Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2019) [CEH-GEAR]

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By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.

Contains material based on Met Éireann data © Met Éireann and Met Office data © Crown copyright.

Users should be aware that the quality of the rainfall data will decrease when the minimum distance (i.e. distance to the closest gauge) increases. The value of the minimum distance is provided alongside rainfall values within the dataset. For values of minimum distance greater than 100 km, rainfall values are not derived.

This dataset is available under the terms of the Open Government Licence

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https://doi.org/10.5285/dbf13dd5-90cd-457a-a986-f2f9dd97e93c

This is the most recent version of this dataset

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 2019.

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: 2021-11-11

8 citations

384 downloads *

4,709 views *

More information

View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)

Format

NetCDF

Spatial information

Study area

Spatial representation type

Raster

Spatial reference systems

OSGB 1936 / British National Grid
OSNI 1952 / Irish National Grid

Temporal information

Temporal extent

1890-01-01 to 2019-12-31

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 (1890-2017) only by temporal coverage. That is, previous years' data have not been modified.

Licensing and constraints

This dataset is available under the terms of the Open Government Licence

Cite this dataset as:

Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D.G.; Keller, V.D.J. (2021). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2019) [CEH-GEAR]. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/dbf13dd5-90cd-457a-a986-f2f9dd97e93c

BibTeX RIS

Contains material based on Met Éireann data © Met Éireann and Met Office data © Crown copyright.

Services associated with this dataset

Estimates of daily river flows for 95 catchments in Great Britain from the GR6J model under present and future climate scenarios, using large ensemble climate model driving data

Citations

Salwey, S., Coxon, G., Pianosi, F., Singer, M.B. & Hutton, C. (2023) National‐Scale Detection of Reservoir Impacts Through Hydrological Signatures. Water Resources Research 59. https://doi.org/10.1029/2022wr033893

Kiraz, M., Coxon, G. & Wagener, T. (2023) A priori selection of hydrological model structures in modular modelling frameworks: application to Great Britain. Hydrological Sciences Journal 68, 2042–2056. https://doi.org/10.1080/02626667.2023.2251968

Robinson, E.L., Brown, M.J., Kay, A.L., Lane, R.A., Chapman, R., Bell, V.A., & Blyth, E.M. (2023). Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom. In Earth System Science Data (Vol. 15, Issue 10, pp. 4433–4461). Copernicus GmbH. https://doi.org/10.5194/essd-15-4433-2023

Hooftman, D.A.P., Bullock, J.M., Evans, P.M., Redhead, J.W., Ridding, L.E., Varma, V., & Pywell, R.F. (2023). A model of sediment retention by vegetation for Great Britain: new methodologies & validation. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2023.08.17.553678

Jacque, H., Knox, J.W., Gush, M., & Holman, I.P. (2023). Modelling the potential of rainwater harvesting to improve the sustainability of landscape and public garden irrigation. In Journal of Environmental Management (Vol. 348, p. 119167). Elsevier BV. https://doi.org/10.1016/j.jenvman.2023.119167

Chan, W.C.H., Arnell, N.W., Darch, G., Facer-Childs, K., Shepherd, T.G., & Tanguy, M. (2024). Added value of seasonal hindcasts to create UK hydrological drought storylines. In Natural Hazards and Earth System Sciences (Vol. 24, Issue 3, pp. 1065–1078). Copernicus GmbH. https://doi.org/10.5194/nhess-24-1065-2024

Thorpe, C., Fisher, A., Manifold, G., Creasey-Gray, S., Jackson, C., Stone, J., Corkhill, C., Boothman, C., Lloyd, J., & Hand, R. (2024). Insights into long-term glass corrosion mechanisms from the Ballidon project: a 50-year-old glass burial experiment in an alkaline near surface environment. Research Square Platform LLC. https://doi.org/10.21203/rs.3.rs-4413120/v1

Tso, C.-H.M., Blyth, E., Tanguy, M., Levy, P.E., Robinson, E.L., Bell, V., Zha, Y., & Fry, M. (2023). Multiproduct Characterization of Surface Soil Moisture Drydowns in the United Kingdom. In Journal of Hydrometeorology (Vol. 24, Issue 12, pp. 2299–2319). American Meteorological Society. https://doi.org/10.1175/jhm-d-23-0018.1