Articles | Volume 26, issue 10
https://doi.org/10.5194/acp-26-6869-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-6869-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Top-down estimate of regional carbon sinks over East Asia for 2010–2019 using satellite observations
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
Jingi Jung
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
Sang-Ik Oh
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
Eunjo S. Ha
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
Jaein I. Jeong
School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
Sang-Wook Yeh
Department of Climate and Energy Systems Engineering, Ewha Womans University, Seoul, Republic of Korea
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Fei Yao, Paul I. Palmer, Xiaolin Wang, Yi Wang, Gitaek T. Lee, Haolin Wang, Liang Feng, Daven K. Henze, and Rokjin J. Park
EGUsphere, https://doi.org/10.5194/egusphere-2026-1499, https://doi.org/10.5194/egusphere-2026-1499, 2026
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We assess the added value of GEMS geostationary satellite observations of tropospheric NO2 to constrain NOx emission estimates and subsequent air quality modelling over a full annual cycle across Asia. We observe a clear seasonal divide, with significant benefits outside summer while limited or even detrimental impacts during summer. Our findings clarify when and how high frequency geostationary data can be most effectively used to improve our understanding of atmospheric composition.
Yun-Soo Na, Sang-Wook Yeh, and Jong-Seong Kug
EGUsphere, https://doi.org/10.5194/egusphere-2026-353, https://doi.org/10.5194/egusphere-2026-353, 2026
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Terrestrial ecosystems in East Asia play a significant role in carbon dioxide uptake, but their response remains uncertain. We demonstrate that ecosystem productivity sensitivity to carbon dioxide has weakened since the late 1990s. This reduction is mainly driven by soil moisture sensitivity in non-monsoon region and decreased photosynthetically active radiation in monsoon region, emphasizing the need to consider regional climate and vegetation differences when predicting future carbon cycles.
Yong-Cheol Jeong, Yuxuan Wang, Wei Li, Hyeonmin Kim, Rokjin J. Park, and Mahmoudreza Momeni
Atmos. Chem. Phys., 25, 15507–15525, https://doi.org/10.5194/acp-25-15507-2025, https://doi.org/10.5194/acp-25-15507-2025, 2025
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Isoprene, which is emitted from the vegetation, is important to regional air quality. Drought is one of the most important meteorological events that can modulate isoprene emissions by high temperature and low soil moisture. The drought stress impact on isoprene emissions is still uncertain, and we aimed to constrain it in South Korea using observation and model simulation. The results presented in this study may give useful information for future studies on drought stress on isoprene emissions.
Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
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Tropical ocean basins influence each other through multiple pathways and mechanisms, referred to here as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models but have obtained conflicting results. This may be partly due to differences in experiment protocols and partly due to systematic model errors. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, Gitaek T. Lee, Sieun D. Lee, Seunga Shin, Dong-Won Lee, Hyunkee Hong, Christophe Lerot, Isabelle De Smedt, Thomas Danckaert, Francois Hendrick, and Hitoshi Irie
Atmos. Meas. Tech., 17, 6369–6384, https://doi.org/10.5194/amt-17-6369-2024, https://doi.org/10.5194/amt-17-6369-2024, 2024
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In this study, we evaluated the GEMS glyoxal products by comparing them with TROPOMI and MAX-DOAS measurements. GEMS and TROPOMI VCDs present similar spatial distributions. Monthly variations in GEMS VCDs and TROPOMI and MAX-DOAS VCDs differ in northeastern Asia, which we attributed to a polluted reference spectrum and high NO2 concentrations. GEMS glyoxal products with unparalleled temporal resolution would enrich our understanding of VOC emissions and diurnal variation.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Gitaek T. Lee, Rokjin J. Park, Hyeong-Ahn Kwon, Eunjo S. Ha, Sieun D. Lee, Seunga Shin, Myoung-Hwan Ahn, Mina Kang, Yong-Sang Choi, Gyuyeon Kim, Dong-Won Lee, Deok-Rae Kim, Hyunkee Hong, Bavo Langerock, Corinne Vigouroux, Christophe Lerot, Francois Hendrick, Gaia Pinardi, Isabelle De Smedt, Michel Van Roozendael, Pucai Wang, Heesung Chong, Yeseul Cho, and Jhoon Kim
Atmos. Chem. Phys., 24, 4733–4749, https://doi.org/10.5194/acp-24-4733-2024, https://doi.org/10.5194/acp-24-4733-2024, 2024
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This study evaluates the Geostationary Environment Monitoring Spectrometer (GEMS) HCHO product by comparing its vertical column densities (VCDs) with those of TROPOMI and ground-based observations. Based on some sensitivity tests, obtaining radiance references under clear-sky conditions significantly improves HCHO retrieval quality. GEMS HCHO VCDs captured seasonal and diurnal variations well during the first year of observation, showing consistency with TROPOMI and ground-based observations.
