Modelled arable area, net primary productivity, runoff, irrigation demand for Great Britain 1998-2008 and 2100 under high-end climate change
Cite this dataset as:
Ritchie, P.D.L.; Smith, G.S. (2019). Modelled arable area, net primary productivity, runoff, irrigation demand for Great Britain 1998-2008 and 2100 under high-end climate change. NERC Environmental Information Data Centre. https://doi.org/10.5285/2efac82b-2438-4806-999d-374663210c34
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© University of Exeter
This dataset is available under the terms of the Open Government Licence 
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https://doi.org/10.5285/2efac82b-2438-4806-999d-374663210c34
The dataset contains model output from the land surface model JULES and the econometric agricultural land use model ECO-AG, at kilometre scale resolution over Great Britain for 8 different scenarios using unmitigated climate change. Modelled arable area, net primary productivity, runoff and irrigation demand are provided for scenarios combining and isolating the effects of climate, CO2 and irrigation. The driving climate data used to drive the models is from Regional Climate Model runs performed for the period 1998-2008 and for an eleven year period at 2100 for CO2 levels corresponding to the unmitigated Regional Concentration Pathway RCP8.5.
Publication date: 2019-10-08
View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)
Formats
NetCDF, Comma-separated values (CSV)
Spatial information
Study area
Spatial representation types
Raster
Tabular (text)
Tabular (text)
Spatial reference system
WGS 84
Temporal information
Temporal extent
1998-01-01 to 2008-12-31
2098-01-01 to 2108-12-31
Provenance & quality
JULES is a community developed land surface model, led by the UK Met Office and Centre for Ecology & Hydrology. The data produced using JULES was model version vn4.9 and the model configuration can be found on the Rose suite u-ao645 under the branch ‘full_UK’, available from https://code.metoffice.gov.uk/trac/roses-u.
ECO-AG outputs have been produced using an approach at the heart of the UK National Ecosystem Assessment and UK NEA Follow-On studies. The data is produced on a 2km grid square (400 hectares) over Great Britain. The land use data are derived from the June Agricultural Census panel (www.edina.ac.uk) collected on a 2km grid square basis over the entirety of GB for ten unevenly spaced years from 1972 to 2010. The approach and input data has been widely peer reviewed and discussed.
ECO-AG outputs have been produced using an approach at the heart of the UK National Ecosystem Assessment and UK NEA Follow-On studies. The data is produced on a 2km grid square (400 hectares) over Great Britain. The land use data are derived from the June Agricultural Census panel (www.edina.ac.uk) collected on a 2km grid square basis over the entirety of GB for ten unevenly spaced years from 1972 to 2010. The approach and input data has been widely peer reviewed and discussed.
Licensing and constraints
This dataset is available under the terms of the Open Government Licence
Cite this dataset as:
Ritchie, P.D.L.; Smith, G.S. (2019). Modelled arable area, net primary productivity, runoff, irrigation demand for Great Britain 1998-2008 and 2100 under high-end climate change. NERC Environmental Information Data Centre. https://doi.org/10.5285/2efac82b-2438-4806-999d-374663210c34
© University of Exeter
Related
This dataset is included in the following collections
Identifying potential tipping points in the benefits derived from the UK's land ecosystems
Correspondence/contact details
Ritchie, P.
University of Exeter
Streatham Campus, Northcote House
Exeter
EX4 4QJ
UK
paul.ritchie@exeter.ac.uk
Exeter
EX4 4QJ
UK
Authors
https://orcid.org/0000-0002-7649-2991
Smith, G.S.
CSIRO
Other contacts
Rights holder
University of Exeter
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk
Additional metadata
Keywords
Funding
Natural Environment Research Council Award: NE/P007880/1
Last updated
21 March 2025 13:22