Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-1963-2021
© Author(s) 2021. 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-21-1963-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Feb 2021
Research article |
| 10 Feb 2021
| 10 Feb 2021
Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical
Information Resource Development and Application, Nanjing 210023, China
Hengmao Wang
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Jing M. Chen
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Department of Geography and Planning, University of Toronto, Toronto,
Ontario M5S3G3, Canada
Weimin Ju
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Xiangjun Tian
The Institute of Atmospheric Physics, Chinese Academy of Sciences,
Beijing 100029, China
Shuzhuang Feng
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Guicai Li
National Satellite Meteorological Center, China Meteorological
Administration, Beijing 100101, China
Zhuoqi Chen
School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519000, China
Shupeng Zhang
School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai 519000, China
Xuehe Lu
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Jane Liu
Department of Geography and Planning, University of Toronto, Toronto,
Ontario M5S3G3, Canada
School of Atmospheric Sciences, Nanjing University, Nanjing 210023,
China
Haikun Wang
School of Atmospheric Sciences, Nanjing University, Nanjing 210023,
China
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Mousong Wu
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, International Institute for Earth System Science, Nanjing
University, Nanjing 210023, China
Related authors
Shuzhuang Feng, Fei Jiang, Yongguang Zhang, Huilin Chen, Honglin Zhuang, Shumin Wang, Shengxi Bai, Hengmao Wang, and Weimin Ju
EGUsphere, https://doi.org/10.5194/egusphere-2025-2669, https://doi.org/10.5194/egusphere-2025-2669, 2025
Short summary
Short summary
Using satellite data and advanced modeling, this study inverted daily high-resolution anthropogenic CH4 emissions across China and Shanxi Province. We found that China's 2022 CH4 emissions were 45.1 TgCH4·yr⁻¹, significantly lower than previous estimates, especially in coal mining and waste sectors. The inversion substantially reduced emission uncertainties and improved CH4 concentration simulations. These results suggest China’s climate mitigation burden may have been overestimated.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yu Mao, Weimin Ju, Hengmao Wang, Liangyun Liu, Haikun Wang, Shuzhuang Feng, Mengwei Jia, and Fei Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3672, https://doi.org/10.5194/egusphere-2024-3672, 2025
Short summary
Short summary
The Russia-Ukraine war in 2022 severely disrupted Ukraine’s economy, with significant reductions in industrial, transportation, and residential activities. Our research used satellite data to track changes in nitrogen oxide emissions, a key indicator of human activity, during the war. We found a 28 % decline in emissions, which was twice of the decrease caused by the COVID-19 pandemic. This study highlights how modern warfare can deeply impact both the environment and economic stability.
Xingyu Wang, Fei Jiang, Hengmao Wang, Zhengqi Zhang, Mousong Wu, Jun Wang, Wei He, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 25, 867–880, https://doi.org/10.5194/acp-25-867-2025, https://doi.org/10.5194/acp-25-867-2025, 2025
Short summary
Short summary
The role of OCO-3 XCO2 retrievals in estimating global terrestrial carbon fluxes is unclear. We investigate this by assimilating OCO-3 XCO2 retrievals alone and in combination with OCO-2 XCO2. The assimilation of OCO-3 XCO2 alone underestimates global land sinks, mainly at high latitudes, due to the lack of observations beyond 52° S and 52° N, large variations in the number of data, and varying observation times, while the joint assimilation of OCO-2 and OCO-3 XCO2 has the best performance.
Ran Yan, Jun Wang, Weimin Ju, Xiuli Xing, Miao Yu, Meirong Wang, Jingye Tan, Xunmei Wang, Hengmao Wang, and Fei Jiang
Biogeosciences, 21, 5027–5043, https://doi.org/10.5194/bg-21-5027-2024, https://doi.org/10.5194/bg-21-5027-2024, 2024
Short summary
Short summary
Our study reveals that the effects of the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on China's gross primary production (GPP) are basically opposite, with obvious seasonal changes. Soil moisture primarily influences GPP during ENSO events (except spring) and temperature during IOD events (except fall). Quantitatively, China's annual GPP displays modest positive anomalies during La Niña and negative anomalies in El Niño years, driven by significant seasonal variations.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
Short summary
Short summary
Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Shuzhuang Feng, Fei Jiang, Tianlu Qian, Nan Wang, Mengwei Jia, Songci Zheng, Jiansong Chen, Fang Ying, and Weimin Ju
Atmos. Chem. Phys., 24, 7481–7498, https://doi.org/10.5194/acp-24-7481-2024, https://doi.org/10.5194/acp-24-7481-2024, 2024
Short summary
Short summary
We developed a multi-air-pollutant inversion system to estimate non-methane volatile organic compound (NMVOC) emissions using TROPOMI formaldehyde retrievals. We found that the inversion significantly improved formaldehyde simulations and reduced NMVOC emission uncertainties. The optimized NMVOC emissions effectively corrected the overestimation of O3 levels, mainly by decreasing the rate of the RO2 + NO reaction and increasing the rate of the NO2 + OH reaction.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
Short summary
Short summary
We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
Short summary
Short summary
A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Shuzhuang Feng, Fei Jiang, Yongguang Zhang, Huilin Chen, Honglin Zhuang, Shumin Wang, Shengxi Bai, Hengmao Wang, and Weimin Ju
EGUsphere, https://doi.org/10.5194/egusphere-2025-2669, https://doi.org/10.5194/egusphere-2025-2669, 2025
Short summary
Short summary
Using satellite data and advanced modeling, this study inverted daily high-resolution anthropogenic CH4 emissions across China and Shanxi Province. We found that China's 2022 CH4 emissions were 45.1 TgCH4·yr⁻¹, significantly lower than previous estimates, especially in coal mining and waste sectors. The inversion substantially reduced emission uncertainties and improved CH4 concentration simulations. These results suggest China’s climate mitigation burden may have been overestimated.
