Articles | Volume 13, issue 2
https://doi.org/10.5194/gmd-13-483-2020
© Author(s) 2020. 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-13-483-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
07 Feb 2020
Model description paper |
| 07 Feb 2020
| 07 Feb 2020
JULES-GL7: the Global Land configuration of the Joint UK Land Environment Simulator version 7.0 and 7.2
Andrew J. Wiltshire
CORRESPONDING AUTHOR
Met Office, Fitzroy Road, Exeter, UK
University of Exeter, Exeter, UK
Maria Carolina Duran Rojas
University of Exeter, Exeter, UK
John M. Edwards
Met Office, Fitzroy Road, Exeter, UK
Nicola Gedney
Met Office, Fitzroy Road, Exeter, UK
Anna B. Harper
University of Exeter, Exeter, UK
Andrew J. Hartley
Met Office, Fitzroy Road, Exeter, UK
Margaret A. Hendry
Met Office, Fitzroy Road, Exeter, UK
Eddy Robertson
Met Office, Fitzroy Road, Exeter, UK
Kerry Smout-Day
Met Office, Fitzroy Road, Exeter, UK
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- Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset B. Pan et al. https://doi.org/10.3390/land14071400
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- Disentangling climate effects of greenhouse gas emissions and land cover change on future gross primary productivity in the Yellow River basin, China X. Ru et al. https://doi.org/10.1016/j.jenvman.2025.126026
- Nocturnal plant respiration is under strong non-temperature control D. Bruhn et al. https://doi.org/10.1038/s41467-022-33370-1
- Scientific land greening under climate change: Theory, modeling, and challenges J. Chen et al. https://doi.org/10.1016/j.accre.2024.08.003
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- A global behavioural model of human fire use and management: WHAM! v1.0 O. Perkins et al. https://doi.org/10.5194/gmd-17-3993-2024
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- Effects of hydraulic conductivity on simulating groundwater–land surface interactions over a typical endorheic river basin Z. Lu et al. https://doi.org/10.1016/j.jhydrol.2024.131542
- Implementation of a multi-layer snow scheme in the GloSea6 seasonal forecast system: impacts on land–atmosphere interactions and climatological biases E. Seo et al. https://doi.org/10.5194/gmd-19-1261-2026
- A multi-data assessment of land use and land cover emissions from Brazil during 2000–2019 T. Rosan et al. https://doi.org/10.1088/1748-9326/ac08c3
- Understanding drivers and biases of simulated CO emissions from the INFERNO fire model over South America M. Velásquez-García et al. https://doi.org/10.5194/bg-23-1341-2026
- Contrasting contributions of surface hydrological pathways in convection permitting and parameterised climate simulations over Africa and their feedbacks on the atmosphere S. Folwell et al. https://doi.org/10.1007/s00382-022-06144-0
- A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma https://doi.org/10.3390/earth2010011
- Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography) N. Smith et al. https://doi.org/10.5194/gmd-15-3603-2022
- Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration C. Bieri et al. https://doi.org/10.5194/gmd-18-3755-2025
- The ozone–climate penalty over South America and Africa by 2100 F. Brown et al. https://doi.org/10.5194/acp-22-12331-2022
- Hydrometeorological response to afforestation in the UK: findings from a kilometer-scale climate model M. Buechel et al. https://doi.org/10.1088/1748-9326/ad4bf6
- Description and evaluation of the JULES-ES set-up for ISIMIP2b C. Mathison et al. https://doi.org/10.5194/gmd-16-4249-2023
- High‐resolution global climate simulations: Representation of cities D. Hertwig et al. https://doi.org/10.1002/joc.7018
- JULES-CN: a coupled terrestrial carbon–nitrogen scheme (JULES vn5.1) A. Wiltshire et al. https://doi.org/10.5194/gmd-14-2161-2021
- Three-dimensional canopy morphology and wind dynamics govern global rainfall interception Q. Li et al. https://doi.org/10.1038/s43247-026-03694-7
- Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. https://doi.org/10.5194/gmd-15-5567-2022
- The Water Table Model (WTM) (v2.0.1): coupled groundwater and dynamic lake modelling K. Callaghan et al. https://doi.org/10.5194/gmd-18-1463-2025
- Constraining the carbon cycle in JULES-ES-1.0 D. McNeall et al. https://doi.org/10.5194/gmd-17-1059-2024
- Non-flooded riparian Amazon trees are a regionally significant methane source V. Gauci et al. https://doi.org/10.1098/rsta.2020.0446
- Biogeodynamics-Ice sheet-Geneva-MITgcm (BIG-MITgcm, v1.0): a simulation tool for exploring climate states with a representation of global ice sheets L. Moinat et al. https://doi.org/10.5194/gmd-19-4357-2026
- Plant phenology evaluation of CRESCENDO land surface models – Part 1: Start and end of the growing season D. Peano et al. https://doi.org/10.5194/bg-18-2405-2021
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- Urban signals in high-resolution weather and climate simulations: role of urban land-surface characterisation D. Hertwig et al. https://doi.org/10.1007/s00704-020-03294-1
- Assessing uncertainties in modeling the climate of the Siberian frozen soils by contrasting CMIP6 and LS3MIP Z. Luo et al. https://doi.org/10.5194/tc-19-6547-2025
Saved (final revised paper)
Latest update: 03 Sep 2026
Short summary
We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator (JULES). JULES-GL7 can be used to simulate the exchange of heat, water and momentum over land and is therefore applicable for helping understand past and future changes, and forms the land component of the HadGEM3-GC3.1 climate model. The configuration is freely available subject to licence restrictions.
We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator...
