{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T01:05:22Z","timestamp":1776733522039,"version":"3.51.2"},"reference-count":69,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T00:00:00Z","timestamp":1627603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Key Research Program of Chinese Academy of Sciences","award":["ZDRW-ZS-2019-1"],"award-info":[{"award-number":["ZDRW-ZS-2019-1"]}]},{"name":"the International Partnership Program of Chinese Academy of Sciences","award":["131211KYSB20180002"],"award-info":[{"award-number":["131211KYSB20180002"]}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr\u22121) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr\u22121, standard deviation: 0.29 Pg C yr\u22121, 9 models in total) and CT2017 (1.19 Pg C yr\u22121). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m\u22122 d\u22121, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan\/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.<\/jats:p>","DOI":"10.3390\/rs13152996","type":"journal-article","created":{"date-parts":[[2021,8,1]],"date-time":"2021-08-01T21:44:32Z","timestamp":1627854272000},"page":"2996","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem\/DART from OCO-2 XCO2 Retrievals"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8813-9677","authenticated-orcid":false,"given":"Qinwei","family":"Zhang","sequence":"first","affiliation":[{"name":"Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2412-9477","authenticated-orcid":false,"given":"Mingqi","family":"Li","sequence":"additional","affiliation":[{"name":"Research Center of Wireless Technologies for New Media, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maohua","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arthur","family":"Mizzi","sequence":"additional","affiliation":[{"name":"National Center for Atmospheric Research, Boulder, CO 80305, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3383-7328","authenticated-orcid":false,"given":"Yongjian","family":"Huang","sequence":"additional","affiliation":[{"name":"Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0632-4324","authenticated-orcid":false,"given":"Chong","family":"Wei","sequence":"additional","affiliation":[{"name":"Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiuping","family":"Jin","sequence":"additional","affiliation":[{"name":"Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianrong","family":"Gu","sequence":"additional","affiliation":[{"name":"Shanghai Carbon Data Research Center, Key Laboratory of Low-Carbon Conversion Science & Engineering, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,30]]},"reference":[{"key":"ref_1","unstructured":"IPCC (2014). Climate Change 2014: Synthesis Report, IPCC."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3269","DOI":"10.5194\/essd-12-3269-2020","article-title":"Global Carbon Budget 2020","volume":"12","author":"Friedlingstein","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_3","unstructured":"UNFCCC (2021, June 08). The Paris Agreement. Available online: http:\/\/unfccc.int\/files\/essential_background\/convention\/application\/pdf\/english_paris_agreement.pdf."},{"key":"ref_4","unstructured":"IPCC (2021, July 29). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Available online: https:\/\/www.ipcc.ch\/report\/2019-refinement-to-the-2006-ipcc-guidelines-for-national-greenhouse-gas-inventories\/."},{"key":"ref_5","unstructured":"UNFCCC-SBSTA (2021, July 20). Subsidiary Body for Scientific and Technological Advice. Available online: https:\/\/unfccc.int\/resource\/docs\/2017\/sbsta\/eng\/07.pdf."},{"key":"ref_6","unstructured":"UNFCCC (2021, July 20). INFORMATION PAPER Systematic Observations. Available online: https:\/\/unfccc.int\/sites\/default\/files\/resource\/Mandates_systematic_%20observation.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Broquet, G., Chevallier, F., Rayner, P., Aulagnier, C., Pison, I., Ramonet, M., Schmidt, M., Vermeulen, A.T., and Ciais, P. (2011). A European summertime CO2 biogenic flux inversion at mesoscale from continuous in situ mixing ratio measurements. