Preprints
https://doi.org/10.5194/egusphere-2025-6216
https://doi.org/10.5194/egusphere-2025-6216
20 Jan 2026
 | 20 Jan 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Km-scale regional coupled system for the Northwest European shelf for weather and climate applications: RCS-UKC4

Ségolène Berthou, Juan Maria Castillo, Vivian Fraser-Leonhardt, Sana Mahmood, Nefeli Makrygianni, Alex Arnold, Claudio Sanchez, Huw W. Lewis, Dale Partridge, Martin Best, Lucy Bricheno, Helen Davies, Douglas Clark, James R. Clark, Jeff Polton, Andrew Saulter, Chris J. Short, Jonathan Tinker, and Simon Tucker

Abstract. Increasing the complexity of regional weather and climate models by developing coupled environmental prediction systems increases prediction skills in coastal areas, where equilibrium assumptions between Earth system components break down. By allowing consistency between earth system components, they also unlock new insights on multi-hazard processes with benefits for enhanced forecasting. We present recent advances in the regional coupled environmental prediction system developed in the UK through the release of the Regional Coupled Suite – UK Coupled domain version 4 (RCS-UKC4) configuration. This includes implementation of the new Regional Atmosphere and Land configuration (RAL3.3) alongside updates to all model components relative to previous releases. RCS-UKC4 also supports enhanced online simulation of river flows and coupling to a biogeochemistry model. New functionality including running near-real time ensemble forecasts and climate hindcasts is demonstrated. We first examine the effects of changing atmospheric and land configurations in both multi-annual simulations and short-term forecasts and assess the quality of river flows. RAL3.3 shows a beneficial increase in shortwave radiation reaching the ocean in summer months and a beneficial reduction in wind speed, which is slightly further reduced with wave coupling. River discharges have good skill in the northern and western regions of the UK, whilst the southeast rivers show too much variability. In a second part, we introduce ensemble forescasts, and show RCS-UKC4 has good skill in terms of wave forecasts during storms compared to the current operational ensemble: it shows lower root mean square error thanks to a good representation of tidal current/wave/wind interactions. Coupling can either increase or decrease the ensemble spread in screen temperature relative to atmosphere-only ensemble simulations, depending on whether latent heat flux or radiative heat flux dominates the spread in near-surface fluxes. Finally, we demonstrate that higher frequency (10-minute coupling) enables new prediction capability with a good representation of high frequency sea surface height variability linked with weather disturbances.

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Ségolène Berthou, Juan Maria Castillo, Vivian Fraser-Leonhardt, Sana Mahmood, Nefeli Makrygianni, Alex Arnold, Claudio Sanchez, Huw W. Lewis, Dale Partridge, Martin Best, Lucy Bricheno, Helen Davies, Douglas Clark, James R. Clark, Jeff Polton, Andrew Saulter, Chris J. Short, Jonathan Tinker, and Simon Tucker

Status: open (until 17 Mar 2026)

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Ségolène Berthou, Juan Maria Castillo, Vivian Fraser-Leonhardt, Sana Mahmood, Nefeli Makrygianni, Alex Arnold, Claudio Sanchez, Huw W. Lewis, Dale Partridge, Martin Best, Lucy Bricheno, Helen Davies, Douglas Clark, James R. Clark, Jeff Polton, Andrew Saulter, Chris J. Short, Jonathan Tinker, and Simon Tucker
Ségolène Berthou, Juan Maria Castillo, Vivian Fraser-Leonhardt, Sana Mahmood, Nefeli Makrygianni, Alex Arnold, Claudio Sanchez, Huw W. Lewis, Dale Partridge, Martin Best, Lucy Bricheno, Helen Davies, Douglas Clark, James R. Clark, Jeff Polton, Andrew Saulter, Chris J. Short, Jonathan Tinker, and Simon Tucker
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Latest update: 20 Jan 2026
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Short summary
The UK’s new RCS-UKC4 system combines atmosphere, ocean, waves, land, rivers, and biogeochemistry models to improve coastal weather and climate predictions. It offers better storm wave predictions, more accurate river flows, and captures rapid sea-level changes. These advances help predict multiple hazards more reliably, supporting safer communities and helping better planning.
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