Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O₂–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

Solar-induced chlorophyll fluorescence (SIF), which can be used as a novel proxy for estimating gross primary production (GPP), can be effectively retrieved using ground-based, airborne and satellite measurements. Absorbed photosynthetically active radiation (APAR) is the key bridge linking SIF and GPP. Remotely sensed SIF at the canopy level ( $SI{F}_{canopy}$ ) is only a part of the total SIF emission at the photosystem level. An SIF-based model for GPP estimation would be strongly influenced by the fraction of SIF photons escaping from the canopy ( $f_{esc}$ ). Understanding the response of $SI{F}_{canopy}$ to the absorbed photosynthetically active radiation absorbed by chlorophyll ( $APA{R}_{chl}$ ) is a key step in estimating GPP but, as yet, this has not been well explored. In this study, we aim to investigate the relationship between remotely sensed $SI{F}_{canopy}$ and $APA{R}_{chl}$ based on simulations made by the Soil Canopy Observation Photosynthesis Energy fluxes (SCOPE) model and field measurements. First, the ratio of the fraction of the absorbed photosynthetically active radiation absorbed by chlorophyll ( ${\mathrm{fPAR}}_{chl}$ ) to the fraction of absorbed photosynthetically active radiation absorbed by green leaves ( ${\mathrm{fPAR}}_{green}$ ) is investigated using a dataset simulated by the SCOPE model. The results give a mean value of 0.722 for Cab at 5 μg cm⁻², 0.761 for Cab at 10 μg cm⁻² and 0.795 for other Cab content (ranging from 0.71 to 0.81). The response of $SI{F}_{canopy}$ to $APA{R}_{chl}$ is then explored using simulations corresponding to different biochemical and biophysical conditions and it is found that $SI{F}_{canopy}$ is well correlated with $APA{R}_{chl}$ . At the O₂-A band, for a given plant type, the relationship between $SI{F}_{canopy}$ and $APA{R}_{chl}$ can be approximately expressed by a linear statistical model even for different values of the leaf area index (LAI) and chlorophyll content, whereas the relationship varies with the LAI and chlorophyll content at the O₂-B band. Finally, the response of $SI{F}_{canopy}$ to $APA{R}_{chl}$ for different leaf angle distribution (LAD) functions is investigated using field observations and simulations; the results show that $f_{esc}$ is larger for a planophile canopy structure. The values of the ratio of $SI{F}_{canopy}$ to $APA{R}_{chl}$ are 0.0092 $\pm 0.0020$ , 0.0076 $\pm 0.0036$ and 0.0052 $\pm 0.0004$ μm⁻¹ sr⁻¹ for planophile vegetables/crops, planophile grass and spherical winter wheat, respectively, at the O₂-A band. At the O₂-B band, the ratios are 0.0063 $\pm 0.0014$ , 0.0049 $\pm 0.0030$ and 0.0033 $\pm 0.0004$ μm⁻¹ sr⁻¹, respectively. The values of this ratio derived from observations agree with simulations, giving values of 0.0055 $\pm 0.0002$ and 0.0068 $\pm 0.0001$ μm⁻¹ sr⁻¹ at the O₂-A band and 0.0032 $\pm 0.0002$ and 0.0047 $\pm 0.0001$ μm⁻¹ sr⁻¹ at the O₂-B band for spherical and planophile canopies, respectively. Therefore, both the simulations and observations confirm that the relationship between $SI{F}_{canopy}$ and ${\mathrm{APAR}}_{chl}$ is species-specific and affected by biochemical components and canopy structure, especially at the O₂-B band. It is also very important to correct for reabsorption and scattering of the SIF radiative transfer from the photosystem to the canopy level before the remotely sensed $SI{F}_{canopy}$ is linked to the GPP.

