The importance of digital elevation model accuracy in X_CO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product

Atmospheric measurement techniques, Journal Year: 2024, Volume and Issue: 17(5), P. 1375 - 1401

Published: March 6, 2024

Abstract. Knowledge of surface pressure is essential for calculating column-averaged dry-air mole fractions trace gases, such as CO2 (XCO2). In the NASA Orbiting Carbon Observatory 2 (OCO-2) Atmospheric Observations from Space (ACOS) retrieval algorithm, retrieved pressures have been found to unacceptable errors, warranting a parametric bias correction. This correction depends on difference between and priori pressures, which are derived meteorological model that hypsometrically adjusted elevation using digital (DEM). As result, effectiveness OCO-2 contingent upon accuracy referenced DEM. Here, we investigate several different DEM datasets use in ACOS algorithm: OCODEM used v10 previous versions, NASADEM+ (a composite SRTMv4, ASTER GDEMv3, GIMP, RAMPv2 DEMs) v11, Copernicus GLO-90 (GLO-90 DEM), two polar regional DEMs (ArcticDEM REMA). We find (ASTER GDEMv3) has persistent negative order 10 20 m across most regions north 60° N latitude, relative all other considered (OCODEM, ArcticDEM, DEM). Variations elevations lead variations XCO2 approximately 0.4 ppm, meaning v11 retrievals tends be 0.8 ppm lower than v10. Our analysis also suggests superior global continuity compared DEMs, motivating post-processing update Lite files (which NASADEM+) v11.1 by substituting globally. improves spatial bias-corrected product both high-latitude while resulting marginal or no change within ± latitude. addition, provides increased data throughput after quality control filtering regions, partly due but mostly corrections parameters. Given large-scale differences NASADEM+, replacing with yields ∼ 100 TgC shift inferred carbon uptake zones spanning 30 60 90° N, 5 % 7 estimated pan-Arctic land sink. Changes fluxes smaller, given evidence improved accuracies this DEM, large changes likely erroneous.

Language: Английский

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Global Daily Column Average CO2 at 0.1° × 0.1° Spatial Resolution Integrating OCO-3, GOSAT, CAMS with EOF and Deep Learning

Scientific Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: Feb. 14, 2025

Accurate global carbon dioxide (CO2) distribution with high spatial and temporal resolution is essential for understanding its dynamics impacts on climate change. This study tackles the challenge of data gaps in satellite observations greenhouse gases, caused by orbital observational limitations. We reconstructed a comprehensive dataset Column-averaged CO2 (XCO2) concentrations integrating re-analyzed from Copernicus Atmosphere Monitoring Service (CAMS) GOSAT OCO-3 satellites. Using two advanced reconstruction methods—Data Interpolating Empirical Orthogonal Functions (DINEOF) Convolutional Auto-Encoder (DINCAE)—we imputed missing data, preserving consistency. The combined approach achieved accuracy, Pearson correlation values between 0.94 0.95 against TCCON measurements, we also reported root mean square error (RMSE) to assess model performance further. Our results indicate that these techniques generate daily, high-resolution, gap-free XCO2 dataset, enabling improved monitoring, modeling, policy development.

Language: Английский

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A method for estimating localized CO₂ emissions from co-located satellite XCO₂ and NO₂ images

Atmospheric measurement techniques, Journal Year: 2024, Volume and Issue: 17(3), P. 1145 - 1173

Published: Feb. 16, 2024

Abstract. Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50 % since beginning of industrial era, causing climate change. Fossil fuel combustion responsible for CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates emissions these are key tracking effectiveness implemented policies mitigate We developed an automatic procedure quantify based on cross-sectional mass-balance approach and applied it infer Bełchatów Power Station (Poland) using observations Orbiting Observatory 3 (OCO-3) in its snapshot area map (SAM) mode. As result challenge identifying emission plumes satellite data with adequate accuracy, we located constrained shape TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. automatically analysed all available OCO-3 overpasses over July 2019 November 2022 found total nine that were suitable estimation our method. The mean uncertainty obtained was 5.8 Mt yr−1 (22.0 %), mainly driven dispersion fluxes downwind source, e.g. due turbulence. This characterized semivariogram, made possible imaging capability target region SAM mode, provides containing plume information up several tens kilometres source. A bottom-up estimate computed hourly power-plant-generated factors validate satellite-based estimates. two independent agree within their 1σ eight out have high Pearson's correlation coefficient 0.92. Our results confirm potential monitor space-based usefulness detection. They also illustrate improve monitoring capabilities planned Copernicus Anthropogenic (CO2M) constellation, will provide simultaneously retrieved XCO2 maps.

