262 citations as recorded by crossref.

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5. Improving Model-Based Carbon Dioxide Datasets Using Deep Learning and Satellite Observations F. Mustafa & M. Xu https://doi.org/10.1109/TGRS.2025.3556309
6. Spatio-temporal approach to moving window block kriging of satellite data v1.0 J. Tadić et al. https://doi.org/10.5194/gmd-10-709-2017
7. Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements L. Wu et al. https://doi.org/10.5194/amt-11-3111-2018
8. Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0) S. Jiang et al. https://doi.org/10.1007/s00382-019-04914-x
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15. Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements A. Fraser et al. https://doi.org/10.5194/acp-13-5697-2013
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19. Research on Calculation Method of On-Orbit Instrumental Line Shape Function for the Greenhouse Gases Monitoring Instrument on the GaoFen-5B Satellite Y. Han et al. https://doi.org/10.3390/rs16122171
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22. Coupled Dynamics of Aerosols and Greenhouse Gases at the Socheongcho Ocean Research Station During High-Concentration Episodes S. Ahn et al. https://doi.org/10.3390/rs18050816
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24. Constraining regional greenhouse gas emissions using geostationary concentration measurements: a theoretical study P. Rayner et al. https://doi.org/10.5194/amt-7-3285-2014
25. Mapping contiguous XCO2 by machine learning and analyzing the spatio-temporal variation in China from 2003 to 2019 M. Zhang & G. Liu https://doi.org/10.1016/j.scitotenv.2022.159588
26. A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. https://doi.org/10.5194/gmd-14-3633-2021
27. Using Dimers to Measure Biosignatures and Atmospheric Pressure for Terrestrial Exoplanets A. Misra et al. https://doi.org/10.1089/ast.2013.0990
28. Temporal and Spatial Patterns of XCO2 and SIF as Observed by OCO-2: A Case Study in the Midwest Region of Brazil G. de Araújo Santos et al. https://doi.org/10.1007/s12524-024-01995-y
29. Review and perspective of remote sensing research on global greenhouse gas monitoring and stocktaking L. Liu et al. https://doi.org/10.1360/TB-2024-1033
30. Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. https://doi.org/10.3390/rs14225635
31. A singular value decomposition framework for retrievals with vertical distribution information from greenhouse gas column absorption spectroscopy measurements A. Ramanathan et al. https://doi.org/10.5194/amt-11-4909-2018
32. Evaluation of Spatio-Temporal Variogram Models for Mapping Xco2Using Satellite Observations: A Case Study in China L. Guo et al. https://doi.org/10.1109/JSTARS.2014.2363019
33. Evaluation and attribution of OCO-2 XCO2 uncertainties J. Worden et al. https://doi.org/10.5194/amt-10-2759-2017
34. Water Stress Dominates 21st‐Century Tropical Land Carbon Uptake P. Levine et al. https://doi.org/10.1029/2023GB007702
35. Retrieving XCO2 from GOSAT FTS over East Asia Using Simultaneous Aerosol Information from CAI W. Kim et al. https://doi.org/10.3390/rs8120994
36. Drivers of atmospheric CO2 concentration in southeast Brazil: Insights from land use change, vegetation, and climate factors L. da Costa et al. https://doi.org/10.1016/j.rsase.2025.101614
37. Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm J. Heymann et al. https://doi.org/10.5194/amt-8-2961-2015
38. Statistical bias and variance for the regularized inverse problem: Application to space‐based atmospheric CO2 retrievals N. Cressie et al. https://doi.org/10.1002/2015JD024353
39. Comparing simulated atmospheric carbon dioxide concentration with GOSAT retrievals H. Zhang et al. https://doi.org/10.1007/s11434-014-0676-9
