Radiative Transfer Speed-Up Combining Optimal Spectral Sampling With a Machine Learning Approach

The Orbiting Carbon Observatories-2 and -3 make space-based measurements in the oxygen A-band and the weak and strong carbon dioxide (CO2) bands using the Atmospheric Carbon Observations from Space (ACOS) retrieval. Within ACOS, a Bayesian optimal estimation approach is employed to retrieve the column-averaged CO2 dry air mole fraction from these measurements. This retrieval requires a large number of polarized, multiple-scattering radiative transfer calculations for each iteration. These calculations take up the majority of the processing time for each retrieval and slow down the algorithm to the point that reprocessing data from the mission over multiple years becomes especially time consuming. To accelerate the radiative transfer model and, thereby, ease this bottleneck, we have developed a novel approach that enables modeling of the full spectra for the three OCO-2/3 instrument bands from radiances calculated at a small subset of monochromatic wavelengths. This allows for a reduction of the number of monochromatic calculations by a factor of 10, which can be achieved with radiance errors of less than 0.01% with respect to the existing algorithm and is easily tunable to a desired accuracy-speed trade-off. For the ACOS retrieval, this speeds up the over-retrievals by about a factor of two. The technique may be applicable to similar retrieval algorithms for other greenhouse gas sensors with large data volumes, such as GeoCarb, GOSAT-3, and CO2M

Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño

The 2015–2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO_2) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO_2, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability

Tracking CO2 emission reductions from space: A case study at Europe’s largest fossil fuel power plant

We quantify CO2 emissions from Europe’s largest fossil fuel power plant, the Bełchatόw Power Station in Poland, using CO2 observations from NASA’s Orbiting Carbon Observatory (OCO) 2 and 3 missions on 10 occasions from March 2017 to June 2022. The space-based CO2 emission estimates reveal emission changes with a trend that is consistent with the independent reported hourly power generation trend that results from both permanent and temporary unit shutdowns. OCO-2 and OCO-3 emission estimates agree with the bottom-up emission estimates within their respective 1σ uncertainties for 9 of the 10 occasions. Different methods for defining background values and corresponding uncertainties are explored in order to better understand this important potential error contribution. These results demonstrate the ability of existing space-based CO2 observations to quantify emission reductions for a large facility when adequate coverage and revisits are available. The results are informative for understanding the expected capability and potential limitations of the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) and other future satellites to support monitoring and verification of CO2 emission reductions resulting from climate change mitigation efforts such as the Paris Agreement

Absorption Coefficient (ABSCO) Tables for the Orbiting Carbon Observatories: Version 5.1

The accuracy of atmospheric trace gas retrievals depends directly on the accuracy of the molecular absorption model used within the retrieval algorithm. For remote sensing of well-mixed gases, such as carbon dioxide (CO₂), where the atmospheric variability is small compared to the background, the quality of the molecular absorption model is key. Recent updates to oxygen (O₂) absorption coefficients (ABSCO) for the 0.76 μm A-band and the water vapor (H₂O) continuum model within the 1.6 μm and 2.06 μm CO₂ bands used within the Orbiting Carbon Observatory (OCO-2 and OCO-3) algorithm are described here. Updates in the O₂ A-band involve the inclusion of new laboratory measurements within multispectrum fits to improve relative consistency between O₂ line shapes and collision-induced absorption (CIA). The H₂O continuum model has been updated to MTCKD v3.2, which has benefited from information from a range of laboratory studies relative to the model utilized in the previous ABSCO version. Impacts of these spectroscopy updates have been evaluated against ground-based atmospheric spectra from the Total Carbon Column Observing Network (TCCON) and within the framework of the OCO-2 algorithm, using OCO-2 soundings covering a range of atmospheric and surface conditions. The updated absorption coefficients (ABSCO version 5.1) are found to offer improved fitting residuals and reduced biases in retrieved surface pressure relative to the previous version (ABSCO v5.0) used within B8 and B9 of the OCO-2 retrieval algorithm and have been adopted for the OCO B10 Level 2 algorithm

Absorption Coefficient (ABSCO) Tables for the Orbiting Carbon Observatories: Version 5.1

The accuracy of atmospheric trace gas retrievals depends directly on the accuracy of the molecular absorption model used within the retrieval algorithm. For remote sensing of well-mixed gases, such as carbon dioxide (CO₂), where the atmospheric variability is small compared to the background, the quality of the molecular absorption model is key. Recent updates to oxygen (O₂) absorption coefficients (ABSCO) for the 0.76 μm A-band and the water vapor (H₂O) continuum model within the 1.6 μm and 2.06 μm CO₂ bands used within the Orbiting Carbon Observatory (OCO-2 and OCO-3) algorithm are described here. Updates in the O₂ A-band involve the inclusion of new laboratory measurements within multispectrum fits to improve relative consistency between O₂ line shapes and collision-induced absorption (CIA). The H₂O continuum model has been updated to MTCKD v3.2, which has benefited from information from a range of laboratory studies relative to the model utilized in the previous ABSCO version. Impacts of these spectroscopy updates have been evaluated against ground-based atmospheric spectra from the Total Carbon Column Observing Network (TCCON) and within the framework of the OCO-2 algorithm, using OCO-2 soundings covering a range of atmospheric and surface conditions. The updated absorption coefficients (ABSCO version 5.1) are found to offer improved fitting residuals and reduced biases in retrieved surface pressure relative to the previous version (ABSCO v5.0) used within B8 and B9 of the OCO-2 retrieval algorithm and have been adopted for the OCO B10 Level 2 algorithm

Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño

The 2015–2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO_2) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO_2, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability

National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake

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 as a country-level dataset. Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 PgCO2 yr-1 (0.90–1.25 PgC 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

Measurement of the triple-differential cross section for photon plus jets production in proton-proton collisions at √s = 7 TeV

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Search for massive resonances in dijet systems containing jets tagged as W or Z boson decays in pp collisions at √s=8 TeV

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Search for disappearing tracks in proton-proton collisions at √s=8 TeV

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