Articles | Volume 10, issue 3
https://doi.org/10.5194/gmd-10-1291-2017
© Author(s) 2017. 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-10-1291-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
27 Mar 2017
Model evaluation paper |
| 27 Mar 2017
Evaluation of JULES-crop performance against site observations of irrigated maize from Mead, Nebraska
Karina Williams
CORRESPONDING AUTHOR
Met Office Hadley Centre, Exeter, UK
Jemma Gornall
Met Office Hadley Centre, Exeter, UK
Anna Harper
College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
Andy Wiltshire
Met Office Hadley Centre, Exeter, UK
Debbie Hemming
Met Office Hadley Centre, Exeter, UK
Tristan Quaife
National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading UK
Tim Arkebauer
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
David Scoby
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
Viewed
Total article views: 5,428 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Oct 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,489 | 1,745 | 194 | 5,428 | 195 | 205 |
- HTML: 3,489
- PDF: 1,745
- XML: 194
- Total: 5,428
- BibTeX: 195
- EndNote: 205
Total article views: 4,692 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Mar 2017)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,078 | 1,432 | 182 | 4,692 | 188 | 195 |
- HTML: 3,078
- PDF: 1,432
- XML: 182
- Total: 4,692
- BibTeX: 188
- EndNote: 195
Total article views: 736 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 06 Oct 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 411 | 313 | 12 | 736 | 7 | 10 |
- HTML: 411
- PDF: 313
- XML: 12
- Total: 736
- BibTeX: 7
- EndNote: 10
Viewed (geographical distribution)
Total article views: 5,428 (including HTML, PDF, and XML)
Thereof 5,057 with geography defined
and 371 with unknown origin.
Total article views: 4,692 (including HTML, PDF, and XML)
Thereof 4,357 with geography defined
and 335 with unknown origin.
Total article views: 736 (including HTML, PDF, and XML)
Thereof 700 with geography defined
and 36 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
23 citations as recorded by crossref.
- Temporal variability in the impacts of particulate matter on crop yields on the North China Plain M. Wolffe et al. 10.1016/j.scitotenv.2021.145135
- Calibration and evaluation of JULES‐crop for maize in Brazil A. Prudente Junior et al. 10.1002/agj2.21066
- The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0 E. Pinnington et al. 10.5194/gmd-13-55-2020
- Influence of sun zenith angle on canopy clumping and the resulting impacts on photosynthesis R. Braghiere et al. 10.1016/j.agrformet.2020.108065
- Disentangling the separate and confounding effects of temperature and precipitation on global maize yield using machine learning, statistical and process crop models X. Yin et al. 10.1088/1748-9326/ac5716
- Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements A. Harper et al. 10.5194/gmd-14-3269-2021
- Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations X. Pedruzo‐Bagazgoitia et al. 10.1029/2022MS003210
- Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types A. Harper et al. 10.5194/gmd-11-2857-2018
- Calibrating soybean parameters in JULES 5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O<sub>3</sub> experiment F. Leung et al. 10.5194/gmd-13-6201-2020
- Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index X. He et al. 10.1029/2020WR028224
- Long-term trajectory of ozone impact on maize and soybean yields in the United States: A 40-year spatial-temporal analysis J. Pei et al. 10.1016/j.envpol.2024.123407
- Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios C. Müller et al. 10.1088/1748-9326/abd8fc
- CO2 fertilization of crops offsets yield losses due to future surface ozone damage and climate change F. Leung et al. 10.1088/1748-9326/ac7246
- Implementation of sequential cropping into JULESvn5.2 land-surface model C. Mathison et al. 10.5194/gmd-14-437-2021
- Underestimation of Global Photosynthesis in Earth System Models Due to Representation of Vegetation Structure R. Braghiere et al. 10.1029/2018GB006135
- Improving maize growth processes in the community land model: Implementation and evaluation B. Peng et al. 10.1016/j.agrformet.2017.11.012
- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
- Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping M. Haworth et al. 10.3390/plants12234015
- Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil A. Prudente Junior et al. 10.1016/j.heliyon.2024.e29555
- The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO<sub>2</sub>, temperature, water, and nitrogen levels (protocol version 1.0) J. Franke et al. 10.5194/gmd-13-2315-2020
- The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO<sub>2</sub>, temperature, water, and nitrogen (version 1.0) J. Franke et al. 10.5194/gmd-13-3995-2020
- Estimation of Water-Use Efficiency Based on Satellite for the Typical Croplands T. Wang et al. 10.1109/ACCESS.2020.3037077
- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
22 citations as recorded by crossref.
- Temporal variability in the impacts of particulate matter on crop yields on the North China Plain M. Wolffe et al. 10.1016/j.scitotenv.2021.145135
- Calibration and evaluation of JULES‐crop for maize in Brazil A. Prudente Junior et al. 10.1002/agj2.21066
- The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0 E. Pinnington et al. 10.5194/gmd-13-55-2020
- Influence of sun zenith angle on canopy clumping and the resulting impacts on photosynthesis R. Braghiere et al. 10.1016/j.agrformet.2020.108065
- Disentangling the separate and confounding effects of temperature and precipitation on global maize yield using machine learning, statistical and process crop models X. Yin et al. 10.1088/1748-9326/ac5716
- Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements A. Harper et al. 10.5194/gmd-14-3269-2021
- Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations X. Pedruzo‐Bagazgoitia et al. 10.1029/2022MS003210
- Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types A. Harper et al. 10.5194/gmd-11-2857-2018
- Calibrating soybean parameters in JULES 5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O<sub>3</sub> experiment F. Leung et al. 10.5194/gmd-13-6201-2020
- Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index X. He et al. 10.1029/2020WR028224
- Long-term trajectory of ozone impact on maize and soybean yields in the United States: A 40-year spatial-temporal analysis J. Pei et al. 10.1016/j.envpol.2024.123407
- Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios C. Müller et al. 10.1088/1748-9326/abd8fc
- CO2 fertilization of crops offsets yield losses due to future surface ozone damage and climate change F. Leung et al. 10.1088/1748-9326/ac7246
- Implementation of sequential cropping into JULESvn5.2 land-surface model C. Mathison et al. 10.5194/gmd-14-437-2021
- Underestimation of Global Photosynthesis in Earth System Models Due to Representation of Vegetation Structure R. Braghiere et al. 10.1029/2018GB006135
- Improving maize growth processes in the community land model: Implementation and evaluation B. Peng et al. 10.1016/j.agrformet.2017.11.012
- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
- Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping M. Haworth et al. 10.3390/plants12234015
- Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil A. Prudente Junior et al. 10.1016/j.heliyon.2024.e29555
- The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO<sub>2</sub>, temperature, water, and nitrogen levels (protocol version 1.0) J. Franke et al. 10.5194/gmd-13-2315-2020
- The GGCMI Phase 2 emulators: global gridded crop model responses to changes in CO<sub>2</sub>, temperature, water, and nitrogen (version 1.0) J. Franke et al. 10.5194/gmd-13-3995-2020
- Estimation of Water-Use Efficiency Based on Satellite for the Typical Croplands T. Wang et al. 10.1109/ACCESS.2020.3037077
Saved (final revised paper)
Saved (preprint)
Latest update: 23 Nov 2024
Short summary
This study looks in detail at how well the crop model within the Joint UK Land Environment Simulator (JULES), a community land-surface model, is able to simulate irrigated maize in Nebraska. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties.
This study looks in detail at how well the crop model within the Joint UK Land Environment...
Special issue