Improving Extreme Precipitation Forecasts in Catalonia (Spain) Using Analog Methods: A Comparison with the GFS Model

Abstract

Flood forecasting in the Mediterranean region remains particularly challenging due to the localized and convectivenature 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 broaderobjective of supporting flood risk management and early warning systems. The tested AMs use geopotentialheight 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 analogbasedforecasting. Model performance was assessed against operational Global Forecast System (GFS) forecastsusing fifth-generation ECMWF Re-Analysis (ERA5) as reference, for both moderate and extreme precipitationevents associated with historical floods. Results show that AMs integrating Seasonal Standardization and thePerfect Prognosis framework markedly improve 24-hour precipitation forecasts relative to GFS, particularly inreproducing the intensity and spatial distribution of extreme events. These findings highlight the operationalpotential 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.