Seungmok Paik, Seung-Ki Min, Seok-Woo Son, Soon-Il An, Jong-Seong Kug, and Sang-Wook Yeh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-187, https://doi.org/10.5194/acp-2022-187, 2022
Revised manuscript not accepted
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This paper investigates Earth’s surface climate response to volcanic eruptions at different latitudes. By analyzing last millennium ensemble simulations of a coupled climate model, we have identified physical processes associated with the diverse impacts of volcanic eruption latitudes, focusing on the tropical ocean surface warming and the stratospheric polar vortex intensification. Our results provide important global implications for atmospheric responses to future volcanic aerosols.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Cited articles
Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P., Denning, A. S., Bousquet, P., Bruhwiler, L., Chen, Y. H., Ciais, P., Fung, I. Y., Heimann, M., John, J., Maki, T., Maksyutov, S., Masarie, K., Prather, M., Pak, B., Taguchi, S., and Zhu, Z.: TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003, Global Biogeochem. Cy., 20, https://doi.org/10.1029/2004GB002439, 2006.
Bastos, A., Friedlingstein, P., Sitch, S., Chen, C., Mialon, A., Wigneron, J. P., Arora, V. K., Briggs, P. R., Canadell, J. G., Ciais, P., Chevallier, F., Cheng, L., Delire, C., Haverd, V., Jain, A. K., Joos, F., Kato, E., Lienert, S., Lombardozzi, D., Melton, J. R., Myneni, R., Nabel, J. E. M. S., Pongratz, J., Poulter, B., Rödenbeck, C., Séférian, R., Tian, H., Van Eck, C., Viovy, N., Vuichard, N., Walker, A. P., Wiltshire, A., Yang, J., Zaehle, S., Zeng, N., and Zhu, D.: Impact of the 2015/2016 El Niño on the terrestrial carbon cycle constrained by bottom-up and top-down approaches, Philos. T. R. Soc. B, 373, https://doi.org/10.1098/rstb.2017.0304, 2018.
Basu, S., Baker, D. F., Chevallier, F., Patra, P. K., Liu, J., and Miller, J. B.: The impact of transport model differences on CO2 surface flux estimates from OCO-2 retrievals of column average CO2, Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, 2018.
Buchmann, N. B. and Schulze, E. D.: Net CO2 and H2O fluxes of terrestrial ecosystems, Global Biogeochem. Cy., 13, 751–760, https://doi.org/10.1029/1999GB900016, 1999.
Byrne, B., Jones, D. B. A., Strong, K., Polavarapu, S. M., Harper, A. B., Baker, D. F., and Maksyutov, S.: On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems?, Atmos. Chem. Phys., 19, 13017–13035, https://doi.org/10.5194/acp-19-13017-2019, 2019.
Canadell, J. G., Ciais, P., Gurney, K., Le Quéré, C., Piao, S., Raupach, M. R., and Sabine, C. L.: An International Effort to Quantify Regional Carbon Fluxes, Eos, Transactions American Geophysical Union, 92, 81–82, https://doi.org/10.1029/2011EO100001, 2011.
Chevallier, F., Remaud, M., O'Dell, C. W., Baker, D., Peylin, P., and Cozic, A.: Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions, Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019, 2019.
Connor, B. J., Boesch, H., Toon, G., Sen, B., Miller, C., and Crisp, D.: Orbiting Carbon Observatory: Inverse method and prospective error analysis, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2006JD008336, 2008.
Cox, P. M., Pearson, D., Booth, B. B., Friedlingstein, P., Huntingford, C., Jones, C. D., and Luke, C. M.: Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability, Nature, 494, 341–344, https://doi.org/10.1038/nature11882, 2013.
Crowell, S., Baker, D., Schuh, A., Basu, S., Jacobson, A. R., Chevallier, F., Liu, J., Deng, F., Feng, L., McKain, K., Chatterjee, A., Miller, J. B., Stephens, B. B., Eldering, A., Crisp, D., Schimel, D., Nassar, R., O'Dell, C. W., Oda, T., Sweeney, C., Palmer, P. I., and Jones, D. B. A.: The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network, Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, 2019.
