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
Related authors
No articles found.
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
This preprint is open for discussion and under review for Biogeosciences (BG).
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.
Tea Thum, Tuuli Miinalainen, Outi Seppälä, Holly Croft, Cheryl Rogers, Ralf Staebler, Silvia Caldararu, and Sönke Zaehle
Biogeosciences, 22, 1781–1807, https://doi.org/10.5194/bg-22-1781-2025, https://doi.org/10.5194/bg-22-1781-2025, 2025
Short summary
Short summary
Climate change has the potential to influence the carbon sequestration potential of terrestrial ecosystems, and here the nitrogen cycle is also important. We used the terrestrial biosphere model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) in a mixed deciduous forest in Canada. We investigated the usefulness of using the leaf area index and leaf chlorophyll content to improve the parameterization of the model. This work paves the way for using spaceborne observations in model parameterizations, also including information on the nitrogen cycle.
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 Discuss., https://doi.org/10.5194/essd-2024-574, https://doi.org/10.5194/essd-2024-574, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Forest age is critical for carbon cycle modelling 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 30-m resolution. By tracking forest disturbances, we annually update ages. Validation shows small errors for disturbed forests and larger for undisturbed forests. CAFA can enhance carbon cycle modelling and forest management in China.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-3745, https://doi.org/10.5194/egusphere-2024-3745, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and an air pollutant, whose distribution and time variability is mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences, but also consistently higher pre- than post-COVID trends.
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
Short summary
Short summary
The Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST) provides a global-scale, long-term ozone climatology that is horizontally and vertically resolved. In this study, we improved, updated and validated TOST from 1970 to 2021. Based on this TOST dataset, we characterized global ozone variations spatially in both the troposphere and stratosphere and temporally by season and decade. We also showed a stagnant lower stratospheric ozone variation since the late 1990s.
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
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
Short summary
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
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
Short summary
Short summary
Southeast Asia has been a global hot spot of land-use change over the past 50 years. Meanwhile, it also hosts some of the most carbon-dense and diverse ecosystems in the world. Here, we explore the impact of land-use change, along with other environmental factors, on the ecosystem in Southeast Asia. We find that elevated CO2 imposed a positive impact on vegetation greenness, but the positive impact was largely offset by intensive land-use changes in the region, particularly cropland expansion.
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
Short summary
Short summary
In this study, we identify 23 suitable pairs of sites from World Ozone and Ultraviolet Radiation Data Centre (WOUDC) and In-service Aircraft for a Global Observing System (IAGOS) datasets (1995 to 2021), compare the average vertical distributions of tropospheric O3 from ozonesonde and aircraft measurements, and analyze the differences based on ozonesonde type and station–airport distance.
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.
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.
Danyang Ma, Tijian Wang, Hao Wu, Yawei Qu, Jian Liu, Jane Liu, Shu Li, Bingliang Zhuang, Mengmeng Li, and Min Xie
Atmos. Chem. Phys., 23, 6525–6544, https://doi.org/10.5194/acp-23-6525-2023, https://doi.org/10.5194/acp-23-6525-2023, 2023
Short summary
Short summary
Increasing surface ozone (O3) concentrations have long been a significant environmental issue in China, despite the Clean Air Action Plan launched in 2013. Most previous research ignores the contributions of CO2 variations. Our study comprehensively analyzed O3 variation across China from various perspectives and highlighted the importance of considering CO2 variations when designing long-term O3 control policies, especially in high-vegetation-coverage areas.
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.
Zhixiong Chen, Jane Liu, Xiushu Qie, Xugeng Cheng, Yukun Shen, Mengmiao Yang, Rubin Jiang, and Xiangke Liu
Atmos. Chem. Phys., 22, 8221–8240, https://doi.org/10.5194/acp-22-8221-2022, https://doi.org/10.5194/acp-22-8221-2022, 2022
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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
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.
Han Han, Jane Liu, Lei Shu, Tijian Wang, and Huiling Yuan
Atmos. Chem. Phys., 20, 203–222, https://doi.org/10.5194/acp-20-203-2020, https://doi.org/10.5194/acp-20-203-2020, 2020
Short summary
Short summary
We statistically assessed the impacts of local and synoptic meteorology on daily surface ozone in eastern China in summer during 2013–2018. The results show that the meteorology described by a multiple linear regression model explains 43 % of variations in surface ozone. The most important local meteorological factors vary with location in eastern China. The maximum impact of the predominant synoptic pattern on surface ozone can reach ± 8 µg m-3 or ± 16 % of the daily mean over some regions.
Han Han, Jane Liu, Huiling Yuan, Tijian Wang, Bingliang Zhuang, and Xun Zhang
Atmos. Chem. Phys., 19, 12495–12514, https://doi.org/10.5194/acp-19-12495-2019, https://doi.org/10.5194/acp-19-12495-2019, 2019
Short summary
Short summary
In the East Asian middle and upper troposphere, foreign ozone is 0.8–4.8 times more than its native counterpart in all the seasons. At the East Asian surface, the annual mean concentrations of foreign ozone and native ozone are comparable, being approximately 20 ppbv. The seasonal and interannual variations in foreign ozone over East Asia are closely related to the East Asian monsoon.
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
Short summary
Short summary
The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Xiaojin Qian, Liangyun Liu, Holly Croft, and Jingming Chen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-228, https://doi.org/10.5194/bg-2019-228, 2019
Preprint withdrawn
Short summary
Short summary
The leaf maximum carboxylation rate (Vcmax) is a key photosynthesis parameter. We attempt to investigate whether a universal and stable relationship exists between leaf Vcmax25 and chlorophyll content across different C3 plant types from a plant physiological perspective and verify it using field experiments. The results confirm that leaf chlorophyll can be a reliable proxy for estimating Vcmax25, providing an operational approach for the global mapping of Vcmax25 across different plant types.
