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The Penman–Monteith (PM) equation is commonly considered the most advanced
physically based approach to computing transpiration rates from plants
considering stomatal conductance and atmospheric drivers. It has been widely
evaluated at the canopy scale, where aerodynamic and canopy resistance to
water vapour are difficult to estimate directly, leading to various empirical
corrections when scaling from leaf to canopy. Here, we evaluated the PM
equation directly at the leaf scale, using a detailed leaf energy balance
model and direct measurements in a controlled, insulated wind tunnel using
artificial leaves with fixed and predefined stomatal conductance.
Experimental results were consistent with a detailed leaf energy balance
model; however, the results revealed systematic deviations from PM-predicted
fluxes, which pointed to fundamental problems with the PM equation. Detailed
analysis of the derivation by Monteith(1965) and
subsequent amendments revealed two errors: one in neglecting two-sided
exchange of sensible heat by a planar leaf, and the other related to the
representation of hypostomatous leaves, which are very common in temperate
climates. The omission of two-sided sensible heat flux led to bias in
simulated latent heat flux by the PM equation, which was as high as 50 %
of the observed flux in some experiments. Furthermore, we found that the
neglect of feedbacks between leaf temperature and radiative energy exchange
can lead to additional bias in both latent and sensible heat fluxes. A
corrected set of analytical solutions for leaf temperature as well as latent
and sensible heat flux is presented, and comparison with the original PM
equation indicates a major improvement in reproducing experimental results at
the leaf scale. The errors in the original PM equation and its failure to
reproduce experimental results at the leaf scale (for which it was originally
derived) propagate into inaccurate sensitivities of transpiration and
sensible heat fluxes to changes in atmospheric conditions, such as those
associated with climate change (even with reasonable present-day performance
after calibration). The new formulation presented here rectifies some of the
shortcomings of the PM equation and could provide a more robust starting
point for canopy representation and climate change studies.
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