Rong Shang, Xudong Lin, Jing M. Chen, Yunjian Liang, Keyan Fang, Mingzhu Xu, Yulin Yan, Weimin Ju, Guirui Yu, Nianpeng He, Li Xu, Liangyun Liu, Jing Li, Wang Li, Jun Zhai, and Zhongmin Hu
Earth Syst. Sci. Data, 17, 3219–3241, https://doi.org/10.5194/essd-17-3219-2025, https://doi.org/10.5194/essd-17-3219-2025, 2025
Short summary
Short summary
Forest age is critical for carbon cycle modeling and effective forest management. Existing datasets, however, have low spatial resolutions or limited temporal coverage. This study introduces China's annual forest age dataset (CAFA), spanning 1986–2022 at a 30 m resolution. By tracking forest disturbances, we annually update ages. Validation shows small errors for disturbed forests and larger errors for undisturbed forests. CAFA can enhance carbon cycle modeling and forest management in China.
Peng Li, Rong Shang, Jing M. Chen, Huiguang Zhang, Xiaoping Zhang, Guoshuai Zhao, Hong Yan, Jun Xiao, Xudong Lin, Lingyun Fan, Rong Wang, Jianjie Cao, and Hongda Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2025-1062, https://doi.org/10.5194/egusphere-2025-1062, 2025
Short summary
Short summary
This study explored species-specific relationships between net primary productivity and forest age for seven forest species in subtropical China based on field data using the Semi-Empirical Model. Compared to nationwide relationships, these species-specific relationships improved simulations of aboveground biomass when using the process-based model. Our findings suggest that these species-specific relationships are crucial for accurate forest carbon modeling and management in subtropical China.
Zhongwang Wei, Qingchen Xu, Fan Bai, Xionghui Xu, Zixin Wei, Wenzong Dong, Hongbin Liang, Nan Wei, Xingjie Lu, Lu Li, Shupeng Zhang, Hua Yuan, Laibo Liu, and Yongjiu Dai
EGUsphere, https://doi.org/10.5194/egusphere-2025-1380, https://doi.org/10.5194/egusphere-2025-1380, 2025
Short summary
Short summary
Land surface models are used for simulating earth's surface interacts with the atmosphere. As models grow more complex and detailed, researchers need better tools to evaluate their performance. OpenBench, a new software system that makes evaluation process more comprehensive and efficient. It stands out by incorporating various factors and working with data at any scale which enabling scientists to incorporate new types of models and measurements as our understanding of Earth’s systems evolves.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yu Mao, Weimin Ju, Hengmao Wang, Liangyun Liu, Haikun Wang, Shuzhuang Feng, Mengwei Jia, and Fei Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3672, https://doi.org/10.5194/egusphere-2024-3672, 2025
Short summary
Short summary
The Russia-Ukraine war in 2022 severely disrupted Ukraine’s economy, with significant reductions in industrial, transportation, and residential activities. Our research used satellite data to track changes in nitrogen oxide emissions, a key indicator of human activity, during the war. We found a 28 % decline in emissions, which was twice of the decrease caused by the COVID-19 pandemic. This study highlights how modern warfare can deeply impact both the environment and economic stability.
Xingyu Wang, Fei Jiang, Hengmao Wang, Zhengqi Zhang, Mousong Wu, Jun Wang, Wei He, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 25, 867–880, https://doi.org/10.5194/acp-25-867-2025, https://doi.org/10.5194/acp-25-867-2025, 2025
Short summary
Short summary
The role of OCO-3 XCO2 retrievals in estimating global terrestrial carbon fluxes is unclear. We investigate this by assimilating OCO-3 XCO2 retrievals alone and in combination with OCO-2 XCO2. The assimilation of OCO-3 XCO2 alone underestimates global land sinks, mainly at high latitudes, due to the lack of observations beyond 52° S and 52° N, large variations in the number of data, and varying observation times, while the joint assimilation of OCO-2 and OCO-3 XCO2 has the best performance.
Jiahao Shi, Hua Yuan, Wanyi Lin, Wenzong Dong, Hongbin Liang, Zhuo Liu, Jianxin Zeng, Haolin Zhang, Nan Wei, Zhongwang Wei, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 17, 117–134, https://doi.org/10.5194/essd-17-117-2025, https://doi.org/10.5194/essd-17-117-2025, 2025
Short summary
Short summary
Flux tower data are widely recognized as benchmarking data for land surface models, but insufficient emphasis on and deficiency in site attribute data limits their true value. We collect site-observed vegetation, soil, and topography data from various sources. The final dataset encompasses 90 sites globally, with relatively complete site attribute data and high-quality flux validation data. This work has provided more reliable site attribute data, benefiting land surface model development.
