UK Hydrological Outlook using historic weather analogues

Chan, Wilson ORCID: https://orcid.org/0000-0003-4296-3203; Facer-Childs, Katie A. ORCID: https://orcid.org/0000-0003-1060-9103; Tanguy, Maliko ORCID: https://orcid.org/0000-0002-1516-6834; Magee, Eugene; Bulut, Burak ORCID: https://orcid.org/0000-0003-4567-5258; Stringer, Nicky; Knight, Jeff; Hannaford, Jamie ORCID: https://orcid.org/0000-0002-5256-3310. 2025 UK Hydrological Outlook using historic weather analogues. EGUsphere, Preprint egusphere-2025-2369. 10.5194/egusphere-2025-2369

Before downloading, please read NORA policies.

Preview

Text egusphere-2025-2369.pdf - Submitted Version Available under License Creative Commons Attribution 4.0. Download (3MB) | Preview

Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.5194/egusphere-2025-2369
UKCEH and CEH Sections/Science Areas:	Water and Climate Science (2025-) UKCEH Fellows
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	Hydrology Meteorology and Climatology Data and Information
Date made live:	10 Jun 2025 09:46 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/539545

Actions (login required)

View Item

Document Downloads

More statistics for this item...