Debora Griffin, Kaley A. Walker, Ingo Wohltmann, Sandip S. Dhomse, Markus Rex, Martyn P. Chipperfield, Wuhu Feng, Gloria L. Manney, Jane Liu, and David Tarasick
Atmos. Chem. Phys., 19, 577–601, https://doi.org/10.5194/acp-19-577-2019, https://doi.org/10.5194/acp-19-577-2019, 2019
Short summary
Short summary
Ozone in the stratosphere is important to protect the Earth from UV radiation. Using measurements taken by the Atmospheric Chemistry Experiment satellite between 2005 and 2013, we examine different methods to calculate the ozone loss in the high Arctic and establish the altitude at which most of the ozone is destroyed. Our results show that the different methods agree within the uncertainties. Recommendations are made on which methods are most appropriate to use.
Jun Hu, Yichen Li, Tianliang Zhao, Jane Liu, Xiao-Ming Hu, Duanyang Liu, Yongcheng Jiang, Jianming Xu, and Luyu Chang
Atmos. Chem. Phys., 18, 16239–16251, https://doi.org/10.5194/acp-18-16239-2018, https://doi.org/10.5194/acp-18-16239-2018, 2018
Short summary
Short summary
Using observational and modeling studies, the importance of the mechanism driving regional O3 transport in the residual layer (RL) with respect to summer smog over the Yangtze River Delta region in eastern China was revealed. This mechanism was also examined in association with diurnal change in the atmospheric boundary layer. Regional O3 transport through the nocturnal RL is believed to have great implications for understanding urban and regional O3 pollution in this area.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
Short summary
Short summary
Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Han Han, Jane Liu, Huiling Yuan, Bingliang Zhuang, Ye Zhu, Yue Wu, Yuhan Yan, and Aijun Ding
Atmos. Chem. Phys., 18, 4251–4276, https://doi.org/10.5194/acp-18-4251-2018, https://doi.org/10.5194/acp-18-4251-2018, 2018
Short summary
Short summary
Imported African ozone peaks in the Asian middle and upper troposphere in March. The seasonality of African ozone influence on Asia is mainly driven by the seasonal swing of the ITCZ, the Hadley circulation, and the northern subtropical westerlies. The stronger the ITCZ over Africa in a boreal winter is, the more African ozone is transported to Asia that winter. The convective divergence over the ITCZ and the Somali jet are drivers of interhemispheric transport of African ozone.
Yang Liu, Ronggao Liu, Jan Pisek, and Jing M. Chen
Biogeosciences, 14, 1093–1110, https://doi.org/10.5194/bg-14-1093-2017, https://doi.org/10.5194/bg-14-1093-2017, 2017
Short summary
Short summary
Forest overstory and understory layers differ in carbon and water cycle regimes and phenology, as well as ecosystem functions. In this paper, overstory and understory LAI values were estimated separately for global needleleaf and deciduous broadleaf forests. This work would help us better understand the seasonal patterns of forest structure, evaluate the ecosystem functions and improve the modeling of the forest carbon and water cycles.
Mohammed K. Osman, David W. Tarasick, Jane Liu, Omid Moeini, Valerie Thouret, Vitali E. Fioletov, Mark Parrington, and Philippe Nédélec
Atmos. Chem. Phys., 16, 10263–10282, https://doi.org/10.5194/acp-16-10263-2016, https://doi.org/10.5194/acp-16-10263-2016, 2016
Short summary
Short summary
A new 3-D gridded climatology of CO has been developed by trajectory mapping of global MOZAIC-IAGOS in situ aircraft measurements. The dataset is archived monthly from 2001–2012 on a grid of 5 × 5deg × 1 km altitude. The dataset facilitates comparison of different years and seasons and offers insight into the global variation and trends of CO. Major CO sources are clearly visible. The dataset can be used as an a priori data for satellite retrieval and for air quality model validation and initialization.
Zhe Jiang, Kazuyuki Miyazaki, John R. Worden, Jane J. Liu, Dylan B. A. Jones, and Daven K. Henze
Atmos. Chem. Phys., 16, 6537–6546, https://doi.org/10.5194/acp-16-6537-2016, https://doi.org/10.5194/acp-16-6537-2016, 2016
Short summary
Short summary
We quantify the impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East, using the adjoint of the GEOS-Chem model with updated NOx emissions estimates from an ensemble Kalman filter. We show that the global total contribution of lightning NOx on free tropospheric O3 over the Middle East is about 2 times larger than that from global anthropogenic sources. The summertime free tropospheric O3 enhancement is primarily due to Asian NOx emissions.
Y. C. Jiang, T. L. Zhao, J. Liu, X. D. Xu, C. H. Tan, X. H. Cheng, X. Y. Bi, J. B. Gan, J. F. You, and S. Z. Zhao
Atmos. Chem. Phys., 15, 13331–13338, https://doi.org/10.5194/acp-15-13331-2015, https://doi.org/10.5194/acp-15-13331-2015, 2015
Short summary
Short summary
An O3 episode with high night-time O3 was observed before typhoon landing over southeastern China. Variations in the observed O3, NO2, CO and meteorology during Typhoon Hagibis event clearly suggest a substantial impact of the peripheral downdrafts in the tropical cyclone on the high O3 episode. This study provides observational evidence of typhoon-driven intrusion of O3 from the upper troposphere and lower stratosphere to surface air threatening to ambient air quality.