Ran Yan, Jun Wang, Weimin Ju, Xiuli Xing, Miao Yu, Meirong Wang, Jingye Tan, Xunmei Wang, Hengmao Wang, and Fei Jiang
Biogeosciences, 21, 5027–5043, https://doi.org/10.5194/bg-21-5027-2024, https://doi.org/10.5194/bg-21-5027-2024, 2024
Short summary
Short summary
Our study reveals that the effects of the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on China's gross primary production (GPP) are basically opposite, with obvious seasonal changes. Soil moisture primarily influences GPP during ENSO events (except spring) and temperature during IOD events (except fall). Quantitatively, China's annual GPP displays modest positive anomalies during La Niña and negative anomalies in El Niño years, driven by significant seasonal variations.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
Short summary
Short summary
Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Shuzhuang Feng, Fei Jiang, Tianlu Qian, Nan Wang, Mengwei Jia, Songci Zheng, Jiansong Chen, Fang Ying, and Weimin Ju
Atmos. Chem. Phys., 24, 7481–7498, https://doi.org/10.5194/acp-24-7481-2024, https://doi.org/10.5194/acp-24-7481-2024, 2024
Short summary
Short summary
We developed a multi-air-pollutant inversion system to estimate non-methane volatile organic compound (NMVOC) emissions using TROPOMI formaldehyde retrievals. We found that the inversion significantly improved formaldehyde simulations and reduced NMVOC emission uncertainties. The optimized NMVOC emissions effectively corrected the overestimation of O3 levels, mainly by decreasing the rate of the RO2 + NO reaction and increasing the rate of the NO2 + OH reaction.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
Short summary
Short summary
We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
Peng Li, Rong Shang, Jing M. Chen, Mingzhu Xu, Xudong Lin, Guirui Yu, Nianpeng He, and Li Xu
Biogeosciences, 21, 625–639, https://doi.org/10.5194/bg-21-625-2024, https://doi.org/10.5194/bg-21-625-2024, 2024
Short summary
Short summary
The amount of carbon that forests gain from the atmosphere, called net primary productivity (NPP), changes a lot with age. These forest NPP–age relationships could be modeled from field survey data, but we are not sure which model works best. Here we tested five different models using 3121 field survey samples in China, and the semi-empirical mathematical (SEM) function was determined as the optimal. The relationships built by SEM can improve China's forest carbon modeling and prediction.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
Short summary
Short summary
The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Shanlei Sun, Zaoying Bi, Jingfeng Xiao, Yi Liu, Ge Sun, Weimin Ju, Chunwei Liu, Mengyuan Mu, Jinjian Li, Yang Zhou, Xiaoyuan Li, Yibo Liu, and Haishan Chen
Earth Syst. Sci. Data, 15, 4849–4876, https://doi.org/10.5194/essd-15-4849-2023, https://doi.org/10.5194/essd-15-4849-2023, 2023
Short summary
Short summary
Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
Short summary
Short summary
We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Sinan Li, Li Zhang, Jingfeng Xiao, Rui Ma, Xiangjun Tian, and Min Yan
Hydrol. Earth Syst. Sci., 26, 6311–6337, https://doi.org/10.5194/hess-26-6311-2022, https://doi.org/10.5194/hess-26-6311-2022, 2022
Short summary
Short summary
Accurate estimation for global GPP and ET is important in climate change studies. In this study, the GLASS LAI, SMOS, and SMAP datasets were assimilated jointly and separately in a coupled model. The results show that the performance of joint assimilation for GPP and ET is better than that of separate assimilation. The joint assimilation in water-limited regions performed better than in humid regions, and the global assimilation results had higher accuracy than other products.
Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
Short summary
Short summary
Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
Fei Jiang, Weimin Ju, Wei He, Mousong Wu, Hengmao Wang, Jun Wang, Mengwei Jia, Shuzhuang Feng, Lingyu Zhang, and Jing M. Chen
Earth Syst. Sci. Data, 14, 3013–3037, https://doi.org/10.5194/essd-14-3013-2022, https://doi.org/10.5194/essd-14-3013-2022, 2022
Short summary
Short summary
A 10-year (2010–2019) global monthly terrestrial NEE dataset (GCAS2021) was inferred from the GOSAT ACOS v9 XCO2 product. It shows strong carbon sinks over eastern N. America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia. It has good quality and can reflect the impacts of extreme climates and large-scale climate anomalies on carbon fluxes well. We believe that this dataset can contribute to regional carbon budget assessment and carbon dynamics research.
Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han
Earth Syst. Dynam., 13, 833–849, https://doi.org/10.5194/esd-13-833-2022, https://doi.org/10.5194/esd-13-833-2022, 2022
Short summary
Short summary
We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary
Short summary
In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, https://doi.org/10.5194/acp-21-2917-2021, 2021
Short summary
Short summary
Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Chenchao Zhan, Min Xie, Chongwu Huang, Jane Liu, Tijian Wang, Meng Xu, Chaoqun Ma, Jianwei Yu, Yumeng Jiao, Mengmeng Li, Shu Li, Bingliang Zhuang, Ming Zhao, and Dongyang Nie
Atmos. Chem. Phys., 20, 13781–13799, https://doi.org/10.5194/acp-20-13781-2020, https://doi.org/10.5194/acp-20-13781-2020, 2020
Short summary
Short summary
The Yangtze River Delta (YRD) region has been suffering from severe ozone (O3) pollution in recent years. Synoptic systems, like typhoons, can have a significant effect on O3 episodes. However, research on landfall typhoons affecting O3 in the YRD is limited. This work aims to reveal the main processes of landfall typhoons affecting surface O3 and estimate health impacts of O3 during the study period in the YRD, which can be useful for taking reasonable pollution control measures in this area.
Yi Zheng, Ruoque Shen, Yawen Wang, Xiangqian Li, Shuguang Liu, Shunlin Liang, Jing M. Chen, Weimin Ju, Li Zhang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, https://doi.org/10.5194/essd-12-2725-2020, 2020
Short summary
Short summary
Accurately reproducing the interannual variations in vegetation gross primary production (GPP) is a major challenge. A global GPP dataset was generated by integrating the regulations of several major environmental variables with long-term changes. The dataset can effectively reproduce the spatial, seasonal, and particularly interannual variations in global GPP. Our study will contribute to accurate carbon flux estimates at long timescales.
Pengfei Han, Ning Zeng, Tom Oda, Xiaohui Lin, Monica Crippa, Dabo Guan, Greet Janssens-Maenhout, Xiaolin Ma, Zhu Liu, Yuli Shan, Shu Tao, Haikun Wang, Rong Wang, Lin Wu, Xiao Yun, Qiang Zhang, Fang Zhao, and Bo Zheng
Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, https://doi.org/10.5194/acp-20-11371-2020, 2020
Short summary
Short summary
An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation, and reducing emissions.
Cited articles
Andres, R. J., Gregg, J. S., Losey, L., Marland, G., and Boden, T. A.:
Monthly, global emissions of carbon dioxide from fossil fuel consumption.
Tellus B, 63, 309–327, https://doi.org/10.1111/j.1600-0889.2011.00530.x,
2011.
Archer, C. L. and Jacobson, M. Z.: Evaluation of global wind power, J.
Geophys. Res., 110, D12110, https://doi.org/10.1029/2004JD005462, 2005.
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, 20170304,
https://doi.org/10.1098/rstb.2017.0304, 2018.
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B., Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, 2013.
Beguería, S., Vicente-Serrano, S. M., and Angulo-Martinez, M.: A
Multiscalar Global Drought Dataset: The SPEIbase: A New Gridded Product for
the Analysis of Drought Variability and Impacts, B. Am.
Meteorol. Soc., 91, 1351–1356, https://doi.org/10.1175/2010BAMS2988.1, 2010.