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2011JD016202"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9039","DOI":"10.5194\/acp-13-9039-2013","article-title":"Regional inversion of CO2 ecosystem fluxes from atmospheric measurements: Reliability of the uncertainty estimates","volume":"13","author":"Broquet","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Peters, W., Miller, J.B., Whitaker, J., Denning, A.S., Hirsch, A., Krol, M.C., Zupanski, D., Bruhwiler, L., and Tans, P.P. (2005). An ensemble data assimilation system to estimate CO2 surface fluxes from atmospheric trace gas observations. J. Geophys. Res.-Atmos., 110.","DOI":"10.1029\/2005JD006157"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"18925","DOI":"10.1073\/pnas.0708986104","article-title":"An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker","volume":"104","author":"Peters","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6699","DOI":"10.5194\/bg-10-6699-2013","article-title":"Global atmospheric carbon budget: Results from an ensemble of atmospheric CO2 inversions","volume":"10","author":"Peylin","year":"2013","journal-title":"Biogeosciences"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10724","DOI":"10.1038\/ncomms10724","article-title":"Top-down assessment of the Asian carbon budget since the mid 1990s","volume":"7","author":"Thompson","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6716","DOI":"10.1364\/AO.48.006716","article-title":"Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring","volume":"48","author":"Kuze","year":"2009","journal-title":"Appl. Opt."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Glumb, R., Davis, G., and Lietzke, C. (2014, January 13\u201318). The TANSO-FTS-2 instrument for the GOSAT-2 greenhouse gas monitoring mission. Proceedings of the IGARSS 2014-2014 IEEE International Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6946656"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Eldering, A., Wennberg, P.O., Crisp, D., Schimel, D.S., Gunson, M.R., Chatterjee, A., Liu, J., Schwandner, F.M., Sun, Y., and O\u2019Dell, C.W. (2017). The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes. Science, 358.","DOI":"10.1126\/science.aam5745"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.5194\/amt-12-2341-2019","article-title":"The OCO-3 mission: Measurement objectives and expected performance based on 1 year of simulated data","volume":"12","author":"Eldering","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Taylor, T.E., Eldering, A., Merrelli, A., Kiel, M., Somkuti, P., Cheng, C., Rosenberg, R., Fisher, B., Crisp, D., and Basilio, R. (2020). OCO-3 early mission operations and initial (vEarly) XCO2 and SIF retrievals. Remote. Sens. Environ., 251.","DOI":"10.1016\/j.rse.2020.112032"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1016\/j.scib.2018.08.004","article-title":"The TanSat mission: Preliminary global observations","volume":"63","author":"Liu","year":"2018","journal-title":"Sci. Bull."},{"key":"ref_19","unstructured":"Karafolas, N., Sodnik, Z., Cugny, B., Buisson, F., Jouglet, D., Tauziede, L., Loesel, J., Buil, C., and Pascal, V. (2017, January 17). An improved microcarb dispersive instrumental concept for the measurement of greenhouse gases concentration in the atmosphere. Proceedings of the International Conference on Space Optics\u2014ICSO 2014, Tenerife, Spain."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3329","DOI":"10.5194\/amt-13-3329-2020","article-title":"The use of the 1.27\u2009\u00b5m O2 absorption band for greenhouse gas monitoring from space and application to MicroCarb","volume":"13","author":"Bertaux","year":"2020","journal-title":"Atmos. Meas. Tech."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"959","DOI":"10.5194\/amt-7-959-2014","article-title":"Performance of a geostationary mission, geoCARB, to measure CO2, CH4 and CO column-averaged concentrations","volume":"7","author":"Polonsky","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Moore, B., Crowell, S.M.R., Rayner, P.J., Kumer, J., O\u2019Dell, C.W., O\u2019Brien, D., Utembe, S., Polonsky, I., Schimel, D., and Lemen, J. (2018). The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas. Front. Environ. Sci., 6.","DOI":"10.3389\/fenvs.2018.00109"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6695","DOI":"10.5194\/amt-12-6695-2019","article-title":"Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission","volume":"12","author":"Kuhlmann","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"E1439","DOI":"10.1175\/BAMS-D-19-0017.1","article-title":"Toward