Y. Zhou, H. Mao, K. Demerjian, C. Hogrefe, and J. Liu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-27253-2015, https://doi.org/10.5194/acpd-15-27253-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
Baseline carbon monoxide (CO) and ozone (O3) were studied at seven rural sites in the Northeast U.S. during varying periods over 2001 – 2010. Baseline CO at all sites decreased significantly at a rate between -4.3 – -2.3 ppbv yr-1, while baseline O3 was relatively constant. Interannual and seasonal variations of baseline CO and O3 were related to increasing Asian emissions, NOx emissions reduction in urban areas, global biomass burning emissions, and meteorological conditions.
S. Zhang, X. Zheng, J. M. Chen, Z. Chen, B. Dan, X. Yi, L. Wang, and G. Wu
Geosci. Model Dev., 8, 805–816, https://doi.org/10.5194/gmd-8-805-2015, https://doi.org/10.5194/gmd-8-805-2015, 2015
Short summary
Short summary
A Global Carbon Assimilation System based on the Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
K. Ding, J. Liu, A. Ding, Q. Liu, T. L. Zhao, J. Shi, Y. Han, H. Wang, and F. Jiang
Atmos. Chem. Phys., 15, 2843–2866, https://doi.org/10.5194/acp-15-2843-2015, https://doi.org/10.5194/acp-15-2843-2015, 2015
Short summary
Short summary
1. High CO abundances of 300-550 ppbv is shown in aircraft MOZAIC data between 700 and 300 hPa over East Asia in three episodes. Correspondingly, elevated CO is observed in satellite MOPITT data at similar altitudes.
2. GEOS-Chem and FLEXPART simulations reveal distinct uplifting processes for CO from fires and anthropogenic sources in the cases.
3. Topography in East Asia affects uplifting of CO in different ways.
4. The new version 5 MOPITT data can help diagnose vertical transport of CO.
H. Zheng, Y. Li, J. M. Chen, T. Wang, Q. Huang, W. X. Huang, L. H. Wang, S. M. Li, W. P. Yuan, X. Zheng, S. P. Zhang, Z. Q. Chen, and F. Jiang
Biogeosciences, 12, 1131–1150, https://doi.org/10.5194/bg-12-1131-2015, https://doi.org/10.5194/bg-12-1131-2015, 2015
Short summary
Short summary
Ecological models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) for an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state on 1 degree grid cells simultaneously.
F. Jiang, H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 10133–10144, https://doi.org/10.5194/acp-14-10133-2014, https://doi.org/10.5194/acp-14-10133-2014, 2014
J. Liu, D. W. Tarasick, V. E. Fioletov, C. McLinden, T. Zhao, S. Gong, C. Sioris, J. J. Jin, G. Liu, and O. Moeini
Atmos. Chem. Phys., 13, 11441–11464, https://doi.org/10.5194/acp-13-11441-2013, https://doi.org/10.5194/acp-13-11441-2013, 2013
M. Liu, H. Wang, H. Wang, T. Oda, Y. Zhao, X. Yang, R. Zang, B. Zang, J. Bi, and J. Chen
Atmos. Chem. Phys., 13, 10873–10882, https://doi.org/10.5194/acp-13-10873-2013, https://doi.org/10.5194/acp-13-10873-2013, 2013
G. Liu, J. Liu, D. W. Tarasick, V. E. Fioletov, J. J. Jin, O. Moeini, X. Liu, C. E. Sioris, and M. Osman
Atmos. Chem. Phys., 13, 10659–10675, https://doi.org/10.5194/acp-13-10659-2013, https://doi.org/10.5194/acp-13-10659-2013, 2013
F. Jiang, H. W. Wang, J. M. Chen, L. X. Zhou, W. M. Ju, A. J. Ding, L. X. Liu, and W. Peters
Biogeosciences, 10, 5311–5324, https://doi.org/10.5194/bg-10-5311-2013, https://doi.org/10.5194/bg-10-5311-2013, 2013
Related subject area
Domain: ESSD – Global | Subject: Meteorology
Global projections of heat stress at high temporal resolution using machine learning
Global tropical cyclone size and intensity reconstruction dataset for 1959–2022 based on IBTrACS and ERA5 data
GloUTCI-M: a global monthly 1 km Universal Thermal Climate Index dataset from 2000 to 2022
Earth Virtualization Engines (EVE)
A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations
Global high-resolution drought indices for 1981–2022
ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China
Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira
Earth Syst. Sci. Data, 17, 1153–1171, https://doi.org/10.5194/essd-17-1153-2025, https://doi.org/10.5194/essd-17-1153-2025, 2025
Short summary
Short summary
Climate change is posing increasing challenges in the dairy cattle farming sector, as heat stress adversely affects the animals' health and milk production. To accurately assess these impacts, we developed a machine learning model to downscale daily climate data to hourly Temperature Humidity Index (THI) values. We utilized historical weather data to train our model and applied them to future climate projections, under two climate scenarios.
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
Short summary
Short summary
Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data, 16, 2407–2424, https://doi.org/10.5194/essd-16-2407-2024, https://doi.org/10.5194/essd-16-2407-2024, 2024
Short summary
Short summary
We produced a monthly Universal Thermal Climate Index dataset (GloUTCI-M) boasting global coverage and an extensive time series spanning March 2000 to October 2022 with a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. GloUTCI-M can enhance our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
Short summary
Short summary
The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
Short summary
Short summary
Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
Short summary
Short summary
To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
Short summary
Short summary
We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
Short summary
Short summary
The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Yinghong Jing, Xinghua Li, and Huanfeng Shen
Earth Syst. Sci. Data, 14, 3137–3156, https://doi.org/10.5194/essd-14-3137-2022, https://doi.org/10.5194/essd-14-3137-2022, 2022
Short summary
Short summary
Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
Cited articles
Baldocchi, D.: An analytical solution for coupled leaf photosynthesis and stomatal conductance models, Tree Physiol., 14, 1069–1079, https://doi.org/10.1093/treephys/14.7-8-9.1069, 1994.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W., Paw U, K. T., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities, B. Am. Meteor. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001.
