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Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations.

Authors :
Pedruzo‐Bagazgoitia, X.
Patton, E. G.
Moene, A. F.
Ouwersloot, H. G.
Gerken, T.
Machado, L. A. T.
Martin, S. T.
Sörgel, M.
Stoy, P. C.
Yamasoe, M. A.
Vilà‐Guerau de Arellano, J.
Source :
Journal of Advances in Modeling Earth Systems; Feb2023, Vol. 15 Issue 2, p1-22, 22p
Publication Year :
2023

Abstract

We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels. Plain Language Summary: Most atmospheric models currently represent the vegetated canopy as one slab layer at the lowest level of the model. This oversimplification leads to limitations in our understanding on how the canopy and the atmosphere interact, as well as when comparing and interpreting model output with real world observations largely influenced by the presence of a canopy. In this study we implemented a more realistic multilayer canopy scheme in a turbulence‐resolving atmospheric model. We focused and analyzed the features and changes that appear in atmospheric variables due to the presence of a three‐dimensional canopy. To do so we designed several numerical experiments to understand how to best represent the relevant physical and biological processes. We quantified the variability of light, humidity and temperature at leaf‐level, and discussed the large variability the features appearing in the lowest atmosphere by the presence of the canopy. We also compare our model simulations with a complete set of atmospheric observations taken inside and above the Amazonian rainforest, and find an overall good agreement. We finally propose future ways to improve the canopy scheme and, in general, simulations including a vegetated canopy. Key Points: We implemented a 1D multilayer canopy scheme at every gridpoint in the Dutch Atmospheric Large Eddy Simulation resolving leaf, canopy and boundary layer scales as a continuumThe model is compared against a data set gathered during the Amazonian dry season, showing that wind and temperature are better represented than humidityWe present the first Large Eddy Simulations validation of in‐canopy CO2 processes [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19422466
Volume :
15
Issue :
2
Database :
Complementary Index
Journal :
Journal of Advances in Modeling Earth Systems
Publication Type :
Academic Journal
Accession number :
162055519
Full Text :
https://doi.org/10.1029/2022MS003210