Bruhwiler, L. M. P., Michalak, A. M., Peters, W., Baker, D. F., and Tans, P.: An improved Kalman Smoother for atmospheric inversions, Atmos. Chem. Phys., 5, 2691–2702, https://doi.org/10.5194/acp-5-2691-2005, 2005.
Buchmann, N. and Schulze, E.D.: Net CO2 and H2O fluxes of
terrestrial ecosystems, Global Biogeochem. Cyc., 13, 751–760,
https://doi.org/10.1029/1999GB900016, 1999.
Buitenhuis, E., Le Quéré, C., Aumont, O., Beaugrand, G., Bunker, A.,
Hirst, A., Ikeda, T., O'Brien, T., Piontkovski, S., and Straile, D.:
Biogeochemical fluxes through mesozooplankton, Global Biogeochem. Cy., 20,
GB2003, https://doi.org/10.1029/2005GB002511, 2006.
Botta, A., Ramankutty, N., and Foley, J. A.: LBA-ECO LC-04 IBIS model
simulations for the Amazon and Tocantins Basins: 1921–1998, ORNL DAAC, Oak
Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1139, 2012.
Bousquet, P., Peylin, P., Ciais, P., Le Quéré, C., Friedlingstein,
P., and Tans, P. P.: Regional Changes in Carbon Dioxide Fluxes of Land and
Oceans Since 1980, Science, 290, 1342–1346,
https://doi.org/10.1126/science.290.5495.1342, 2000.
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.
Chen, J. M., Ju, W., Ciais, P., Viovy, N., Liu, R. G., Liu, Y., and Lu, X.
H.: Vegetation structural change since 1981 significantly enhanced the
terrestrial carbon sink, Nat. Commun., 10, 4259,
https://doi.org/10.1038/s41467-019-12257-8, 2019.
Chen, J. M., Ju, W., Cihlar, J., Price, D., Liu, J., Chen, W., Pan, J.,
Black, A., and Barr, A.: Spatial distribution of carbon sources and sinks in
Canada's forests, Tellus B, 55, 622–642,
https://doi.org/10.1034/j.1600-0889.2003.00036.x, 2003.
Chen, J. M., Liu, J., Cihlar, J., and Goulden, M. L.: Daily canopy
photosynthesis model through temporal and spatial scaling for remote sensing
applications, Ecol. Modell., 124, 99–119,
https://doi.org/10.1016/S0304-3800(99)00156-8, 1999.
Chen, J. M., Menges, C. H., and Leblanc, S. G.: Global mapping of foliage
clumping index using multi-angular satellite data, Remote Sens. Environ., 97, 447–457, https://doi.org/10.1016/j.rse.2005.05.003, 2005.
Chevallier, F., Breon, F.-M., and Rayner, P. J.: 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.-Atmos., 112, d09307, https://doi.org/10.1029/2006JD007375, 2007.
Chevallier, F., Palmer, P. I., Feng, L., Boesch, H., O'Dell, C. W., and
Bousquet, P.: Toward robust and consistent regional CO2 flux estimates
from in situ and spaceborne measurements of atmospheric CO2, Geophys.
Res. Lett., 41, 1065–1070, https://doi.org/10.1002/2013GL058772, 2014.
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.
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V.,
Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F., De
Noblet, N., Friend, A. D., Friedlingstein, P., Grünwald, T., Heinesch, B.,
Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci, G.,
Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S.,
Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala, T., and
Valentini, R.: Europewide reduction in primary productivity caused by the
heat and drought in 2003, Nature, 437, 529–533,
https://doi.org/10.1038/nature03972, 2005.
Ciais, P., Bombelli, A., Williams, M., Piao, S.L., Chave, J., Ryan, C.M.,
Henry, M., Brender, P., and Valentini, R.: The carbon balance of Africa:
synthesis of recent research studies, Philos. T. R. Soc. S.-A., 369, 2038–2057, https://doi.org/10.1098/rsta.2010.0328, 2011.
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., 113, D05305, https://doi.org/10.1029/2006JD008336, 2008.
Crisp, D., Fisher, B. M., O'Dell, C., Frankenberg, C., Basilio, R., Bösch, H., Brown, L. R., Castano, R., Connor, B., Deutscher, N. M., Eldering, A., Griffith, D., Gunson, M., Kuze, A., Mandrake, L., McDuffie, J., Messerschmidt, J., Miller, C. E., Morino, I., Natraj, V., Notholt, J., O'Brien, D. M., Oyafuso, F., Polonsky, I., Robinson, J., Salawitch, R., Sherlock, V., Smyth, M., Suto, H., Taylor, T. E., Thompson, D. R., Wennberg, P. O., Wunch, D., and Yung, Y. L.: The ACOS CO2 retrieval algorithm – Part II: Global XCO2 data characterization, Atmos. Meas. Tech., 5, 687–707, https://doi.org/10.5194/amt-5-687-2012, 2012.
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 XCO2 data, Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, 2014.
Deng, F., Jones, D. B. A., O'Dell, C. W., Nassar, R., and Parazoo, N. C.:
Combining GOSAT XCO2 observations over land and ocean to improve
regional CO2 flux estimates, J. Geophys. Res.-Atmos., 121, 1896–1913,
https://doi.org/10.1002/2015JD024157, 2016.
Detmers, R. G., Hasekamp, O., Aben, I., Houweling, S., van Leeuwen, T. T.,
Butz, A., Landgraf, J., Köhler, P., Guanter, L., and Poulter, B.:
Anomalous carbon uptake in Australia as seen by GOSAT, Geophys. Res. Lett.,
42, 8177–8184, https://doi.org/10.1002/2015GL065161, 2015.
Dlugokencky, E. and Tans, P.: Trends in atmospheric carbon dioxide,
National Oceanic & Atmospheric Administration, Earth System Research
Laboratory (NOAA/ESRL), available at:
http://www.esrl.noaa.gov/gmd/ccgg/trends/global.html (last access: 10 March 2020), 2018.
Doughty, C. E., Metcalfe, D. B., Girardin, C. A. J., Amezquita, F. F.,
Cabrera, D. G., Huasco, W. H., Silva-Espejo, J. E., Araujo-Murakami, A., da
Costa, M. C., Rocha, W., Feldpausch, T. R., Mendoza, A. L. M., da Costa, A.
