THIS DATASET HAS BEEN SUPERSEDED The latest version is Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2019) [CEH-GEAR]
Data has been updated to include data for 2016 and 2017
If you need access to the archived version, please contact the EIDC
Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2015) [CEH-GEAR]
https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca
Download/Access
THIS DATASET HAS BEEN SUPERSEDED The latest version is Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2019) [CEH-GEAR]
Data has been updated to include data for 2016 and 2017
If you need access to the archived version, please contact the EIDC
1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2015. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012.
Publication date: 2016-11-04
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Format
netCDF
Spatial information
Study area
Spatial representation type
Raster
Spatial reference systems
OSGB 1936 / British National Grid
OSNI 1952 / Irish National Grid
OSNI 1952
OSNI 1952 / Irish National Grid
OSNI 1952
Temporal information
Temporal extent
1890-01-01 to 2015-12-31
Provenance & quality
The rainfall estimates are derived from the Met Office national database of observed precipitations. To derive the monthly estimates, monthly and daily (when complete month available) precipitation totals from the UK raingauge network are used. An additional quality control step (data already quality controlled by the Met Office) was introduced to check events greater than the 200 year return period. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall (SAAR61-90), was used to generate the daily and monthly rainfall grids. The daily grids are adjusted so that the monthly totals calculated from those are in agreement with the monthly grids. As an indicator of the quality of the estimates, the dataset also contains for each grid generated a grid containing the distance to the closest raingauge used to interpolate the grid point. A grid containing the number of missing estimates for each year is also provided. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012.
This version of the CEH-GEAR dataset differs from the previous version (1890-2014) only by temporal coverage. That is, previous years' data have not been modified.
This version of the CEH-GEAR dataset differs from the previous version (1890-2014) only by temporal coverage. That is, previous years' data have not been modified.
Licensing and constraints
THIS DATASET HAS BEEN SUPERSEDED The latest version is Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2019) [CEH-GEAR]
Data has been updated to include data for 2016 and 2017
If you need access to the archived version, please contact the EIDC
Licence terms and conditions apply
Cite this dataset as:
Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D.G.; Keller, V.D.J. (2016). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2015) [CEH-GEAR]. NERC Environmental Information Data Centre. https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca
Related
Citations
Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J. A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., and Dixon, H. (2015). CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use, Earth Syst. Sci. Data Discuss., 8, 83-112. https://doi.org/10.5194/essdd-8-83-2015
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Nesbitt, A., Dorling, S., & Lovett, A. (2018). A suitability model for viticulture in England and Wales: opportunities for investment, sector growth and increased climate resilience. Journal of Land Use Science, 13(4), 414–438. https://doi.org/10.1080/1747423x.2018.1537312
Simpson, I. R., & McCarthy, M. P. (2018). Structural and sampling uncertainty in observed UK daily precipitation extremes derived from an intercomparison of gridded data sets. International Journal of Climatology, 39(1), 128–142. https://doi.org/10.1002/joc.5789
Parsons, D. J., Rey, D., Tanguy, M., & Holman, I. P. (2019). Regional variations in the link between drought indices and reported agricultural impacts of drought. Agricultural Systems, 173, 119–129. https://doi.org/10.1016/j.agsy.2019.02.015
Coxon, G., Freer, J., Lane, R., Dunne, T., Knoben, W. J. M., Howden, N. J. K., … Woods, R. (2019). DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology. Geoscientific Model Development, 12(6), 2285–2306. https://doi.org/10.5194/gmd-12-2285-2019
Rust, W., Holman, I., Bloomfield, J., Cuthbert, M., & Corstanje, R. (2019). Understanding the potential of climate teleconnections to project future groundwater drought. Hydrology and Earth System Sciences, 23(8), 3233–3245. https://doi.org/10.5194/hess-23-3233-2019
Gnann, S.J., Woods, R. A., & Howden, N.J.K. (2019). Is There a Baseflow Budyko Curve? Water Resources Research, 55(4), 2838–2855. https://doi.org/10.1029/2018wr024464
