Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25^∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.

On 20 August 2018 a flash flood affected the Raganello Creek (southern Italy) causing 10 casualties. The rainfall event was so highly localized that the spatial coverage of rain gauges were inadequate to measure it, while radar products showed a storm cell with rain peaks of about 70–100 mm h−1. This scientific report provides a preliminary hydro-meteorological analysis of the event and evaluates the forecasting skills of a system based on the WRF–WRF-Hydro models, using both one-way and fully coupled approaches. The first results show a reasonable simulation of the event in terms of both rainfall and hydrological impact.

Reliable reanalysis products can be exploited to drive mesoscale numerical models and generate high-resolution reconstructions of high-impact weather events. Within this framework, regional weather and climate models may greatly benefit from the recent release of the ERA5 product, an improvement to the ERA-Interim dataset. In this study, two different convection-permitting models driven by these two reanalysis datasets are used to reproduce three heavy precipitation events affecting a Mediterranean region. Moreover, different sea surface temperature (SST) initializations are tested to assess how higher-resolution SST fields improve the simulation of high-impact events characterized by strong air–sea interactions. Finally, the coupling with a distributed hydrological model allows evaluating the impact at the ground, specifically assessing the possible added value of the ERA5 dataset for the high-resolution simulation of extreme hydrometeorological events over the Calabria region (southern Italy). Results, based on the comparison against multiple-source precipitation observations, show no clear systematic benefit to using the ERA5 dataset; moreover, intense convective activity can introduce uncertainties masking the signal provided by the boundary conditions of the different reanalyses. The effect of the high-resolution SST fields is even more difficult to detect. The uncertainties propagate and amplify along the modeling chain, where the spatial resolution increases up to the hydrological model. Nevertheless, even in very small catchments, some of the experiments provide reasonably accurate results, suggesting that an ensemble approach could be suitable to cope with uncertainties affecting the overall meteo-hydrological chain, especially for small catchments.

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.

The uncertainties that affect hydrometeorological modelling chains can be addressed through ensemble approaches. In this paper, a convection-permitting ensemble system was assessed based on the downscaling of all members of the ECMWF ensemble prediction system through the coupled atmospheric-hydrological WRF-Hydro modelling system. An exemplary highly localized convective event that occurred in a morphologically complex area of the southern Italian coast was selected as a case study, evaluating the performance of the system for two consecutive lead times up to the hydrological forecast on a very small (11.4 km²) catchment. The proposed approach accurately downscales the signal provided by the global model, improving up to almost 200% the quantitative forecast of the accumulated rainfall peak in the area affected by the event and supplying clear information about the forecast uncertainty. Some members of the ensemble simulations provide accurate results up to the hydrological scale over the catchment, with unit peak discharge forecasts up to 3 m³∙s⁻¹∙km⁻². Overall, the study highlights that for highly localized convective events in coastal Mediterranean catchments, ensemble approaches should be preferred to a classic single-based simulation approach, because they improve the forecast skills and provide spatially distributed information about the forecast uncertainty, which can be particularly useful for operational purposes.