124 citations as recorded by crossref.

1. Technical Note: Comparison of ensemble Kalman filter and variational approaches for CO2 data assimilation A. Chatterjee & A. Michalak 10.5194/acp-13-11643-2013
2. Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate L. Feng et al. 10.1038/s41467-022-28989-z
3. Towards the Optimization of TanSat-2: Assessment of a Large-Swath Methane Measurement S. Zhu et al. 10.3390/rs17030543
4. Large Chinese land carbon sink estimated from atmospheric carbon dioxide data J. Wang et al. 10.1038/s41586-020-2849-9
5. The effect of optimization and the nesting domain on carbon flux analyses in Asia using a carbon tracking system based on the ensemble Kalman filter J. Kim et al. 10.1007/s13143-014-0020-y
6. Does GOSAT capture the true seasonal cycle of carbon dioxide? H. Lindqvist et al. 10.5194/acp-15-13023-2015
7. Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm C. O'Dell et al. 10.5194/amt-11-6539-2018
8. Application of Ensemble Kalman Smoothing in Inverse Modeling of Advection and Diffusion E. Klimova 10.1134/S1995423924030030
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10. Impact of Prior Terrestrial Carbon Fluxes on Simulations of Atmospheric CO2 Concentrations Y. Fu et al. 10.1029/2021JD034794
11. A regional CO2 observing system simulation experiment for the ASCENDS satellite mission J. Wang et al. 10.5194/acp-14-12897-2014
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14. Inverse Modeling of CO₂ Fluxes Using GOSAT Data and Multi-Year Ground-Based Observations T. Saeki et al. 10.2151/sola.2013-011
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16. On the parallelization of atmospheric inversions of CO2 surface fluxes within a variational framework F. Chevallier 10.5194/gmd-6-783-2013
17. An algorithm for estimating greenhouse gas fluxes using satellite data for a global transport and diffusion model M. Platonova & E. Klimova 10.1088/1742-6596/1715/1/012021
18. A Comparison of the Atmospheric CO2Concentrations Obtained by an Inverse Modeling System and Passenger Aircraft Based Measurement H. Kim et al. 10.14191/Atmos.2016.26.3.387
19. Scattering properties of the heterogeneous and non-spherical haze particles in the SWIR band M. Fan et al. 10.1088/1755-1315/17/1/012024
20. Application of the ensemble Kalman filter to environmental data assimilation E. Klimova 10.1088/1755-1315/211/1/012049
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24. Global inverse modeling of CH4 sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
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26. How bias correction goes wrong: measurement of XCO2 affected by erroneous surface pressure estimates M. Kiel et al. 10.5194/amt-12-2241-2019
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28. Global Carbon Budget 2022 P. Friedlingstein et al. 10.5194/essd-14-4811-2022
29. The Significance of Fast Radiative Transfer for Hyperspectral SWIR XCO2 Retrievals P. Somkuti et al. 10.3390/atmos11111219
30. Estimates of European uptake of CO2 inferred from GOSAT XCO2 retrievals: sensitivity to measurement bias inside and outside Europe L. Feng et al. 10.5194/acp-16-1289-2016
31. Global Carbon Budget 2023 P. Friedlingstein et al. 10.5194/essd-15-5301-2023
32. Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics Z. Zeng et al. 10.1080/17538947.2016.1156777
33. Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design T. Kaminski & P. Rayner 10.5194/bg-14-4755-2017
34. Real-data assimilation experiment with a joint data assimilation system: assimilating carbon dioxide mole fraction measurements from the Greenhouse gases Observing Satellite R. Han et al. 10.1080/16742834.2016.1133070
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36. An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm T. Taylor et al. 10.5194/essd-14-325-2022
37. TanSat Mission Achievements: from Scientific Driving to Preliminary Observations Y. LIU et al. 10.11728/cjss2018.05.627
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39. Assimilation of POLDER observations to estimate aerosol emissions A. Tsikerdekis et al. 10.5194/acp-23-9495-2023
40. Observed and simulated features of the CO2 diurnal cycle in the boundary layer at Beijing and Hefei, China Y. Wang et al. 10.1007/s11434-014-0194-9
41. Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission H. Boesch et al. 10.3390/rs3020270
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44. Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal P. Palmer et al. 10.1038/s41467-019-11097-w
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48. Estimation of Surface Methane Concentration based on the Ensemble Kalman Filter Algorithm using a Transport Chemical Model M. Platonova et al. 10.25205/1818-7900-2024-22-1-62-72
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50. Measurement of atmospheric CO2 column concentrations to cloud tops with a pulsed multi-wavelength airborne lidar J. Mao et al. 10.5194/amt-11-127-2018
51. The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements D. Yang et al. 10.1007/s00376-021-1179-7
52. The Chinese carbon cycle data-assimilation system (Tan-Tracker) X. Tian et al. 10.1007/s11434-014-0238-1
53. Quantifying the benefit of A-SCOPE data for reducing uncertainties in terrestrial carbon fluxes in CCDAS T. Kaminski et al. 10.1111/j.1600-0889.2010.00483.x
54. Retrievals of atmospheric CO_2 from simulated space-borne measurements of backscattered near-infrared sunlight: accounting for aerosol effects A. Butz et al. 10.1364/AO.48.003322
55. Quantification of regional net CO2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements J. Yun et al. 10.5194/acp-25-1725-2025
56. Influence of CO2 observations on the optimized CO2 flux in an ensemble Kalman filter J. Kim et al. 10.5194/acp-14-13515-2014
57. Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01 J. Thanwerdas et al. 10.5194/gmd-18-1505-2025
58. Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm T. Taylor et al. 10.5194/amt-16-3173-2023
59. Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign J. Mao et al. 10.5194/amt-17-1061-2024
60. Atmospheric data support a multi-decadal shift in the global methane budget towards natural tropical emissions A. Drinkwater et al. 10.5194/acp-23-8429-2023
61. A regional carbon data assimilation system and its preliminary evaluation in East Asia Z. Peng et al. 10.5194/acp-15-1087-2015
62. Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System F. Jiang et al. 10.5194/acp-21-1963-2021
63. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. 10.5194/acp-19-13911-2019
64. Consistent regional fluxes of CH4 and CO2 inferred from GOSAT proxy XCH4 : XCO2 retrievals, 2010–2014 L. Feng et al. 10.5194/acp-17-4781-2017
65. Estimating Aerosol Emissions by Assimilating Remote Sensing Observations into a Global Transport Model N. Schutgens et al. 10.3390/rs4113528
66. Assessing the potential and utilization of solar energy at the building-scale in Shanghai Z. Chen et al. 10.1016/j.scs.2022.103917
67. A new space-borne perspective of crop productivity variations over the US Corn Belt P. Somkuti et al. 10.1016/j.agrformet.2019.107826
68. Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance T. Kaminski et al. 10.5194/tc-12-2569-2018
69. Estimation of global CO2 fluxes using ground-based and satellite (GOSAT) observation data with empirical orthogonal functions R. Zhuravlev et al. 10.1134/S1024856013060158
70. Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs) A. Tsikerdekis et al. 10.5194/gmd-15-3253-2022
71. Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
72. Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. 10.5194/amt-16-581-2023
73. Issues in the assimilation of the sources of a trace gas by inverse modelling R. Bannister 10.1016/j.compfluid.2010.11.017
74. Characterization of Tropospheric Emission Spectrometer (TES) CO2 for carbon cycle science S. Kulawik et al. 10.5194/acp-10-5601-2010
75. WOMBAT v1.0: a fully Bayesian global flux-inversion framework A. Zammit-Mangion et al. 10.5194/gmd-15-45-2022
76. Potential improvements in global carbon flux estimates from a network of laser heterodyne radiometer measurements of column carbon dioxide P. Palmer et al. 10.5194/amt-12-2579-2019
77. China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
78. Evaluating a 3-D transport model of atmospheric CO2 using ground-based, aircraft, and space-borne data L. Feng et al. 10.5194/acp-11-2789-2011