40. Retrievals of tropospheric ozone profiles from the synergism of AIRS and OMI: methodology and validation D. Fu et al. https://doi.org/10.5194/amt-11-5587-2018
41. XCO2 estimates from the OCO-2 measurements using a neural network approach L. David et al. https://doi.org/10.5194/amt-14-117-2021
42. An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil L. da Costa et al. https://doi.org/10.1186/s13021-022-00209-7
43. High-resolution GEOS-Chem model for Indian monsoon region: Seasonal cycle and budget of tropospheric CO2 S. Allahudheen et al. https://doi.org/10.1016/j.atmosenv.2023.119913
44. Toward anthropogenic combustion emission constraints from space‐based analysis of urban CO2/CO sensitivity S. Silva et al. https://doi.org/10.1002/grl.50954
45. Quantifying the model structural error in carbon cycle data assimilation systems S. Kuppel et al. https://doi.org/10.5194/gmd-6-45-2013
46. Performance of a geostationary mission, geoCARB, to measure CO2, CH4 and CO column-averaged concentrations I. Polonsky et al. https://doi.org/10.5194/amt-7-959-2014
47. The Wintertime Covariation of CO2 and Criteria Pollutants in an Urban Valley of the Western United States R. Bares et al. https://doi.org/10.1002/2017JD027917
48. Two-Year Comparison of Airborne Measurements of CO2 and CH4 With GOSAT at Railroad Valley, Nevada T. Tanaka et al. https://doi.org/10.1109/TGRS.2016.2539973
49. The status of carbon neutrality of the world's top 5 CO2 emitters as seen by carbon satellites F. Jiang et al. https://doi.org/10.1016/j.fmre.2022.02.001
50. Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO2 and chlorophyll fluorescence from GOSAT N. Parazoo et al. https://doi.org/10.1002/grl.50452
51. Neural-network-based estimation of regional-scale anthropogenic CO2 emissions using an Orbiting Carbon Observatory-2 (OCO-2) dataset over East and West Asia F. Mustafa et al. https://doi.org/10.5194/amt-14-7277-2021
52. Impact of Aerosol Property on the Accuracy of a CO2 Retrieval Algorithm from Satellite Remote Sensing Y. Jung et al. https://doi.org/10.3390/rs8040322
53. Emissions and topographic effects on column CO2 () variations, with a focus on the Southern California Megacity J. Hedelius et al. https://doi.org/10.1002/2017JD026455
54. OCO-2 Solar-Induced Chlorophyll Fluorescence Variability across Ecoregions of the Amazon Basin and the Extreme Drought Effects of El Niño (2015–2016) A. Castro et al. https://doi.org/10.3390/rs12071202
55. Spaceborne detection of XCO2 enhancement induced by Australian mega-bushfires J. Wang et al. https://doi.org/10.1088/1748-9326/abc846
56. Machine-learning reconstruction of high-resolution XCO2 over Thailand (2015–2024) using integrated satellite and environmental data U. Nacksriphod et al. https://doi.org/10.1016/j.atmosenv.2026.122214
57. Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data M. Inoue et al. https://doi.org/10.5194/amt-9-3491-2016
58. Mapping of satellite Earth observations using moving window block kriging J. Tadić et al. https://doi.org/10.5194/gmd-8-3311-2015
59. Water vapor isotopologue retrievals from high-resolution GOSAT shortwave infrared spectra C. Frankenberg et al. https://doi.org/10.5194/amt-6-263-2013
60. Validation of OCO-2 error analysis using simulated retrievals S. Kulawik et al. https://doi.org/10.5194/amt-12-5317-2019
61. La surveillance des émissions anthropiques de CO2 depuis l’espace : un enjeu géopolitique émergent G. Broquet & F. Chevallier https://doi.org/10.4000/12de3
62. Evaluating GPP and Respiration Estimates Over Northern Midlatitude Ecosystems Using Solar‐Induced Fluorescence and Atmospheric CO2 Measurements B. Byrne et al. https://doi.org/10.1029/2018JG004472
63. Retrieved XCO2 Accuracy Improvement by Reducing Aerosol-Induced Bias for China’s Future High-Precision Greenhouse Gases Monitoring Satellite Mission J. Ke et al. https://doi.org/10.3390/atmos13091384
