Improving extreme precipitation forecasts in Catalonia (NE Iberian Peninsula) using analog methods: A comparison with the GFS model

Flood forecasting in the Mediterranean region remains particularly challenging due to the localized and convective nature of extreme precipitation events. This study evaluates the potential of analog-based methods (AMs) to enhance 24-hour precipitation forecasts for Catalonia (northeastern Iberian Peninsula), with the broader objective of supporting flood risk management and early warning systems. The tested AMs use geopotential height fields at 500 and 1000 hPa as predictors and differ in complexity, combining Weather-Type classification (WT), Seasonal Standardization (S), and the Perfect Prognosis (PP) framework,a novel configuration in analog-based forecasting. Model performance was assessed against operational Global Forecast System (GFS) forecasts using fifth-generation ECMWF Re-Analysis (ERA5) as reference, for both moderate and extreme precipitation events associated with historical floods. Results show that AMs integrating Seasonal Standardization and the Perfect Prognosis framework markedly improve 24-hour precipitation forecasts relative to GFS, particularly in reproducing the intensity and spatial distribution of extreme events. These findings highlight the operational potential of enhanced AMs as efficient, data-driven complements to numerical weather prediction models, offering improved skill for flash-flood forecasting and impact-based risk management. • Analog methods with weather type classification and seasonal standardization outperform GFS-24h forecasts for general and extreme precipitation events for Catalonia region (NE of Spain). • The analogh method that assumes perfect prognosis hypotesis between GFS Analysis and ERA5 reanalysis shows the best performance for extreme precipitation events. • Analog-based forecasts offer added value for operational use and flood risk management.