Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes
<p>Canopy structural and leaf photosynthesis parameterizations such as maximum carboxylation capacity (<span class="inline-formula"><i>V</i><sub>cmax</sub></span>), slope of the Ball–Berry stomatal conductance model (BB<span class="inline-f...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-01-01
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| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/16/77/2019/bg-16-77-2019.pdf |
| _version_ | 1829111517323198464 |
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| author | D. Dutta D. S. Schimel Y. Sun C. van der Tol C. Frankenberg C. Frankenberg |
| author_facet | D. Dutta D. S. Schimel Y. Sun C. van der Tol C. Frankenberg C. Frankenberg |
| author_sort | D. Dutta |
| collection | DOAJ |
| description | <p>Canopy
structural and leaf photosynthesis parameterizations such as maximum
carboxylation capacity (<span class="inline-formula"><i>V</i><sub>cmax</sub></span>), slope of the Ball–Berry
stomatal conductance model (BB<span class="inline-formula"><sub>slope</sub></span>) and leaf area index (LAI)
are crucial for modeling plant physiological processes and canopy radiative
transfer. These parameters are large sources of uncertainty in predictions of
carbon and water fluxes. In this study, we develop an optimal moving window
nonlinear Bayesian inversion framework to use the Soil Canopy Observation
Photochemistry and Energy fluxes (SCOPE) model for constraining
<span class="inline-formula"><i>V</i><sub>cmax</sub></span>, BB<span class="inline-formula"><sub>slope</sub></span> and LAI with observations of
coupled carbon and energy fluxes and spectral reflectance from satellites. We
adapted SCOPE to follow the biochemical implementation of the Community Land
Model and applied the inversion framework for parameter retrievals of plant
species that have both the C<span class="inline-formula"><sub>3</sub></span> and C<span class="inline-formula"><sub>4</sub></span> photosynthetic pathways across
three ecosystems. We present comparative analysis of parameter retrievals
using observations of (i) gross primary productivity (GPP) and latent energy
(LE) fluxes and (ii) improvement in results when using flux observations
along with reflectance. Our results demonstrate the applicability of the
approach in terms of capturing the seasonal variability and posterior error
reduction (40 %–90 %) of key ecosystem parameters. The optimized
parameters capture the diurnal and seasonal variability in the GPP and LE
fluxes well when compared to flux tower observations (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">0.95</mn><mo>></mo><msup><mi>R</mi><mn mathvariant="normal">2</mn></msup><mo>></mo><mn mathvariant="normal">0.79</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="83pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="14262529bbc61cc2969bf296e20a9b93"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-16-77-2019-ie00001.svg" width="83pt" height="13pt" src="bg-16-77-2019-ie00001.png"/></svg:svg></span></span>).
This study thus demonstrates the feasibility of parameter inversions using
SCOPE, which can be easily adapted to incorporate additional data sources
such as spectrally resolved reflectance and fluorescence and thermal
emissions.</p> |
| first_indexed | 2024-12-12T12:21:49Z |
| format | Article |
| id | doaj.art-8dc1799e239a42ce9f25a3f45c6d00f8 |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-12-12T12:21:49Z |
| publishDate | 2019-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-8dc1799e239a42ce9f25a3f45c6d00f82022-12-22T00:24:39ZengCopernicus PublicationsBiogeosciences1726-41701726-41892019-01-01167710310.5194/bg-16-77-2019Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxesD. Dutta0D. S. Schimel1Y. Sun2C. van der Tol3C. Frankenberg4C. Frankenberg5Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USAJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USASchool of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, NY, USAFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the NetherlandsJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USADivision of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA<p>Canopy structural and leaf photosynthesis parameterizations such as maximum carboxylation capacity (<span class="inline-formula"><i>V</i><sub>cmax</sub></span>), slope of the Ball–Berry stomatal conductance model (BB<span class="inline-formula"><sub>slope</sub></span>) and leaf area index (LAI) are crucial for modeling plant physiological processes and canopy radiative transfer. These parameters are large sources of uncertainty in predictions of carbon and water fluxes. In this study, we develop an optimal moving window nonlinear Bayesian inversion framework to use the Soil Canopy Observation Photochemistry and Energy fluxes (SCOPE) model for constraining <span class="inline-formula"><i>V</i><sub>cmax</sub></span>, BB<span class="inline-formula"><sub>slope</sub></span> and LAI with observations of coupled carbon and energy fluxes and spectral reflectance from satellites. We adapted SCOPE to follow the biochemical implementation of the Community Land Model and applied the inversion framework for parameter retrievals of plant species that have both the C<span class="inline-formula"><sub>3</sub></span> and C<span class="inline-formula"><sub>4</sub></span> photosynthetic pathways across three ecosystems. We present comparative analysis of parameter retrievals using observations of (i) gross primary productivity (GPP) and latent energy (LE) fluxes and (ii) improvement in results when using flux observations along with reflectance. Our results demonstrate the applicability of the approach in terms of capturing the seasonal variability and posterior error reduction (40 %–90 %) of key ecosystem parameters. The optimized parameters capture the diurnal and seasonal variability in the GPP and LE fluxes well when compared to flux tower observations (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">0.95</mn><mo>></mo><msup><mi>R</mi><mn mathvariant="normal">2</mn></msup><mo>></mo><mn mathvariant="normal">0.79</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="83pt" height="13pt" class="svg-formula" dspmath="mathimg" md5hash="14262529bbc61cc2969bf296e20a9b93"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-16-77-2019-ie00001.svg" width="83pt" height="13pt" src="bg-16-77-2019-ie00001.png"/></svg:svg></span></span>). This study thus demonstrates the feasibility of parameter inversions using SCOPE, which can be easily adapted to incorporate additional data sources such as spectrally resolved reflectance and fluorescence and thermal emissions.</p>https://www.biogeosciences.net/16/77/2019/bg-16-77-2019.pdf |
| spellingShingle | D. Dutta D. S. Schimel Y. Sun C. van der Tol C. Frankenberg C. Frankenberg Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes Biogeosciences |
| title | Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| title_full | Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| title_fullStr | Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| title_full_unstemmed | Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| title_short | Optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| title_sort | optimal inverse estimation of ecosystem parameters from observations of carbon and energy fluxes |
| url | https://www.biogeosciences.net/16/77/2019/bg-16-77-2019.pdf |
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