaborative Carbon Column Observing Network (COCCON) to identify potential biases and errors in the B11 data version and establish its robustness for use by the science community. COCCON uses portable Fourier-Transform InfraRed (FTIR) spectrometers (EM27/SUN) to measure greenhouse gases at several global sites. Comparison of OCO-2 measurements against COCCON sites indicate similar temporal trends in XCO2 variability, with OCO-2 typically reporting higher values. Further, we evaluate the differences between the B11 OCO-2 and COCCON data sets. Finally, we analyze how OCO-2’s B11 version compares to selected COCCON and TCCON sites’ measurements in terms of capturing the seasonal cycle and growth rate of XCO2.