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 article
| 
13 Mar 2024
Data description article |
| 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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- Short-term and long-term impacts of climate extremes on global plant photosynthesis S. Zhang et al. https://doi.org/10.1080/17538947.2026.2630444
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- A global hourly gross primary production dataset from 2001 to 2020 Y. Wang et al. https://doi.org/10.1038/s41597-025-06371-0
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- Attentional BiLSTM with Ecological Process Constraints for Carbon–Water Flux Prediction in Cold, Temperate Coniferous Forests X. Wang et al. https://doi.org/10.3390/f17030307
- Direct radiative effects of aerosols and clouds and their impacts on the ecosystem gross primary productivity in summer at typical sites in China X. Deng et al. https://doi.org/10.1016/j.envres.2025.122138
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- NASA’s ECOSTRESS satellite reveals widespread midday depression in ecosystem evapotranspiration J. Bu et al. https://doi.org/10.1038/s41467-026-76873-x
- From carbon stocks to carbon fluxes: methods, challenges, and uncertainties in forest carbon sink accounting Y. He et al. https://doi.org/10.48130/fra-0026-0007
- Daily global transpiration estimation (2001–2018) by integrating satellite solar-induced fluorescence and spatially heterogeneous slope parameter in a conductance-photosynthesis model J. Jin et al. https://doi.org/10.1016/j.agrformet.2025.110993
- Enhancing Machine Learning-Based GPP Upscaling Error Correction: An Equidistant Sampling Method with Optimized Step Size and Intervals Z. Wang et al. https://doi.org/10.3390/rs18010023
- Overestimated carbon uptake stability due to inadequate vegetation dynamics in ecosystem models H. Gui et al. https://doi.org/10.1093/jpe/rtaf193
- Quantitative assessment of spatiotemporal variations and drivers of gross primary productivity in tropical ecosystems at higher resolution R. Xu et al. https://doi.org/10.1016/j.jag.2024.104248
- Geostationary Satellite-Derived Diurnal Cycles of Photosynthesis and Their Drivers in a Subtropical Forest J. Xu et al. https://doi.org/10.3390/rs17173079
- How does gross primary production uncertainty impact evapotranspiration prediction within the carbon–water coupled model? L. Huang et al. https://doi.org/10.1016/j.jhydrol.2026.135131
- Enhancing understanding of vegetation responses to flash droughts: the need for high-temporal-resolution monitoring data Z. Qi et al. https://doi.org/10.1016/j.jhydrol.2026.135659
- Vegetation Photosynthesis Model v3.0: Improved Estimates of Terrestrial Gross Primary Production from Individual Eddy Flux Tower Sites to the Globe L. Pan et al. https://doi.org/10.34133/remotesensing.0471
- Sensing Plant Photosynthesis Using Solar-Induced Chlorophyll Fluorescence: From Chloroplasts to the Globe X. Yang et al. https://doi.org/10.1146/annurev-arplant-090324-115537
- Incorporating dynamic ozone stress and parameter optimization into the BEPS model for improved GPP simulation J. Wang et al. https://doi.org/10.1016/j.ecolmodel.2026.111707
- Field-scale evaluation of a satellite-based terrestrial biosphere model for estimating crop response to management practices and productivity J. Wang et al. https://doi.org/10.1016/j.isprsjprs.2024.11.008
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- CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization Y. Kang et al. https://doi.org/10.5194/essd-17-3009-2025
- Revisiting global cropland water use efficiency: Insights from satellite remote sensing L. Huang et al. https://doi.org/10.1016/j.gloplacha.2026.105310
- Extended global terrestrial evapotranspiration and gross primary production dataset from 1982 to near present Z. Xu et al. https://doi.org/10.5194/essd-18-5663-2026
- Machine learning-based multi-scale dynamics of terrestrial carbon fluxes and their environmental drivers along the U.S. East Coast J. Wang et al. https://doi.org/10.1007/s12145-026-02203-w
- Development of an ecohydrological model for coupled simulation of water and carbon fluxes, crop growth, and canopy spectra over croplands C. Yang et al. https://doi.org/10.1016/j.compag.2025.110336
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Saved (final revised paper)
Latest update: 30 Aug 2026
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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