64. Aerosol and cloud retrieval algorithm of TANSO-3/GOSAT-GW: theoretical basis and validations during the 2024 ASIA-AQ campaign using the TROPOMI observations as a testbed H. Lim et al. https://doi.org/10.1186/s40645-026-00820-z
65. Carbon monitoring system flux estimation and attribution: impact of ACOS-GOSAT XCO₂ sampling on the inference of terrestrial biospheric sources and sinks J. Liu et al. https://doi.org/10.3402/tellusb.v66.22486
66. Global Daily Atmospheric Methane Column Concentration Retrieval From TROPOMI Satellite Spectral Measurements by Two-Stage Machine Learning Algorithm Y. Bao et al. https://doi.org/10.1109/JSTARS.2026.3688284
67. Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. https://doi.org/10.1016/j.rse.2016.12.027
68. Carbon Dioxide Retrieval from TanSat Observations and Validation with TCCON Measurements S. Wang et al. https://doi.org/10.3390/rs12142204
69. Long-Term Vicarious Calibration of GOSAT Short-Wave Sensors: Techniques for Error Reduction and New Estimates of Radiometric Degradation Factors A. Kuze et al. https://doi.org/10.1109/TGRS.2013.2278696
70. Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A A. Sanders et al. https://doi.org/10.5194/amt-8-4947-2015
71. Measurements of Atmospheric CO2Column in Cloudy Weather Conditions using An IM-CW Lidar at 1.57 Micron B. Lin et al. https://doi.org/10.1051/epjconf/201611903002
72. Validation of TANSO-FTS/GOSAT XCO2 and XCH4 glint mode retrievals using TCCON data from near-ocean sites M. Zhou et al. https://doi.org/10.5194/amt-9-1415-2016
73. Substantial Discrepancies Across Global Satellite XCO2 Products: A Systematic Evaluation J. Yang et al. https://doi.org/10.3390/rs18020371
74. The Cross-Calibration of Spectral Radiances and Cross-Validation of CO2 Estimates from GOSAT and OCO-2 F. Kataoka et al. https://doi.org/10.3390/rs9111158
75. Spatiotemporal Investigation of Near-Surface CO2 and Its Affecting Factors Over Asia F. Mustafa et al. https://doi.org/10.1109/TGRS.2022.3178125
76. Semi-autonomous sounding selection for OCO-2 L. Mandrake et al. https://doi.org/10.5194/amt-6-2851-2013
77. Spatial distribution of atmospheric CO2 absorption detected around 2 µm on the reflectance spectra derived from Hyperion images B. Raychaudhuri https://doi.org/10.1080/01431161.2017.1295483
78. China's Terrestrial Carbon Sink Over 2010–2015 Constrained by Satellite Observations of Atmospheric CO2 and Land Surface Variables W. He et al. https://doi.org/10.1029/2021JG006644
79. Satellite Detection of Diffuse Tectonic CO2 Degassing in the East African Rift C. Flesia et al. https://doi.org/10.3390/rs18152586
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81. Quality controls, bias, and seasonality of CO2 columns in the boreal forest with Orbiting Carbon Observatory-2, Total Carbon Column Observing Network, and EM27/SUN measurements N. Jacobs et al. https://doi.org/10.5194/amt-13-5033-2020
82. Characterizing Regional-Scale Combustion Using Satellite Retrievals of CO, NO2 and CO2 S. Silva & A. Arellano https://doi.org/10.3390/rs9070744
83. Simulated retrievals for the remote sensing of CO2, CH4, CO, and H2O from geostationary orbit X. Xi et al. https://doi.org/10.5194/amt-8-4817-2015
84. A comparison of satellite observations with the XCO 2 surface obtained by fusing TCCON measurements and GEOS-Chem model outputs L. Zhang et al. https://doi.org/10.1016/j.scitotenv.2017.06.018
85. Multi-Year Comparison of CO2 Concentration from NOAA Carbon Tracker Reanalysis Model with Data from GOSAT and OCO-2 over Asia F. Mustafa et al. https://doi.org/10.3390/rs12152498
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88. The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations C. O'Dell et al. https://doi.org/10.5194/amt-5-99-2012
89. Simulations of column-averaged CO2 and CH4 using the NIES TM with a hybrid sigma-isentropic (σ-θ) vertical coordinate D. Belikov et al. https://doi.org/10.5194/acp-13-1713-2013
