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Improvement of modelling 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.
Rojas, Maria Carolina Duran
Hemming, Debbie
Verhoef, Anne
Huntingford, Chris
Rowland, Lucy
Marthews, Toby
Eller, Cleiton Breder
Mathison, Camilla
Nobrega, Rodolfo L. B.
Gedney, Nicola
Vidale, Pier Luigi
Otu-Larbi, Fred
Pandey, Divya
Garrigues, Sebastien
Wright, Azin
Slevin, Darren
Kauwe, Martin G. De
Source :
Geoscientific Model Development Discussions; 9/24/2020, p1-42, 42p
Publication Year :
2020

Abstract

Drought is predicted to increase in the future due to climate change, bringing with it a myriad of 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/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 ten different representations of stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high latitudes/cold region sites, while LE was best simulated in temperate and high latitude/cold sites. Errors not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savannah 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 3m to 10.8m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation, when the onset of stress was delayed, and when roots extended deeper into the soil. 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 made the simulation worse. Further evaluation into 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19919611
Database :
Complementary Index
Journal :
Geoscientific Model Development Discussions
Publication Type :
Academic Journal
Accession number :
146184167
Full Text :
https://doi.org/10.5194/gmd-2020-273