Deng, F. and Chen, J. M.: Recent global CO2 flux inferred from atmospheric CO2 observations and its regional analyses, Biogeosciences, 8, 3263–3281, https://doi.org/10.5194/bg-8-3263-2011, 2011.
Deng, F., Chen, J. M., Ishizawa, M., Yuen, C. W., Mo, G., Higuchi, K., Chan, D., and Maksyutov, S.: Global monthly CO2 flux inversion with a focus over North America, Tellus B, 179–190, https://doi.org/10.1111/j.1600-0889.2006.00235.x, 2007.
Deng, F., Jones, D. B. A., Henze, D. K., Bousserez, N., Bowman, K. W., Fisher, J. B., Nassar, R., O'Dell, C., Wunch, D., Wennberg, P. O., Kort, E. A., Wofsy, S. C., Blumenstock, T., Deutscher, N. M., Griffith, D. W. T., Hase, F., Heikkinen, P., Sherlock, V., Strong, K., Sussmann, R., and Warneke, T.: Inferring regional sources and sinks of atmospheric CO2 from GOSAT data, Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, 2014.
Didan, K.: MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V061, NASA Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MOD13C2.061, 2021.
Didan, K. and Barreto-Muñoz, A.: MODIS Vegetation Index User's Guide (MOD13 Series), Version 3.10, Collection 6.1, Vegetation Index and Phenology Lab, University of Arizona, https://lpdaac.usgs.gov/documents/621/MOD13_User_Guide_V61.pdf (last access: 1 May 2026), 2019.
E.U. Copernicus Marine Service Information (CMEMS): Surface ocean carbon fields, Marine Data Store [data set], https://doi.org/10.48670/moi-00047, 2026.
Fang, Y., Michalak, A. M., Schwalm, C. R., Huntzinger, D. N., Berry, J. A., Ciais, P., Piao, S., Poulter, B., Fisher, J. B., Cook, R. B., Hayes, D., Huang, M., Ito, A., Jain, A., Lei, H., Lu, C., Mao, J., Parazoo, N. C., Peng, S., Ricciuto, D. M., Shi, X., Tao, B., Tian, H., Wang, W., Wei, Y., and Yang, J.: Global land carbon sink response to temperature and precipitation varies with ENSO phase, Environ. Res. Lett., 12, https://doi.org/10.1088/1748-9326/aa6e8e, 2017.
Feng, S., Jiang, F., Wu, Z., Wang, H., Ju, W., and Wang, H.: CO Emissions Inferred From Surface CO Observations Over China in December 2013 and 2017, J. Geophys. Res.-Atmos., 125, https://doi.org/10.1029/2019JD031808, 2020.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens, B. B., Bakwin, P. S., and Grainger, C. A.: Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework, J. Geophys. Res.-Atmos., 108, https://doi.org/10.1029/2003jd003770, 2003.
Gilfillan, D. and Marland, G.: CDIAC-FF: global and national CO2 emissions from fossil fuel combustion and cement manufacture: 1751–2017, Earth Syst. Sci. Data, 13, 1667–1680, https://doi.org/10.5194/essd-13-1667-2021, 2021.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fan, S., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Masarie, K., Peylin, P., Prather, M., Pak, B. C., Randerson, J., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C.-W.: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models, Nature, 415, 626–630, https://doi.org/10.1038/415626a, 2002.
Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y.-H., Ciais, P., Fan, S., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Kowalczyk, E., Maki, T., Maksyutov, S., Peylin, P., Prather, M., Pak, B. C., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C.-W.: TransCom 3 CO2 inversion intercomparison: 1. Annual mean control results and sensitivity to transport and prior flux information, Tellus B, 55, 555–579, https://doi.org/10.1034/j.1600-0889.2003.00049.x, 2003.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Houweling, S., Baker, D., Basu, S., Boesch, H., Butz, A., Chevallier, F., Deng, F., Dlugokencky, E. J., Feng, L., Ganshin, A., Hasekamp, O., Jones, D., Maksyutov, S., Marshall, J., Oda, T., O'Dell, C. W., Oshchepkov, S., Palmer, P. I., Peylin, P., Poussi, Z., Reum, F., Takagi, H., Yoshida, Y., and Zhuravlev, R.: An intercomparison of inversemodels for estimating sources and sinks of CO2 using GOSAT measurements, J. Geophys. Res., 120, 5253–5266, https://doi.org/10.1002/2014JD022962, 2015.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L. G.: Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195–213, https://doi.org/10.1016/S0034-4257(02)00096-2, 2002.