an Operational Anthropogenic CO2 Emissions Monitoring and Verification Support Capacity","volume":"101","author":"Pinty","year":"2020","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"8695","DOI":"10.5194\/acp-13-8695-2013","article-title":"Global CO2 fluxes estimated from GOSAT retrievals of total column CO2","volume":"13","author":"Basu","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5253","DOI":"10.1002\/2014JD022962","article-title":"An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements","volume":"120","author":"Houweling","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"9351","DOI":"10.5194\/acp-13-9351-2013","article-title":"Regional CO2 flux estimates for 2009\u20132010 based on GOSAT and ground-based CO2 observations","volume":"13","author":"Maksyutov","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3703","DOI":"10.5194\/acp-14-3703-2014","article-title":"Inferring regional sources and sinks of atmospheric CO2 from GOSAT XCO2 data","volume":"14","author":"Deng","year":"2014","journal-title":"Atmos. Chem. Phys."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"13,066","DOI":"10.1002\/2016JD025100","article-title":"Comparison between the Local Ensemble Transform Kalman Filter (LETKF) and 4D-Var in atmospheric CO2 flux inversion with the Goddard Earth Observing System-Chem model and the observation impact diagnostics from the LETKF","volume":"121","author":"Liu","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1002\/2013GL058772","article-title":"Toward robust and consistent regional CO2 flux estimates from in situ and spaceborne measurements of atmospheric CO2","volume":"41","author":"Chevallier","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1896","DOI":"10.1002\/2015JD024157","article-title":"Combining GOSAT XCO2 observations over land and ocean to improve regional CO2 flux estimates","volume":"121","author":"Deng","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"9797","DOI":"10.5194\/acp-19-9797-2019","article-title":"The 2015\u20132016 carbon cycle as seen from OCO-2 and the global in situ network","volume":"19","author":"Crowell","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"14233","DOI":"10.5194\/acp-19-14233-2019","article-title":"Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions","volume":"19","author":"Chevallier","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"12067","DOI":"10.5194\/acp-19-12067-2019","article-title":"Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals","volume":"19","author":"Wang","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"8473","DOI":"10.5194\/acp-20-8473-2020","article-title":"The potential of Orbiting Carbon Observatory-2 data to reduce the uncertainties in CO2 surface fluxes over Australia using a variational assimilation scheme","volume":"20","author":"Villalobos","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.5194\/gmd-11-1725-2018","article-title":"Development of the WRF-CO2 4D-Var assimilation system v1.0","volume":"11","author":"Zheng","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.5194\/acp-15-1087-2015","article-title":"A regional carbon data assimilation system and its preliminary evaluation in East Asia","volume":"15","author":"Peng","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"118106","DOI":"10.1016\/j.atmosenv.2020.118106","article-title":"Assimilation of OCO-2 retrievals with WRF-Chem\/DART: A case study for the Midwestern United States","volume":"246","author":"Zhang","year":"2021","journal-title":"Atmos. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"6957","DOI":"10.1016\/j.atmosenv.2005.04.027","article-title":"Fully coupled \u201conline\u201d chemistry within the WRF model","volume":"39","author":"Grell","year":"2005","journal-title":"Atmos. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.1175\/2009BAMS2618.1","article-title":"The Data Assimilation Research Testbed A Community Facility","volume":"90","author":"Anderson","year":"2009","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2884","DOI":"10.1175\/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2","article-title":"An ensemble adjustment Kalman filter for data assimilation","volume":"129","author":"Anderson","year":"2001","journal-title":"Mon. Weather Rev."