Solar-induced chlorophyll fluorescence (SIF) is closely linked to the photosynthesis of plants and has the potential to estimate gross primary production (GPP) at different temporal and spatial scales. However, remotely sensed SIF at a ground or space level is usually instantaneous, which cannot represent the daily total SIF. The temporal mismatch between instantaneous SIF (SIF_inst) and daily GPP (GPP_daily) impacts their correlation across space and time. Previous studies have upscaled SIF_inst to the daily scale based on the diurnal cycle in the cosine of the solar zenith angle ( $\cos \left(\mathrm{SZA}\right)$ ) to correct the effects of latitude and length of the day on the variations in the SIF-GPP correlation. However, the important effects of diurnal weather changes due to cloud and atmospheric scattering were not considered. In this study, we present a SIF upscaling method using photosynthetically active radiation (PAR) as a driving variable. First, a conversion factor (i.e., the ratio of the instantaneous PAR (PAR_inst) to daily PAR (PAR_daily)) was used to upscale in-situ SIF measurements from the instantaneous to daily scale. Then, the performance of the SIF upscaling method was evaluated under changing weather conditions and different latitudes using continuous tower-based measurements at two sites. The results prove that our PAR-based method can reduce not only latitude-dependent but also the weather-dependent variations in the SIF-GPP model. Specifically, the PAR-based method gave a more accurate prediction of diurnal and daily SIF (SIF_daily) than the $\cos \left(\mathrm{SZA}\right)$ -based method, with decreased relative root mean square error (RRMSE) values from 42.2% to 25.6% at half-hour intervals and from 25.4% to 13.3% at daily intervals. Moreover, the PAR-based upscaled SIF_daily had a stronger correlation with the daily absorbed PAR (APAR) than both the SIF_inst and $\cos \left(\mathrm{SZA}\right)$ -based upscaled SIF_daily, especially for cloudy days with a coefficient of determination (R²) that increased from approximately 0.5 to 0.8. Finally, the PAR-based SIF_daily was linked to GPP_daily and compared to the SIF_inst or $\cos \left(\mathrm{SZA}\right)$ -based SIF_daily. The results indicate that the SIF-GPP correlation can obviously be improved, with an increased R² from approximately 0.65 to 0.75. Our study confirms the importance of upscaling SIF from the instantaneous to daily scale when linking SIF with GPP and emphasizes the need to take diurnal weather changes into account for SIF temporal upscaling.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) has been widely investigated with satellites/sensors covering the spectral range of SIF emission with fine spectral resolutions (SRs). The potential precision of SIF retrievals is limited by instruments’ spectral specifications. Here, the influence of spectral characteristics (SR, signal-to-noise ratio (SNR), and spectral coverage) on data-driven SIF retrieval was assessed using simulations, and the SIF retrieval capability of the obsolete, in-orbit, and planned satellites was evaluated from the spectral perspective. As a result, the 757–759- and 735–758-nm fitting windows (FWs) were found to be optimal for far-red SIF retrieval on satellites with fine (< 0.1 nm) and moderate (0.1–0.5 nm) SR. The 682–697-nm FW was found to perform better for red SIF retrievals. For far-red SIF retrievals, Orbiting Carbon Observatory 2 (OCO-2) and TanSat were found to have the best SIF retrieval performance, with a root-mean-square-error (RMSE $^{\ast}$ ) of lower than 0. 25 mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1, followed by satellites with moderate SRs (0.1–0.5 nm) such as CO2 monitoring (CO2M), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment 2 (GOME-2) (RMSE $^{\ast} < 0.5$ mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1). The high SNR of SCanning Imaging Absorption Spectro Meter for Atmospheric CHartographY (SCIAMACHY) did not improve the far-red SIF retrieval greatly (RMSE $^{\ast} =0.47$ mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1) but obtained a low RMSE $^{\ast} $ at the red band (0.43 mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1). The highest red SIF retrieval potential was found on TROPOMI, with an RMSE $^{\ast} $ of 0.41 mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1. Tropospheric Emissions Monitoring of Pollution (TEMPO) and FLuorescence Explorer (FLEX) gave poor performance (RMSE $^{\ast} >0.9$ mW $\cdot \,\,\text{m}^{-2}\,\,\cdot $ sr $^{-1}\,\,\cdot $ nm-1) with their current spectral specifications. Improvement of the spectral characteristics is still needed to obtain precise SIF retrievals.

