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Among severe weather events generated by deep convection, hail represents one of the most hazardous perils for agriculture, buildings, and properties. Moreover, in response to global warming, hailstorm frequency and severity are expected to increase in Europe. Therefore, a better understanding of hail hazards and risks is becoming increasingly crucial. However, major hurdles are posed by direct observations, by being heterogeneous, temporally limited, and scarce, as well as by numerical simulations, which generally lack sufficient detail to represent hailstorm dynamics properly. As a possible solution, hail likelihood can be indirectly assessed by combining multiple data sources, such as remote-sensing detections and ambient numerical predictors. The new high-resolution reanalysis SPHERA (High rEsolution ReAnalysis over Italy), developed at ARPAE, is considered to describe hail-favoring environments over Italy and nearby countries. SPHERA is dynamically downscaled from ERA5 and driven by the model COSMO at the convection-permitting resolution of 2.2 km. A set of predictors is selected and combined with Overshooting cloud Top (OT) satellite detections, constituting a reliable proxy for hail. OTs are automatically detected with a probabilistic algorithm (NASA) from geostationary Meteosat Second Generation SEVIRI infrared images. However, not all OTs are linked to hail. Hence, a filter based on their surrounding ambient conditions is developed to retain only OT occurrences with the potential for hailstorm formation. For this purpose, ESWD (European Severe Weather Database) crowdsourced hail reports are coupled with SPHERA proxies to characterize hailstorm environments. The analysis is performed over 2016-2020. Hence, the primary intent is to present the methodology rather than a comprehensive hail frequency characterization. More than a quarter of non-hailing OTs are removed, mainly over the Mediterranean sea and complex-topography areas. Maximum hail likelihood characterizes pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, agreeing with previous European hail climatologies. The hit rate of ESWD reports with OTs exceeds 60%, i.e., ~20% more than the previous coupling of non-probabilistic OT detections with ERA-Interim over Europe. Different ambient characteristics are revealed by separating hit/miss reports for small/large hail events. Most hits present hailstones with diameters ≥3 cm, suggesting a better suitability of the method in case of severe hailstorms. Further, missed small-hail reports show peculiar environmental signatures characterized by lower instability, less wind shear, and colder atmospheric profiles. These results suggest a promising avenue to enhance hailstorm events identification. In addition, further extension of the analysis should shed more light on the climatology of hailstorms.

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. 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. 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 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 ≥ 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. 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.

Accurate estimates of hail risk to exposed assets, such as crops, infrastructure, and vehicles, are required for both insurance pricing and preventive measures. Here we present an event catalog to describe the hail hazard in South Africa guided by 14 years of geostationary satellite observations of convective storms. Overshooting cloud tops have been detected, grouped, and tracked to describe the spatiotemporal extent of potential hail events. It is found that hail events concentrate mainly in the southeast of the country, along the Highveld, and around the eastern slopes. Events are most frequent from mid-November through February and peak in the afternoon, between 13:00 and 17:00 UTC. Multivariate stochastic modeling of event properties yields an event catalog spanning 25 000 years, aiming to estimate, in combination with vulnerability and exposure data, hail risk for return periods of 200 years.

Over three weeks in May and June 2018, an exceptionally large number of thunderstorms hit vast parts of western and central Europe, causing precipitation of up to 80 mm and several flash floods. During this time, the large-scale atmospheric circulation, which was characterized by a blocking situation over northern Europe, influenced atmospheric conditions relevant for thunderstorm development. Initially, the southwesterly flow on the western flank of the blocking anticyclone induced the advection of warm, moist, and unstably stratified air masses. Due to a low-pressure gradient associated with the blocking anticyclone, these air masses were trapped in western and central Europe, remained almost stationary and prevented a significant air mass exchange. In addition, the low-pressure gradient led to weak flow conditions in the mid-troposphere and thus to low vertical wind shear that prevented thunderstorms from developing into severe organized systems. Most of the storms formed as local-scale, relatively slow-moving single cells. However, due to the related weak propagation speed, several thunderstorms were able to produce torrential heavy rain that affected local-scale areas and triggered several flash floods. Atmospheric blocking also increased the upper-level cut-off low frequency on its upstream regions, which was up to 10 times higher than the climatological mean. Together with filaments of positive potential vorticity (PV), the cut-offs served as trigger mechanisms for a majority of the thunderstorms. For the 22-day study period, we found that more than 50 % of lightning strikes can be linked to a nearby cut-off low or PV filament. The exceptional persistence of low stability combined with weak wind speed in the mid-troposphere over three weeks has not been observed during the past 30 years.