C. L., Meir, P., Phillips, O. L., and Malhi, Y.: Drought impact on forest
carbon dynamics and fluxes in Amazonia, Nature, 519, 78–82,
https://doi.org/10.1038/nature14213, 2015.
Dolman, A. J., Shvidenko, A., Schepaschenko, D., Ciais, P., Tchebakova, N., Chen, T., van der Molen, M. K., Belelli Marchesini, L., Maximov, T. C., Maksyutov, S., and Schulze, E.-D.: An estimate of the terrestrial carbon budget of Russia using inventory-based, eddy covariance and inversion methods, Biogeosciences, 9, 5323–5340, https://doi.org/10.5194/bg-9-5323-2012, 2012.
Emmons, L. K., Walters, S., Hess, P. G., Lamarque, J.-F., Pfister, G. G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S. L., and Kloster, S.: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3, 43–67, https://doi.org/10.5194/gmd-3-43-2010, 2010.
Enting, I. G. and Newsam, G. N.: Atmospheric constituent inversion
problems: Implications for baseline monitoring, J. Atmos. Chem., 11, 69–87, https://doi.org/10.1007/BF00053668, 1990.
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, e2019JD031808, https://doi.org/10.1029/2019JD031808, 2020.
Feng, L., Palmer, P. I., Bösch, H., and Dance, S.: Estimating surface CO2 fluxes from space-borne CO2 dry air mole fraction observations using an ensemble Kalman Filter, Atmos. Chem. Phys., 9, 2619–2633, https://doi.org/10.5194/acp-9-2619-2009, 2009.
Feng, L., Palmer, P. I., Parker, R. J., Deutscher, N. M., Feist, D. G., Kivi, R., Morino, I., and Sussmann, R.: Estimates of European uptake of CO2 inferred from GOSAT XCO2 retrievals: sensitivity to measurement bias inside and outside Europe, Atmos. Chem. Phys., 16, 1289–1302, https://doi.org/10.5194/acp-16-1289-2016, 2016.
Feng, L., Palmer, P. I., Bösch, H., Parker, R. J., Webb, A. J., Correia, C. S. C., Deutscher, N. M., Domingues, L. G., Feist, D. G., Gatti, L. V., Gloor, E., Hase, F., Kivi, R., Liu, Y., Miller, J. B., Morino, I., Sussmann, R., Strong, K., Uchino, O., Wang, J., and Zahn, A.: Consistent regional fluxes of CH4 and CO2 inferred from GOSAT proxy XCH4 : XCO2 retrievals, 2010–2014, Atmos. Chem. Phys., 17, 4781–4797, https://doi.org/10.5194/acp-17-4781-2017, 2017.
Gatti, L. V., Gloor, M., Miller, J. B., Doughty, C. E., Malhi, Y.,
Domingues, L. G., Basso, L. S., Martinewski, A., Correia, C. S. C., Borges,
V. F., Freitas, S., Braz, R., Anderson, L. O., Rocha, H., Grace, J.,
Phillips, O. L., and Lloyd, J.: Drought sensitivity of Amazonian carbon
balance revealed by atmospheric measurements, Nature 506, 76–80,
https://doi.org/10.1038/nature12957, 2014.
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.
Hayes, D. J., Vargas, R., Alin, S. R., Conant, R. T., Hutyra, L. R.,
Jacobson, A. R., Kurz, W. A., Liu, S., McGuire, A. D., Poulter, B., and
Woodall, C. W.: Chapter 2: The North American carbon budget, in: Second State
of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report, edited by:Cavallaro, N., G. Shrestha, R. Birdsey, M. A. Mayes, R. G. Najjar, S. C.
Reed, P. Romero-Lankao, and Z. Zhu, U.S. Global Change Research
Program, Washington, DC, USA, 71–108, https://doi.org/10.7930/SOCCR2.2018.Ch2, 2018.
Hayes, D. J., McGuire, A. D., Kicklighter, D. W., Gurney, K. R., Burnside,
T. J., and Melillo, J. M.: Is the northern high-latitude land-based CO2
sink weakening?, Global Biogeochem. Cy., 25, GB3018,
https://doi.org/10.1029/2010GB003813, 2011.
He, L., Chen, J., Pisek, J., Schaaf, C. B., and Strahler, A. H.: Global
clumping index map derived from the MODIS BRDF product, Remote Sens.
Environ., 119, 118–130, https://doi.org/10.1016/j.rse.2011.12.008, 2012.
Houtekamer, P. L. and Mitchell, H. L.: A sequential ensemble Kalman filter
for atmospheric data assimilation, Mon. Weather Rev., 129, 123–137,
https://doi.org/10.1175/1520-0493(2001)129<0123:ASEKFF>2.0.CO;2, 2001.
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 inverse models for estimating
sources and sinks of CO2 using GOSAT measurements, J. Geophys.
Res.-Atmos., 120, 5253–5266, https://doi.org/10.1002/2014JD022962, 2015.
Hungershoefer, K., Breon, F.-M., Peylin, P., Chevallier, F., Rayner, P., Klonecki, A., Houweling, S., and Marshall, J.: Evaluation of various observing systems for the global monitoring of CO2 surface fluxes, Atmos. Chem. Phys., 10, 10503–10520, https://doi.org/10.5194/acp-10-10503-2010, 2010.
IPCC, 2014: Climate Change 2014: Synthesis Report, Contribution of Working
Groups I, II and III to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Pachauri, R. K. and Meyer, L. A., IPCC, Geneva, Switzerland, 151 pp., 2014.
Jiang, F.: Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System, Zenodo, https://doi.org/10.5281/zenodo.4500439, 2021.
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., Chen, J. M., Zhou, L. X., Ju, W. M., Zhang, H. F., Machida T.,
Ciais, P., Peters, W., Wang, H. M., Chen, B. Z., Liu, L. X., Zhang, C. H.,
Matsueda, H., and Sawa, Y.: A comprehensive estimate of recent carbon sinks
in China using both top-down and bottom-up approaches, Sci. Rep.,
6, 22130, https://doi.org/10.1038/srep22130, 2016.