Baldocchi, D. D.: How eddy covariance flux measurements have contributed to our understanding of Global Change Biology, Glob. Change Biol., 26, 242–260, https://doi.org/10.1111/gcb.14807, 2020.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Progress in Photosynthesis Research: Volume 4 Proceedings of the VIIth International Congress on Photosynthesis Providence, Rhode Island, USA, 10–15 August 1986, edited by: Biggins, J., Springer Netherlands, Dordrecht, 221–224, https://doi.org/10.1007/978-94-017-0519-6_48, 1987.
Bastos, A., Ciais, P., Friedlingstein, P., Sitch, S., Pongratz, J., Fan, L., Wigneron, J. P., Weber, U., Reichstein, M., Fu, Z., Anthoni, P., Arneth, A., Haverd, V., Jain, A. K., Joetzjer, E., Knauer, J., Lienert, S., Loughran, T., McGuire, P. C., Tian, H., Viovy, N., and Zaehle, S.: Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity, Sci. Adv., 6, eaba2724, https://doi.org/10.1126/sciadv.aba2724, 2020.
Bauerle, W. L., Daniels, A. B., and Barnard, D. M.: Carbon and water flux responses to physiology by environment interactions: a sensitivity analysis of variation in climate on photosynthetic and stomatal parameters, Clim. Dynam., 42, 2539–2554, https://doi.org/10.1007/s00382-013-1894-6, 2014.
Bodesheim, P., Jung, M., Gans, F., Mahecha, M. D., and Reichstein, M.: Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product, Earth Syst. Sci. Data, 10, 1327–1365, https://doi.org/10.5194/essd-10-1327-2018, 2018.
Bonan, G.: Climate Change and Terrestrial Ecosystem Modeling, Cambridge University Press, Cambridge, https://doi.org/10.1017/9781107339217, 2019.
Bonan, G. B., Levis, S., Kergoat, L., and Oleson, K. W.: Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models, Global Biogeochem. Cy., 16, 5-1–5-23, 10.1029/2000GB001360, 2002.
Bonan, G. B., Lawrence, P. J., Oleson, K. W., Levis, S., Jung, M., Reichstein, M., Lawrence, D. M., and Swenson, S. C.: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data, J. Geophys. Res., 116, G02014, https://doi.org/10.1029/2010jg001593, 2011.
Cao, M. and Woodward, F. I.: Dynamic responses of terrestrial ecosystem carbon cycling to global climate change, Nature, 393, 249–252, https://doi.org/10.1038/30460, 1998.
Chen, J. M.: Spatial Scaling of a Remotely Sensed Surface Parameter by Contexture, Remote Sens. Environ., 69, 30–42, https://doi.org/10.1016/S0034-4257(99)00006-1, 1999.
Chen, J. M. and Liu, J.: Evolution of evapotranspiration models using thermal and shortwave remote sensing data, Remote Sens. Environ., 237, 111594, https://doi.org/10.1016/j.rse.2019.111594, 2020.
Chen, J. M., Rich, P. M., Gower, S. T., Norman, J. M., and Plummer, S.: Leaf area index of boreal forests: Theory, techniques, and measurements, J. Geophys. Res.-Atmos., 102, 29429–29443, https://doi.org/10.1029/97JD01107, 1997.
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. Model., 124, 99–119, https://doi.org/10.1016/S0304-3800(99)00156-8, 1999.
Chen, J. M., Deng, F., and Chen, M.: Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter, IEEE T. Geosci. Remote, 44, 2230–2238, https://doi.org/10.1109/TGRS.2006.872089, 2006.
Chen, J. M., Mo, G., Pisek, J., Liu, J., Deng, F., Ishizawa, M., and Chan, D.: Effects of foliage clumping on the estimation of global terrestrial gross primary productivity, Global Biogeochem. Cy., 26, GB1019, https://doi.org/10.1029/2010GB003996, 2012.
Chen, J. M., Chen, X., and Ju, W.: Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity, Biogeosciences, 10, 4879–4896, https://doi.org/10.5194/bg-10-4879-2013, 2013.
Chen, J. M., Ju, W., Ciais, P., Viovy, N., Liu, R., Liu, Y., and Lu, X.: 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., Wang, R., Liu, Y., He, L., Croft, H., Luo, X., Wang, H., Smith, N. G., Keenan, T. F., Prentice, I. C., Zhang, Y., Ju, W., and Dong, N.: Global datasets of leaf photosynthetic capacity for ecological and earth system research, Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, 2022.
Christian, J. I., Basara, J. B., Hunt, E. D., Otkin, J. A., Furtado, J. C., Mishra, V., Xiao, X., and Randall, R. M.: Global distribution, trends, and drivers of flash drought occurrence, Nat. Commun., 12, 6330, https://doi.org/10.1038/s41467-021-26692-z, 2021.
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., and Zona, D.: Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites, Agr. Forest Meteorol., 301–302, 108350, https://doi.org/10.1016/j.agrformet.2021.108350, 2021.
Croft, H., Chen, J. M., Luo, X., Bartlett, P., Chen, B., and Staebler, R. M.: Leaf chlorophyll content as a proxy for leaf photosynthetic capacity, Glob. Change Biol., 23, 3513–3524, https://doi.org/10.1111/gcb.13599, 2017.