90. High-Resolution Geos-Chem Model for Indian Monsoon Region: Seasonal Cycle and Budget of Tropospheric Co2 S. Allahudheen et al. https://doi.org/10.2139/ssrn.4161842
91. Estimating bias in the OCO-2 retrieval algorithm caused by 3-D radiation scattering from unresolved boundary layer clouds A. Merrelli et al. https://doi.org/10.5194/amt-8-1641-2015
92. A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10 W. Keely et al. https://doi.org/10.5194/amt-16-5725-2023
93. Carbon dioxide spatial variability and dynamics for contrasting land uses in central Brazil agricultural frontier from remote sensing data F. Rossi et al. https://doi.org/10.1016/j.jsames.2022.103809
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102. Global height-resolved methane retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp R. Siddans et al. https://doi.org/10.5194/amt-10-4135-2017
103. Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON S. Kulawik et al. https://doi.org/10.5194/amt-9-683-2016
104. A joint effort to deliver satellite retrieved atmospheric CO2 concentrations for surface flux inversions: the ensemble median algorithm EMMA M. Reuter et al. https://doi.org/10.5194/acp-13-1771-2013
105. Drivers of column-average CO2 variability at Southern Hemispheric Total Carbon Column Observing Network sites N. Deutscher et al. https://doi.org/10.5194/acp-14-9883-2014
106. Optimizing 4 years of CO2 biospheric fluxes from OCO-2 and in situ data in TM5: fire emissions from GFED and inferred from MOPITT CO data H. Peiro et al. https://doi.org/10.5194/acp-22-15817-2022
107. Atmospheric Simulations of Total Column CO2 Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework M. Butler et al. https://doi.org/10.3390/atmos11080787
108. Modelling of XCO2 Surfaces Based on Flight Tests of TanSat Instruments L. Zhang et al. https://doi.org/10.3390/s16111818
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113. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020) J. Liu et al. https://doi.org/10.5194/essd-13-299-2021
114. Earth’s Climate History from 4.5 Billion Years to One Minute J. Lin & T. Qian https://doi.org/10.1080/07055900.2022.2082914
115. The Greenhouse Gas Climate Change Initiative (GHG-CCI): Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets M. Buchwitz et al. https://doi.org/10.1016/j.rse.2013.04.024
116. Toward High Precision XCO2Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements D. Yang et al. https://doi.org/10.1029/2020JD032794
117. Spatiotemporal variability of atmospheric CO2 concentration and controlling factors over sugarcane cultivation areas in southern Brazil L. da Costa et al. https://doi.org/10.1007/s10668-021-01677-6
118. Carbon Monitoring Satellite (CarbonSat): assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization M. Buchwitz et al. https://doi.org/10.5194/amt-6-3477-2013
119. Calibration, Level 1 Processing, and Radiometric Validation for TANSO-FTS TIR on GOSAT F. Kataoka et al. https://doi.org/10.1109/TGRS.2018.2885162
120. Satellite derived trends and variability of CO2 concentrations in the Middle East during 2014–2023 R. Fonseca & D. Francis https://doi.org/10.3389/fenvs.2023.1289142
121. Global monthly 0.1° land XCO2 data (2017–2024) estimated via multi-source fusion and spatiotemporal pattern integration H. Yu et al. https://doi.org/10.1088/2752-5295/ae6887
122. Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm C. O'Dell et al. https://doi.org/10.5194/amt-11-6539-2018
123. A novel transformer-based CO2 retrieval framework incorporating prior constraint and hierarchical features injection: assessment of transferability for Tansat-2 L. Zhang et al. https://doi.org/10.1016/j.isprsjprs.2026.01.039
