Articles | Volume 8, issue 2
https://doi.org/10.5194/gmd-8-295-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-295-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
13 Feb 2015
Development and technical paper |
| 13 Feb 2015
Multi-site evaluation of the JULES land surface model using global and local data
School of Geosciences, The University of Edinburgh, Grant Institute, James Hutton Road, Edinburgh, EH9 3FE, UK
S. F. B. Tett
School of Geosciences, The University of Edinburgh, Grant Institute, James Hutton Road, Edinburgh, EH9 3FE, UK
M. Williams
School of Geosciences, The University of Edinburgh, Grant Institute, James Hutton Road, Edinburgh, EH9 3FE, UK
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Cited
16 citations as recorded by crossref.
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- Hydrological impact of widespread afforestation in Great Britain using a large ensemble of modelled scenarios M. Buechel et al. https://doi.org/10.1038/s43247-021-00334-0
- Effects of Meteorological and Ancillary Data, Temporal Averaging, and Evaluation Methods on Model Performance and Uncertainty in a Land Surface Model C. Ménard et al. https://doi.org/10.1175/JHM-D-15-0013.1
- Modeling and improving Ethiopian pasture systems S. Parisi et al. https://doi.org/10.1007/s00484-017-1492-0
- Does predictability of fluxes vary between FLUXNET sites? N. Haughton et al. https://doi.org/10.5194/bg-15-4495-2018
- Embedding a novel phenology model into the Common Land Model for improving the modeling of land-atmosphere fluxes H. Gui et al. https://doi.org/10.1016/j.ecolmodel.2024.110782
- Global evaluation of gross primary productivity in the JULES land surface model v3.4.1 D. Slevin et al. https://doi.org/10.5194/gmd-10-2651-2017
- HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands M. Raivonen et al. https://doi.org/10.5194/gmd-10-4665-2017
- Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the JULES land surface model H. Lee et al. https://doi.org/10.1016/j.agrformet.2019.107614
- Quantifying the prediction accuracy of a 1-D SVAT model at a range of ecosystems in the USA and Australia: evidence towards its use as a tool to study Earth's system interactions G. Petropoulos et al. https://doi.org/10.5194/gmd-8-3257-2015
- Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites A. Collalti et al. https://doi.org/10.5194/gmd-9-479-2016
- Improving UAV-Based LAI Estimation for Forests Over Complex Terrain by Reducing Topographic Effects on Multispectral Reflectance Z. Cheng et al. https://doi.org/10.1109/TGRS.2023.3337177
- Investigation of factors that affect post-fire recovery of photosynthetic activity at global scale Y. Shen et al. https://doi.org/10.1016/j.ecolind.2025.113206
- Mitigation of drought negative effect on ecosystem productivity by vegetation mixing C. Van den Hoof & F. Lambert https://doi.org/10.1002/2016JG003625
- Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production N. Vuichard et al. https://doi.org/10.5194/gmd-12-4751-2019
- An audacious approach to conservation R. Ewers https://doi.org/10.1016/j.tree.2024.07.003
16 citations as recorded by crossref.
- New insights to be gained from a Virtual Ecosystem R. Ewers et al. https://doi.org/10.1016/j.ecolmodel.2024.110866
- Hydrological impact of widespread afforestation in Great Britain using a large ensemble of modelled scenarios M. Buechel et al. https://doi.org/10.1038/s43247-021-00334-0
- Effects of Meteorological and Ancillary Data, Temporal Averaging, and Evaluation Methods on Model Performance and Uncertainty in a Land Surface Model C. Ménard et al. https://doi.org/10.1175/JHM-D-15-0013.1
- Modeling and improving Ethiopian pasture systems S. Parisi et al. https://doi.org/10.1007/s00484-017-1492-0
- Does predictability of fluxes vary between FLUXNET sites? N. Haughton et al. https://doi.org/10.5194/bg-15-4495-2018
- Embedding a novel phenology model into the Common Land Model for improving the modeling of land-atmosphere fluxes H. Gui et al. https://doi.org/10.1016/j.ecolmodel.2024.110782
- Global evaluation of gross primary productivity in the JULES land surface model v3.4.1 D. Slevin et al. https://doi.org/10.5194/gmd-10-2651-2017
- HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands M. Raivonen et al. https://doi.org/10.5194/gmd-10-4665-2017
- Impact of leaf area index from various sources on estimating gross primary production in temperate forests using the JULES land surface model H. Lee et al. https://doi.org/10.1016/j.agrformet.2019.107614
- Quantifying the prediction accuracy of a 1-D SVAT model at a range of ecosystems in the USA and Australia: evidence towards its use as a tool to study Earth's system interactions G. Petropoulos et al. https://doi.org/10.5194/gmd-8-3257-2015
- Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites A. Collalti et al. https://doi.org/10.5194/gmd-9-479-2016
- Improving UAV-Based LAI Estimation for Forests Over Complex Terrain by Reducing Topographic Effects on Multispectral Reflectance Z. Cheng et al. https://doi.org/10.1109/TGRS.2023.3337177
- Investigation of factors that affect post-fire recovery of photosynthetic activity at global scale Y. Shen et al. https://doi.org/10.1016/j.ecolind.2025.113206
- Mitigation of drought negative effect on ecosystem productivity by vegetation mixing C. Van den Hoof & F. Lambert https://doi.org/10.1002/2016JG003625
- Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production N. Vuichard et al. https://doi.org/10.5194/gmd-12-4751-2019
- An audacious approach to conservation R. Ewers https://doi.org/10.1016/j.tree.2024.07.003
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