79. Integration of surface-based and space-based atmospheric CO2 measurements for improving carbon flux estimates using a new developed 3-GAS inversion model S. Liu et al. 10.1016/j.atmosres.2024.107477
80. CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations Z. Peng et al. 10.1029/2022JD037154
81. ECONOMIC ALGORITHM FOR EVALUATING THE PARAMETER FOR THE GLOBAL MODEL OF TRANSFER AND DIFFUSION M. Platonova & E. Klimova 10.33764/2618-981X-2020-4-1-123-128
82. A comparison of CO2 emissions from the national greenhouse gases inventory report with CO2 emissions from the global inverse models and the regional WRF-Chem in the Korean Peninsula Y. Cho et al. 10.1007/s11027-024-10195-5
83. Greenhouse gas column observations from a portable spectrometer in Uganda N. Humpage et al. 10.5194/amt-17-5679-2024
84. Source‐receptor relationships of column‐average CO2 and implications for the impact of observations on flux inversions J. Liu et al. 10.1002/2014JD022914
85. Mission CO2ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide N. Cressie 10.1080/01621459.2017.1419136
86. Errors and uncertainties in a gridded carbon dioxide emissions inventory T. Oda et al. 10.1007/s11027-019-09877-2
87. An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019 C. Wu et al. 10.1016/j.accre.2023.01.001
88. Evaluating the Ability of the Pre-Launch TanSat-2 Satellite to Quantify Urban CO2 Emissions K. Wu et al. 10.3390/rs15204904
89. TransCom satellite intercomparison experiment: Construction of a bias corrected atmospheric CO2climatology R. Saito et al. 10.1029/2011JD016033
90. Surface fluxes of bromoform and dibromomethane over the tropical western Pacific inferred from airborne in situ measurements L. Feng et al. 10.5194/acp-18-14787-2018
91. Global and regional carbon budget for 2015–2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem Y. Kong et al. 10.5194/acp-22-10769-2022
92. Interpreting seasonal changes of low-tropospheric CO 2 over China based on SCIAMACHY observations during 2003–2011 W. Xi et al. 10.1016/j.atmosenv.2014.12.053
93. Modeling global atmospheric CO2 with improved emission inventories and CO2 production from the oxidation of other carbon species R. Nassar et al. 10.5194/gmd-3-689-2010
94. Application of Carbon Tracking System based on Ensemble Kalman Filter on the Diagnosis of Carbon Cycle in Asia J. Kim et al. 10.14191/Atmos.2012.22.4.415
95. The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS) X. Kou et al. 10.5194/acp-23-6719-2023
96. A remote sensing technique for global monitoring of power plant CO2emissions from space and related applications H. Bovensmann et al. 10.5194/amt-3-781-2010
97. The Temporal and Spatial Distributions of the Near-Surface CO2 Concentrations in Central Asia and Analysis of Their Controlling Factors L. Cao et al. 10.3390/atmos8050085
98. An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements S. Houweling et al. 10.1002/2014JD022962
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100. Error correlation between CO2 and CO as constraint for CO2 flux inversions using satellite data H. Wang et al. 10.5194/acp-9-7313-2009
101. Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements A. Fraser et al. 10.5194/acp-13-5697-2013
102. Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions Z. Deng et al. 10.5194/essd-14-1639-2022
103. A Cluster of CO2 Change Characteristics with GOSAT Observations for Viewing the Spatial Pattern of CO2 Emission and Absorption D. Liu et al. 10.3390/atmos6111695
104. Country-scale greenhouse gas budgets using shipborne measurements: a case study for the UK and Ireland C. Helfter et al. 10.5194/acp-19-3043-2019
105. Numerical experiments with real data for estimating greenhouse gas fluxes in a region M. Platonova & E. Klimova 10.33764/2618-981X-2022-4-132-137
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109. Verifying national inventory-based combustion emissions of CO2 across the UK and mainland Europe using satellite observations of atmospheric CO and CO2 T. Scarpelli et al. 10.5194/acp-24-10773-2024
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118. Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia H. Kim et al. 10.1007/s13143-017-0049-9
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