Duarte Rocha, A., Vulova, S., van der Tol, C., Förster, M., and Kleinschmit, B.: Modelling hourly evapotranspiration in urban environments with SCOPE using open remote sensing and meteorological data, Hydrol. Earth Syst. Sci., 26, 1111–1129, https://doi.org/10.5194/hess-26-1111-2022, 2022.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, https://doi.org/10.1007/BF00386231, 1980.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Franks, P. J., Bonan, G. B., Berry, J. A., Lombardozzi, D. L., Holbrook, N. M., Herold, N., and Oleson, K. W.: Comparing optimal and empirical stomatal conductance models for application in Earth system models, Glob. Change Biol., 24, 5708–5723, https://doi.org/10.1111/gcb.14445, 2018.
Friedl, M. and Sulla-Menashe, D.: MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD12C1.006, 2015.
Gamon, J. A., Huemmrich, K. F., Peddle, D. R., Chen, J., Fuentes, D., Hall, F. G., Kimball, J. S., Goetz, S., Gu, J., McDonald, K. C., Miller, J. R., Moghaddam, M., Rahman, A. F., Roujean, J. L., Smith, E. A., Walthall, C. L., Zarco-Tejada, P., Hu, B., Fernandes, R., and Cihlar, J.: Remote sensing in BOREAS: Lessons learned, Remote Sens. Environ., 89, 139–162, https://doi.org/10.1016/j.rse.2003.08.017, 2004.
Goulden, M. L., Miller, S. D., da Rocha, H. R., Menton, M. C., de Freitas, H. C., e Silva Figueira, A. M., and de Sousa, C. A. D.: Diel and seasonal patterns of tropical forest CO2 exchange, Ecol. Appl., 14, 42–54, https://doi.org/10.1890/02-6008, 2004.
Hashimoto, H., Wang, W., Michaelis, A., Takenaka, H., Higuchi, A., and Nemani, R. R.: Hourly GPP Estimation in Australia Using Himawari-8 AHI Products, IGARSS 2020 – 2020 IEEE International Geoscience and Remote Sensing Symposium, Hawaii, USA, 26 September–2 October 2020, 4513–4515, https://doi.org/10.1109/IGARSS39084.2020.9323462, 2020.
He, L., Chen, J. M., 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.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.adbb2d47, 2023.
Hu, X., Shi, L., Lin, G., and Lin, L.: Comparison of physical-based, data-driven and hybrid modeling approaches for evapotranspiration estimation, J. Hydrol., 601, 126592, https://doi.org/10.1016/j.jhydrol.2021.126592, 2021.
Jasechko, S., Sharp, Z. D., Gibson, J. J., Birks, S. J., Yi, Y., and Fawcett, P. J.: Terrestrial water fluxes dominated by transpiration, Nature, 496, 347–350, https://doi.org/10.1038/nature11983, 2013.
Jeong, S., Ryu, Y., Dechant, B., Li, X., Kong, J., Choi, W., Kang, M., Yeom, J., Lim, J., Jang, K., and Chun, J.: Tracking diurnal to seasonal variations of gross primary productivity using a geostationary satellite, GK-2A advanced meteorological imager, Remote Sens. Environ., 284, 113365, https://doi.org/10.1016/j.rse.2022.113365, 2023.
Ju, W., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., and Chen, B.: 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.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J., Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A. J., Eugster, W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball, J., Law, B. E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D., Richardson, A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N., Weber, U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline in the global land evapotranspiration trend due to limited moisture supply, Nature, 467, 951–954, https://doi.org/10.1038/nature09396, 2010.
Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale, D., Schwalm, C., Tramontana, G., and Reichstein, M.: The FLUXCOM ensemble of global land-atmosphere energy fluxes, Sci. Data, 6, 1–14, https://doi.org/10.1038/s41597-019-0076-8, 2019.
Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., Chevallier, F., Gans, F., Goll, D. S., Haverd, V., Köhler, P., Ichii, K., Jain, A. K., Liu, J., Lombardozzi, D., Nabel, J. E. M. S., Nelson, J. A., O'Sullivan, M., Pallandt, M., Papale, D., Peters, W., Pongratz, J., Rödenbeck, C., Sitch, S., Tramontana, G., Walker, A., Weber, U., and Reichstein, M.: Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach, Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, 2020.
Kattge, J., Knorr, W., Raddatz, T., and Wirth, C.: Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models, Glob. Change Biol., 15, 976–991, https://doi.org/10.1111/j.1365-2486.2008.01744.x, 2009.
Kong, J., Ryu, Y., Liu, J., Dechant, B., Rey-Sanchez, C., Shortt, R., Szutu, D., Verfaillie, J., Houborg, R., and Baldocchi, D. D.: Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates, Agr. Forest Meteorol., 316, 108878, https://doi.org/10.1016/j.agrformet.2022.108878, 2022.
Koppa, A., Rains, D., Hulsman, P., Poyatos, R., and Miralles, D. G.: A deep learning-based hybrid model of global terrestrial evaporation, Nat. Commun., 13, 1912, https://doi.org/10.1038/s41467-022-29543-7, 2022.
Lee, J.-E., Oliveira, R. S., Dawson, T. E., and Fung, I.: Root functioning modifies seasonal climate, P. Natl. Acad. Sci. USA, 102, 17576–17581, https://doi.org/10.1073/pnas.0508785102, 2005.
Li, B., Ryu, Y., Jiang, C., Dechant, B., Liu, J., Yan, Y., and Li, X.: BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land–atmosphere fluxes, Remote Sens. Environ., 295, 113696, https://doi.org/10.1016/j.rse.2023.113696, 2023.
Leng, J., Chen, J. M., Li, W., Luo, X., Xu, M., Liu, J., Wang, R., Rogers, C., Li, B., and Yan, Y.: Global Datasets of Hourly Carbon and Water Fluxes Simulated Using a Satellite-based Process Model with Dynamic Parameterizations [DS/OL], V1, Science Data Bank, https://doi.org/10.57760/sciencedb.ecodb.00163, 2023a.
