Impacts of leaf traits on vegetation optical properties in Earth system modeling
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1.
University of Science and Technology of China
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2.
California Institute of Technology
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3.
Jet Propulsion Lab
- 4. School of Biosciences, University of Sheffield, S10 2TN, Sheffield, Germany
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5.
Max Planck Institute for Biogeochemistry
Abstract
Quantifying surface energy and carbon budgets is essential for projecting Earth’s climate. Earth System Models (ESMs) typically simulate land surface processes based on plant functional types (PFTs), neglecting the diversity of plant functional traits or characteristics (PFCs; e.g., chlorophyll content and leaf mass per area). Here, we demonstrate substantial differences in modeled leaf optical properties (LOP) and surface albedo between traditional PFT-based and PFC-based approaches, particularly in tropical and boreal forests. We configure the canopy radiative transfer scheme in the Community Earth System Model using PFC-based LOP. This new configuration produces lower shortwave surface albedo in the tropics but higher albedo in boreal regions (>5 W m−2 radiative flux differences), and a weaker tropical but stronger boreal carbon sink. Through land-atmosphere coupling, the PFC-based configuration further alters atmospheric processes, leading to different temperature, cloud cover, and precipitation patterns. Our findings highlight the need to move beyond traditional PFT-based approaches in ESMs.
Copyright and License
© The Author(s) 2025.
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Acknowledgement
We gratefully acknowledge funding support from the University of Science and Technology of China (Award #KY2080000142, received by YW), the National Aeronautics and Space Administration (NASA) Carbon Cycle Science (Award #80NSSC21K1712, received by CF) and OCO2/3 Science Team (Award #80NSSC21K1075 and #80NSSC24K0761, received by CF). CF and TS acknowledge support from Schmidt Sciences, LLC. Part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. This work was supported in part by the Resnick Sustainability Institute at Caltech. We would like to acknowledge high-performance computing support from the Derecho system (https://doi.org/10.5065/qx9a-pg09) provided by the NSF National Center for Atmospheric Research (NCAR), sponsored by the National Science Foundation.
Data Availability
The CHL42 and LMA37,38 maps and benchmark datasets62,98 used in this study are available from GriddingMachine.jl94. Global scale LOP maps derived using CliMA Land, CESM modifications, and CESM model output are available at https://doi.org/10.5281/zenodo.757031490.
Code Availability
The CliMA Land model used to simulate leaf hyperspectral reflectance and transmittance is available at https://github.com/CliMA/Land. All figures were generated using Python with the matplotlib and cartopy modules. The code for generating and analyzing the data can be found at https://doi.org/10.5281/zenodo.757031490.
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Additional details
- PMCID
- PMC12119829
- University of Science and Technology of China
- KY2080000142
- National Aeronautics and Space Administration
- 80NSSC21K1712
- National Aeronautics and Space Administration
- 80NSSC21K1075
- National Aeronautics and Space Administration
- 80NSSC24K0761
- Schmidt Family Foundation
- Jet Propulsion Laboratory
- Resnick Sustainability Institute
- Accepted
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2025-05-16
- Caltech groups
- Resnick Sustainability Institute, Division of Geological and Planetary Sciences (GPS)
- Publication Status
- Published