Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates

Abstract

The opening and closing of plant stomata regulates the global water, carbon and energy cycles. Biophysical feedbacks on climate are highly dependent on transpiration, which is mediated by vegetation phenology and plant responses to stress conditions. Here, we explore the potential of satellite observations of solar-induced chlorophyll fluorescence (SIF)-normalized by photosynthetically-active radiation (PAR)-to diagnose the ratio of transpiration to potential evaporation ('transpiration efficiency', τ). This potential is validated at 25 eddy-covariance sites from seven biomes worldwide. The skill of the state-of-the-art land surface models (LSMs) from the eartH2Observe project to estimate τ is also contrasted against eddy-covariance data. Despite its relatively coarse (0.5 • ) resolution, SIF/PAR estimates, based on data from the Global Ozone Monitoring Experiment 2 (GOME-2) and the Clouds and Earth's Radiant Energy System (CERES), correlate to the in situ τ significantly (average inter-site correlation of 0.59), with higher correlations during growing seasons (0.64) compared to decaying periods (0.53). In addition, the skill to diagnose the variability of in situ τ demonstrated by all LSMs is on average lower, indicating the potential of SIF data to constrain the formulations of transpiration in global models via, e.g., data assimilation. Overall, SIF/PAR estimates successfully capture the effect of phenological changes and environmental stress on natural ecosystem transpiration, adequately reflecting the timing of this variability without complex parameterizations.However, perhaps unsurprisingly, current LSMs still constrain transpiration based on empirical relationships between stomatal conductance and environmental variables such as soil moisture, temperature and vapor pressure deficit [18][19][20]. These formulations are supported by limited observational evidence at global scales, and their assumptions affect the modelled heat and drought response of ecosystem transpiration, which remains uncertain in current models [7,21,22]. The effect of water stress on transpiration is typically introduced in LSMs through a dimensionless empirical factor based on an assumed relationship between soil moisture and stomatal conductance, net photosynthesis, mesophyll conductance and/or carboxylation rate [21,[23][24][25]. Pure hydrologic and remote-sensing models-which have no explicit photosynthesis and coupled stomatal dependence-use similar empirical water-stress functions to constrain the potential transpiration estimates from Penman-Monteith or Priestley and Taylor approaches [26][27][28][29][30]. Two-source energy balance models utilize remotely sensed surface temperatures to constrain transpiration, but often still rely on Penman-Monteith, Priestley and Taylor, or aerodynamic formulations [31], or solve for latent heat as the residual term in the energy balance [32,33].Given (a) the importance of transpiration for global hydrology and climate, (b) the dependency of transpiration on phenology and physiological respons...

Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

“…SIF emission is related to the light reactions of photosynthesis but GPP estimation also requires information on the dark reactions and stomatal conductance such that the remote sensing community is currently challenged by how to use SIF to estimate GPP. New studies also propose that SIF might be used to monitor T, possibly in combination with surface temperature 10 measurements, acknowledging the close link between GPP and T due to their joint dependence on stomatal conductance and common meteorological and environmental drivers (Alemohammad et al, 2017;Damm et al, 2018;Lu et al, 2018;Pagán et al, 2019;Shan et al, 2019).…”

“…The authors suggested that the decoupling between GPP and T during water stress episodes hampered the use of SIF to predict T, 20 particularly in grasslands, noting that T can occur without GPP under periods of plant stress (Bunce, 1988;De Kauwe et al, 2019). There is a strong empirical link between the ratio of T over potential evaporation and the ratio of SIF over PAR, and the relationship depends on the atmospheric demand for water, with larger transpiration for the same SIF when potential evaporation is higher Alemohammad et al, 2017;Damm et al, 2018;Lu et al, 2018;Pagán et al, 2019;Shan et al, 2019).…”

Remote sensing of forest gas exchange: Considerations derived from a tomographic perspective

“…Recent RS approaches based on measurements of sun-induced chlorophyll fluorescence propose complementary pathways to advance estimates of actual A n (Damm, Erler, & Gioli, 2010;Damm et al, 2015;Mohammed, Colombo, & Middleton, 2019), T (Lu et al, 2018;Pagán, Maes, Gentine, Martes, & Miralles, 2019) and even g s (Shan et al, 2019). Despite the partial success of observational approaches, data scarcity (i.e.…”

Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

“…SIF emission is related to the light reactions of photosynthesis, but GPP estimation also requires information on the dark reactions and stomatal conductance such that the remote sensing community is currently challenged by how to use SIF to estimate GPP. New studies also propose that SIF might be used to monitor T , possibly in combination with surface temperature measurements, acknowledging the close link between GPP and T due to their joint dependence on stomatal conductance and common meteorological and environmental drivers (Alemohammad et al, 2017;Damm et al, 2018;Lu et al, 2018;Pagán et al, 2019;Shan et al, 2019).…”

“…The authors suggested that the decoupling between GPP and T during water stress hampered the use of SIF to predict T , particularly in grasslands, noting that T can occur without GPP under periods of plant stress (Bunce, 1988;De Kauwe et al, 2019). There is a strong empirical link between the ratio of T over potential evaporation and the ratio of SIF over PAR, and the relationship depends on the atmospheric demand for water, with larger transpiration for the same SIF when potential evaporation is higher (Alemohammad et al, 2017;Damm et al, 2018;Lu et al, 2018;Pagán et al, 2019;Shan et al, 2019). These ratios vary with assumptions regarding the potential evaporation calculation as well (Fisher et al, 2010).…”