Language: Английский

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Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(18), P. 3394 - 3394

Published: Sept. 12, 2024

With the rapid development of satellite remote sensing technology, carbon-cycle research, as a key focus global climate change, has also been widely developed in terms carbon source/sink-research methods. The internationally recognized “top-down” approach, which is based on observations, an important means to verify greenhouse gas-emission inventories. This article reviews principles, categories, and detection payloads for gases introduces inversion algorithms datasets XCO2. It emphasizes methods machine learning assimilation algorithms. Additionally, it presents technology achievements carbon-assimilation systems used estimate fluxes. Finally, summarizes prospects future improve accuracy estimating monitoring Earth’s processes.

Language: Английский

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Two years of satellite-based carbon dioxide emission quantification at the world's largest coal-fired power plants

Atmospheric chemistry and physics, Journal Year: 2023, Volume and Issue: 23(22), P. 14577 - 14591

Published: Nov. 24, 2023

Abstract. Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have ability to detect and quantify large CO2 point sources, including coal-fired power plants. In this study, we routinely made observations with PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite imaging spectrometer Orbiting Observatory-3 (OCO-3) instrument aboard International Space Station at over 30 plants between 2021 2022. plumes were detected 50 % of acquired PRISMA scenes, which is consistent combined influence viewing parameters on detection (solar illumination surface reflectance) unknown factors (e.g., daily operational status). We compare satellite-derived emission rates situ stack find average agreement within 27 for OCO-3, although more needed robustly characterize error. highlight two examples fusing OCO-2 OCO-3 South Africa India. For India, same day used high-spatial-resolution capability (30 m spatial/pixel resolution) partition relative contributions distinct emitting net emission. Although an encouraging start, 2 years these satellites did not produce sufficient estimate annual low (<15 %) uncertainties. However, as constellation CO2-observing poised significantly improve coming decade, study offers approach leverage multiple observation platforms better uncertainty anthropogenic sources.

Language: Английский

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Multi-sensor integrated mapping of global XCO2 from 2015 to 2021 with a local random forest model

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 208, P. 107 - 120

Published: Jan. 18, 2024

Language: Английский

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The role of OCO-3 XCO₂ retrievals in estimating global terrestrial net ecosystem exchanges

Atmospheric chemistry and physics, Journal Year: 2025, Volume and Issue: 25(2), P. 867 - 880

Published: Jan. 22, 2025

Abstract. Satellite-based column-averaged dry-air CO2 mole fraction (XCO2) retrievals are frequently used to improve the estimates of terrestrial net ecosystem exchanges (NEEs). The Orbiting Carbon Observatory 3 (OCO-3) satellite, launched in May 2019, was designed address important questions about distribution carbon fluxes on Earth, but its role estimating global NEE remains unclear. Here, using Global Assimilation System, version 2, we investigate impact OCO-3 XCO2 estimation by assimilating alone and combination with OCO-2 retrievals. results show that when only is assimilated (Exp_OCO3), estimated land sink significantly lower than from experiment (Exp_OCO2). estimate joint assimilation (Exp_OCO3&amp;2) comparable a scale Exp_OCO2. However, there significant regional differences. Compared observed annual growth rate, Exp_OCO3 has largest bias Exp_OCO3&amp;2 shows best performance. Furthermore, validation independent observations biases larger those Exp_OCO2 at middle high latitudes. reasons for poor performance include lack beyond 52° S N, large fluctuations number data, varied observation time. Our study indicates leads an underestimation sinks latitudes afternoon required better NEE.

