Forecasting extreme precipitation in the central Mediterranean: Changes in predictors' strength with prediction lead time. (9th November 2022)

• Record Type: Journal Article
• Authors: Mastrantonas, Nikolaos; Furnari, Luca; Magnusson, Linus; Senatore, Alfonso; Mendicino, Giuseppe; Pappenberger, Florian; Matschullat, Jörg
• Is Part Of: Meteorological applications. Volume 29:Number 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-09
• Subjects: Calabria -- Europe -- seamless forecasting -- weather patterns; Meteorology -- Periodicals; Meteorological services -- Periodicals; 551.5
• DOI: 10.1002/met.2101
• Languages: English
• ISSNs: 1350-4827

Abstract

Abstract: This work compares forecasting strategies for improving the prediction of extreme precipitation events at different timescales. Our study focuses on forecasting extreme precipitation in Calabria, southern Italy. This region with complex and abruptly varying topography poses additional challenges in forecasting precipitation. Here, we use gridded observational precipitation data from the E‐OBS dataset, reanalysis data from ERA5, and forecasts from ECMWF reforecasts. We show that different forecasting horizons require different forecasting strategies. For short to medium‐range lead times, post‐processing the forecasted extreme precipitation probabilities provides the most informative outputs for end users. For extended‐range forecasts though, it is beneficial to use the large‐scale weather variability, as depicted based on nine Mediterranean patterns in combination with moisture‐related information, to infer reliable information about extreme precipitation. We present benefits and limitations of the methods based on long‐term statistical analysis using a range of indicators, such as the Brier skill score and its decomposition, and the cost–loss model. Abstract : This study presents forecasting strategies for predicting extreme precipitation in Calabria, Italy, at different lead times. Data from E‐OBS, ERA5, and ECMWF reforecasts show that different predictors are preferential for different forecasting horizons. For short to medium‐range forecasts, we suggest to post‐process the predicted extreme precipitation probabilities. For second‐ to third‐week forecasts though, the most reliable information can be extracted based on the forecasted large‐scale variability over the Mediterranean in combination with localized moisture conditions.