Intergovernmental Panel on Climate Change (IPCC): Global Carbon and Other Biogeochemical Cycles and Feedbacks, in: Climate Change 2021 – The Physical Science Basis, Cambridge University Press, 673–816, https://doi.org/10.1017/9781009157896.007, 2023.
Jiang, F.: A ten-year (2010–2019) global terrestrial NEE inferred from the GOSAT v9 XCO2 retrievals (GCAS2021), Zenodo [data set], https://doi.org/10.5281/zenodo.5829774, 2022.
Jiang, F., Wang, H. W., Chen, J. M., Zhou, L. X., Ju, W. M., Ding, A. J., Liu, L. X., and Peters, W.: Nested atmospheric inversion for the terrestrial carbon sources and sinks in China, Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, 2013.
Jiang, F., Wang, H., Chen, J. M., Ju, W., Tian, X., Feng, S., Li, G., Chen, Z., Zhang, S., Lu, X., Liu, J., Wang, H., Wang, J., He, W., and Wu, M.: Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT retrievals using a new version of the Global Carbon Assimilation System, Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, 2021.
Jiang, F., Ju, W., He, W., Wu, M., Wang, H., Wang, J., Jia, M., Feng, S., Zhang, L., and Chen, J. M.: A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO2 retrievals (GCAS2021), Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, 2022a.
Jiang, P., Ding, W., Yuan, Y., Ye, W., and Mu, Y.: Interannual variability of vegetation sensitivity to climate in China, J. Environ. Manage., 301, https://doi.org/10.1016/j.jenvman.2021.113768, 2022b.
Jin, J., Lin, H. X., Heemink, A., and Segers, A.: Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar, Atmos. Environ., 187, 358–373, https://doi.org/10.1016/j.atmosenv.2018.05.060, 2018.
Joos, F. and Spahni, R.: Rates of change in natural and anthropogenic radiative forcing over the past 20,000 years, P. Natl. Acad. Sci. USA, 105, 1425–1430, https://doi.org/10.1073/pnas.0707386105, 2008.
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020.
Kaminski, T., Scholze, M., and Houweling, S.: Quantifying the benefit of A-SCOPE data for reducing uncertainties in terrestrial carbon fluxes in CCDAS, Tellus B, 62, 784–796, https://doi.org/10.1111/j.1600-0889.2010.00483.x, 2010.
Kondo, M., Patra, P. K., Sitch, S., Friedlingstein, P., Poulter, B., Chevallier, F., Ciais, P., Canadell, J. G., Bastos, A., Lauerwald, R., Calle, L., Ichii, K., Anthoni, P., Arneth, A., Haverd, V., Jain, A. K., Kato, E., Kautz, M., Law, R. M., Lienert, S., Lombardozzi, D., Maki, T., Nakamura, T., Peylin, P., Rödenbeck, C., Zhuravlev, R., Saeki, T., Tian, H., Zhu, D., and Ziehn, T.: State of the science in reconciling top-down and bottom-up approaches for terrestrial CO2 budget, Glob. Change Biol., 26, 1068–1084, https://doi.org/10.1111/gcb.14917, 2020.
Kou, X., Peng, Z., Zhang, M., Hu, F., Han, X., Li, Z., and Lei, L.: 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), Atmos. Chem. Phys., 23, 6719–6741, https://doi.org/10.5194/acp-23-6719-2023, 2023.
Kulawik, S. S., Crowell, S., Baker, D., Liu, J., McKain, K., Sweeney, C., Biraud, S. C., Wofsy, S., O'Dell, C. W., Wennberg, P. O., Wunch, D., Roehl, C. M., Deutscher, N. M., Kiel, M., Griffith, D. W. T., Velazco, V. A., Notholt, J., Warneke, T., Petri, C., De Mazière, M., Sha, M. K., Sussmann, R., Rettinger, M., Pollard, D. F., Morino, I., Uchino, O., Hase, F., Feist, D. G., Roche, S., Strong, K., Kivi, R., Iraci, L., Shiomi, K., Dubey, M. K., Sepulveda, E., Rodriguez, O. E. G., Té, Y., Jeseck, P., Heikkinen, P., Dlugokencky, E. J., Gunson, M. R., Eldering, A., Crisp, D., Fisher, B., and Osterman, G. B.: Characterization of OCO-2 and ACOS-GOSAT biases and errors for CO2 flux estimates, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2019-257, 2019.