124. Evaluating Anthropogenic CO2 Bottom-Up Emission Inventories Using Satellite Observations from GOSAT and OCO-2 S. Zhang et al. https://doi.org/10.3390/rs14195024
125. Combining XCO2 Measurements Derived from SCIAMACHY and GOSAT for Potentially Generating Global CO2 Maps with High Spatiotemporal Resolution T. Wang et al. https://doi.org/10.1371/journal.pone.0105050
126. Exploring correlation between OCO-2 XCO2 and DMSP/OLS nightlight imagery signature in four selected locations in India A. Matloob et al. https://doi.org/10.1007/s41324-021-00381-x
127. Impact of Amazonian Fires on Atmospheric CO2 X. Jiang et al. https://doi.org/10.1029/2020GL091875
128. Aerosols in OCO-2/GOSAT retrievals of XCO2: An information content and error analysis S. Sanghavi et al. https://doi.org/10.1016/j.rse.2020.112053
129. Note on rotational-Raman scattering in the O2 A- and B-bands A. Vasilkov et al. https://doi.org/10.5194/amt-6-981-2013
130. Effect of spectral resolution and signal-to-noise ratios on retrieval of XCO2 and XCH4 using an ultra-hyperspectral sensor R. Chipade et al. https://doi.org/10.1016/j.jqsrt.2026.110019
131. Congo Basin Rainforest Is a Net Carbon Source During the Dry Season X. Jiang et al. https://doi.org/10.1029/2022EA002644
132. Spatiotemporal pattern and driving factors of atmospheric CO2 concentrations based on satellite remote sensing from 2001 to 2022 in central Yunnan plateau Y. He et al. https://doi.org/10.1016/j.ecolind.2025.113371
133. Aerosol scattering effects on water vapor retrievals over the Los Angeles Basin Z. Zeng et al. https://doi.org/10.5194/acp-17-2495-2017
134. Tropospheric aerosol profile information from high-resolution oxygen A-band measurements from space A. Geddes & H. Bösch https://doi.org/10.5194/amt-8-859-2015
135. Study of mid-latitude retrieval XCO2 greenhouse gas: Validation of satellite-based shortwave infrared spectroscopy with ground-based TCCON observations S. Karbasi et al. https://doi.org/10.1016/j.scitotenv.2022.155513
136. A Top-Down Method for Estimating Regional Fossil Fuel Carbon Emissions Based on Satellite XCO2 Retrievals L. Zhang et al. https://doi.org/10.3390/rs17030447
137. Mapping CH4 : CO2 ratios in Los Angeles with CLARS-FTS from Mount Wilson, California K. Wong et al. https://doi.org/10.5194/acp-15-241-2015
138. Line parameters including temperature dependences of self- and air-broadened line shapes of 12C16O2: 1.6-μm region V. Devi et al. https://doi.org/10.1016/j.jqsrt.2015.12.020
139. On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases E. Malina et al. https://doi.org/10.5194/amt-15-2377-2022
140. Isolating Cabannes and rotational Raman scattering to determine forward modeling error due to Rayleigh scattering in the Earth’s atmosphere S. Sanghavi https://doi.org/10.1016/j.jqsrt.2026.110077
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142. Variability of fire carbon emissions in equatorial Asia and its nonlinear sensitivity to El Niño Y. Yin et al. https://doi.org/10.1002/2016GL070971
143. An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm T. Taylor et al. https://doi.org/10.5194/essd-14-325-2022
144. Refining Spatial and Temporal XCO2 Characteristics Observed by Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3 Using Sentinel-5P Tropospheric Monitoring Instrument NO2 Observations in China K. Guo et al. https://doi.org/10.3390/rs16132456
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146. The covariation of Northern Hemisphere summertime CO2 with surface temperature in boreal regions D. Wunch et al. https://doi.org/10.5194/acp-13-9447-2013
147. Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation O. Lamminpää et al. https://doi.org/10.5194/amt-18-673-2025
148. Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface‐Based and Space‐Based Atmospheric CO2 Measurements B. Byrne et al. https://doi.org/10.1029/2019JD032029
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