Leng, J., Chen, J. M., Li, W., Luo, X., Xu, M., Liu, J., Wang, R., Rogers, C., Li, B., and Yan, Y.: Global Datasets of Daily Carbon and Water Fluxes Simulated Using a Satellite-based Process Model with Dynamic Parameterizations [DS/OL], V1, Science Data Bank, https://doi.org/10.57760/sciencedb.ecodb.00165, 2023b.
Leng, J., Chen, J. M., Li, W., Luo, X., Rogers, C., Croft, H., Xie, X., and Staebler, R. M.: Optimizing seasonally variable photosynthetic parameters based on joint carbon and water flux constraints, Research Square [preprint], https://doi.org/10.21203/rs.3.rs-3832505/v1, 2024a.
Leng, J., Chen, J. M., Li, W., Luo, X., Xu, M., Rogers, C., and Yan, Y.: Declining global sensitivity of stomatal conductance to photosynthesis, Research Square [preprint], https://doi.org/10.21203/rs.3.rs-3832529/v1, 2024b.
Leng, J., Chen, J. M., Luo, X., and Liu, J.: Biosphere-atmosphere Exchange Process Simulator (BEPS) (4.10), Zenodo [code], https://doi.org/10.5281/zenodo.10804469, 2024.
Li, B., Ryu, Y., Jiang, C., Dechant, B., Liu, J., Yan, Y., and Li, X.: BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land–atmosphere fluxes, Remote Sens. Environ., 295, 113696, https://doi.org/10.1016/j.rse.2023.113696, 2023.
Li, F., Kustas, W. P., Anderson, M. C., Prueger, J. H., and Scott, R. L.: Effect of remote sensing spatial resolution on interpreting tower-based flux observations, Remote Sens. Environ., 112, 337–349, https://doi.org/10.1016/j.rse.2006.11.032, 2008.
Li, X. and Xiao, J.: Mapping Photosynthesis Solely from Solar-Induced Chlorophyll Fluorescence: A Global, Fine-Resolution Dataset of Gross Primary Production Derived from OCO-2, Remote Sens., 11, 2563, https://doi.org/10.3390/rs11212563, 2019.
Liang, S., Zhao, X., Liu, S., Yuan, W., Cheng, X., Xiao, Z., Zhang, X., Liu, Q., Cheng, J., Tang, H., Qu, Y., Bo, Y., Qu, Y., Ren, H., Yu, K., and Townshend, J.: A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies, Int. J. Digit. Earth, 6, 5–33, https://doi.org/10.1080/17538947.2013.805262, 2013.
Liang, S., Cheng, J., Jia, K., Jiang, B., Liu, Q., Xiao, Z., Yao, Y., Yuan, W., Zhang, X., Zhao, X., and Zhou, J.: The Global Land Surface Satellite (GLASS) Product Suite, B. Am. Meteor. Soc., 102, E323–E337, https://doi.org/10.1175/BAMS-D-18-0341.1, 2021.
Lin, C., Gentine, P., Frankenberg, C., Zhou, S., Kennedy, D., and Li, X.: Evaluation and mechanism exploration of the diurnal hysteresis of ecosystem fluxes, Agr. Forest Meteorol., 278, 107642, https://doi.org/10.1016/j.agrformet.2019.107642, 2019.
Lin, Y.-S., Medlyn, B. E., Duursma, R. A., Prentice, I. C., Wang, H., Baig, S., Eamus, D., de Dios, Victor R., Mitchell, P., Ellsworth, D. S., de Beeck, M. O., Wallin, G., Uddling, J., Tarvainen, L., Linderson, M.-L., Cernusak, L. A., Nippert, J. B., Ocheltree, T. W., Tissue, D. T., Martin-StPaul, N. K., Rogers, A., Warren, J. M., De Angelis, P., Hikosaka, K., Han, Q., Onoda, Y., Gimeno, T. E., Barton, C. V. M., Bennie, J., Bonal, D., Bosc, A., Löw, M., Macinins-Ng, C., Rey, A., Rowland, L., Setterfield, S. A., Tausz-Posch, S., Zaragoza-Castells, J., Broadmeadow, M. S. J., Drake, J. E., Freeman, M., Ghannoum, O., Hutley, Lindsay B., Kelly, J. W., Kikuzawa, K., Kolari, P., Koyama, K., Limousin, J.-M., Meir, P., Lola da Costa, A. C., Mikkelsen, T. N., Salinas, N., Sun, W., and Wingate, L.: Optimal stomatal behaviour around the world, Nat. Clim. Change, 5, 459–464, https://doi.org/10.1038/nclimate2550, 2015.
Liu, J., Chen, J. M., Cihlar, J., and Park, W. M.: A process-based boreal ecosystem productivity simulator using remote sensing inputs, Remote Sens. Environ., 62, 158–175, https://doi.org/10.1016/S0034-4257(97)00089-8, 1997.
Liu, J., Chen, J. M., and Cihlar, J.: Mapping evapotranspiration based on remote sensing: An application to Canada's landmass, Water Resour. Res., 39, 1189, https://doi.org/10.1029/2002WR001680, 2003.
Liu, Y., Liu, R., 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.-Biogeo., 117, G04003, https://doi.org/10.1029/2012JG002084, 2012.
Liu, Y., Chen, J. M., He, L., Wang, R., Smith, N. G., Keenan, T. F., Rogers, C., Li, W., and Leng, J.: Global photosynthetic capacity of C3 biomes retrieved from solar-induced chlorophyll fluorescence and leaf chlorophyll content, Remote Sens. Environ., 287, 113457, https://doi.org/10.1016/j.rse.2023.113457, 2023.