Lan, X., Tans, P., and Thoning, K. W.: Trends in globally-averaged CO2 determined from NOAA Global Monitoring Laboratory measurements, NOAA Global Monitoring Laboratory, https://doi.org/10.15138/9N0H-ZH07, 2025.
Lian, Y., Li, H., Renyang, Q., Liu, L., Dong, J., Liu, X., Qu, Z., Lee, L. C., Chen, L., Wang, D., and Zhang, H.: Mapping the net ecosystem exchange of CO2 of global terrestrial systems, Int. J. Appl. Earth Obs., 116, 103176, https://doi.org/10.1016/j.jag.2022.103176, 2023.
Liu, J. and Bowman, K.: Carbon Monitoring System Carbon Flux Ocean L4 V3, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/9H6GCQKP28AI, 2024.
Liu, J., Baskaran, L., Bowman, K., Schimel, D., Bloom, A. A., Parazoo, N. C., Oda, T., Carroll, D., Menemenlis, D., Joiner, J., Commane, R., Daube, B., Gatti, L. V., McKain, K., Miller, J., Stephens, B. B., Sweeney, C., and Wofsy, S.: Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020), Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, 2021.
Liu, Y., Zhao, Y., Wu, W., Ao, X., and Chen, R.: The Response of Vegetation Dynamics to Climate in Xinjiang from 1991 to 2018, Forests, 15, https://doi.org/10.3390/f15122065, 2024.
Lu, B., Li, H., Wu, J., Zhang, T., Liu, J., Liu, B., Chen, Y., and Baishan, J.: Impact of El Niño and Southern Oscillation on the summer precipitation over Northwest China, Atmos. Sci. Lett., 20, https://doi.org/10.1002/asl.928, 2019.
Ma, F., Ye, A., You, J., and Duan, Q.: 2015–16 floods and droughts in China, and its response to the strong El Niño, Sci. Total Environ., 627, 1473–1484, https://doi.org/10.1016/j.scitotenv.2018.01.280, 2018.
Monteil, G., Broquet, G., Scholze, M., Lang, M., Karstens, U., Gerbig, C., Koch, F.-T., Smith, N. E., Thompson, R. L., Luijkx, I. T., White, E., Meesters, A., Ciais, P., Ganesan, A. L., Manning, A., Mischurow, M., Peters, W., Peylin, P., Tarniewicz, J., Rigby, M., Rödenbeck, C., Vermeulen, A., and Walton, E. M.: The regional European atmospheric transport inversion comparison, EUROCOM: first results on European-wide terrestrial carbon fluxes for the period 2006–2015, Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, 2020.
Munassar, S., Rödenbeck, C., Koch, F.-T., Totsche, K. U., Gałkowski, M., Walther, S., and Gerbig, C.: Net ecosystem exchange (NEE) estimates 2006–2019 over Europe from a pre-operational ensemble-inversion system, Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, 2022.
Nassar, R., Jones, D. B. A., Suntharalingam, P., Chen, J. M., Andres, R. J., Wecht, K. J., Yantosca, R. M., Kulawik, S. S., Bowman, K. W., Worden, J. R., Machida, T., and Matsueda, H.: Modeling global atmospheric CO2 with improved emission inventories and CO2 production from the oxidation of other carbon species, Geosci. Model Dev., 3, 689–716, https://doi.org/10.5194/gmd-3-689-2010, 2010.
Nassar, R., Jones, D. B. A., Kulawik, S. S., Worden, J. R., Bowman, K. W., Andres, R. J., Suntharalingam, P., Chen, J. M., Brenninkmeijer, C. A. M., Schuck, T. J., Conway, T. J., and Worthy, D. E.: Inverse modeling of CO2 sources and sinks using satellite observations of CO2 from TES and surface flask measurements, Atmos. Chem. Phys., 11, 6029–6047, https://doi.org/10.5194/acp-11-6029-2011, 2011.
Nassar, R., Napier-Linton, L., Gurney, K. R., Andres, R. J., Oda, T., Vogel, F. R., and Deng, F.: Improving the temporal and spatial distribution of co2 emissions from global fossil fuel emission data sets, J. Geophys. Res.-Atmos., 118, 917–933, https://doi.org/10.1029/2012JD018196, 2013.