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://10.1016/j.atmosenv.2018.05.060, 2018.
Ju, W. M., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., and Chen, B. Z.:
Modelling multi-year coupled carbon and water fluxes in a boreal aspen
forest, Agr. Forest Meteorol., 140, 136–151,
https://doi.org/10.1016/j.agrformet.2006.08.008, 2006.
Kadygrov, N., Maksyutov, S., Eguchi, N., Aoki, T., Nakazawa, T., Yokota, T.,
and Inoue, G.: Role of simulated GOSAT total column CO2 observations in
surface CO2 flux uncertainty reduction, J. Geophys. Res., 114, D21208,
https://doi.org/10.1029/2008JD011597, 2009.
Kang, J.-S., Kalnay, E., Miyoshi, T., Liu, J., and Fung, I.: Estimation of
surface carbon fluxes with an advanced data assimilation methodology, J.
Geophys. Res., 117, D24101, https://doi.org/10.1029/2012JD018259, 2012.
Koren, G., van Schaik, E., Araújo, A.C., Boersma, K.F., Gärtner, A.,
Killaars, L., Kooreman, M. L., Kruijt, B., van der Laan-Luijkx, I. T., Von
Randow, C., Smith, N. E., and Peters, W.: Widespread reduction in sun-induced
fluorescence from the Amazon during the 2015/2016 El Niño. Phil. Trans.
R. Soc. B, 373, 20170408, https://doi.org/10.1098/rstb.2017.0408, 2018.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near
infrared sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl.
Opt., 48, 6716, https://doi.org/10.1364/AO.48.006716, 2009.
Liu, Y., Liu, R. G., and Chen, J. M.: Retrospective retrieval of long-term
consistent global leaf area index (1981–2011) from combined AVHRR and MODIS
data, J. Geophys. Res., 117, G04003, https://doi.org/10.1029/2012JG002084,
2012.
Liu, J., Bowman, K., Parazoo, N. C., Bloom, A. A., Wunch, D., Jiang, Z.,
Gurney, K. R., and Schimel, D.: Detecting drought impact on terrestrial
biosphere carbon fluxes over contiguous US with satellite observations,
Environ. Res. Lett., 13, 095003,
https://doi.org/10.1088/1748-9326/aad5ef, 2018.
Liu, J., Bowman, K. W., Schimel, D. S., Parazoo, N. C., Jiang, Z., Lee, M.,
Bloom, A. A., Wunch, D., Frankenberg, C., Sun, Y., O'Dell, C. W., Gurney, K.
R., Menemenlis, D., Gierach, M., Crisp, D., and Eldering, A.: Contrasting
carbon cycle responses of the tropical continents to the 2015–2016 El
Niño, Science, 358, eaam5690, https://doi.org/10.1126/science.aam5690,
2017.
Ma, Z. H., Peng, C. H., Zhu, Q., Chen, H., Yu, G. R., Li, W. Z., Zhou, X.
L., Wang, W. F., and Zhang, W. H.: Regional drought-induced reduction in the
biomass carbon sink of Canada's boreal forests, P. Natl. Acad. Sci. USA, 109, 2423–2427, https://doi.org/10.1073/pnas.1111576109, 2012.
Maksyutov, S., Takagi, H., Valsala, V. K., Saito, M., Oda, T., Saeki, T., Belikov, D. A., Saito, R., Ito, A., Yoshida, Y., Morino, I., Uchino, O., Andres, R. J., and Yokota, T.: Regional CO2 flux estimates for 2009–2010 based on GOSAT and ground-based CO2 observations, Atmos. Chem. Phys., 13, 9351–9373, https://doi.org/10.5194/acp-13-9351-2013, 2013.
Miller, C. E., Crisp, D., DeCola, P. L., Olsen, S. C., Randerson, J. T.,
Michalak, A. M., Alkhaled, A., Rayner, P., Jacob, D. J., Suntharalingam, P.,
Jones, D. B. A., Denning, A. S., Nicholls, M. E., Doney, S. C., Pawson, S.,
Boesch, H., Connor, B. J., Fung, I. Y., O'Brien, D., Salawitch, R. J.,
Sander, S. P., Sen, B., Tans, P., Toon, G. C., Wennberg, P. O., Wofsy, S. C.,
Yung, Y. L., and Law, R. M.: Precision requirements for space-based
XCO2 data, J. Geophys. Res., 112, D10314,
https://doi.org/10.1029/2006JD007659, 2007.
Miyazaki, K., Maki, T., Patra, P., and Nakazawa, T.: Assessing the impact of
satellite, aircraft, and surface observations on CO2 flux estimation
using an ensemble-based 4-D data assimilation system, J. Geophys. Res., 116,
D16306, https://doi.org/10.1029/2010JD015 366, 2011.
Miyazaki, K., Eskes, H. J., Sudo, K., Takigawa, M., van Weele, M., and Boersma, K. F.: Simultaneous assimilation of satellite NO2, O3, CO, and HNO3 data for the analysis of tropospheric chemical composition and emissions, Atmos. Chem. Phys., 12, 9545–9579, https://doi.org/10.5194/acp-12-9545-2012, 2012.
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.
Nilsson S., Vaganov, E. A., Shvidenko, A., Stolbovoi, V., Rozhkov, V. A.,
McCallum, I., and Jonas, M.: Carbon budget of vegetation ecosystems of
Russia, Doklady Earth Sci., 363A, 1281–1283, 2003.
ObsPack: Cooperative Global Atmospheric Data Integration Project:
Multi-laboratory compilation of atmospheric carbon dioxide data for the
period 1957-2018; obspack_co2_1_GLOBALVIEWplus_ v5.0_ 2019_08_12; NOAA Earth System Research Laboratory, Global Monitoring Division, https://doi.org/10.25925/20190812, 2019.
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., Feng, L., Baker, D., Chevallier, F., Bösch, H., and
Somkuti, P.: Net carbon emissions from African biosphere dominate
pan-tropical atmospheric CO2 signal, Nat. Commun., 10, 3344,
https://doi.org/10.1038/s41467-019-11097-w, 2019.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A.,
Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., Ciais, P.,
Jackson, R. B., Pacala, S., McGuire, A. D., Piao, S., Rautiainen, A., Sitch,
S., and Hayes, D.: A large and persistent carbon sink in the world's
forests, Science, 333, 988–993, https://doi.org/10.1126/science.1201609,
2011.