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1175\/1520-0493(2003)131<0634:ALLSFF>2.0.CO;2","article-title":"A Local Least Squares Framework for Ensemble Filtering","volume":"131","author":"Anderson","year":"2003","journal-title":"Mon. Weather Rev."},{"key":"ref_43","unstructured":"NCEP (2021, July 29). NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. Available online: https:\/\/data.ucar.edu\/dataset\/ncep-fnl-operational-model-global-tropospheric-analyses-continuing-from-july-19993."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"549","DOI":"10.5194\/amt-10-549-2017","article-title":"The Orbiting Carbon Observatory-2: First 18 months of science data products","volume":"10","author":"Eldering","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"59","DOI":"10.5194\/amt-10-59-2017","article-title":"The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products","volume":"10","author":"Crisp","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_46","unstructured":"Osterman, G., Eldering, A., Avis, C., Chafin, B., O\u2019Dell, C., Frankenberg, C., Fisher, B., Mandrake, L., Wunch, D., and Granat, R. (2021, June 08). Orbiting Carbon Observatory\u20132 (OCO-2) Data Product User\u2019s Guide, Operational L1 and L2 Data Versions 8 and Lite File Version 9, Version 1, Revision J., October 10, 2018, Available online: https:\/\/docserver.gesdisc.eosdis.nasa.gov\/public\/project\/OCO\/OCO2_DUG.V9.pdf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2209","DOI":"10.5194\/amt-10-2209-2017","article-title":"Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2 measurements with TCCON","volume":"10","author":"Wunch","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_48","unstructured":"OCO-2 Science Team\/Michael Gunson, and Eldering, A. (2021, July 29). OCO-2 Level 2 Bias-Corrected XCO2 and Other Select Fields from the Full-Physics Retrieval Aggregated as Daily Files, Retrospective Processing V9r, Available online: https:\/\/disc.gsfc.nasa.gov\/datasets\/OCO2_L2_Lite_FP_9r\/summary."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.5194\/amt-12-2241-2019","article-title":"How bias correction goes wrong: Measurement of XCO2 affected by erroneous surface pressure estimates","volume":"12","author":"Kiel","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Connor, B.J., Boesch, H., Toon, G., Sen, B., Miller, C., and Crisp, D. (2008). Orbiting Carbon Observatory: Inverse method and prospective error analysis. J. Geophys. Res. Atmos., 113.","DOI":"10.1029\/2006JD008336"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"7393","DOI":"10.1029\/2019JD030421","article-title":"Multiconstituent Data Assimilation with WRF-Chem\/DART: Potential for Adjusting Anthropogenic Emissions and Improving Air Quality Forecasts Over Eastern China","volume":"124","author":"Ma","year":"2019","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3727","DOI":"10.5194\/gmd-11-3727-2018","article-title":"Assimilating compact phase space retrievals (CPSRs): Comparison with independent observations (MOZAIC in situ and IASI retrievals) and extension to assimilation of truncated retrieval profiles","volume":"11","author":"Mizzi","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"7067","DOI":"10.5194\/acp-17-7067-2017","article-title":"Assimilation of satellite NO2 observations at high spatial resolution using OSSEs","volume":"17","author":"Liu","year":"2017","journal-title":"Atmos. Chem. Phys."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"965","DOI":"10.5194\/gmd-9-965-2016","article-title":"Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem\/DART: A regional chemical transport\/ensemble Kalman filter data assimilation system","volume":"9","author":"Mizzi","year":"2016","journal-title":"Geosci. Model Dev."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Kang, J.-S., Kalnay, E., Liu, J., Fung, I., Miyoshi, T., and Ide, K. (2011). \u201cVariable localization\u201d in an ensemble Kalman filter: Application to the carbon cycle data assimilation. J. Geophys. Res., 116.","DOI":"10.1029\/2010JD014673"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Kang, J.