Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land.
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| Title: | Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land. |
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| Authors: | Wang, Y.1 (AUTHOR) wyujie@caltech.edu, Braghiere, R. K.1,2 (AUTHOR), Longo, M.2,3 (AUTHOR), Norton, A. J.2 (AUTHOR), Köhler, P.1 (AUTHOR), Doughty, R.1,4 (AUTHOR), Yin, Y.1 (AUTHOR), Bloom, A. A.2 (AUTHOR) alexis.a.bloom@jpl.nasa.gov, Frankenberg, C.1,2 (AUTHOR) cfranken@caltech.edu |
| Source: | Journal of Advances in Modeling Earth Systems. Mar2023, Vol. 15 Issue 3, p1-19. 19p. |
| Subject Terms: | *Vegetation monitoring, Radiative transfer, Primary productivity (Biology), Eddy flux, Chlorophyll spectra, Fluorescence spectroscopy, Radiance, Spatial resolution |
| Abstract: | Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For example, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT; 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar‐induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun‐sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data‐driven products (mean R2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for example, providing insights into when GPP, SIF, and NIRv diverge. Plain Language Summary: Terrestrial plants exchange water for CO2, but there is not a direct way to measure the carbon gain and water loss at the global scale. Researchers often use eddy covariance flux tower measurements and satellite observations to infer vegetation gross primary productivity (GPP) and transpiration (T). However, flux towers with high temporal resolution are too sparsely distributed, and satellites with high spatial coverage can only detect vegetation properties indirectly, such as solar induced chlorophyll fluorescence, rather than GPP and T themselves. We bridge these two aspects in a new generation land surface model that simultaneously simulates GPP and T, as well as spectrally resolved canopy radiative transfer. We compare our model outputs directly to not only GPP and T estimations but also satellite retrievals of fluorescence and vegetation indices. We show that our new model can represent how GPP and T, as well as canopy radiative properties vary across the globe. Key Points: Overview of Climate Modeling Alliance Land model at the global scale and comparison to existing productsVegetation gross primary productivity, transpiration, and hyperspectral canopy radiative transfer are simulated simultaneouslyModeled fluxes and canopy reflectance and fluorescence well capture the spatial patterns across the globe compared to existing observations [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Advances in Modeling Earth Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Y%2E%22">Wang, Y.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wyujie@caltech.edu</i><br /><searchLink fieldCode="AR" term="%22Braghiere%2C+R%2E+K%2E%22">Braghiere, R. K.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Longo%2C+M%2E%22">Longo, M.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Norton%2C+A%2E+J%2E%22">Norton, A. J.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Köhler%2C+P%2E%22">Köhler, P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Doughty%2C+R%2E%22">Doughty, R.</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yin%2C+Y%2E%22">Yin, Y.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bloom%2C+A%2E+A%2E%22">Bloom, A. A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> alexis.a.bloom@jpl.nasa.gov</i><br /><searchLink fieldCode="AR" term="%22Frankenberg%2C+C%2E%22">Frankenberg, C.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> cfranken@caltech.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Advances+in+Modeling+Earth+Systems%22">Journal of Advances in Modeling Earth Systems</searchLink>. Mar2023, Vol. 15 Issue 3, p1-19. 19p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Vegetation+monitoring%22">Vegetation monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Radiative+transfer%22">Radiative transfer</searchLink><br /><searchLink fieldCode="DE" term="%22Primary+productivity+%28Biology%29%22">Primary productivity (Biology)</searchLink><br /><searchLink fieldCode="DE" term="%22Eddy+flux%22">Eddy flux</searchLink><br /><searchLink fieldCode="DE" term="%22Chlorophyll+spectra%22">Chlorophyll spectra</searchLink><br /><searchLink fieldCode="DE" term="%22Fluorescence+spectroscopy%22">Fluorescence spectroscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Radiance%22">Radiance</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+resolution%22">Spatial resolution</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For example, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT; 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar‐induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun‐sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data‐driven products (mean R2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for example, providing insights into when GPP, SIF, and NIRv diverge. Plain Language Summary: Terrestrial plants exchange water for CO2, but there is not a direct way to measure the carbon gain and water loss at the global scale. Researchers often use eddy covariance flux tower measurements and satellite observations to infer vegetation gross primary productivity (GPP) and transpiration (T). However, flux towers with high temporal resolution are too sparsely distributed, and satellites with high spatial coverage can only detect vegetation properties indirectly, such as solar induced chlorophyll fluorescence, rather than GPP and T themselves. We bridge these two aspects in a new generation land surface model that simultaneously simulates GPP and T, as well as spectrally resolved canopy radiative transfer. We compare our model outputs directly to not only GPP and T estimations but also satellite retrievals of fluorescence and vegetation indices. We show that our new model can represent how GPP and T, as well as canopy radiative properties vary across the globe. Key Points: Overview of Climate Modeling Alliance Land model at the global scale and comparison to existing productsVegetation gross primary productivity, transpiration, and hyperspectral canopy radiative transfer are simulated simultaneouslyModeled fluxes and canopy reflectance and fluorescence well capture the spatial patterns across the globe compared to existing observations [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Advances in Modeling Earth Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2021MS002964 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 1 Subjects: – SubjectFull: Vegetation monitoring Type: general – SubjectFull: Radiative transfer Type: general – SubjectFull: Primary productivity (Biology) Type: general – SubjectFull: Eddy flux Type: general – SubjectFull: Chlorophyll spectra Type: general – SubjectFull: Fluorescence spectroscopy Type: general – SubjectFull: Radiance Type: general – SubjectFull: Spatial resolution Type: general Titles: – TitleFull: Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Y. – PersonEntity: Name: NameFull: Braghiere, R. K. – PersonEntity: Name: NameFull: Longo, M. – PersonEntity: Name: NameFull: Norton, A. J. – PersonEntity: Name: NameFull: Köhler, P. – PersonEntity: Name: NameFull: Doughty, R. – PersonEntity: Name: NameFull: Yin, Y. – PersonEntity: Name: NameFull: Bloom, A. A. – PersonEntity: Name: NameFull: Frankenberg, C. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 19422466 Numbering: – Type: volume Value: 15 – Type: issue Value: 3 Titles: – TitleFull: Journal of Advances in Modeling Earth Systems Type: main |
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