Noumonvi, K. D. and Ferlan, M.: Empirical vs. light-use efficiency modelling for estimating carbon fluxes in a mid-succession ecosystem developed on abandoned karst grassland, PLoS One, 15, https://doi.org/10.1371/journal.pone.0237351, 2020.
Oda, T. and Maksyutov, S.: A very high-resolution (1 km × 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights, Atmos. Chem. Phys., 11, 543–556, https://doi.org/10.5194/acp-11-543-2011, 2011.
Oda, T., Maksyutov, S., and Andres, R. J.: The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions, Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, 2018.
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C., Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J., Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T., Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99–121, https://doi.org/10.5194/amt-5-99-2012, 2012.
Palmer, P. I., Jacob, D. J., Jones, D. B. A., Heald, C. L., Yantosca, R. M., Logan, J. A., Sachse, G. W., and Streets, D. G.: Inverting for emissions of carbon monoxide from Asia using aircraft observations over the western Pacific, J. Geophys. Res.-Atmos., 108, https://doi.org/10.1029/2003jd003397, 2003.
Park, J. and Kim, H. M.: Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments, Atmos. Chem. Phys., 20, 5175–5195, https://doi.org/10.5194/acp-20-5175-2020, 2020.
Patra, P. K., Hajima, T., Saito, R., Chandra, N., Yoshida, Y., Ichii, K., Kawamiya, M., Kondo, M., Ito, A., and Crisp, D.: Evaluation of earth system model and atmospheric inversion using total column CO2 observations from GOSAT and OCO-2, Prog. Earth Planet. Sci., 8, https://doi.org/10.1186/s40645-021-00420-z, 2021.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J., Masarie, K., Miller, J. B., Bruhwiler, L. M. P., Pétron, G., Hirsch, A. I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O., Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104, 18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Peylin, P., Law, R. M., Gurney, K. R., Chevallier, F., Jacobson, A. R., Maki, T., Niwa, Y., Patra, P. K., Peters, W., Rayner, P. J., Rödenbeck, C., van der Laan-Luijkx, I. T., and Zhang, X.: Global atmospheric carbon budget: results from an ensemble of atmospheric CO2 inversions, Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, 2013.
Potithep, S., Nagai, S., Nasahara, K. N., Muraoka, H., and Suzuki, R.: Two separate periods of the LAI-VIs relationships using in situ measurements in a deciduous broadleaf forest, Agr. Forest Meteorol., 169, 148–155, https://doi.org/10.1016/j.agrformet.2012.09.003, 2013.
Randerson, J. T., van der Werf, G. R., Giglio, L., Collatz, G. J., and Kasibhatla, P. S.: Global Fire Emissions Database, Version 4.1 (GFEDv4), ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1293 , 2018.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J. M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and Valentini, R.: On the separation of net ecosystem exchange into assimilation and ecosystem respiration: Review and improved algorithm, Glob. Change Biol., https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Ren, H. L., Wang, R., Zhai, P., Ding, Y., and Lu, B.: Upper-ocean dynamical features and prediction of the super El Niño in 2015/16: A comparison with the cases in 1982/83 and 1997/98, J. Meteorol. Res.-PRC, 31, 278–294, https://doi.org/10.1007/s13351-017-6194-3, 2017.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice, World Scientific, https://doi.org/10.1142/3171, 2000.
Schourup-Kristensen, V., Wekerle, C., Wolf-Gladrow, D. A., and Völker, C.: Arctic Ocean biogeochemistry in the high resolution FESOM 1.4-REcoM2 model, Prog. Oceanogr., 168, 65–81, https://doi.org/10.1016/j.pocean.2018.09.006, 2018.
Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs), Glob. Change Biol., 14, 2015–2039, https://doi.org/10.1111/j.1365-2486.2008.01626.x, 2008.
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015.
Suntharalingam, P., Jacob, D. D., Palmer, P. I., Logan, J. A., Yantosca, R. M., Xiao, Y., Evans, M. J., Streets, D. G., Vay, S. L., and Sachse, G. W.: Improved quantificaion of Chinese carbon fluxes using CO2/CO correlations in Asian outflow, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD004362, 2004.