Afzal, M., & Ragab, R. (2019). Drought Risk under Climate and Land Use Changes: Implication to Water Resource Availability at Catchment Scale. Water, 11(9), 1790. https://doi.org/10.3390/w11091790
Kay, A. L., Bell, V. A., Guillod, B. P., Jones, R. G., & Rudd, A. C. (2018). National-scale analysis of low flow frequency: historical trends and potential future changes. Climatic Change, 147(3-4), 585–599. https://doi.org/10.1007/s10584-018-2145-y
Gnann, S.J., Howden, N.J.K., & Woods, R.A. (2020). Hydrological signatures describing the translation of climate seasonality into streamflow seasonality. Hydrology and Earth System Sciences, 24(2), 561–580. https://doi.org/10.5194/hess-24-561-2020
Wendt, D.E., Van Loon, A.F., Bloomfield, J.P., & Hannah, D.M. (2020). Asymmetric impact of groundwater use on groundwater droughts. Hydrology and Earth System Sciences, 24(10), 4853–4868. https://doi.org/10.5194/hess-24-4853-2020
Kay, A.L., Davies, H.N., Lane, R. A., Rudd, A.C., & Bell, V.A. (2021). Grid-based simulation of river flows in Northern Ireland: Model performance and future flow changes. In Journal of Hydrology: Regional Studies (Vol. 38, p. 100967). Elsevier BV. https://doi.org/10.1016/j.ejrh.2021.100967
Chengot, R., Knox, J. W., & Holman, I. P. (2021). Evaluating the Feasibility of Water Sharing as a Drought Risk Management Tool for Irrigated Agriculture. Sustainability, 13(3), 1456. https://doi.org/10.3390/su13031456
Stevenson, M., & Bravo, C. (2019). Advanced turbidity prediction for operational water supply planning. Decision Support Systems, 119, 72–84. https://doi.org/10.1016/j.dss.2019.02.009
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Wang, H., & Xuan, Y. (2020). SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies. Environmental Modelling & Software, 124, 104598. https://doi.org/10.1016/j.envsoft.2019.104598
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Wang, H., & Xuan, Y. (2022). Spatial variation of catchment-oriented extreme rainfall in England and Wales. Atmospheric Research, 266, 105968. https://doi.org/10.1016/j.atmosres.2021.105968
Afzal, M., & Ragab, R. (2020). Assessment of the potential impacts of climate change on the hydrology at catchment scale: modelling approach including prediction of future drought events using drought indices. Applied Water Science, 10(10). https://doi.org/10.1007/s13201-020-01293-1
Ridding, L. E., Newton, A. C., Redhead, J. W., Watson, S. C. L., Rowland, C. S., & Bullock, J. M. (2020). Modelling historical landscape changes. Landscape Ecology, 35(12), 2695–2712. https://doi.org/10.1007/s10980-020-01059-9
Ragab, R., Kaelin, A., Afzal, M., & Panagea, I. (2020). Application of Generalized Likelihood Uncertainty Estimation (GLUE) at different temporal scales to reduce the uncertainty level in modelled river flows. Hydrological Sciences Journal, 65(11), 1856–1871. https://doi.org/10.1080/02626667.2020.1764961
Roy, B., Singh, M. P., & Singh, A. (2019). A novel approach for rainfall-runoff modelling using a biogeography-based optimization technique. International Journal of River Basin Management, 19(1), 67–80. https://doi.org/10.1080/15715124.2019.1628035
West, H., Quinn, N., & Horswell, M. (2022). Spatio-temporal propagation of North Atlantic Oscillation (NAO) rainfall deviations to streamflow in British catchments. Hydrological Sciences Journal, 67(5), 676–688. https://doi.org/10.1080/02626667.2022.2038791
Faulkner, D., Warren, S., Spencer, P., & Sharkey, P. (2019). Can we still predict the future from the past? Implementing non‐stationary flood frequency analysis in the UK. Journal of Flood Risk Management, 13(1). Portico. https://doi.org/10.1111/jfr3.12582
Kay, A. L., Watts, G., Wells, S. C., & Allen, S. (2019). The impact of climate change on U. K. river flows: A preliminary comparison of two generations of probabilistic climate projections. Hydrological Processes, 34(4), 1081–1088. Portico. https://doi.org/10.1002/hyp.13644
Kay, A. L. (2021). Simulation of river flow in Britain under climate change: Baseline performance and future seasonal changes. Hydrological Processes, 35(4). Portico. https://doi.org/10.1002/hyp.14137
Hicks, H., Lambert, J., Pywell, R., Hulmes, L., Hulmes, S., Walker, K., Childs, D. Z., & Freckleton, R. P. (2021). Characterizing the environmental drivers of the abundance and distribution of Alopecurus myosuroides on a national scale. Pest Management Science, 77(6), 2726–2736. Portico. https://doi.org/10.1002/ps.6301
Afzal, M., & Ragab, R. (2020). How do climate and land use changes affect the water cycle? Modelling study including future drought events prediction using reliable drought indices. Irrigation and Drainage, 69(4), 806–825. Portico. https://doi.org/10.1002/ird.2467
Dobson, B., Coxon, G., Freer, J., Gavin, H., Mortazavi‐Naeini, M., & Hall, J. W. (2020). The Spatial Dynamics of Droughts and Water Scarcity in England and Wales. Water Resources Research, 56(9). Portico. https://doi.org/10.1029/2020WR027187
