Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3269-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3269-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
03 Jun 2021
Model evaluation paper |
| 03 Jun 2021
| 03 Jun 2021
Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements
College of Engineering, Mathematics, and Physical Sciences,
University of Exeter, Exeter EX4 4PY, UK
Global Systems Institute, University of Exeter, Exeter EX4 4PY, UK
Karina E. Williams
CORRESPONDING AUTHOR
Global Systems Institute, University of Exeter, Exeter EX4 4PY, UK
UK Met Office, Fitzroy Road, Exeter EX1 3PB, UK
Patrick C. McGuire
Department of Meteorology and National Centre for Atmospheric
Science, University of Reading, Reading RG6 6BB, UK
Department of Geography & Environmental Science, University of
Reading, Reading RG6 6BB, UK
Maria Carolina Duran Rojas
College of Engineering, Mathematics, and Physical Sciences,
University of Exeter, Exeter EX4 4PY, UK
Debbie Hemming
UK Met Office, Fitzroy Road, Exeter EX1 3PB, UK
Birmingham Institute of Forest Research, University of Birmingham,
Birmingham ST20 0FJ, UK
Anne Verhoef
Department of Geography & Environmental Science, University of
Reading, Reading RG6 6BB, UK
Chris Huntingford
UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Lucy Rowland
College of Life and Environmental Sciences, University of Exeter,
Exeter EX4 4PY, UK
Toby Marthews
UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Cleiton Breder Eller
Department of Plant Biology, University of Campinas, Campinas
13083-862, Brazil
Camilla Mathison
UK Met Office, Fitzroy Road, Exeter EX1 3PB, UK
Rodolfo L. B. Nobrega
Department of Life Sciences, Imperial College London, Silwood Park
Campus, Ascot, Berkshire, SL5 7PY, UK
Nicola Gedney
Met Office Hadley Centre, Joint Centre for Hydrometeorological
Research, Maclean Building, Wallingford OX10 8BB, UK
Pier Luigi Vidale
Department of Meteorology and National Centre for Atmospheric
Science, University of Reading, Reading RG6 6BB, UK
Fred Otu-Larbi
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
Divya Pandey
Stockholm Environment Institute at York, University of York, York YO10 5NG,
UK
Sebastien Garrigues
ECMWF, Copernicus Atmospheric Monitoring Service, Reading RG2 9AX, UK
Azin Wright
Department of Geography & Environmental Science, University of
Reading, Reading RG6 6BB, UK
Darren Slevin
Forest Research, Northern Research Station, Roslin, Midlothian,
EH25 9SY, UK
Martin G. De Kauwe
ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052,
Australia
Climate Change Research Centre, University of New South Wales,
Sydney, NSW 2052, Australia
Evolution & Ecology Research Centre, University of New South
Wales, Sydney, NSW 2052, Australia
Eleanor Blyth
UK Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Jonas Ardö
Department of Physical Geography and Ecosystem Science, Lund
University Sölvegatan 12, 223 62 Lund, Sweden
Andrew Black
Faculty of Land and Food Systems, University of British Columbia,
Vancouver, British Columbia, Canada
Damien Bonal
Université de Lorraine, AgroParisTech, INRAE, UMR Silva, 54000
Nancy, France
Nina Buchmann
Department of Environmental Systems Science, ETH Zurich, Zurich,
Switzerland
Benoit Burban
INRAE, AgroParisTech, CIRAD, Paris, France
CNRS, Université de Guyane, Université des Antilles, UMR
Ecofog, Campus Agronomique, 97387 Kourou, French Guiana, France
Kathrin Fuchs
Department of Environmental Systems Science, ETH Zurich, Zurich,
Switzerland
Institute of Meteorology and Climate Research – Atmospheric
Environmental Research, Karlsruhe Institute of Technology (KIT Campus
Alpin), 82467 Garmisch-Partenkirchen, Germany
Agnès de Grandcourt
CRDPI, BP 1291, Pointe Noire, Republic of Congo
CIRAD, UMR Eco&Sols, Ecologie Fonctionnelle & Biogéochimie
des Sols & Agro-écosystèmes, 34060 Montpellier, France
Ivan Mammarella
Institute for Atmospheric and Earth System Research/Physics,
Faculty of Science, University of Helsinki, Helsinki, Finland
Lutz Merbold
International Livestock Research Institute (ILRI), Mazingira Centre, P.O. Box 30709, 00100 Nairobi, Kenya
Leonardo Montagnani
Faculty of Science and Technology, Free University of Bolzano,
Bolzano, Italy
Forest Services, Autonomous Province of Bolzano, Bolzano,
Italy
Yann Nouvellon
CRDPI, BP 1291, Pointe Noire, Republic of Congo
CIRAD, UMR Eco&Sols, Ecologie Fonctionnelle & Biogéochimie
des Sols & Agro-écosystèmes, 34060 Montpellier, France
Natalia Restrepo-Coupe
Department of Ecology and Evolutionary Biology, University of
Arizona, Tucson, AZ 85721, USA
School of Life Science, University of Technology Sydney, Sydney,
NSW 2006, Australia
Georg Wohlfahrt
Department of Ecology, University of Innsbruck, Sternwartestr. 15,
6020 Innsbruck, Austria
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21 citations as recorded by crossref.
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- Reduced productivity and carbon drawdown of tropical forests from ground-level ozone exposure A. Cheesman et al. 10.1038/s41561-024-01530-1
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- Global decadal variability of plant carbon isotope discrimination and its link to gross primary production A. Lavergne et al. 10.1111/gcb.15924
- A flux tower dataset tailored for land model evaluation A. Ukkola et al. 10.5194/essd-14-449-2022
- Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest B. Bahrami et al. 10.5194/gmd-15-6957-2022
- Hydrological feedback from projected Earth greening in the 21st century J. Wu et al. 10.1016/j.horiz.2022.100007
- Improving land surface feedbacks to the atmosphere in convection-permitting climate simulations for Europe K. Halladay et al. 10.1007/s00382-024-07192-4
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- Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model D. Du et al. 10.3390/rs14071722
- Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models J. Green et al. 10.1029/2023AV001026
- Convection-permitting climate simulations for South America with the Met Office Unified Model K. Halladay et al. 10.1007/s00382-023-06853-0
- Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. 10.5194/gmd-15-5567-2022
- FORCAsT‐gs: Importance of Stomatal Conductance Parameterization to Estimated Ozone Deposition Velocity F. Otu‐Larbi et al. 10.1029/2021MS002581
- Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0) E. Weng et al. 10.5194/gmd-15-8153-2022
- Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality J. Lam et al. 10.5194/gmd-16-2323-2023
- On the Uncertainty Induced by Pedotransfer Functions in Terrestrial Biosphere Modeling A. Paschalis et al. 10.1029/2021WR031871
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- Hydrometeorological response to afforestation in the UK: findings from a kilometer-scale climate model M. Buechel et al. 10.1088/1748-9326/ad4bf6
- Contrasting responses of vegetation productivity to intraseasonal rainfall in Earth system models B. Harris et al. 10.5194/esd-15-1019-2024
3 citations as recorded by crossref.
- Assessing Model Predictions of Carbon Dynamics in Global Drylands D. Fawcett et al. 10.3389/fenvs.2022.790200
- Implementation of sequential cropping into JULESvn5.2 land-surface model C. Mathison et al. 10.5194/gmd-14-437-2021
- On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology P. Vidale et al. 10.3389/fenvs.2021.689301
Latest update: 20 Nov 2024
Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. 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. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
We evaluated 10 representations of soil moisture stress in the JULES land surface model against...
