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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Bias-Corrected UKCP18 Convection-Permitting Model (CPM) Projections of Precipitation and Temperature Using Non-Parametric Quantile Mapping

Authors: Zha, Qianyu; He, Yi; Osborn, Timothy; Forstenhäusler, Nicole;

Bias-Corrected UKCP18 Convection-Permitting Model (CPM) Projections of Precipitation and Temperature Using Non-Parametric Quantile Mapping

Abstract

This dataset provides bias-corrected hourly precipitation and daily mean temperature projections for England, based on the UK Climate Projections 2018 Convection-Permitting Model (UKCP18-CPM). The original UKCP18-CPM outputs are available at a 5 km resolution from 1980 to 2080 under the high-emissions scenario RCP8.5 (Met Office Hadley Centre, 2019). These outputs were remapped to a 1 km grid consistent with the HadUK-Grid observational framework (Met Office et al., 2022) to support high-resolution climate impact assessments. The dataset includes three 20-year time slices: 1981–2000, 2021–2040, and 2061–2080, for four selected ensemble members (EM01, EM04, EM07, EM08). Two key climate variables are included: Hourly precipitation, bias-corrected using the CEH-GEAR1hr observational dataset (Lewis et al., 2022); Daily mean temperature, bias-corrected against the HadUK-Grid dataset (Hollis et al., 2019; Met Office et al., 2022). Bias correction was performed using empirical quantile mapping, a non-parametric technique that adjusts the entire distribution of model outputs to match observations. For hourly precipitation, an enhanced diurnal bias correction method (Faghih et al., 2022) was applied to better represent the diurnal cycle of precipitation, which is particularly important in high-resolution climate simulations. This gridded dataset spans the areas of 249 catchments in England and is particularly suitable for high-resolution hydrological impact assessments. ------------------------------------------------- Faghih, M., Brissette, F., and Sabeti, P.: Impact of correcting sub-daily climate model biases for hydrological studies, Hydrology and Earth System Sciences, 26, 1545–1563, https://doi.org/10.5194/hess-26-1545-2022, 2022. Hollis, D., McCarthy, M., Kendon, M., Legg, T., and Simpson, I.: HadUK‐Grid—A new UK dataset of gridded climate observations, Geosci Data J, 6, 151–159, https://doi.org/10.1002/gdj3.78, 2019. Lewis, E., Quinn, N., Blenkinsop, S., Fowler, H. J., Freer, J., Tanguy, M., Hitt, O., Coxon, G., Bates, P., Woods, R., Fry, M., Chevuturi, A., Swain, O., and White, S. M.: Gridded estimates of hourly areal rainfall for Great Britain 1990-2016 [CEH-GEAR1hr] v2, 2022. Met Office Hadley Centre: UKCP Local Projections on a 5km grid over the UK for 1980-2080, 2019. Met Office, Hollis, D., McCarthy, M., Kendon, M., and Legg, T.: HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.1.0.0 (1836-2021), https://doi.org/10.5285/BBCA3267DC7D4219AF484976734C9527, 2022.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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