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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-273
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-273
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 24 Sep 2020

Submitted as: model evaluation paper | 24 Sep 2020

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This preprint is currently under review for the journal GMD.

Improvement of modelling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

Anna B. Harper1,2, Karina E. Williams3,4, Patrick C. McGuire5,6, Maria Carolina Duran Rojas1, Debbie Hemming3,7, Anne Verhoef6, Chris Huntingford8, Lucy Rowland4, Toby Marthews8, Cleiton Breder Eller4, Camilla Mathison3, Rodolfo L. B. Nobrega9, Nicola Gedney10, Pier Luigi Vidale5, Fred Otu-Larbi11, Divya Pandey12, Sebastien Garrigues13, Azin Wright6, Darren Slevin14, Martin G. De Kauwe15,16,17, Eleanor Blyth8, Jonas Ärdo18, Andrew Black32, Damien Bonal19, Nina Buchmann20, Benoit Burban21,22, Kathrin Fuchs23, Agnès de Grandcourt24,25, Ivan Mammarella26, Lutz Merbold27, Leonardo Montagnani28, Yann Nouvellon24,25, Natalia Restrepo-Coupe29,30, and Georg Wohlfahrt31 Anna B. Harper et al.
  • 1College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
  • 2Global Systems Institute, University of Exeter, Exeter, UK
  • 3UK Met Office, Fitzroy Road, Exeter, UK
  • 4College of Life and Environmental Sciences, University of Exeter, Exeter, UK
  • 5Department of MeteorologyandNational Centre for Atmospheric Science, University of Reading, Reading RG 66 BB, UK
  • 6Department of Geography & Environmental Science, University of Reading, Reading RG 66 BB, UK
  • 7Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK
  • 8Centre for Ecology and Hydrology, Wallingford, UK
  • 9Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire, SL5 7PY, UK
  • 10Met Office Hadley Centre, Joint Centre for Hydrometeorological Research, Maclean Building, Wallingford OX10 8BB, UK
  • 11Lancaster Environment Centre, Lancaster University, LA1 4YQ, UK
  • 12Stockholm Environment Institute at York, University of York, York, UK
  • 13ECMWF, Copernicus Atmospheric Monitoring Service, Reading, UK
  • 14Forest Research, Northern Research Station, Roslin, Midlothian, EH25 9SY, UK
  • 15ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052, Australia
  • 16Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
  • 17Evolution & Ecology Research Centre, University of New South Wales, Sydney, NSW2052, Australia
  • 18Department of Physical Geography and Ecosystem Science, Lund University Sölvegatan 12 S-223 62 Lund, Sweden
  • 19Université de Lorraine, AgroParisTech, INRAE, UMR Silva, 54000 Nancy, France
  • 20Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
  • 21INRAE, AgroParisTech, CIRAD, France
  • 22CNRS, Université de Guyane, Universitédes Antilles, UMR Ecofog, Campus Agronomique, 97387 Kourou, Guyane Française, France
  • 23Institute of Meteorology and Climate Research-Atmospheric Environmental Research, Karlsruhe Institute of Technology (KIT Campus Alpin), 82467 Garmisch-Partenkirchen, Germany
  • 24CRDPI, BP 1291 Pointe Noire, Republic of Congo
  • 25CIRAD, UMR Eco&Sols, Ecologie Fonctionnelle & Biogéochimie des Sols & Agro-écosystèmes, 34060 Montpellier, France
  • 26Institutefor Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
  • 27International Livestock Research Institute (ILRI), Mazingira Centre, PO Box 30709, 00100 Nairobi, Kenya
  • 28Faculty of Science and Technology, Free University of Bolzano, Bolzano, Italy; Forest Services, Autonomous Province of Bolzano, Bolzano, Italy
  • 29Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA
  • 30School of Life Science, University of Technology Sydney, Sydney, NSW, 2006, Australia
  • 31Department of Ecology, Universityof Innsbruck, Sternwartestr. 15, 6020 Innsbruck, Australia
  • 32Faculty of Land and Food Systems, University of British Columbia, Vancouver, British Columbia, Canada

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.

Anna B. Harper et al.

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Short summary
Drought is predicted to increase in the future due to climate change. Plants respond to drier soils by reducing stomatal conductance, in order to conserve water and avoid damage, and this response is important for the global carbon cycle and local/regional climate feedbacks. We evaluated ten representations of stress in the JULES land-surface model against site observations, and make recommendations for future use of the model.
Drought is predicted to increase in the future due to climate change. Plants respond to drier...
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