Articles | Volume 16, issue 3
https://doi.org/10.5194/essd-16-1283-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-1283-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
13 Mar 2024
Data description paper |
| 13 Mar 2024
| 13 Mar 2024
Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations
Jiye Leng
Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Jing M. Chen
CORRESPONDING AUTHOR
Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Wenyu Li
Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Xiangzhong Luo
Department of Geography, National University of Singapore, 1 Arts Link, 117570, Singapore
Mingzhu Xu
School of Geographical Science, Fujian Normal University, Fuzhou 350007, China
Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Rong Wang
School of Geographical Science, Fujian Normal University, Fuzhou 350007, China
Cheryl Rogers
School of Earth, Environment and Society, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada
Bolun Li
School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yulin Yan
School of Geographical Science, Fujian Normal University, Fuzhou 350007, China
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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.
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
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Tea Thum, Tuuli Miinalainen, Outi Seppälä, Holly Croft, Cheryl Rogers, Ralf Staebler, Silvia Caldararu, and Sönke Zaehle
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Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
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Zhou Zang, Jane Liu, David Tarasick, Omid Moeini, Jianchun Bian, Jinqiang Zhang, Anne M. Thompson, Roeland Van Malderen, Herman G. J. Smit, Ryan M. Stauffer, Bryan J. Johnson, and Debra E. Kollonige
Atmos. Chem. Phys., 24, 13889–13912, https://doi.org/10.5194/acp-24-13889-2024, https://doi.org/10.5194/acp-24-13889-2024, 2024
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Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
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Ruiying Zhao, Xiangzhong Luo, Yuheng Yang, Luri Nurlaila Syahid, Chi Chen, and Janice Ser Huay Lee
Biogeosciences, 21, 5393–5406, https://doi.org/10.5194/bg-21-5393-2024, https://doi.org/10.5194/bg-21-5393-2024, 2024
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Honglei Wang, David W. Tarasick, Jane Liu, Herman G. J. Smit, Roeland Van Malderen, Lijuan Shen, Romain Blot, and Tianliang Zhao
Atmos. Chem. Phys., 24, 11927–11942, https://doi.org/10.5194/acp-24-11927-2024, https://doi.org/10.5194/acp-24-11927-2024, 2024
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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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Danyang Ma, Tijian Wang, Hao Wu, Yawei Qu, Jian Liu, Jane Liu, Shu Li, Bingliang Zhuang, Mengmeng Li, and Min Xie
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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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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.
Zhixiong Chen, Jane Liu, Xiushu Qie, Xugeng Cheng, Yukun Shen, Mengmiao Yang, Rubin Jiang, and Xiangke Liu
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A vigorous surface ozone surge event of stratospheric origin occurred in the North China Plain at night. Surface ozone concentrations were 40–50 ppbv higher than the corresponding monthly mean, whereas surface carbon monoxide concentrations declined abruptly, which confirmed the direct stratospheric intrusions to the surface. We further addressed the notion that a combined effect of the dying typhoon and mesoscale convective systems was responsible for this vigorous ozone surge.
Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, and Feng Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-452, https://doi.org/10.5194/essd-2021-452, 2022
Revised manuscript not accepted
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The dataset provided the vegetation photosynthetic phenology instead of traditional phenology to represent plant seasonal activities. This dataset had the latest period (2001–2020) and a fine spatial resolution (0.05 degree). Our phenology metrics revealed the spatial-temporal patterns of the multiple growing seasons in the Northern Hemisphere. The dataset will facilitate various research such as developing models, evaluating phenology shifts, and monitoring climate change worldwide.
Zhixiong Chen, Jane Liu, Xugeng Cheng, Mengmiao Yang, and Hong Wang
Atmos. Chem. Phys., 21, 16911–16923, https://doi.org/10.5194/acp-21-16911-2021, https://doi.org/10.5194/acp-21-16911-2021, 2021
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Using a large ensemble of typhoons, we investigate the impacts of evolving typhoons on tropospheric ozone and address the linkages between typhoon-affected meteorological conditions and ozone variations. The influences of typhoon-induced stratospheric intrusions on lower-troposphere ozone are also quantified. Thus, the results obtained in this study have important implications for a full understanding of the multifaced roles of typhoons in modulating tropospheric ozone variation.
Da Gao, Min Xie, Jane Liu, Tijian Wang, Chaoqun Ma, Haokun Bai, Xing Chen, Mengmeng Li, Bingliang Zhuang, and Shu Li
Atmos. Chem. Phys., 21, 5847–5864, https://doi.org/10.5194/acp-21-5847-2021, https://doi.org/10.5194/acp-21-5847-2021, 2021
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O3 has been increasing in recent years over the Yangtze River Delta region of China and is closely associated with dominant weather systems. Still, the study on the impact of changes in synoptic weather patterns (SWPs) on O3 variation is quite limited. This work aims to reveal the unique features of changes in each SWP under O3 variation and quantifies the effects of meteorological conditions on O3 variation. Our findings could be helpful in strategy planning for O3 pollution control.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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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.
Han Han, Yue Wu, Jane Liu, Tianliang Zhao, Bingliang Zhuang, Honglei Wang, Yichen Li, Huimin Chen, Ye Zhu, Hongnian Liu, Qin'geng Wang, Shu Li, Tijian Wang, Min Xie, and Mengmeng Li
Atmos. Chem. Phys., 20, 13591–13610, https://doi.org/10.5194/acp-20-13591-2020, https://doi.org/10.5194/acp-20-13591-2020, 2020
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Combining simulations from a global chemical transport model and a trajectory model, we find that black carbon aerosols from South Asia and East Asia contribute 77 % of the surface black carbon in the Tibetan Plateau. The Asian monsoon largely modulates inter-annual transport of black carbon from non-local regions to the Tibetan Plateau surface in most seasons, while inter-annual fire activities in South Asia influence black carbon concentration over the Tibetan Plateau surface mainly in spring.
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
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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.
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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.
We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration...
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