Articles | Volume 25, issue 2
https://doi.org/10.5194/acp-25-867-2025
© Author(s) 2025. 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-25-867-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2025
Research article |
| 22 Jan 2025
| 22 Jan 2025
The role of OCO-3 XCO2 retrievals in estimating global terrestrial net ecosystem exchanges
Xingyu Wang
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
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, 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
Zhengqi Zhang
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
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Wei He
Zhejiang Carbon Neutral Innovation Institute, Zhejiang University of Technology, Hangzhou, 310014, China
Weimin Ju
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, 210023, China
Jing M. Chen
Department of Geography and Planning, University of Toronto, Toronto, Ontario, M5S 3G3, Canada
School of Geographical Sciences, Fujian Normal University, Fuzhou, 350007, China
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EGUsphere, https://doi.org/10.5194/egusphere-2026-5193, https://doi.org/10.5194/egusphere-2026-5193, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Northern peatlands store vast amounts of carbon, but their response to climate change remains uncertain. We compared 15 ecosystem models with observations from a long-term warming and elevated carbon dioxide experiment in Minnesota. Models differed widely in their carbon responses, reflecting differences in ecosystem processes and model parameters. The results identify priorities for improving peatland models and projections of future carbon–climate feedbacks.
Shuo Liu, Zeping Jin, Ziyi Chen, Haolin Li, Zihan Fan, Shaohui Li, Haiwang Fu, Wei He, Kunpeng Zang, Shuangxi Fang, and Peng Yan
Biogeosciences, 23, 5497–5513, https://doi.org/10.5194/bg-23-5497-2026, https://doi.org/10.5194/bg-23-5497-2026, 2026
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We studied how planting green manure between tea rows affects carbon dioxide release from tea fields. Mixing legume and grass species improved soil health, reduced emissions from tea rows, and stabilized carbon over time. Although inter-row areas released more carbon, overall emissions declined with continued intercropping. This shows that green manure can make tea farming more climate-friendly and sustainable.
Chengcheng Huang, Wei He, Brendan Byrne, Ngoc Tu Nguyen, Jingfeng Xiao, Hua Yang, Phillipe Ciais, Songhan Wang, Xing Li, Han Ma, Peipei Xu, Mengyao Zhao, Hui Chen, and Weimin Ju
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-418, https://doi.org/10.5194/essd-2026-418, 2026
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Shenpeng Qiu, Shuzhuang Feng, Fei Jiang, Chong Wei, Yusheng Shi, Mengwei Jia, Honglin Zhuang, Hengmao Wang, Yongguang Zhang, and Weimin Ju
EGUsphere, https://doi.org/10.5194/egusphere-2026-3241, https://doi.org/10.5194/egusphere-2026-3241, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Satellite measurements and a model were used to estimate China's CO2 emissions in winter 2022–2023. National total was 16 % higher than previous estimates. The Beijing-Tianjin-Hebei region showed higher emissions due to winter heating, while the Yangtze River Delta showed lower emissions. Emission drops during the Spring Festival holiday were also captured. This work offers a reliable, independent way to monitor CO2 emissions and support climate policies.
Hao Zheng, Jun Wang, Hao Zhou, Jingfeng Ding, Haijin Dai, Zhi Huang, Zishan Wang, Meirong Wang, Jianying Li, Hengmao Wang, Fei Jiang, and Weimin Ju
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-318, https://doi.org/10.5194/essd-2026-318, 2026
Revised manuscript under review for ESSD
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Lightning can trigger wildfires and severe storms, but long-term global records are limited. We reconstructed monthly land lightning density worldwide from 1979 to 2025 using weather data and machine-learning models trained on observations. The dataset captures observed lightning patterns and can support wildfire, climate, and air-quality studies.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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The Global Carbon Budget 2025 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 (1750–2025). 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.
Shengxi Bai, Huilin Chen, Zhen Zhang, Shushi Peng, Fei Jiang, Fei Li, Shuzhuang Feng, Yingqi Yan, Qidan Huang, and Yongguang Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4610, https://doi.org/10.5194/egusphere-2025-4610, 2026
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We examined methane emissions from coal mines in Shanxi Province, China’s major coal production region. Using satellite observations and advanced analysis, we found that rare but very large methane releases play a major role in total emissions. Policies to cut coal capacity initially reduced methane, but emissions rose again with production recovery. Our findings improve understanding of how energy policies affect climate pollution and offer a framework for better methane monitoring worldwide.
