Articles | Volume 7, issue 1
https://doi.org/10.5194/essd-7-143-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-7-143-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications
V. D. J. Keller
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
I. Prosdocimi
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
J. A. Terry
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
O. Hitt
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
S. J. Cole
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
M. Fry
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
D. G. Morris
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
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Jamie Hannaford, Stephen Turner, Amulya Chevuturi, Wilson Chan, Lucy J. Barker, Maliko Tanguy, Simon Parry, and Stuart Allen
Hydrol. Earth Syst. Sci., 29, 4371–4394, https://doi.org/10.5194/hess-29-4371-2025, https://doi.org/10.5194/hess-29-4371-2025, 2025
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This extended review asks whether hydrological (river flow) droughts have become more severe over time in the UK based on literature review and original analyses. The UK is a good international exemplar, given the richness of available data. We find that there is little compelling evidence for a trend towards worsening river flow droughts, at odds with future climate change projections. We outline reasons for this discrepancy and make recommendations to guide researchers and policymakers.
Srinidhi Jha, Lucy J. Barker, Jamie Hannaford, and Maliko Tanguy
EGUsphere, https://doi.org/10.5194/egusphere-2025-4096, https://doi.org/10.5194/egusphere-2025-4096, 2025
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The influence of climate change on drought in the UK has gained attention recently. However, a probabilistic assessment of temperature’s nonstationary influences on hydrological drought characteristics, which could provide key insights into future risks and uncertainties, has not been conducted. This study evaluates changes across seasons and warming scenarios, finding that rare droughts may become more severe, while frequent summer droughts are shorter but more intense.
Burak Bulut, Eugene Magee, Rachael Armitage, Opeyemi E. Adedipe, Maliko Tanguy, Lucy J. Barker, and Jamie Hannaford
EGUsphere, https://doi.org/10.5194/egusphere-2025-3176, https://doi.org/10.5194/egusphere-2025-3176, 2025
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This study developed a generic machine learning model to forecast drought impacts, with the UK as the main focus. The same model was successfully validated in Germany, showing potential for use in other regions. It captured local patterns of past drought impacts, matching observed events. Using weather and soil data, the model supports early warning and drought risk management. Results are promising, though testing in more climates and conditions would strengthen confidence.
Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford
EGUsphere, https://doi.org/10.5194/egusphere-2025-2369, https://doi.org/10.5194/egusphere-2025-2369, 2025
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The UK Hydrological Outlook river flow forecasting system recently implemented the Historic Weather Analogues method. The method improves winter river flow forecast skill across the UK, especially in upland, fast-responding catchments with low catchment storage. Forecast skill is highest in winter due to accurate prediction of atmospheric circulation patterns like the North Atlantic Oscillation. The Ensemble Streamflow prediction method remains a robust benchmark, especially for other seasons.
Maliko Tanguy, Michael Eastman, Amulya Chevuturi, Eugene Magee, Elizabeth Cooper, Robert H. B. Johnson, Katie Facer-Childs, and Jamie Hannaford
Hydrol. Earth Syst. Sci., 29, 1587–1614, https://doi.org/10.5194/hess-29-1587-2025, https://doi.org/10.5194/hess-29-1587-2025, 2025
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Our research compares two techniques, bias correction (BC) and data assimilation (DA), for improving river flow forecasts across 316 UK catchments. BC, which corrects errors after simulation, showed broad improvements, while DA, adjusting model states before forecast, excelled under specific conditions like snowmelt and high baseflows. Each method's unique strengths suit different scenarios. These insights can enhance forecasting systems, offering reliable and user-friendly hydrological predictions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078, https://doi.org/10.5194/nhess-24-1065-2024, https://doi.org/10.5194/nhess-24-1065-2024, 2024
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The most recent drought in the UK was declared in summer 2022. We pooled a large sample of plausible winters from seasonal hindcasts and grouped them into four clusters based on their atmospheric circulation configurations. Drought storylines representative of what the drought could have looked like if winter 2022/23 resembled each winter circulation storyline were created to explore counterfactuals of how bad the 2022 drought could have been over winter 2022/23 and beyond.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Maliko Tanguy, Michael Eastman, Eugene Magee, Lucy J. Barker, Thomas Chitson, Chaiwat Ekkawatpanit, Daniel Goodwin, Jamie Hannaford, Ian Holman, Liwa Pardthaisong, Simon Parry, Dolores Rey Vicario, and Supattra Visessri
Nat. Hazards Earth Syst. Sci., 23, 2419–2441, https://doi.org/10.5194/nhess-23-2419-2023, https://doi.org/10.5194/nhess-23-2419-2023, 2023
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Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.
Jamie Hannaford, Jonathan D. Mackay, Matthew Ascott, Victoria A. Bell, Thomas Chitson, Steven Cole, Christian Counsell, Mason Durant, Christopher R. Jackson, Alison L. Kay, Rosanna A. Lane, Majdi Mansour, Robert Moore, Simon Parry, Alison C. Rudd, Michael Simpson, Katie Facer-Childs, Stephen Turner, John R. Wallbank, Steven Wells, and Amy Wilcox
Earth Syst. Sci. Data, 15, 2391–2415, https://doi.org/10.5194/essd-15-2391-2023, https://doi.org/10.5194/essd-15-2391-2023, 2023
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The eFLaG dataset is a nationally consistent set of projections of future climate change impacts on hydrology. eFLaG uses the latest available UK climate projections (UKCP18) run through a series of computer simulation models which enable us to produce future projections of river flows, groundwater levels and groundwater recharge. These simulations are designed for use by water resource planners and managers but could also be used for a wide range of other purposes.
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Short summary
The CEH – Gridded Estimates of Areal Rainfall (CEH–GEAR) dataset contains 1 km gridded estimates of daily and monthly rainfall for Great Britain and Northern Ireland (plus approximately 3000 km2 in the Republic of Ireland) from 1890 to 2012. The rainfall estimates are derived from the Met Office national database of observed precipitation, using a natural neighbour interpolation methodology which includes a normalisation step based on average annual rainfall.
The CEH – Gridded Estimates of Areal Rainfall (CEH–GEAR) dataset contains 1 km gridded...
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