Luo, X., Chen, J. M., Liu, J., Black, T. A., Croft, H., Staebler, R., He, L., Arain, M. A., Chen, B., Mo, G., Gonsamo, A., and McCaughey, H.: Comparison of Big-Leaf, Two-Big-Leaf, and Two-Leaf Upscaling Schemes for Evapotranspiration Estimation Using Coupled Carbon-Water Modeling, J. Geophys. Res.-Biogeo., 123, 207–225, https://doi.org/10.1002/2017JG003978, 2018.
Luo, X., Croft, H., Chen, J. M., He, L., and Keenan, T. F.: Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content, Glob. Change Biol., 25, 2499–2514, https://doi.org/10.1111/gcb.14624, 2019.
Luo, X., Keenan, T. F., Chen, J. M., Croft, H., Colin Prentice, I., Smith, N. G., Walker, A. P., Wang, H., Wang, R., Xu, C., and Zhang, Y.: Global variation in the fraction of leaf nitrogen allocated to photosynthesis, Nat. Commun., 12, 4866, https://doi.org/10.1038/s41467-021-25163-9, 2021.
Ma, R., Xiao, J., Liang, S., Ma, H., He, T., Guo, D., Liu, X., and Lu, H.: Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data, Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, 2022.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017.
Miner, G. L. and Bauerle, W. L.: Seasonal variability of the parameters of the Ball–Berry model of stomatal conductance in maize (Zea mays L.) and sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions, Plant Cell Environ., 40, 1874–1886, https://doi.org/10.1111/pce.12990, 2017.
Miner, G. L., Bauerle, W. L., and Baldocchi, D. D.: Estimating the sensitivity of stomatal conductance to photosynthesis: a review, Plant, Cell Environ., 40, 1214–1238, https://doi.org/10.1111/pce.12871, 2017.
Miralles, D. G., De Jeu, R. A. M., Gash, J. H., Holmes, T. R. H., and Dolman, A. J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011, 2011.
Misson, L., Panek, J. A., and Goldstein, A. H.: A comparison of three approaches to modeling leaf gas exchange in annually drought-stressed ponderosa pine forests, Tree Physiol., 24, 529–541, https://doi.org/10.1093/treephys/24.5.529, 2004.
Mohammed, G. H., Colombo, R., Middleton, E. M., Rascher, U., van der Tol, C., Nedbal, L., Goulas, Y., Pérez-Priego, O., Damm, A., Meroni, M., Joiner, J., Cogliati, S., Verhoef, W., Malenovský, Z., Gastellu-Etchegorry, J.-P., Miller, J. R., Guanter, L., Moreno, J., Moya, I., Berry, J. A., Frankenberg, C., and Zarco-Tejada, P. J.: Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress, Remote Sens. Environ., 231, 111177, https://doi.org/10.1016/j.rse.2019.04.030, 2019.
Moreno, A., Maselli, F., Gilabert, M. A., Chiesi, M., Martínez, B., and Seufert, G.: Assessment of MODIS imagery to track light-use efficiency in a water-limited Mediterranean pine forest, Remote Sens. Environ., 123, 359–367, https://doi.org/10.1016/j.rse.2012.04.003, 2012.
Nelson, J. A., Pérez-Priego, O., Zhou, S., Poyatos, R., Zhang, Y., Blanken, P. D., Gimeno, T. E., Wohlfahrt, G., Desai, A. R., Gioli, B., Limousin, J.-M., Bonal, D., Paul-Limoges, E., Scott, R. L., Varlagin, A., Fuchs, K., Montagnani, L., Wolf, S., Delpierre, N., Berveiller, D., Gharun, M., Belelli Marchesini, L., Gianelle, D., Šigut, L., Mammarella, I., Siebicke, L., Andrew Black, T., Knohl, A., Hörtnagl, L., Magliulo, V., Besnard, S., Weber, U., Carvalhais, N., Migliavacca, M., Reichstein, M., and Jung, M.: Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites, Glob. Change Biol., 26, 6916–6930, https://doi.org/10.1111/gcb.15314, 2020.
Neumann, R. B. and Cardon, Z. G.: The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modeling studies, New Phytol., 194, 337–352, https://doi.org/10.1111/j.1469-8137.2012.04088.x, 2012.
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.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., and Prabhat: Deep learning and process understanding for data-driven Earth system science, Nature, 566, 195–204, https://doi.org/10.1038/s41586-019-0912-1, 2019.
Ryu, Y., Baldocchi, D. D., Kobayashi, H., van Ingen, C., Li, J., Black, T. A., Beringer, J., van Gorsel, E., Knohl, A., Law, B. E., and Roupsard, O.: Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales, Global Biogeochem. Cy., 25, GB4017, https://doi.org/10.1029/2011GB004053, 2011.
Ryu, Y., Berry, J. A., and Baldocchi, D. D.: What is global photosynthesis? History, uncertainties and opportunities, Remote Sens. Environ., 223, 95–114, https://doi.org/10.1016/j.rse.2019.01.016, 2019.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Smith, N. G., Keenan, T. F., Colin Prentice, I., Wang, H., Wright, I. J., Niinemets, U., Crous, K. Y., Domingues, T. F., Guerrieri, R., Yoko Ishida, F., Kattge, J., Kruger, E. L., Maire, V., Rogers, A., Serbin, S. P., Tarvainen, L., Togashi, H. F., Townsend, P. A., Wang, M., Weerasinghe, L. K., and Zhou, S. X.: Global photosynthetic capacity is optimized to the environment, Ecol. Lett., 22, 506–517, https://doi.org/10.1111/ele.13210, 2019.