Takagi, H., Saeki, T., Oda, T., Saito, M., Valsala, V., Belikov, D., Saito, R., Yoshida, Y., Morino, I., Uchino, O., Andres, R. J., Yokota, T., and Maksyutov, S.: On the benefit of GOSAT observations to the estimation of regional CO2 fluxes, Scientific Online Letters on the Atmosphere, 7, 161–164, https://doi.org/10.2151/sola.2011-041, 2011.
Taylor, T. E., O'Dell, C. W., Crisp, D., Kuze, A., Lindqvist, H., Wennberg, P. O., Chatterjee, A., Gunson, M., Eldering, A., Fisher, B., Kiel, M., Nelson, R. R., Merrelli, A., Osterman, G., Chevallier, F., Palmer, P. I., Feng, L., Deutscher, N. M., Dubey, M. K., Feist, D. G., García, O. E., Griffith, D. W. T., Hase, F., Iraci, L. T., Kivi, R., Liu, C., De Mazière, M., Morino, I., Notholt, J., Oh, Y.-S., Ohyama, H., Pollard, D. F., Rettinger, M., Schneider, M., Roehl, C. M., Sha, M. K., Shiomi, K., Strong, K., Sussmann, R., Té, Y., Velazco, V. A., Vrekoussis, M., Warneke, T., and Wunch, D.: An 11-year record of estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm, Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, 2022.
Thompson, R. L., Patra, P. K., Chevallier, F., Maksyutov, S., Law, R. M., Ziehn, T., Van Der Laan-Luijkx, I. T., Peters, W., Ganshin, A., Zhuravlev, R., Maki, T., Nakamura, T., Shirai, T., Ishizawa, M., Saeki, T., Machida, T., Poulter, B., Canadell, J. G., and Ciais, P.: Top-down assessment of the Asian carbon budget since the mid 1990s, Nat. Commun., 7, https://doi.org/10.1038/ncomms10724, 2016.
Tian, H., Chen, G., Liu, M., Zhang, C., Sun, G., Lu, C., Xu, X., Ren, W., Pan, S., and Chappelka, A.: Model estimates of net primary productivity, evapotranspiration, and water use efficiency in the terrestrial ecosystems of the southern United States during 1895-2007, Forest Ecol. Manag., 259, 1311–1327, https://doi.org/10.1016/j.foreco.2009.10.009, 2010.
Tolk, L. F., Meesters, A. G. C. A., Dolman, A. J., and Peters, W.: Modelling representation errors of atmospheric CO2 mixing ratios at a regional scale, Atmos. Chem. Phys., 8, 6587–6596, https://doi.org/10.5194/acp-8-6587-2008, 2008.
UNFCCC: Paris Agreement, https://unfccc.int/process-and-meetings/the-paris-agreement (last access: 28 April 2026), 2015.
Wang, H., Jiang, F., Wang, J., Ju, W., and Chen, J. M.: Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 retrievals, Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, 2019.
Wang, J., Feng, L., Palmer, P. I., Liu, Y., Fang, S., Bösch, H., O'Dell, C. W., Tang, X., Yang, D., Liu, L., and Xia, C. Z.: Large Chinese land carbon sink estimated from atmospheric carbon dioxide data, Nature, 586, 720–723, https://doi.org/10.1038/s41586-020-2849-9, 2020.
Wang, W., Ciais, P., Nemani, R. R., Canadell, J. G., Piao, S., Sitch, S., White, M. A., Hashimoto, H., Milesi, C., and Myneni, R. B.: Variations in atmospheric CO2 growth rates coupled with tropical temperature, P. Natl. Acad. Sci. USA, 110, 13061–13066, https://doi.org/10.1073/pnas.1219683110, 2013.
Wang, X., Piao, S., Ciais, P., Friedlingstein, P., Myneni, R. B., Cox, P., Heimann, M., Miller, J., Peng, S., Wang, T., Yang, H., and Chen, A.: A two-fold increase of carbon cycle sensitivity to tropical temperature variations, Nature, 506, 212–215, https://doi.org/10.1038/nature12915, 2014.
Wang, X., Gao, Y., Jeong, S., Ito, A., Bastos, A., Poulter, B., Wang, Y., Ciais, P., Tian, H., Yuan, W., Chandra, N., Chevallier, F., Fan, L., Hong, S., Lauerwald, R., Li, W., Lin, Z., Pan, N., Patra, P. K., Peng, S., Ran, L., Sang, Y., Sitch, S., Takashi, M., Thompson, R. L., Wang, C., Wang, K., Wang, T., Xi, Y., Xu, L., Yan, Y., Yun, J., Zhang, Y., Zhang, Y., Zhang, Z., Zheng, B., Zhou, F., Tao, S., Canadell, J. G., and Piao, S.: The Greenhouse Gas Budget of Terrestrial Ecosystems in East Asia Since 2000, Global Biogeochem. Cy., 38, https://doi.org/10.1029/2023GB007865, 2024.