Language: Английский

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The greenhouse gas observation mission with Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW): objectives, conceptual framework and scientific contributions

Progress in Earth and Planetary Science, Journal Year: 2025, Volume and Issue: 12(1)

Published: Jan. 23, 2025

Abstract The Japanese Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW) will be an Earth-observing satellite to conduct global observations of atmospheric carbon dioxide (CO 2 ), methane (CH 4 nitrogen (NO ) simultaneously from a single platform. GOSAT-GW is the third in series currently operating (GOSAT) GOSAT-2. It carry two sensors, Total Anthropogenic Natural emissions mapping SpectrOmeter-3 (TANSO-3) Advanced Microwave Scanning Radiometer 3 (AMSR3), with latter dedicated observation physical parameters related water cycle. TANSO-3 high-resolution grating spectrometer designed measure reflected sunlight visible short-wave infrared spectral ranges. aims retrieve column-averaged dry-air mole fractions CO CH (denoted as XCO XCH , respectively), well vertical column density tropospheric NO . sensor onboard utilize wavelength bands 0.45, 0.76, 1.61 µm O retrievals, respectively. fly sun-synchronous orbit local overpass time approximately 13:30 3-day ground-track repeat has modes push-broom operation: Wide Mode, which provides globally covered maps 10-km spatial resolution within days, Focus snapshot over targeted areas high 1–3 km. objectives mission include (1) monitoring global-mean concentrations greenhouse gasses (GHGs), (2) verifying national anthropogenic GHG inventories, (3) detecting large sources, such megacities power plants. A comprehensive validation exercise conducted ensure that products’ quality meets required precision achieve above objectives. With projected operational lifetime seven years, provide vital space-based constraints on both natural emissions. These measurements contribute significantly climate change mitigation efforts, particularly by supporting Stocktake (GST) mechanism, key element Paris Agreement.

Language: Английский

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Seasonal and interannual variability in CO₂ fluxes in southern Africa seen by GOSAT

Biogeosciences, Journal Year: 2025, Volume and Issue: 22(2), P. 555 - 584

Published: Jan. 30, 2025

Abstract. The interannual variability in the global carbon sink is heavily influenced by semiarid regions. Southern hemispheric Africa has large and arid However, there only a sparse coverage of situ CO2 measurements Hemisphere. This leads to uncertainties measurement-based flux estimates for these Furthermore, dynamic vegetation models (DGVMs) show inconsistencies Satellite offer spatially extensive independent source information about southern African cycle. We examine Greenhouse Gases Observing (GOSAT) concentration from 2009 2018 Africa. infer land–atmosphere fluxes which are consistent with GOSAT using TM5-4DVar atmospheric inversion system. find systematic differences between inversions performed on satellite observations versus that assimilate measurements. suggests limited measurement content latter. use GOSAT-based solar-induced fluorescence (SIF; proxy photosynthesis) as constraints select DGVMs TRENDYv9 ensemble compatible fluxes. selected allow study processes driving By doing so, our satellite-based process analyses pinpoint photosynthetic uptake grasslands be main driver fluxes, agreeing former studies based alone. seasonal cycle, however, substantially enhanced soil respiration due rewetting at beginning rainy season. latter result emphasizes importance correctly representing response ecosystems DGVMs.

Language: Английский

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Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01

Geoscientific model development, Journal Year: 2025, Volume and Issue: 18(5), P. 1505 - 1544

Published: March 10, 2025

Abstract. The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. While the analytical and variational optimization implemented in CIF are operational have proved to be accurate efficient, initial ensemble method was found incomplete could hardly compared other employed inversion community, mainly owing strong performance limitations absence of localization methods. In this paper, we present evaluate a new implementation mode, building upon developments. As first step, chose implement serial batch versions square root filter (EnSRF) algorithm because it is widely community. We provide comprehensive description technical useful features can users. Finally, demonstrate capabilities CIF-EnSRF system using large number synthetic experiments over Europe with flexible scalable high-performance transport model ICON-ART, exploring system’s sensitivity multiple parameters that tuned by expected, results sensitive size parameters. Other tested parameters, such as lags, propagation factors, or function, also substantial influence on results. introduce way interpreting set metrics automatically computed help assess success inversions compare them. This work complements previous efforts focused within CIF. ICON-ART has been used testing work, integration these algorithms enables any perform inversions, fully leveraging CIF's robust capabilities.

Language: Английский

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