Tagesson, T., Tian, F., Schurgers, G., Horion, S., Scholes, R., Ahlström, A., Ardö, J., Moreno, A., Madani, N., Olin, S., and Fensholt, R.: A physiology-based Earth observation model indicates stagnation in the global gross primary production during recent decades, Glob. Change Biol., 27, 836–854, https://doi.org/10.1111/gcb.15424, 2021.
Urban, O., JanouŠ, D., Acosta, M., CzernÝ, R., MarkovÁ, I., NavrÁTil, M., Pavelka, M., PokornÝ, R., ŠPrtovÁ, M., Zhang, R. U. I., ŠPunda, V., Grace, J., and Marek, M. V.: Ecophysiological controls over the net ecosystem exchange of mountain spruce stand. Comparison of the response in direct vs. diffuse solar radiation, Glob. Change Biol., 13, 157–168, https://doi.org/10.1111/j.1365-2486.2006.01265.x, 2007.
Wang, H., Guan, H., Liu, N., Soulsby, C., Tetzlaff, D., and Zhang, X.: Improving the Jarvis-type model with modified temperature and radiation functions for sap flow simulations, J. Hydrol., 587, 124981, https://doi.org/10.1016/j.jhydrol.2020.124981, 2020.
Wang, Y. P. and Leuning, R.: A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I:: Model description and comparison with a multi-layered model, Agr. Forest Meteorol., 91, 89–111, https://doi.org/10.1016/S0168-1923(98)00061-6, 1998.
Wang, Y. P., Baldocchi, D., Leuning, R. A. Y., Falge, E. V. A., and Vesala, T.: Estimating parameters in a land-surface model by applying nonlinear inversion to eddy covariance flux measurements from eight FLUXNET sites, Glob. Change Biol., 13, 652–670, https://doi.org/10.1111/j.1365-2486.2006.01225.x, 2007.
Wilson, K. B., Baldocchi, D. D., and Hanson, P. J.: Spatial and seasonal variability of photosynthetic parameters and their relationship to leaf nitrogen in a deciduous forest, Tree Physiol., 20, 565–578, https://doi.org/10.1093/treephys/20.9.565, 2000.
Wolz, K. J., Wertin, T. M., Abordo, M., Wang, D., and Leakey, A. D. B.: Diversity in stomatal function is integral to modelling plant carbon and water fluxes, Nat. Ecol. Evol., 1, 1292–1298, https://doi.org/10.1038/s41559-017-0238-z, 2017.
Xiao, J., Fisher, J. B., Hashimoto, H., Ichii, K., and Parazoo, N. C.: Emerging satellite observations for diurnal cycling of ecosystem processes, Nat. Plants, 7, 877–887, https://doi.org/10.1038/s41477-021-00952-8, 2021.
Xu, M., Liu, R., Chen, J. M., Liu, Y., Wolanin, A., Croft, H., He, L., Shang, R., Ju, W., Zhang, Y., He, Y., and Wang, R.: A 21-Year Time Series of Global Leaf Chlorophyll Content Maps From MODIS Imagery, IEEE T. Geosci. Remote, 60, 1–13, https://doi.org/10.1109/TGRS.2022.3204185, 2022.
Yamamoto, Y., Ichii, K., Ryu, Y., Kang, M., Murayama, S., Kim, S.-J., and Cleverly, J. R.: Detection of vegetation drying signals using diurnal variation of land surface temperature: Application to the 2018 East Asia heatwave, Remote Sens. Environ., 291, 113572, https://doi.org/10.1016/j.rse.2023.113572, 2023.
Yu, L., Qiu, G. Y., Yan, C., Zhao, W., Zou, Z., Ding, J., Qin, L., and Xiong, Y.: A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement, Earth Syst. Sci. Data, 14, 3673–3693, https://doi.org/10.5194/essd-14-3673-2022, 2022.
Yuan, W., Liu, S., Yu, G., Bonnefond, J.-M., Chen, J., Davis, K., Desai, A. R., Goldstein, A. H., Gianelle, D., Rossi, F., Suyker, A. E., and Verma, S. B.: Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data, Remote Sens. Environ., 114, 1416–1431, https://doi.org/10.1016/j.rse.2010.01.022, 2010.
Zhang, Y., Fang, J., Smith, W. K., Wang, X., Gentine, P., Scott, R. L., Migliavacca, M., Jeong, S., Litvak, M., and Zhou, S.: Satellite solar-induced chlorophyll fluorescence tracks physiological drought stress development during 2020 southwest US drought, Glob. Change Biol., 29, 3395–3408, https://doi.org/10.1111/gcb.16683, 2023a.
Zhang, Z., Cescatti, A., Wang, Y.-P., Gentine, P., Xiao, J., Guanter, L., Huete, A. R., Wu, J., Chen, J. M., Ju, W., Peñuelas, J., and Zhang, Y.: Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying, Sci. Adv., 9, eabq4974, https://doi.org/10.1126/sciadv.abq4974, 2023b.
Zhao, W. L., Gentine, P., Reichstein, M., Zhang, Y., Zhou, S., Wen, Y., Lin, C., Li, X., and Qiu, G. Y.: Physics-Constrained Machine Learning of Evapotranspiration, Geophys. Res. Lett., 46, 14496–14507, https://doi.org/10.1029/2019GL085291, 2019.
Zheng, Y., Shen, R., Wang, Y., Li, X., Liu, S., Liang, S., Chen, J. M., Ju, W., Zhang, L., and Yuan, W.: Improved estimate of global gross primary production for reproducing its long-term variation, 1982–2017, Earth Syst. Sci. Data, 12, 2725–2746, https://doi.org/10.5194/essd-12-2725-2020, 2020.
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...
Altmetrics
Final-revised paper
Preprint