Paulo, A. A., Rosa, R. D., and Pereira, L. S.: Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in Portugal, Nat. Hazards Earth Syst. Sci., 12, 1481–1491, https://doi.org/10.5194/nhess-12-1481-2012, 2012.
Peters, W., Miller, J. B., Whitaker, J., Denning, A. S., Hirsch, A., Krol,
M. C., Zupanski, D., Bruhwiler, L., and Tans, P. P.: An ensemble data
assimilation system to estimate CO2 surface fluxes from atmospheric
trace gas observations, J. Geophys. Res., 110, D24304,
https://doi.org/10.1029/2005JD006157, 2005.
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.
Peters, W., Krol, M. C., van der Werf, G. R., Houweling, S., Jones, C. D.,
Hughes, J., Schaefer, K., Masarie, K. A., Jacobson, A. R., Miller, J. B.,
Cho, C. H., Ramonet, M., Schmidt, M., Ciattaglia, L., Apadula, F., Helta,
D., Meinhardt, F., di Sarra, A. G., Piacentino, S., Sferlazzo, D., Aalto,
T., Hatakka, J., Strom, J., Haszpra, L., Meijer, H. A. J., van der Laan, S.,
Neubert, R. E. M., Jordan, A., Rodo, X., Morgui, J. A., Vermeulen, A. T.,
Popa, E., Rozanski, K., Zimnoch, M., Manning, A. C., Leuenberger, M.,
Uglietti, C., Dolman, A. J., Ciais, P., Heimann, M., and Tans, P. P.: Seven
years of recent European net terrestrial carbon dioxide exchange constrained
by atmospheric observations, Glob. Change Biol., 16, 1317–1337,
https://doi.org/10.1111/j.1365-2486.2009.02078.x, 2010.
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.
Phillips, O. L., Aragão, L., Lewis, S. L., Fisher, J. B., Lloyd, J.,
López-González, G., Malhi, Y., Monteagudo, A., Peacock, J., Quesada, C. A.,
van der Heijden, G., Almeida, S., Amaral, I., Arroyo, L., Aymard, G., Baker,
T. R., Bánki, O., Blanc, L., Bonal, D., Brando, P., Chave, J., de Oliveira,
A. C. A., Cardozo, N. D., Czimczik, C. I., Feldpausch, T. R., Freitas, M.
A., Gloor, E., Higuchi, N., Jiménez, E., Lloyd, G., Meir, P., Mendoza, C.,
Morel, A., Neill, D. A., Nepstad, D., Patiño, S., Peñuela, M. C., Prieto,
A., Ramírez, F., Schwarz, M., Silva, J., Silveira, M., Thomas, A. S., ter
Steege, H., Stropp, J., Vásquez, R., Zelazowski, P., Dávila, E. A.,
Andelman, S., Andrade, A., Chao, K. J., Erwin, T., Di Fiore, A., Honorio,
E., Keeling, H., Killeen, T. J., Laurance, W. F., Cruz, A. P., Pitman, N. C.
A., Vargas, P. N., Ramírez-Angulo, H., Rudas, A., Salamao, R., Silva, N.,
Terborgh, J., and Torres-Lezama, A.: Drought sensitivity of the Amazon
forest, Science, 323, 1344–1347, https://doi.org/10.1126/science.1164033,
2009.
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais,
P., Friedlingstein, P., and Sitch, S.: Interannual variation of terrestrial
carbon cycle: Issues and perspectives, Glob. Change Biol., 26, 300–318,
https://doi.org/10.1111/gcb.14884, 2020.
Rödenbeck, C.: Estimating CO2 sources and sinks from atmospheric
mixing ratio measurements using a global inversion of atmospheric transport,
Technical Report 6, Max Planck Institute for Biogeochemistry, Jena, 2005.
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, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1293, 2017.
Saeki, T., Maksyutov, S., Saito, M., Valsala, V., Oda, T., Andres, R. J.,
Belikov, D., Tans, P., Dlugokencky, E., Yoshida, Y., Morino, I., Uchino, O.,
and Yokota, T.: Inverse modeling of CO2 fluxes using GOSAT data and
multi-year ground-based observations, SOLA, 9, 45–50,
https://doi.org/10.2151/sola.2013-011, 2013a.
Saeki, T., Maksyutov, S., Sasakawa, M., Machida, T., Arshinov, M., Tans, P.,
Conway, T. J., Saito, M., Valsala, V., Oda, T., Andres, R. J., and Belikov,
D.: Carbon flux estimation for Siberia by inverse modeling constrained by
aircraft and tower CO2 measurements, J. Geophys. Res.-Atmos., 118,
1100–1122, https://doi.org/10.1002/jgrd.50127, 2013b.
Scholze, M., Kaminski, T., Knorr, W., Voßbeck, M., Wu, M., Ferrazzoli,
P., Kerr, Y., Mialon, A., Richaume P., Rodríguez-Fernández, N.,
Vittucci, C., Wigneron, J.-P., Mecklenburg, S., and Drusch, M.: Mean
European carbon sink over 2010–2015 estimated by simultaneous assimilation
of atmospheric CO2, soil moisture, and vegetation optical depth,
Geophys. Res. Lett., 46, 13796–13803, https://doi.org/10.1029/2019GL085725, 2019.
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, Sola, 7, 161-164, https://doi.org/10.2151/sola.2011-041, 2011.
