Accounting for photosynthetic traits acclimation improves the simulation of forest canopy temperature in Terrestrial Biosphere Models at the ecosystem level

Leaf photosynthesis and respiration respond to leaf temperature, which differs from air temperature depending on radiation load, transpiration and heat exchange rates. However, most terrestrial biosphere models (TBMs) do not use leaf temperature to compute photosynthesis and respiration. Instead, they use directly air temperature, or an average surface temperature that incorporate soil and non-green biomass compartments. While these two approaches are computationally efficient, the absence of explicit leaf temperature simulation potentially hinders the representation of extreme events (e.g. heat stress) and their repercussion on carbon and water fluxes. To predict leaf temperature, it is necessary to explicitly account for leaf energy budget, photosynthesis and transpiration feedbacks (E-P-T).

Here, we explored the merits of coupling E-P-T processes in TBMs to simulate explicit leaf temperature and its feedback on carbon assimilation. Sensitivity analysis of the coupled E-P-T processes using the big-leaf configuration of the ORCHIDEE v2.2 TBM (used in CMIP6) resulted into leaf-to-air temperature differences varying between 1 and 10 °C in natural conditions. This translated into a change in carbon assimilation ranging from -35 % to +110 % at the leaf level. A comparison of simulated leaf temperature with measured canopy surface temperature at eddy-covariance fluxes sites in various E-P-T configurations showed that adding ecological constraints on photosynthesis and transpiration through the photosynthesis coordination and the least-cost hypothesis (P-model) improved the representation of top canopy temperature compared to a classical fixed parameterization. The improvement in canopy temperature estimates was best for deciduous broadleaved forests with an average reduction of the error by 1.2 ± 0.8 °C (9 sites). More importantly, the improvement in leaf temperature estimates mainly occurs at elevated temperature (> 30°C). 

Our results argue for the inclusion of an explicit representation of leaf temperature in TBMs to avoid biases in the carbon balance estimates. Fully coupling leaf processes through temperature will also be essential for accurately simulating and disentangling the effects of heat and drought stresses under future conditions. However, such implementation will only be possible if accompanied with space-time concomitant observations of leaf temperature and traits that are currently lacking. The ongoing deployment of digital cameras (e.g. thermal, multispectral, SIF etc.) on existing networks (e.g. ICOS) for tracking canopy temperature and trait variability, combined with punctual field observation campaigns, future remote sensing missions (e.g. TRISHNA), as well as new hybrid modelling methods are all timely and promising ways for improving our understanding and representation of leaf temperature in TBMs.