Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
Authors: Harper Anna B. , Williams Karina E. , McGuire Patrick C. , Duran Rojas Maria Carolina , Hemming Debbie , Verhoef Anne , Huntingford Chris , Rowland Lucy , Marthews Toby , Breder Eller Cleiton , Mathison Camilla , Nobrega Rodolfo L. B. , Gedney Nicola , Vidale Pier Luigi , Otu-Larbi Fred , Pandey Divya , Garrigues Sebastien , Wright Azin , Slevin Darren , De Kauwe Martin G. , Blyth Eleanor , Ardö Jonas , Black Andrew , Bonal Damien , Buchmann Nina , Burban Benoit , Fuchs Kathrin , de Grandcourt Agnès , Mammarella Ivan , Merbold Lutz , Montagnani Leonardo , Nouvellon Yann , Restrepo-Coupe Natalia , Wohlfahrt Georg 
Published: June 2021

Abstract. Drought is predicted to increase in the future due to climate change,
bringing with it myriad impacts on ecosystems. Plants respond to drier
soils by reducing stomatal conductance in order to conserve water and avoid
hydraulic damage. Despite the importance of plant drought responses for the
global carbon cycle and local and regional climate feedbacks, land surface
models are unable to capture observed plant responses to soil moisture
stress. We assessed the impact of soil moisture stress on simulated gross
primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land
Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and
evaluated 10 different representations of soil moisture stress in the
model. For the default configuration, GPP was more realistic in temperate
biome sites than in the tropics or high-latitude (cold-region) sites, while
LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not
due to soil moisture stress, possibly linked to phenology, contributed to
model biases for GPP in tropical savanna and deciduous forest sites. We
found that three alternative approaches to calculating soil moisture stress
produced more realistic results than the default parameterization for most
biomes and climates. All of these involved increasing the number of soil
layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition,
we found improvements when soil matric potential replaced volumetric water
content in the stress equation (the “soil14_psi”
experiments), when the critical threshold value for inducing soil moisture
stress was reduced (“soil14_p0”), and when plants were able
to access soil moisture in deeper soil layers (“soil14_dr*2”). For LE, the biases were highest in the default configuration in
temperate mixed forests, with overestimation occurring during most of the
year. At these sites, reducing soil moisture stress (with the new
parameterizations mentioned above) increased LE and increased model biases
but improved the simulated seasonal cycle and brought the monthly variance
closer to the measured variance of LE. Further evaluation of the reason for
the high bias in LE at many of the sites would enable improvements in both
carbon and energy fluxes with new parameterizations for soil moisture
stress. Increasing the soil depth and plant access to deep soil moisture
improved many aspects of the simulations, and we recommend these settings in
future work using JULES or as a general way to improve land surface carbon
and water fluxes in other models. In addition, using soil matric potential
presents the opportunity to include plant functional type-specific
parameters to further improve modeled fluxes.