In the context of global warming, the contribution of the two major ice sheets, Antarctica and Greenland, to global sea level rise is a subject of key importance for the scientific community (4th assessment report of the Intergovernmental Panel on climate change, IPCC-AR4, Meehl et al., 2007). By the end of the next century, a 3–5 °C warm up is expected in Greenland. Similar temperatures in this region were reached during the last interglacial (LIG) period due to a change in orbital configuration rather than to anthropogenic forcing. Ice core evidence suggests that the Greenland Ice Sheet (GIS) has survived this warm period but great uncertainties remain about the total Greenland ice reduction during the LIG and its sea level rise contribution. In order to improve our confidence in future state projections, we first intend to reconstruct the past states of the GIS using ice sheet modelling, and confront the simulations with paleo data. The chosen methodoly of paleoclimate reconstruction is strongly based on proxy data. Proxy data are also used to constrain the ice sheet model during the calibration phase. Our estimates of Greenland melting contribution to sea level rise during the LIG period range from 0.65 to 1.5 m of sea level equivalent.

The prediction of future climate and ice sheet evolution requires coupling of ice sheet and climate models. Before proceeding to a coupled setup, we propose to analyze the impact of model simulated climate on an ice sheet. Here, we undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary condition to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyr of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed ones, there are considerable deviations among the ice sheets on regional scales. These can be explained by difficulties in modelling local temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations of each climate model are also due to the differences in the atmospheric general circulation. In the context of coupling ice sheet and climate models, we conclude that appropriate downscaling methods will be needed and systematic corrections of the climatic variables at the interface may be required in some cases to obtain realistic results for the Greenland ice sheet (GIS).

The quasi-biennial oscillation (QBO) of zonal wind is a prominent mode of variability in the tropical stratosphere. It affects not only the meridional circulation and temperature over a wide latitude range but also the transport and chemistry of trace gases such as ozone. Compared to a QBO less circulation, the long-term climatological means of these quantities are also different. These climatological net effects of the QBO can be studied in general circulation models that extend into the middle atmosphere and have a chemistry and transport component, so-called Chemistry Climate Models (CCMs). In this work we show that the CCM MAECHAM4-CHEM can reproduce the observed QBO variations in temperature and ozone mole fractions when nudged towards observed winds. In particular, it is shown that the QBO signal in transport of nitrogen oxides NOx plays an important role in reproducing the observed ozone QBO, which features a phase reversal slightly below the level of maximum of the ozone mole fraction in the tropics. We then compare two 20-year experiments with the MAECHAM4-CHEM model that differ by including or not including the QBO. The mean wind fields differ between the two model runs, especially during summer and fall seasons in both hemispheres. The differences in the wind field lead to differences in the meridional circulation, by the same mechanism that causes the QBO's secondary meridional circulation, and thereby affect mean temperatures and the mean transport of tracers. In the tropics, the net effect on ozone is mostly due to net differences in upwelling and, higher up, the associated temperature change. We show that a net surplus of up to 15% in NOx in the tropics above 10 hPa in the experiment that includes the QBO does not lead to significantly different volume mixing ratios of ozone. We also note a slight increase in the southern vortex strength as well as earlier vortex formation in northern winter. Polar temperatures differ accordingly. Differences in the strength of the Brewer-Dobson circulation and in further trace gas concentrations are analysed. Our findings underline the importance of a representation of the QBO in CCMs.