From weather patterns to warnings: supporting multi-day bathing water advisories using synoptic weather regimes

Climate change is intensifying short-duration heavy rainfall over Northwestern Europe, increasing the frequency of rapid hydrometeorological impacts. These events increase the probability of short-term bathing water (BW) pollution, especially in catchments affected by combined sewer overflows and agricultural runoff. In England, mandatory monitoring of all storm overflows has revealed 450,398 recorded spills in 2024, leaving bathers unacceptably exposed. Coinciding increases in self-reported illness following contact with polluted BW highlight the need to reconsider how BW quality is forecast in the context of increasing extreme rainfall regimes.

Operational BW forecasts in England currently combine radar nowcasts, deterministic (UKV) rainfall forecasts, wind and UV data in a multiple linear regression model. Crucially, the forecast is issued once in the morning and not revised later in the day, even if rainfall forecasts change, providing only static, same-day guidance and constraining bathers’ ability to make informed decisions. While improvements in numerical weather prediction and monitoring remain critical, recent UK bathing water regulatory reforms increase the operational value of anticipating sustained or clustered pollution episodes across the bathing season and beyond, rather than relying on single-day exceedances.

Here we explore the use of synoptic weather patterns as a complementary framework for anticipating multi-day bathing water pollution risk. Synoptic weather patterns describe persistent, physically coherent circulation regimes. They influence not only how much rain falls, but also the type of rainfall (frontal versus convective) and the accompanying conditions (wind, cloud cover and solar irradiance). Using the Met Office 30-class daily weather pattern (WP) catalogue, microbiological data and 1 km Nimrod radar composites for South West England (May–September 2012–2023), we derive daily rainfall depth, intensity and wet fraction and link these, together with WP, to the site-day intestinal enterococci exceedances (IE ≥ 63 cfu/100 mL) used to inform operational advice against bathing.

We collapse 30 synoptic weather patterns into four physically interpretable families: Cyclonic Atlantic (frontal), Showery maritime/unsettled, Convective extremes, and Settled anticyclonic quiet. In observed data, “advice against bathing” varies significantly by family; it is highest under Cyclonic Atlantic and elevated under Showery maritime/unsettled. We use these families to construct plausible bathing water season storylines (persistent wet, persistent dry, dry with storm outbreaks, and transition scenarios wet to dry and dry to wet). For each storyline, we simulate 5,000 May–September seasons by resampling historically observed, physically coherent daily driver “packages”.

Comparing rainfall-only and weather pattern-based statistical models under a fixed advisory frequency shows that pattern-based approaches identify fewer, longer advisory windows, while rainfall-only methods produce shorter, intermittent alerts. In practice, this would mean fewer stop-start bathing advisories and clearer identification of sustained periods when extra attention, sampling, or precautionary messaging is needed. Since weather patterns can often be forecast several days ahead, this suggests that synoptic-scale information can support more actionable multi-day guidance for bathing water management, monitoring, and public communication.