Solar-induced chlorophyll fluorescence (SIF) provides a new and direct way of monitoring photosynthetic activity. However, current SIF products are limited by low spatial resolution or sparse sampling. In this paper, we present a data-driven method of generating a global, spatially continuous TanSat SIF product. Firstly, the key explanatory variables for modelling canopy SIF were investigated using in-situ and satellite observations. According to theoretical and experimental analysis, the solar radiation intensity was found to be a dominant driving environmental variable for the SIF yield at both the canopy and global scales; this has, however, been neglected in previous research. The cosine value of the solar zenith angle at noon (cos (SZA₀)), a proxy for solar radiation intensity, was found to be a dominant abiotic factor for the SIF yield. Next, a Random Forest (RF) approach was employed for SIF prediction based on Moderate Resolution Imaging Spectroradiometer (MODIS) visible-to-NIR reflectance data, the normalized difference vegetation (NDVI), cos (SZA₀), and air temperature. The machine learning model performed well at predicting SIF, giving R² values of 0.73, an RMSE of 0.30 mW m⁻² nm⁻¹ sr⁻¹ and a bias of 0.22 mW m⁻² nm⁻¹ sr⁻¹ for 2018. If cos (SZA₀) was not included, the accuracy of the RF model decreased: the R² value was then 0.65, the RMSE 0.34 mW m⁻² nm⁻¹ sr⁻¹ and an bias of 0.26 mW m⁻² nm⁻¹ sr⁻¹, further verifying the importance of cos (SZA₀). Finally, the globally continuous TanSat SIF product was developed and compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIF data. The results showed that the globally continuous TanSat SIF product agreed well with the TROPOMI SIF data, with an R² value of 0.73. Thus, this paper presents an improved approach to modelling satellite SIF that has a better accuracy, and the study also generated a global, spatially continuous TanSat SIF product with a spatial resolution of 0.05°.

Structural–physiological factors affect the accurate estimation of vegetation gross primary production (GPP) under various types of environmental stress. Solar-induced chlorophyll fluorescence (SIF), which is directly linked to photosynthesis, has been effectively used to estimate and monitor GPP. However, understanding of the physiological mechanism linking SIF to GPP under stress remains limited. In this article, the link between SIF and GPP at diurnal and seasonal timescales was explored for a maize field and its response to drought stress (as defined by the crop water stress index, CWSI) using three-years of continuous tower-based measurements was investigated. The results show that the ratio of GPP to SIF decreased with increasing drought stress levels, and the canopy stomata conductance (Gs) declined synchronously. Compared to two canopy structural factors (NDVI and NIRv), both the Pearson and partial correlation coefficients for the relationship between Gs and the ratio of GPP to the total SIF was higher (0.38, p < 0.01 and 0.32, p < 0.01 with photosynthetically active radiation as the control variable, respectively). We also found that ${{\bf \Phi }_F}$ tracked the changes in LUE well under drought conditions (CWSI > 0.6), which demonstrated that SIF can be a powerful parameter for estimating GPP under drought stress. However, there was a smaller drop in ${{\bf \Phi }_F}$ under drought stress (slope = –0.002) compared to the slope for the relationship between LUE and CWSI (–0.08). The response of light reactions to drought stress may be muted compared to the stomatal response. These findings confirm that the Gs is sensitive to drought and is important for the SIF-based GPP estimation model. It also provides reliable evidence that SIF data include a large amount of physiological information and can serve as a potential indicator for detecting drought and estimating GPP.