The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange

Abstract

Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y.; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.; Gu, L.; and Marchesini, L. Belelli, "The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange" (2014 Mapping of terrestrial chlorophyll fluorescence from space has shown potential for providing global measurements related to gross primary productivity (GPP). In particular, space-based fluorescence may provide information on the length of the carbon uptake period. Here, for the first time we test the ability of satellite fluorescence retrievals to track seasonal cycle of photosynthesis as estimated from a diverse set of tower gas exchange measurements from around the world. The satellite fluorescence retrievals are obtained using new observations near the 740 nm emission feature from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument offering the highest temporal and spatial resolution of available global measurements. Because GOME-2 has a large ground footprint (~40 × 80 km 2 ) as compared with that of the flux towers and the GOME-2 data require averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP estimated from a machine learning approach averaged over the same temporal and spatial domain as the satellite data surrounding the tower locations. We also examine the seasonality of absorbed photosynthetically-active radiation (APAR) estimated from satellite measurements. Finally, to assess whether global vegetation models may benefit from the satellite fluorescence retrievals through validation or additional constraints, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested (especially deciduous broadleaf and mixed forests) and cropland sites, the GOME-2 fluorescence data track the spring onset and autumn shutoff of photosynthesis as delineated by the upscaled GPP estimates. In contrast, the reflectance-based indicators and many of the models, particularly those driven by data, tend to overestimate the length of the photosynthetically-active period for these biomes. Satellite fluorescence measurements therefore show potential for improving the seasonal dependence of photosynthesis simulated by global models at similar spatial scales.

Parallel Seasonal Patterns of Photosynthesis, Fluorescence, and Reflectance Indices in Boreal Trees

“…If the CCI is sensitive to both canopy structural changes influencing absorbed light (A PAR ) and photosynthetic ε, then the CCI can be used as a direct indicator of photosynthetic activity in multiple vegetation types, as proposed in Figure 1. SIF may also have a similar capability to the CCI in providing a direct indicator of photosynthetic activity [31], which has been suggested in large-scale studies linking fluorescence to GPP in multiple biomes [29], as it is known to be sensitive to photosynthetic downregulation and absorbed light [10].…”

“…With high-spectral resolution spectrometers that can resolve atmospheric absorption bands (Fraunhofer lines), fluorescence can now be passively detected from a distance as a small signal present in the "gaps" of the solar spectrum [27]). This solar-induced fluorescence (SIF) is closely linked to gross primary productivity (GPP) [28][29][30], however, the coarse spatial and temporal scales of many satellite-based SIF measurements cannot resolve detailed seasonal dynamics or explain underlying mechanisms driving changes in GPP. At leaf-scales, the PAM method can measure steady-state chlorophyll fluorescence (F S ) without delivering a saturating pulse of light, which is an analogous measurement to SIF measured at large scales, as both can be measured under ambient illumination, allowing for more mechanistic studies of individual leaves and canopies.…”

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

“…We used the GOME ‐ 2 version 26 (V26) far‐red 740 nm (near O 2 A‐band) terrestrial chlorophyll fluorescence data retrieval, which was provided by Dr. Joanna Joiner (Joiner et al, 2013, 2014, 2016). The data are available at 0.5° spatial resolution and at biweekly temporal resolution which covers the period January 2007 to September 2017.…”

“…Similar to GPP, SIF can be written using a LUE strategy as follows: SIF =  fesc  ×  ε  × fPAR Ch  × PAR (Joiner et al, 2014; Lee et al, 2013), with fesc a parameter related to the optical properties of the canopy and sensor angle (accounting for fraction of SIF photons escaping from leaf level to the canopy level) and ε as SIF yield. SIF variations at the leaf level and at short time scales may reflect changes in LUE (Agati et al, 1995; Corp et al, 2003; Long & Bernacchi, 2003; van der Tol et al, 2009); however, it is less clear whether the signal seen by coarse satellite observations over longer term period (several days) reflects mainly changes in LUE.…”

Comparison of solar-induced chlorophyll fluorescence, light-use efficiency, and process-based GPP models in maize

“…A recent empirical study showed the ability of space-borne SIF to monitor crop photosynthesis at regional and global scales and to correct existing underestimations by LUE models like MODIS-PSN ). Compared to reflectance-based satellite data (e.g., FPAR), Joiner et al (2014) showed that SIF can track spring onset and autumn decline of photosynthesis more closely in different biomes. Zhang et al (2014) demonstrated that key parameters for photosynthesis modeling, such as the maximum carboxylation capacity (V cmax ) can be derived from space-borne SIF data and the SCOPE model, which could improve GPP estimates.…”