Modeling radiative transfer in tropical rainforest canopies: sensitivity of simulated albedo to canopy architectural and optical parameters

Yanagi, S. N. M.; Costa, Marcos Heil

doi:10.1590/s0001-37652011000400010

Cited by 8 publications

(4 citation statements)

References 10 publications

(11 reference statements)

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“…Quantitatively, investigating and understanding the relative contributions of different parameters to surface albedo is fundamental for its accurate modeling and retrievals in remote sensing (Gao et al, ) and also plays an important role in constraining the albedo uncertainties of the Earth's radiation budget in the climate modeling (Dickinson, ; Liang, ) and predicting how the ongoing changes in vegetation areas might affect the global climate (Lukeš et al, ). Some studies clearly demonstrated that the surface albedos of different plant species show different spatial and temporal patterns due to different canopy architecture and composition optical properties (Betts, ; Gao et al, ; Kuusinen et al, ; Kuusinen et al, ; Tian et al, ; Yanagi & Costa, ). For instance, there exists a general negative logarithmic relationship between LAI and the albedo on both the Mongolian Plateau and Tibetan Plateau (Tian et al, ); the foliage and branches clumping at the shoot and crown level can increase the probability for multiple interactions of photons in the canopy, thus reducing forest albedo (Hovi et al, ).…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Coarse‐Scale Snow‐Free Land Surface Shortwave Albedo to Topography

et al. 2019

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As a widespread landscape, rugged terrain significantly distorts the land surface albedo. Simply neglecting the topographic effects in the land surface albedo modeling and retrievals can lead to large biases and uncertainties over rugged terrain. In spite of gradually increasing research about the topographic effects on the albedo, the albedo sensitivities over rugged terrain to different variables remain unclear. In this paper, the sensitivities of coarse‐scale snow‐free albedo to topography were quantitatively investigated using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface albedo data and the variance‐based global sensitivity analysis based on a well‐established mechanistically‐based land surface albedo parameterized model over rugged terrain. The results based on the MODIS data revealed that MODIS land surface albedo over the Tibetan Plateau was highly sensitive to the topographic distribution, and the differences of the spatially averaged snow‐free black‐sky albedos over grasslands induced by different terrain could reach up to 0.10 in winter. The topographic effects on MODIS albedo are tightly relevant to the land cover type, solar illumination geometries, and vegetation characteristics. The global sensitivity analysis results underscored that topography was an important driving factor of the snow‐free albedo, and it accounted for more than 30% of the total variance, respectively. These results highlight the necessities for the topographic consideration in the land surface albedo modeling and retrievals even though the terrain is gentle (10–20°) and advance our understanding of the albedo sensitivities to different variables over rugged terrain, which will facilitate the improvement of land surface albedo parameterization in the land surface models.

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Section: Introductionmentioning

confidence: 99%

Sensitivity of Coarse‐Scale Snow‐Free Land Surface Shortwave Albedo to Topography

et al. 2019

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“…Within each layer, the upward and downward radiation fluxes [3,9,21,28], respectively, are described by…”

Section: Upward and Downward Diffuse Radiative Fluxes: Two-streammentioning

confidence: 99%

Inverse Modeling of Radiative Transfer by Two-Stream Approximation using the Luus-Jaakola Method

Ferreira

Krieger²,

Lyra³

et al. 2021

TCAM

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The simulation of terrestrial ecosystem processes, using numerical biosphere-atmosphere models that can be coupled to the Atmospheric Models, assist in a better diagnosis and forecast of climate and weather. To be able to represent a particular region, biome or ecosystem, the model parameters need to be adjusted for local conditions. This work aims to assess the Luus-Jaakola (LJ) method in the optimization of the parameters in a two-stream radiative transfer model applied to a vegetation canopy. Solar radiation components (incident, S↓, and reflected, S↑) were measured above a sugarcane crop in a Tropical region from February 17 to 24, 2006. Among the combinations of internal and external iterations evaluated for Luss-Jaakola method, 60/30 (external/internal) iterations presented more precise albedo (∝ = S↑/S↓) simulated (r^2 = 0.7386) and, for the accuracy of the simulated ∝, even though the 60/40 combination had the smallest percentual error (6.40%), the 60/30 combination was 0.03% higher. The precision and accuracy of S↑ was greater with the parameters obtained by the inverse problem with the combination of 60/30 (external/internal) iterations respectively. In general, the behavior of simulated S↑ at the top of the canopy was underestimated compared to the observed S↑, especially in the early morning. For the simulated ∝ at the top of the canopy, the model's overestimation was observed at the lowest values of albedo. When the largest albedos are observed, only at the beginning of the day the model underestimated the values. As shown by the tests result, the parameters optimized by Luus-Jaakola method have an adequate representation of the observed data.

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“…Within each layer, the upward and downward radiation fluxes [1,4,7,9], respectively, are described by…”

Section: Upward and Downward Diffuse Radiative Fluxes: Two-streammentioning

confidence: 99%

Inverse Modeling of Radiative Transfer by Two-Stream Approximation using the Luus-Jaakola Method.

Krieger¹,

Lyra²,

Ferreira³

et al. 2020

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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The simulation of terrestrial ecosystem processes, using numerical biosphere-atmosphere models that can be directly coupled to the Atmospheric General Circulation Models (AGCM) and Regional Atmospheric Models, assists to a more accurate diagnosis and prognosis of climate and weather. These models describe the interaction processes with the atmosphere and the transient changes that occur in vegetation composition and structure. The solar radiation module of the biosphere-atmosphere models is relevant when considering dynamic models due to being the main mechanism of energy contribution to an ecosystem. The distribution of solar radiation inside the vegetation canopy controls the entire dynamics of plant growth through the portion absorbed by photosynthesis. This also influences the assimilation of water and nutrients in the soil by the mechanisms of heat and mass exchange. In this work the two-stream radiative transfer model, [2,5] was adopted. The Shooting Method was used to solve the Ordinary Differential Equations (ODE) system in the Scilab mathematical modeling environment, as well as the Luus-Jaakola method, [6], to obtain the necessary parameters to solve the direct problem.

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Modeling radiative transfer in tropical rainforest canopies: sensitivity of simulated albedo to canopy architectural and optical parameters

Cited by 8 publications

References 10 publications

Sensitivity of Coarse‐Scale Snow‐Free Land Surface Shortwave Albedo to Topography

Sensitivity of Coarse‐Scale Snow‐Free Land Surface Shortwave Albedo to Topography

Inverse Modeling of Radiative Transfer by Two-Stream Approximation using the Luus-Jaakola Method

Inverse Modeling of Radiative Transfer by Two-Stream Approximation using the Luus-Jaakola Method.

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