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Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1)

Wang, Yujie and Köhler, Philipp and He, Liyin and Doughty, Russell B. and Braghiere, Renato K. and Wood, Jeffrey D. and Frankenberg, Christian (2021) Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1). Geoscientific Model Development, 14 (11). pp. 6741-6763. ISSN 1991-9603. doi:10.5194/gmd-14-6741-2021. https://resolver.caltech.edu/CaltechAUTHORS:20211208-951472000

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Abstract

At the leaf level, stomata control the exchange of water and carbon across the air–leaf interface. Stomatal conductance is typically modeled empirically, based on environmental conditions at the leaf surface. Recently developed stomatal optimization models show great skills at predicting carbon and water fluxes at both the leaf and tree levels. However, how well the optimization models perform at larger scales has not been extensively evaluated. Furthermore, stomatal models are often used with simple single-leaf representations of canopy radiative transfer (RT), such as big-leaf models. Nevertheless, the single-leaf canopy RT schemes do not have the capability to model optical properties of the leaves nor the entire canopy. As a result, they are unable to directly link canopy optical properties with light distribution within the canopy to remote sensing data observed from afar. Here, we incorporated one optimization-based and two empirical stomatal models with a comprehensive RT model in the land component of a new Earth system model within CliMA, the Climate Modelling Alliance. The model allowed us to simultaneously simulate carbon and water fluxes as well as leaf and canopy reflectance and fluorescence spectra. We tested our model by comparing our modeled carbon and water fluxes and solar-induced chlorophyll fluorescence (SIF) to two flux tower observations (a gymnosperm forest and an angiosperm forest) and satellite SIF retrievals, respectively. All three stomatal models quantitatively predicted the carbon and water fluxes for both forests. The optimization model, in particular, showed increased skill in predicting the water flux given the lower error (ca. 14.2 % and 21.8 % improvement for the gymnosperm and angiosperm forests, respectively) and better 1:1 comparison (slope increases from ca. 0.34 to 0.91 for the gymnosperm forest and from ca. 0.38 to 0.62 for the angiosperm forest). Our model also predicted the SIF yield, quantitatively reproducing seasonal cycles for both forests. We found that using stomatal optimization with a comprehensive RT model showed high accuracy in simulating land surface processes. The ever-increasing number of regional and global datasets of terrestrial plants, such as leaf area index and chlorophyll contents, will help parameterize the land model and improve future Earth system modeling in general.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.5194/gmd-14-6741-2021DOIArticle
https://doi.org/10.5194/gmd-14-6741-2021-supplementPublisherSupporting Information
https://doi.org/10.17190/AMF/1246088DOIFlux tower datasets - AmeriFlux
https://doi.org/10.17190/AMF/1246081DOIFlux tower datasets - US-MOz
http://globalchange.bnu.edu.cn/research/laiv6Related Itemgridded MODIS LAI
https://github.com/CliMA/GriddingMachine.jlDOIArtifacts of GriddingMachine.jl (v0.2) for land modeling
https://github.com/CliMA/LandRelated ItemCliMA Land model -- current version
https://doi.org/10.5281/zenodo.4762775DOICliMA Land model -- exact version of model used
ORCID:
AuthorORCID
Wang, Yujie0000-0002-3729-2743
Köhler, Philipp0000-0002-7820-1318
He, Liyin0000-0003-4427-1438
Doughty, Russell B.0000-0001-5191-2155
Braghiere, Renato K.0000-0002-7722-717X
Wood, Jeffrey D.0000-0001-6422-2882
Frankenberg, Christian0000-0002-0546-5857
Additional Information:© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 14 May 2021 – Discussion started: 01 Jun 2021 – Revised: 10 Sep 2021 – Accepted: 03 Oct 2021 – Published: 05 Nov 2021. We gratefully acknowledge the generous support of Eric and Wendy Schmidt (by recommendation of the Schmidt Futures) and the Heising-Simons Foundation. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). This research has been supported by the NASA Earth Sciences Division (grant no. NNX15AH95G), the Schmidt Futures program, and the Heising-Simons Foundation. Author contributions. YW designed and conducted the research. YW, CF, and RKB developed the CliMA Land model. PK performed the TROPOMI SIF retrieval. YW, PK, LH, RD, RKB, JDW, and CF performed the general data analysis and wrote the paper. Code and data availability Flux tower datasets are freely available at AmeriFlux (registration required; US-NR1: https://doi.org/10.17190/AMF/1246088, Blanken et al., 2021; US-MOz: https://doi.org/10.17190/AMF/1246081, Wood and Gu, 2021). The gridded MODIS LAI is available at http://globalchange.bnu.edu.cn/research/laiv6 (Yuan et al., 2020, 2011) and has also been made available via “GriddingMachine.jl” (https://github.com/CliMA/GriddingMachine.jl, last access: 27 September 2021; https://doi.org/10.22002/D1.2129, Wang, 2021b). We refer the reader to the online documentation of “GriddingMachine.jl” for access to the datasets (along with other high-quality gridded datasets such as TROPOMI SIF). We coded our model and did the analysis using Julia (version 1.6.0), and the current version of the CliMA Land model is available from the project website (under the Apache 2.0 License): https://github.com/CliMA/Land (last access: 29 March 2021). The exact version of the model used to produce the results employed in this paper is archived on Zenodo (https://doi.org/10.5281/zenodo.4762775, Wang, 2021a), as are the input data and scripts to run the model and produce the plots for all the simulations presented (Wang, 2021a). The supplement related to this article is available online at: https://doi.org/10.5194/gmd-14-6741-2021-supplement. The contact author has declared that neither they nor their co-authors have any competing interests. This paper was edited by Christoph Müller and reviewed by two anonymous referees.
Funders:
Funding AgencyGrant Number
NASANNX15AH95G
Schmidt Futures ProgramUNSPECIFIED
Heising-Simons FoundationUNSPECIFIED
NASA/JPL/CaltechUNSPECIFIED
Issue or Number:11
DOI:10.5194/gmd-14-6741-2021
Record Number:CaltechAUTHORS:20211208-951472000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20211208-951472000
Official Citation:Wang, Y., Köhler, P., He, L., Doughty, R., Braghiere, R. K., Wood, J. D., and Frankenberg, C.: Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1), Geosci. Model Dev., 14, 6741–6763, https://doi.org/10.5194/gmd-14-6741-2021, 2021.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:112313
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:10 Dec 2021 20:34
Last Modified:10 Dec 2021 20:34

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