In this section
@article{Mengoli:2022:10.5194/egusphere-egu22-1331,
author = {Mengoli, G and Harrison, SP and Prentice, IC},
doi = {10.5194/egusphere-egu22-1331},
title = {Towards a land surface model based on optimality principles},
url = {http://dx.doi.org/10.5194/egusphere-egu22-1331},
year = {2022}
}
TY - JOUR
AB - <jats:p><p>Plants take up water from the soil via roots and release it into the atmosphere through stomata; uptake of CO<sub>2</sub> from the atmosphere also proceeds through the stomata, implying tight coupling of transpiration and photosynthesis. We distinguish leaf-level (biochemical and stomatal) responses to external stimuli on different timescales: fast responses taking place over seconds to hours, and longer-term (acclimation) responses taking place over weeks to months. Typically, land-surface models (LSMs) have focused on the fast responses, and have not accounted for acclimation responses, although these can be different in magnitude and even in sign. We have developed a method that explicitly separates these two timescales in order to implement an existing optimality-based model, the P model, with a sub-daily timestep; and, thereby, to include acclimated responses within an LSM framework. The resulting model, compared to flux-tower gross primary production (GPP) data in five &#8220;well-watered&#8221; biomes from boreal to tropical, correctly reproduces diurnal cycles of GPP throughout the growing season. No changes of parameters are required between biomes, because optimality ensures that current parameter values are always adapted to the local environment. This is a clear practical advantage because it eliminates the need to specify different parameter values for different plant functional types. However, in areas with large seasonal variations in moisture variability, the model does not perform well. Here we address the issue of soil-moisture controls on GPP, which is a challenging issue for LSMs in general. We note two problems: an error in magnitude, and an error in shape. The model tends to overestimate GPP in dry areas because it does not consider the effect of low soil moisture (as opposed to atmospheric dryness) on photosynthesis; and it does not simul
AU - Mengoli,G
AU - Harrison,SP
AU - Prentice,IC
DO - 10.5194/egusphere-egu22-1331
PY - 2022///
TI - Towards a land surface model based on optimality principles
UR - http://dx.doi.org/10.5194/egusphere-egu22-1331
ER -