Takahashi, T., Sutherland, S. C., Wanninkhof, R., Sweeney, C., Feely, R. A.,
Chipman, D. W., Hales, B., Friederich, G., Chavez, F., Sabine, C., Watson,
A., Bakker, D. C. E., Schuster, U., Metzl, N., Yoshikawa-Inoue, H., Ishii,
M., Midorikawa, T., Nojiri, Y., Körtzinger, A., Steinhoff, T., Hoppema,
M., Olafsson, J., Arnarson, T. S., Tilbrook, B., Johannessen, T., Olsen, A.,
Bellerby, R., Wong, C. S., Delille, B., Bates, N. R., and de Baar, H. J. W.:
Climatological mean and decadal change in surface ocean pCO2, and net
sea-air CO2 flux over the global oceans, Deep Sea Res. Pt. II, 56, 554–577, https://doi.org/10.1016/j.dsr2.2008.12.009, 2009.
van der Laan-Luijkx, I. T., van der Velde, I. R., Krol, M. C., Gatti, L. V.,
Domingues, L. G., Correia, C. S. C., Miller, J. B., Gloor, M., van Leeuwen,
T. T., Kaiser, J. W., Wiedinmyer, C., Basu, S., Clerbaux, C., and Peters,
W.: Response of the Amazon carbon balance to the 2010 drought derived with
CarbonTracker South America, Global Biogeochem. Cy., 29, 1092–1108,
https://doi.org/10.1002/2014GB005082, 2015.
Vicente-Serrano, S. M., Gouveia, C., Camarero, J. J., Beguería, S.,
Trigo, R., López-Moreno, J. I., Azorín-Molina, C., Pasho, E.,
Lorenzo-Lacruz, J., Revuelto, J., and Morán-Tejeda, E.: Response of
vegetation to drought time-scales across global land biomes, P. Natl. Acad.
Sci. USA, 110, 52–57, https://doi.org/10.1073/pnas.1207068110, 2013.
Wang, H., Jiang, F., Wang, J., Ju, W., and Chen, J. M.: Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals, Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, 2019.
Wang, J., Zeng, N., Wang, M., Jiang, F., Wang, H., and Jiang, Z.: Contrasting terrestrial carbon cycle responses to the 1997/98 and 2015/16 extreme El Niño events, Earth Syst. Dynam., 9, 1–14, https://doi.org/10.5194/esd-9-1-2018, 2018b.
Wang, J. S., Kawa, S. R., Collatz, G. J., Sasakawa, M., Gatti, L. V., Machida, T., Liu, Y., and Manyin, M. E.: A global synthesis inversion analysis of recent variability in CO2 fluxes using GOSAT and in situ observations, Atmos. Chem. Phys., 18, 11097–11124, https://doi.org/10.5194/acp-18-11097-2018, 2018a.
Wang, J. S., Kawa, S. R., Collatz, G. J., Sasakawa, M., Gatti, L. V., Machida, T., Liu, Y., and Manyin, M. E.: A global synthesis inversion analysis of recent variability in CO2 fluxes using GOSAT and in situ observations, Atmos. Chem. Phys., 18, 11097–11124, https://doi.org/10.5194/acp-18-11097-2018, 2018b.
Whitaker, J. S. and Hamill, T. M.: Ensemble data assimilation without
perturbed observations, Mon. Weather Rev., 130, 1913–1924,
https://doi.org/10.1175/1520-0493(2002)130<1913:Edawpo>2.0.Co;2, 2002.
Wolf, S., Keenan, T. F., Fisher, J. B., Baldocchi, D. D., Desai, A. R.,
Richardson, A. D., Scott, R. L., Law, B. E., Litvak, M. E., Brunsell, N. A.,
Peters, W., and van der Laan-Luijkx, I. T.: Warm spring reduced carbon cycle
impact of the 2012 US summer drought, P. Natl. Acad. Sci. USA, 113, 5880–5885, https://doi.org/10.1073/pnas.1519620113, 2016.
Wunch, D., Wennberg, P. O., Toon, G. C., Connor, B. J., Fisher, B., Osterman, G. B., Frankenberg, C., Mandrake, L., O'Dell, C., Ahonen, P., Biraud, S. C., Castano, R., Cressie, N., Crisp, D., Deutscher, N. M., Eldering, A., Fisher, M. L., Griffith, D. W. T., Gunson, M., Heikkinen, P., Keppel-Aleks, G., Kyrö, E., Lindenmaier, R., Macatangay, R., Mendonca, J., Messerschmidt, J., Miller, C. E., Morino, I., Notholt, J., Oyafuso, F. A., Rettinger, M., Robinson, J., Roehl, C. M., Salawitch, R. J., Sherlock, V., Strong, K., Sussmann, R., Tanaka, T., Thompson, D. R., Uchino, O., Warneke, T., and Wofsy, S. C.: A method for evaluating bias in global measurements of CO2 total columns from space, Atmos. Chem. Phys., 11, 12317–12337, https://doi.org/10.5194/acp-11-12317-2011, 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) XCO2 measurements with TCCON, Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, 2017.
Zamolodchikov, D. G., Grabovskii, V. I., Shulyak, P. P., and Chestnykh, O.
V.: Recent decrease in carbon sink to Russian forests, Dokl. Biol.
Sci., 476, 200–202, https://doi.org/10.1134/S0012496617050064, 2017.
Zhang, S., Zheng, X., Chen, J. M., Chen, Z., Dan, B., Yi, X., Wang, L., and Wu, G.: A global carbon assimilation system using a modified ensemble Kalman filter, Geosci. Model Dev., 8, 805–816, https://doi.org/10.5194/gmd-8-805-2015, 2015.
Zhao, M. S. and Running, S. W.: Drought-Induced Reduction in Global
Terrestrial Net Primary Production from 2000 Through 2009, Science, 329,
940–943, https://doi.org/10.1126/science.1192666, 2010.
Zhang, H. F., Chen, B. Z., van der Laan-Luijk, I. T., Machida, T., Matsueda, H., Sawa, Y., Fukuyama, Y., Langenfelds, R., van der Schoot, M., Xu, G., Yan, J. W., Cheng, M. L., Zhou, L. X., Tans, P. P., and Peters, W.: Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO2 observations for the period 2006–2010, Atmos. Chem. Phys., 14, 5807–5824, https://doi.org/10.5194/acp-14-5807-2014, 2014.
Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao,
S., Nemani, R. R., and Myneni, R. B.: Global Data Sets of Vegetation Leaf
Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation
(FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS)
Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011,
Remote Sens., 5, 927–948, https://doi.org/10.3390/rs5020927, 2013.
Short summary
We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using...
Altmetrics
Final-revised paper
Preprint