Cheng, S., Cheng, L., Liu, P., Qin, S., Zhang, L., Xu, C., Xiong, L., Liu, L., & Xia, J. (2021). An Analytical Baseflow Coefficient Curve for Depicting the Spatial Variability of Mean Annual Catchment Baseflow. Water Resources Research, 57(8). Portico. https://doi.org/10.1029/2020WR029529
Wang, H., & Xuan, Y. (2021). Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets. Geophysical Research Letters, 48(8). Portico. https://doi.org/10.1029/2020GL091933
Rameshwaran, P., Bell, V. A., Brown, M. J., Davies, H. N., Kay, A. L., Rudd, A. C., & Sefton, C. (2021). Use of Abstraction and Discharge Data to Improve the Performance of a National‐Scale Hydrological Model. Water Resources Research, 58(1). Portico. https://doi.org/10.1029/2021WR029787
Byers, E. A., Coxon, G., Freer, J., & Hall, J. W. (2020). Drought and climate change impacts on cooling water shortages and electricity prices in Great Britain. Nature Communications, 11(1). https://doi.org/10.1038/s41467-020-16012-2
West, H., Quinn, N., & Horswell, M. (2019). Regional rainfall response to the North Atlantic Oscillation (NAO) across Great Britain. Hydrology Research, 50(6), 1549–1563. https://doi.org/10.2166/nh.2019.015
Kay, A. L., Rudd, A. C., Fry, M., Nash, G., & Allen, S. (2021). Climate change impacts on peak river flows: Combining national-scale hydrological modelling and probabilistic projections. Climate Risk Management, 31, 100263. https://doi.org/10.1016/j.crm.2020.100263
Rudd, A. C., Bell, V. A., & Kay, A. L. (2017). National-scale analysis of simulated hydrological droughts (1891–2015). Journal of Hydrology, 550, 368–385. https://doi.org/10.1016/j.jhydrol.2017.05.018
Kay, A.L., Rudd, A.C., & Coulson, J. (2023). Spatial downscaling of precipitation for hydrological modelling: Assessing a simple method and its application under climate change in Britain. In Hydrological Processes (Vol. 37, Issue 2). Wiley. https://doi.org/10.1002/hyp.14823
Wang, H., & Xuan, Y. (2022). An Area-Orientated Analysis of the Temporal Variation of Extreme Daily Rainfall in Great Britain and Australia. In Water (Vol. 15, Issue 1, p. 128). MDPI AG. https://doi.org/10.3390/w15010128
Kay, A.L., Lane, R.A., & Bell, V.A. (2022). Grid-based simulation of soil moisture in the UK: future changes in extremes and wetting and drying dates. Environmental Research Letters, 17(7), 074029. https://doi.org/10.1088/1748-9326/ac7a4e
Wang, H., & Xuan, Y. (2022). A Spatial Pattern Extraction and Recognition Toolbox Supporting Machine Learning Applications on Large Hydroclimatic Datasets. Remote Sensing, 14(15), 3823. https://doi.org/10.3390/rs14153823
Kay, A. (2022). Differences in hydrological impacts using regional climate model and nested convection-permitting model data. Climatic Change, 173(1-2). https://doi.org/10.1007/s10584-022-03405-z
Wang, H., & Xuan, Y. (2023). Deep Learning of Extreme Rainfall Patterns Using Enhanced Spatial Random Sampling With Pattern Recognition. In Advanced Hydroinformatics (pp. 343–356). Wiley. https://doi.org/10.1002/9781119639268.ch12
Faulkner, D.S., Longfield, S., Warren, S., & Tawn, J.A. (2024). Modelling non-stationary flood frequency in England and Wales using physical covariates. In Hydrology Research. IWA Publishing. https://doi.org/10.2166/nh.2024.134
Kay, A.L., Bell, V.A., Davies, H.N., Lane, R.A. & Rudd, A.C. (2023) The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates. Earth System Science Data 15, 2533–2546. https://doi.org/10.5194/essd-15-2533-2023
Environment Agency (2020). Development of interim national guidance on non-stationary fluvial flood frequency estimation. The UK Government. https://www.gov.uk/government/publications/development-of-interim-national-guidance-on-non-stationary-fluvial-flood-frequency-estimation
Environment Agency (2020). Meeting our future water needs: a national framework for water resources. The UK Government. https://www.gov.uk/government/publications/meeting-our-future-water-needs-a-national-framework-for-water-resources
Weedon, G.P., Robinson, E.L., Bloomfield, J.P., Turner, S., Crane, E.J., & Best, M.J. (2023). Geological controls of discharge variability in the Thames Basin, UK from cross-spectral analyses: Observations versus modelling. In Journal of Hydrology (Vol. 625, p. 130104). Elsevier BV. https://doi.org/10.1016/j.jhydrol.2023.130104
Correspondence/contact details
Tanguy, M.
UK Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford
Wallingford
Oxfordshire
OX10 8BB
UNITED KINGDOM
enquiries@ceh.ac.uk
Wallingford
Oxfordshire
OX10 8BB
UNITED KINGDOM
Authors
https://orcid.org/0000-0002-1516-6834
Morris, D.G.
Centre for Ecology & Hydrology
Keller, V.D.J.
Centre for Ecology & Hydrology
Other contacts
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk