Literature DB >> 25881891

Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4.

Jung-Eun Lee1, Joseph A Berry2,3, Christiaan van der Tol4, Xi Yang1, Luis Guanter5, Alexander Damm6, Ian Baker7, Christian Frankenberg8.   

Abstract

Several studies have shown that satellite retrievals of solar-induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux-tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (Vmax ) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.
© 2015 John Wiley & Sons Ltd.

Entities:  

Keywords:  GOSAT; NCAR CLM; chlorophyll fluorescence; gross primary production; land surface model; model evaluation; remote sensing; tropical forests

Mesh:

Substances:

Year:  2015        PMID: 25881891     DOI: 10.1111/gcb.12948

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  9 in total

1.  Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Authors:  Gina H Mohammed; Roberto Colombo; Elizabeth M Middleton; Uwe Rascher; Christiaan van der Tol; Ladislav Nedbal; Yves Goulas; Oscar Pérez-Priego; Alexander Damm; Michele Meroni; Joanna Joiner; Sergio Cogliati; Wouter Verhoef; Zbyněk Malenovský; Jean-Philippe Gastellu-Etchegorry; John R Miller; Luis Guanter; Jose Moreno; Ismael Moya; Joseph A Berry; Christian Frankenberg; Pablo J Zarco-Tejada
Journal:  Remote Sens Environ       Date:  2019-07-13       Impact factor: 10.164

2.  Estimating leaf photosynthesis of C3 plants grown under different environments from pigment index, photochemical reflectance index, and chlorophyll fluorescence.

Authors:  Katsuto Tsujimoto; Kouki Hikosaka
Journal:  Photosynth Res       Date:  2021-04-28       Impact factor: 3.573

3.  Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically-based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence.

Authors:  Seyed Hamed Alemohammad; Bin Fang; Alexandra G Konings; Filipe Aires; Julia K Green; Jana Kolassa; Diego Miralles; Catherine Prigent; Pierre Gentine
Journal:  Biogeosciences       Date:  2017-09-20       Impact factor: 4.295

4.  A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020.

Authors:  Wenjun Bi; Wei He; Yanlian Zhou; Weimin Ju; Yibo Liu; Yang Liu; Xiaoyu Zhang; Xiaonan Wei; Nuo Cheng
Journal:  Sci Data       Date:  2022-05-16       Impact factor: 8.501

5.  Integrating SIF and Clearness Index to Improve Maize GPP Estimation Using Continuous Tower-Based Observations.

Authors:  Jidai Chen; Xinjie Liu; Shanshan Du; Yan Ma; Liangyun Liu
Journal:  Sensors (Basel)       Date:  2020-04-28       Impact factor: 3.576

6.  FluoSpec 2-An Automated Field Spectroscopy System to Monitor Canopy Solar-Induced Fluorescence.

Authors:  Xi Yang; Hanyu Shi; Atticus Stovall; Kaiyu Guan; Guofang Miao; Yongguang Zhang; Yao Zhang; Xiangming Xiao; Youngryel Ryu; Jung-Eun Lee
Journal:  Sensors (Basel)       Date:  2018-06-28       Impact factor: 3.847

7.  Representation of Leaf-to-Canopy Radiative Transfer Processes Improves Simulation of Far-Red Solar-Induced Chlorophyll Fluorescence in the Community Land Model Version 5.

Authors:  Rong Li; Danica Lombardozzi; Mingjie Shi; Christian Frankenberg; Nicholas C Parazoo; Philipp Köhler; Koong Yi; Kaiyu Guan; Xi Yang
Journal:  J Adv Model Earth Syst       Date:  2022-03-20       Impact factor: 8.469

8.  Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data.

Authors:  Natasha MacBean; Fabienne Maignan; Cédric Bacour; Philip Lewis; Philippe Peylin; Luis Guanter; Philipp Köhler; Jose Gómez-Dans; Mathias Disney
Journal:  Sci Rep       Date:  2018-01-31       Impact factor: 4.379

9.  Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence.

Authors:  P Gentine; S H Alemohammad
Journal:  Geophys Res Lett       Date:  2018-04-13       Impact factor: 4.720

  9 in total

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