Preprints
https://doi.org/10.5194/egusphere-2025-2369
https://doi.org/10.5194/egusphere-2025-2369
03 Jun 2025
 | 03 Jun 2025
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

UK Hydrological Outlook using Historic Weather Analogues

Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford

Abstract. Skilful seasonal hydrological forecasts are beneficial for water resources planning and disaster risk reduction. The UK Hydrological Outlook (UKHO) provides river flow and groundwater level forecasts at the national scale. Alongside the standard Ensemble Streamflow Prediction (ESP) method, a new Historic Weather Analogues (HWA) method has recently been implemented. The HWA method samples within high resolution historical observations for analogue months that matches the atmospheric circulation patterns forecasted by a dynamical weather forecasting model. In this study, we conduct a hindcast experiment using the GR6J hydrological model to assess where and when the HWA method is skilful across a set of 314 UK catchments for different seasons. We benchmark the skill against the standard ESP and climatology forecasts to understand to what extent the HWA method represents an improvement to existing forecasting methods. Results show the HWA method yields skilful winter river flow forecasts across the UK compared to the standard ESP method where skilful forecasts were only possible in southeast England. Winter river flow forecasts using the HWA method were also more skilful in discriminating high and low flows across all regions. Catchments with the greatest improvement tended to be upland, fast responding catchments with limited catchment storage and where river flow variability is strongly tied with climate variability. Skilful winter river flow predictability was possible due to relatively high forecast skill of atmospheric circulation patterns (e.g. winter NAO) and the ability of the HWA method to derive high resolution meteorological inputs suitable for hydrological modelling. However, skill was not uniform across different seasons. Improvement in river flow forecast skill for other seasons was modest, such as moderate improvements in northern England and northeast Scotland during spring and little change in autumn. Skilful summer flow predictability remains possible only for southeast England and skill scores were mostly reduced compared to the ESP method elsewhere. This study demonstrates that the HWA method can leverage both climate information from dynamical weather forecasting models and the influence of initial hydrological conditions. An incorporation of climate information improved winter river flow predictability nationally, with the advantage of exploring historically unseen weather sequences. The strong influence of initial hydrological conditions contributed to retaining year-round forecast skill of river flows in southeast England. Overall, this study provides justification for when and where the HWA method is more skilful than existing forecasting approaches and confirms the standard ESP method as a “tough to beat” forecasting system that future improvements should be tested against.

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Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford

Status: open (until 25 Jul 2025)

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Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford
Wilson Chan, Katie Facer-Childs, Maliko Tanguy, Eugene Magee, Burak Bulut, Nicky Stringer, Jeff Knight, and Jamie Hannaford

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Short summary
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.
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