A new convection‐permitting regional reanalysis, SPHERA (High Resolution REAnalysis over Italy), has been developed over Italy and the surrounding seas using the COSMO model at 2.2 km horizontal resolution. The reanalysis system is nested in the global reanalysis ERA5; upper‐air and surface observations are assimilated at the convection‐permitting scale by the COSMO nudging scheme. Before the complete production of the hourly three‐dimensional fields and surface/soil parameters over the period 1995–2020, general issues regarding the reanalysis set‐up needed to be addressed over a shorter test period. These include the identification of the best approach to downscale the lateral boundary conditions from the global driver, and the definition of the bottom boundary condition related to deep soil temperature. With respect to the downscaling methodology, the results show a clear benefit in using lateral boundary conditions directly from the global ERA5, despite the large resolution difference between the two modes (1:15), instead of providing them from an intermediate resolution COSMO‐based reanalysis. Moreover, the soil bottom boundary condition for temperature is reconstructed from the shallower ERA5 soil, using a site‐dependent method based on a delayed running mean of the ERA5 temperature at the deepest soil level. Finally, an evaluation of SPHERA has been performed with respect to the skill in simulating daily precipitation over 2 years. Compared with ERA5, SPHERA shows a higher ability in simulating moderate and intense events, markedly during summer, in terms of skill scores, frequency of occurrence and bias.
Ensemble flood forecasts are an established tool to provide information about the uncertainty of runoff predictions. However, their interpretation may not be straightforward, especially when dealing with extreme events; therefore, the development of new tools to enhance their understanding and visualization is necessary. Recently, the so-called “peak-box” approach has been developed to help decision makers in the interpretation and verification of peak-flow forecasts, receiving positive feedbacks within the hydrological community. However, this method has proven to be limited when multiple peak-flow events occur within the forecast, being unable to separate close discharge peaks. The aim of this paper is then to develop a new algorithm designed to accomplish this task. To do so, we consider runoff probabilistic forecasts obtained with a coupled hydrometeorological flood forecasting system formed by the high resolution meteorological Ensemble model COSMO-E and the hydrological model PREVAH, for the small Verzasca basin, Switzerland, during October and November 2018. The application of this new method, despite the limitation given by the small sample size considered in this study, indicates a successful implementation: the new algorithm is able to distinguish among different events and to provide sharper and more skillful forecasts, and its verification yields slightly better timing estimations compared to the former approach.
<p>Hail is one of the most dangerous hazards for agriculture, infrastructures, and buildings of all severe-weather phenomena linked to deep moist convection. Due to global warming, the frequency and severity of hailstorms are expected to increase throughout Europe. It is, therefore, increasingly urgent to improve our understanding of hail hazard and risk. However, the intrinsic difficulties in systematically observing and simulating hail are still a major hurdle. While direct hail observations are heterogeneous, temporally-limited, and scarce, numerical simulations lack sufficient detail to represent the localized and rapidly-evolving hailstorm dynamics. A possible way to indirectly assess hail likelihood is through remote-sensing detections combined with numerical dynamical and thermodynamical characteristics of convective environments prone to hailstorm formation. Indeed, multiple data sources are necessary as, to date, more than a singular proxy is required to characterize hail.</p> <p>The new high-resolution reanalysis dataset SPHERA (High rEsolution ReAnalysis over Italy), developed at ARPAE, is considered for investigating hail-favoring environments over Italy and nearby countries. SPHERA is dynamically downscaled from ERA5, driven by the convection-permitting model COSMO (at 2.2 km grid spacing), providing meteorological data at hourly frequency. A set of parameters is extracted from SPHERA and combined with Overshooting cloud Top (OT) satellite detections, constituting a reliable proxy for hail. A probabilistic algorithm recently developed at NASA automatically detects OTs from geostationary Meteosat Second Generation SEVIRI infrared images. However, not all OTs are associated with hail formation in the storm. Hence, a filter is developed to retain only those occurrences linked to potential hailstorm formation based on the surrounding environmental conditions. To do so, ESWD (European Severe Weather Database) crowdsourced reports, representing the most reliable hail observational dataset in Europe, are coupled with SPHERA proxies to investigate convective environments nearby hailstorm events.</p> <p>The procedure is applied over five years (2016-2020). Hence, the primary purpose is to present the methodology rather than a sound hail frequency estimate. The resulting hailstorm characterization reveals a non-hailing OTs removal exceeding a quarter, mainly over the Mediterranean sea and complex-topography areas. The maximum hail likelihood is observed over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The validation against ESWD reports provides a hit rate exceeding 60%, roughly 20% more than the previous&#160;non-probabilistic OT detections coupling with ERA-Interim over Europe. Separating hit/miss reports and small/large hail reveals different characteristics of hail-prone environments. Most hit reports pertain to large hailstones (diameters &#8805; 3 cm), suggesting an inclination of the method to perform better in cases of severe hail occurrences. Investigating the interrelations among SPHERA parameters quantifying the main mechanisms needed for hail formation (i.e., atmospheric instability, freezing level height, and storm organization), the leading role of thermal and thermodynamical factors over the kinetics of the storm emerges.</p> <p>These results suggest promising opportunities to enhance hail dynamics comprehension owing to the advancements in remote-sensing techniques and the development of convection-permitting numerical simulations. In addition, further extension of the analysis should shed more light on the climatology of hailstorms.</p>
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