Ji Li, Xuguang Chi, Aijun Ding, Weimin Ju, Yongguang Zhang, Jing M. Chen, and Huilin Chen
Atmos. Meas. Tech., 19, 1763–1781, https://doi.org/10.5194/amt-19-1763-2026, https://doi.org/10.5194/amt-19-1763-2026, 2026
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Accurate measurement of methane's isotopic fingerprint is crucial for identifying its sources. However, water vapor interference and instrument drift can cause significant errors, especially in humid air. This study evaluated two calibration methods and found that calibrating for individual methane isotopes with a water vapor correction provided accurate and stable results for both dry and humid air. This highlights the need for robust calibration to ensure reliable methane source attribution.
Linying Ma, Jun Wang, Zishan Wang, Qian Zhang, Ran Yan, Zhi Huang, Yabin Ye, Hao Zheng, Shuyue Xiao, Xiaokang Zhang, Zhenhai Li, Hongzhang Wang, Tao Wei, Haijin Dai, Meirong Wang, and Xiuying Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2026-142, https://doi.org/10.5194/egusphere-2026-142, 2026
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From April to June 2024, the North China Plain experienced an extreme dry-hot event. Satellite data showed rapid crop growth in April but record-low levels in June under combined heat and drought stress. Consistent with vegetation signals, Yield statistics and field observations confirmed higher winter wheat yields but lower summer maize yields. Growth was enhanced by warming and carryover in April, dominated by carryover in May, and strongly limited by high vapor pressure deficit in June.
Jingjing Wu, Qiaoli Wu, Wei He, and Jie Jiang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W14-2025, 319–325, https://doi.org/10.5194/isprs-archives-XLVIII-4-W14-2025-319-2025, https://doi.org/10.5194/isprs-archives-XLVIII-4-W14-2025-319-2025, 2025
Wensi Ma, Qiaoli Wu, Wei He, and Jie Jiang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W14-2025, 227–235, https://doi.org/10.5194/isprs-archives-XLVIII-4-W14-2025-227-2025, https://doi.org/10.5194/isprs-archives-XLVIII-4-W14-2025-227-2025, 2025
Shuzhuang Feng, Fei Jiang, Yongguang Zhang, Huilin Chen, Honglin Zhuang, Shumin Wang, Shengxi Bai, Hengmao Wang, and Weimin Ju
Atmos. Chem. Phys., 25, 15121–15143, https://doi.org/10.5194/acp-25-15121-2025, https://doi.org/10.5194/acp-25-15121-2025, 2025
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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.
Yu Mao, Weimin Ju, Hengmao Wang, Liangyun Liu, Haikun Wang, Shuzhuang Feng, Mengwei Jia, and Fei Jiang
Atmos. Chem. Phys., 25, 14187–14204, https://doi.org/10.5194/acp-25-14187-2025, https://doi.org/10.5194/acp-25-14187-2025, 2025
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The Russia-Ukraine war caused significant NOx emission reductions in Ukraine, exceeding COVID-19 impacts. Using TROPOMI data, we found a 15% drop in 2022 and 8% in 2023, with Eastern Ukraine (frontline) seeing declines of 29% and 17%. Industry emissions fell most (34% in 2022), while war-related NOx partially offset reductions (8-10%). Emissions closely tracked military actions, revealing conflict’s disruptive effects on socio-economic activity and air pollution.
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
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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.
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
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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.
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
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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.
Lei Huang, Yong Luo, Jing M. Chen, Qiuhong Tang, Tammo Steenhuis, Wei Cheng, and Wen Shi
Earth Syst. Sci. Data, 16, 3993–4019, https://doi.org/10.5194/essd-16-3993-2024, https://doi.org/10.5194/essd-16-3993-2024, 2024
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Timely global terrestrial evapotranspiration (ET) data are crucial for water resource management and drought forecasting. This study introduces the VISEA algorithm, which integrates satellite data and shortwave radiation to provide daily 0.05° gridded near-real-time ET estimates. By employing a vegetation index–temperature method, this algorithm can estimate ET without requiring additional data. Evaluation results demonstrate VISEA's comparable accuracy with accelerated data availability.
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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.
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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.
The role of OCO-3 XCO2 retrievals in estimating global terrestrial carbon fluxes is...
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