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  6. Data from: Systematic assessment of retrieval methods for canopy far-red solar-induced chlorophyll fluorescence (SIF) using automated high-frequency field spectroscopy

Data from: Systematic assessment of retrieval methods for canopy far-red solar-induced chlorophyll fluorescence (SIF) using automated high-frequency field spectroscopy

File(s)
Aurora2018_SIF.csv (10.74 MB)
measurements from SIF tower
ECtower_data.csv (279.38 KB)
SCOPE inputs measured from eddy covariance tower
canopy_height.csv (908 B)
SCOPE optional input for canopy height
LAI.csv (145 B)
SCOPE optional input for leaf area index
JGR_RetrievalMethodsComparison_readme.txt (7.96 KB)
Permanent Link(s)
https://doi.org/10.7298/wqx5-ba07
https://hdl.handle.net/1813/69711
Collections
Soil and Crop Sciences Research
Author
Chang, Christine Y.
Melkonian, Jeffrey
Riha, Susan J.
Frankenberg, Christian
Guanter, Luis
Gu, Lianhong
Sun, Ying
Abstract

Data in support of the following research: Remote sensing of solar-induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top-of-canopy SIF using ground-based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco-physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal- and spectral-resolution ground-based spectroscopy, we aimed to 1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; 2) assess method sensitivity to fluctuating light, reflectance and fluorescence emission spectra; and 3) inform users for optimal ground-based SIF retrieval. Analysis included field measurements from bi-hemispherical and hemispherical-conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance and simulated fluorescence for benchmarking. Fraunhofer-based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF-PAR relationships and diurnal consistency across different sky conditions while O2A-based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF-PAR relationships across sky conditions. Such behavior holds across system configurations, though hemispherical-conical systems diverge less across sky conditions. O2A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally-local spectra. This may impact SIF-photosynthesis relationships interpreted by previous studies using O2A-based retrievals with standard (759-767.76 nm) fitting windows. Fraunhofer-based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O2A-based retrievals. We recommend SVD or SFM using reduced fitting window (759.5-761.5 nm) for robust far-red SIF retrievals across sky conditions.

Description
Christine Y. Chang, Jeffrey Melkonian, Susan J. Riha, Christian Frankenberg, Luis Guanter, Lianhong Gu, Ying Sun. (2020) Data from: Systematic assessment of retrieval methods for canopy far-red solar-induced chlorophyll fluorescence (SIF) using automated high-frequency field spectroscopy. [dataset] Cornell University Library eCommons Repository. https://doi.org/10.7298/wqx5-ba07
Date Issued
2020
Keywords
solar-induced chlorophyll fluorescence (SIF)
•
assessment of retrieval methods
•
field spectroscopy
Related Publication(s)
Chang C.Y., Guanter L., Frankenberg C., Köhler P., Gu L., Magney T.S., Grossmann K., Sun Y. (2020) Systematic assessment of retrieval methods for canopy far-red solar-induced chlorophyll fluorescence (SIF) using high-frequency automated field spectroscopy. Journal of Geophysical Research: Biogeosciences. 125:e2019JG005533 https://doi.org/10.1029/2019JG005533
Christine Yao-Yun Chang. (2020). SunCornell/SIF_retrieval_methods: SIF_retrieval_methods (Version v1.0). [code] Zenodo. https://doi.org/10.5281/zenodo.3759965
Link(s) to Related Publication(s)
https://doi.org/10.1029/2019JG005533
Rights
Attribution 4.0 International
Rights URI
http://creativecommons.org/licenses/by/4.0/
Type
dataset

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