-S., Kalnay, E., Miyoshi, T., Liu, J., and Fung, I. (2012). Estimation of surface carbon fluxes with an advanced data assimilation methodology. J. Geophys. Res. Atmos., 117.","DOI":"10.1029\/2012JD018259"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1002\/qj.49712555417","article-title":"Construction of correlation functions in two and three dimensions","volume":"125","author":"Gaspari","year":"1999","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2899","DOI":"10.5194\/gmd-12-2899-2019","article-title":"Estimating surface carbon fluxes based on a local ensemble transform Kalman filter with a short assimilation window and a long observation window: An observing system simulation experiment test in GEOS-Chem 10.1","volume":"12","author":"Liu","year":"2019","journal-title":"Geosci. Model Dev."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/j.agrformet.2017.10.009","article-title":"The AmeriFlux network: A coalition of the willing","volume":"249","author":"Novick","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1038\/s41597-020-0534-3","article-title":"The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data","volume":"7","author":"Pastorello","year":"2020","journal-title":"Sci. Data"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2087","DOI":"10.1098\/rsta.2010.0240","article-title":"The total carbon column observing network","volume":"369","author":"Wunch","year":"2011","journal-title":"Philos. Trans. R. Soc. A"},{"key":"ref_62","unstructured":"Wennberg, P.O., Roehl, C.M., Wunch, D., Toon, G.C., Blavier, J.-F., Washenfelder, R., Keppel-Aleks, G., Allen, N.T., and Ayers, J. (2021, July 29). TCCON data from Park Falls (US); Release GGG2014.R1; 2017. Available online: https:\/\/data.caltech.edu\/records\/295."},{"key":"ref_63","unstructured":"Wennberg, P.O., Wunch, D., Roehl, C.M., Blavier, J.-F., Toon, G.C., and Allen, N.T. (2021, July 29). TCCON Data from Lamont (US); Release GGG2014.R1; 2016. Available online: https:\/\/data.caltech.edu\/records\/279."},{"key":"ref_64","unstructured":"Iraci, L.T., Podolske, J.R., Hillyard, P.W., Roehl, C., Wennberg, P.O., Blavier, J.-F., Landeros, J., Allen, N., Wunch, D., and Zavaleta, J. (2021, July 29). TCCON Data from Edwards (US); Release GGG2014.R1; 2016. Available online: https:\/\/data.caltech.edu\/records\/270."},{"key":"ref_65","unstructured":"Wennberg, P.O., Wunch, D., Roehl, C.M., Blavier, J.-F., Toon, G.C., and Allen, N.T. (2021, July 29). TCCON Data from Caltech (US); Release GGG2014.R1; 2015. Available online: https:\/\/data.caltech.edu\/records\/285."},{"key":"ref_66","unstructured":"Cooperative Global Atmospheric Data Integration Project (2021, July 29). Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957\u20132018, Available online: https:\/\/gml.noaa.gov\/ccgg\/obspack\/providerlist\/obspack_co2_1_GLOBALVIEWplus_v4.2_2019-03-19.html."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"375","DOI":"10.5194\/essd-6-375-2014","article-title":"ObsPack: A framework for the preparation, delivery, and attribution of atmospheric greenhouse gas measurements","volume":"6","author":"Masarie","year":"2014","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Chevallier, F., Br\u00e9on, F.-M., and Rayner, P.J. (2007). Contribution of the Orbiting Carbon Observatory to the estimation of CO2 sources and sinks: Theoretical study in a variational data assimilation framework. J. Geophys. Res., 112.","DOI":"10.1029\/2006JD007375"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"337","DOI":"10.5194\/acp-12-337-2012","article-title":"Constraining the CO2 budget of the corn belt: Exploring uncertainties from the assumptions in a mesoscale inverse system","volume":"12","author":"Lauvaux","year":"2012","journal-title":"Atmos. Chem. Phys."}],"updated-by":[{"DOI":"10.3390\/rs14061397","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T00:00:00Z","timestamp":1627603200000}}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/15\/2996\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T22:33:54Z","timestamp":1754260434000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/15\/2996"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,30]]},"references-count":69,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13152996"],"URL":"https:\/\/doi.org\/10.3390\/rs13152996","relation":{"correction":[{"id-type":"doi","id":"10.3390\/rs14061397","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,30]]}}}