Using different radiative transfer schemes for solar-induced chlorophyll fluorescence (SIF) in evergreen coniferous forests with a terrestrial biosphere model

Abstract. Solar-induced chlorophyll fluorescence (SIF) is a small light signal emitted during the initial steps of photosynthesis and can be observed across scales (from photosystem level to satellite observation footprints). To be able to model SIF, we need to understand the mechanistic processes (including both physical and biological) leading to the observed SIF signal. In this study, we implemented a representation of SIF emission and transmission processes into the terrestrial biosphere model QUINCY (“QUantifying Interactions between terrestrial Nutrient CYcles and the climate system”). We tested the model across three different boreal coniferous forests located in North America and Europe that have eddy covariance derived CO2 fluxes and tower-based SIF observations. We found that different SIF radiative transfer approaches (one based on mSCOPE, one on two-stream radiative transfer model L2SM, and one empirically based) overestimated the SIF signal, but showed no large differences in the timing of their seasonal and diurnal predictions. The two-stream radiative transfer model approach, L2SM, provided stable performance while being comparatively computationally efficient. Our parameterization for sustained non-photochemical quenching was important for successfully simulating the timing of the SIF seasonal cycle. However, our parameterization did not perform equally well at all three sites, likely because of different temperature regimes at each site. We further evaluated the potential of remote sensing-based SIF from TROPOMI (the TROPOspheric Monitoring Instrument) to provide accurate information on SIF and found that it could potentially be used in model development. This study demonstrated the usefulness of observations at various spatial scales and the linkages between SIF and GPP and their seasonal cycle at three different evergreen forest sites.

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Publication Details

Journal
Biogeosciences
Published
2026-05-22
DOI
https://doi.org/10.5194/bg-23-3541-2026
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Using different radiative transfer schemes for solar-induced chlorophyll fluorescence (SIF) in evergreen coniferous forests with a terrestrial biosphere model

Zoe Pierrat, Hannakaisa Lindqvist, Tea Thum, Marika Honkanen et al.
Biogeosciences
Remote Sensing in Agriculture
article

Using different radiative transfer schemes for solar-induced chlorophyll fluorescence (SIF) in evergreen coniferous forests with a terrestrial biosphere model

Zoe Pierrat, Hannakaisa Lindqvist, Tea Thum, Marika Honkanen, Javier Pacheco-Labrador, Mika Aurela, Alan Barr, Bruce Johnson, Tristan Quaife, Mirco Migliavacca, Troy Magney, Jochen Stutz, Sönke Zaehle
article en

Abstract

Abstract. Solar-induced chlorophyll fluorescence (SIF) is a small light signal emitted during the initial steps of photosynthesis and can be observed across scales (from photosystem level to satellite observation footprints). To be able to model SIF, we need to understand the mechanistic processes (including both physical and biological) leading to the observed SIF signal. In this study, we implemented a representation of SIF emission and transmission processes into the terrestrial biosphere model QUINCY (“QUantifying Interactions between terrestrial Nutrient CYcles and the climate system”). We tested the model across three different boreal coniferous forests located in North America and Europe that have eddy covariance derived CO2 fluxes and tower-based SIF observations. We found that different SIF radiative transfer approaches (one based on mSCOPE, one on two-stream radiative transfer model L2SM, and one empirically based) overestimated the SIF signal, but showed no large differences in the timing of their seasonal and diurnal predictions. The two-stream radiative transfer model approach, L2SM, provided stable performance while being comparatively computationally efficient. Our parameterization for sustained non-photochemical quenching was important for successfully simulating the timing of the SIF seasonal cycle. However, our parameterization did not perform equally well at all three sites, likely because of different temperature regimes at each site. We further evaluated the potential of remote sensing-based SIF from TROPOMI (the TROPOspheric Monitoring Instrument) to provide accurate information on SIF and found that it could potentially be used in model development. This study demonstrated the usefulness of observations at various spatial scales and the linkages between SIF and GPP and their seasonal cycle at three different evergreen forest sites.

BiogeosciencesVol. 23(10)
National Science Foundation, National Aeronautics and Space Administration, UK Research and Innovation, European Space Agency, Academy of Finland
Climate action
Openalex Percentile: Top 5%
Remote Sensing in Agriculture
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