WMO: WMO statement on the state of the global climate in 2016, World Meteorological Organization, Geneva, https://library.wmo.int/viewer/56097 (last access: 1 May 2026), 2017.
Wu, Z., Lu, W., Roobaert, A., Song, L., Yan, X.-H., and Cai, W.-J.: A machine-learning reconstruction of sea surface pCO2 in the North American Atlantic Coastal Ocean Margin from 1993 to 2021, Earth Syst. Sci. Data, 17, 43–63, https://doi.org/10.5194/essd-17-43-2025, 2025.
Wunch, D., Toon, G. C., Blavier, J.-F. L., Washenfelder, R. A., Notholt, J., Connor, B. J., Griffith, D. W. T., Sherlock, V., and Wennberg, P. O.: The Total Carbon Column Observing Network, Philos. T. R. Soc. A, 369, 2087–2112, https://doi.org/10.1098/rsta.2010.0240, 2011.
Wunch, D., Wennberg, P. O., Osterman, G., Fisher, B., Naylor, B., Roehl, C. M., O'Dell, C., Mandrake, L., Viatte, C., Kiel, M., Griffith, D. W. T., Deutscher, N. M., Velazco, V. A., Notholt, J., Warneke, T., Petri, C., De Maziere, M., Sha, M. K., Sussmann, R., Rettinger, M., Pollard, D., Robinson, J., Morino, I., Uchino, O., Hase, F., Blumenstock, T., Feist, D. G., Arnold, S. G., Strong, K., Mendonca, J., Kivi, R., Heikkinen, P., Iraci, L., Podolske, J., Hillyard, P. W., Kawakami, S., Dubey, M. K., Parker, H. A., Sepulveda, E., García, O. E., Te, Y., Jeseck, P., Gunson, M. R., Crisp, D., and Eldering, A.: Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) measurements with TCCON, Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, 2017.
Yeh, S. W., Shin, M. S., Ma, S. J., Kug, J. S., and Moon, B. K.: Understanding elevated CO2 concentrations in East Asia relative to the global mean during boreal spring on the slow and interannual timescales, Sci. Total Environ., 901, https://doi.org/10.1016/j.scitotenv.2023.166098, 2023.
You, Y., Tian, H., Pan, S., Shi, H., Bian, Z., Gurgel, A., Huang, Y., Kicklighter, D., Liang, X. Z., Lu, C., Melillo, J., Miao, R., Pan, N., Reilly, J., Ren, W., Xu, R., Yang, J., Yu, Q., and Zhang, J.: Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework, Agr. Forest Meteorol., 325, https://doi.org/10.1016/j.agrformet.2022.109144, 2022.
Yue, C., Ciais, P., Bastos, A., Chevallier, F., Yin, Y., Rödenbeck, C., and Park, T.: Vegetation greenness and land carbon-flux anomalies associated with climate variations: a focus on the year 2015, Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, 2017.
Zhai, P., Yu, R., Guo, Y., Li, Q., Ren, X., Wang, Y., Xu, W., Liu, Y., and Ding, Y.: The Strong El Niño of 2015/16 and Its Dominant Impacts on Global and China's Climate, J. Meteorol. Res.-PRC, 30, 283–297, https://doi.org/10.1007/s13351-016-6101-3, 2016.
Zhu, H. and Tan, Y.: The Origin of Evergreen Broad-Leaved Forests in East Asia from the Evidence of Floristic Elements, Plants (Basel), 13, 1106, https://doi.org/10.3390/plants13081106, 2024.
Short summary
Given that East Asia has the highest CO2 emissions in the world, understanding the region’s carbon uptake is essential for planning mitigation strategies. We estimated natural carbon sinks in East Asia from 2010 to 2019 using satellite observations and a chemical transport model within a Bayesian inversion framework. Natural sinks offset 13.6 % of fossil fuel emissions, indicating that emissions exceed the region's carbon uptake capacity and highlighting the need for stronger mitigation efforts.
Given that East Asia has the highest CO2 emissions in the world, understanding the region’s...
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