B039-03
Considering the effects of canopy structure on hyperspectral radiative transfer and terrestrial photosynthesis

Wednesday, 9 December 2020: 05:38
Virtual
Renato Kerches Braghiere1,2, A. Anthony Bloom3, John Worden3, Marcos Longo1, Daniel Sousa3, Troy Magney4, Pierre Gentine5, Yujie Wang6 and Christian Frankenberg1, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)University of California at Los Angeles, Joint Institute for Regional Earth System Science and Engineering, Los Angeles, CA, United States, (3)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (4)University of California Davis, Plant Sciences, Davis, CA, United States, (5)Columbia University, Earth and Environmental Engineering, New York, NY, United States, (6)California Institute of Technology, Pasadena, United States
Recorded Presentation
Abstract:
Neglecting canopy structural heterogeneity in Earth System Models (ESMs) leads to uncertainties in the energy and water budgets, as well as in the terrestrial carbon cycling. Here, we introduce a parameterization scheme of horizontal canopy structure into the land component of a new generation ESM, the Climate Model Alliance (CliMA), for better representing the 3D canopy structure and hyperspectral radiative processes. The radiative transfer in the CliMA Land model is based on the four-stream theory with explicit representations of solar fluxes in the direct, downward diffuse, and upward diffuse forms, as well as the flux in the viewing direction. Canopy optical variables are derived from several intrinsic canopy properties including leaf pigments and leaf water content, following the Fluspect model assumptions. The horizontal structural heterogeneity of the canopy is simulated using an effective leaf area index (eLAI) in radiative terms – LAI scaled by a clumping index – instead of ‘true’ LAI. We compare the newly developed model against more accurate state-of-the-art 3D radiative transfer models from the Radiation transfer Model Intercomparison (RAMI), which cannot be directly used in ESMs due to its parametric complexity and high computational demand. We evaluate the impacts of different structural variables (leaf angular distribution, canopy clumping, vertical LAI) on proxies of terrestrial photosynthesis by exploring the impacts of canopy structure on vegetation indices commonly used as Gross Primary Productivity (GPP) predictors. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the near-infrared reflectance of vegetation (NIRv), and Solar Induced Fluorescence (SIF) emission are among the evaluated indices. For a sparse canopy scene with LAI = 0.5 m2.m-2 and 10% vegetation cover, the average root-mean-square error (RMSE) for the three terms of the radiation partitioning (absorptance, reflectance, and transmittance) is reduced from 24% to 7% when the structure parameterization scheme is included. We discuss open directions for the existing model framework, including more realistic representations of canopy structure interacting with ecosystem processes, and we show that our implementation of horizontal canopy heterogeneity on hyperspectral radiative transfer models is suitable for ESMs, adding information on how future hyperspectral datasets may be used to more accurately constrain the terrestrial carbon, energy, and water cycles.
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