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Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain language summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organising evacuations. We review and compare the state‐of‐the‐art of impact forcasting across a wide range of natural hazards, and outline opportunities and key challenges for research and development of impact forecasting.

Over 3 weeks in May and June 2018, an exceptionally large number of thunderstorms hit vast parts of western and central Europe, causing precipitation accumulations of up to 80 mm within 1 h and several flash floods. This study examines the conditions and processes that made this particular thunderstorm episode exceptional, with a particular focus on the interaction of processes across scales. During the episode, a blocking situation persisted over northern Europe. 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 the 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 weak geopotential height gradients led to predominantly weak flow conditions in the mid-troposphere and thus to low vertical wind shear that prevented thunderstorms from developing into severe organized systems. Due to a weak propagation speed in combination with high rain rates, several thunderstorms were able to accumulate enormous amounts of precipitation that affected local-scale areas and triggered several torrential 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 provided the mesoscale setting for the development of a large number of thunderstorms. During the 22 d study period, more than 50 % of lightning strikes can be linked to a nearby cut-off low or PV filament. The exceptionally persistent low stability over 3 weeks combined with a weak wind speed in the mid-troposphere has not been observed during the past 30 years., Weather and Climate Dynamics, 1 (2), ISSN:2698-4016, ISSN:2698-4008

A 10-yr geostationary (GEO) overshooting cloud-top (OT) detection database using Multifunction Transport Satellite (MTSAT) Japanese Advanced Meteorological Imager (JAMI) observations has been developed over the Australian region. GEO satellite imagers collect spatially and temporally detailed observations of deep convection, providing insight into the development and evolution of hazardous storms, particularly where surface observations of hazardous storms and deep convection are sparse and ground-based radar or lightning sensor networks are limited. Hazardous storms often produce one or more OTs that indicate the location of strong updrafts where weather hazards are typically concentrated, which can cause substantial impacts on the ground such as hail, damaging winds, tornadoes, and lightning and to aviation such as turbulence and in-flight icing. The 10-yr OT database produced using an automated OT detection algorithm is demonstrated for analysis of storm frequency, diurnally, spatially, and seasonally relative to known features such as the Australian monsoon, expected regions of hazardous storms along the southeastern coastal regions of southern Queensland and New South Wales, and the preferential extratropical cyclone track along the Indian Ocean and southern Australian coast. A filter based on atmospheric instability, deep-layer wind shear, and freezing level was used to identify OTs that could have produced hail. The filtered OT database is used to generate a hail frequency estimate that identifies a region extending from north of Brisbane to Sydney and the Goldfields–Esperance region of eastern Western Australia as the most hail-prone regions.

At the end of July 2013, a series of severe thunderstorms associated with heavy rainfall, severe wind gusts, and large hail affected parts of Germany. On 28 July 2013, two supercells formed almost simultaneously in southern Germany, from which only the more southerly cell produced hailstones up to 10 cm in diameter on a hailswath approximately 120 km long and 15–20 km wide. For the insurance industry, this event with losses of more than EUR 1 billion was one of the most expensive natural disasters that has ever occurred in Germany. This paper investigates the creation, temporal evolution, and effects of the most severe supercell that day by considering and merging radar and satellite data, eyewitness reports, insurance loss data, and numerical model studies. Observations of hail at ground level fit very well with a cold–ring-shaped structure in the cloud top brightness temperature observed by a geostationary satellite imager. Various simulations conducted with the convection-permitting COnsortium for Small-scale MOdeling (COSMO) revealed that the track of the hailstorm could be reproduced only when convection was triggered artificially by two warm bubbles that produced single cells that were precursors of the supercell. The model results suggested that the supercell developed near a pre-existing single cell through low-level flow convergence in an environment with moderate CAPE, but substantial wind shear and storm-relative helicity, both of which persisted for several hours in the area in which the supercell moved.

This article presents a hail frequency estimation based on the detection of cold overshooting cloud tops (OTs) from the Meteosat Second Generation (MSG) operational weather satellites, in combination with a hail-specific filter derived from the ERA-INTERIM reanalysis. This filter has been designed based on the atmospheric properties in the vicinity of hail reports registered in the European Severe Weather Database (ESWD). These include Convective Available Potential Energy (CAPE), 0–6-km bulk wind shear and freezing level height, evaluated at the nearest time step and interpolated from the reanalysis grid to the location of the hail report. Regions highly exposed to hail events include Northern Italy, followed by South-Eastern Austria and Eastern Spain. Pronounced hail frequency is also found in large parts of Eastern Europe, around the Alps, the Czech Republic, Southern Germany, Southern and Eastern France, and in the Iberic and Apennine mountain ranges.

The analyses specific threshold of lightning discharges density and thunderstorms days for different type of landscape and level of altitudes were determinate. For Central Europe from 9° W to 20° E and from 42° to 56° N (11° x 14° sectors) for April–September period from 2001 to 2014 were investigated. For Europe for the altitude range from 10 m below sea level (bsl) to 200 m above sea level (asl) the highest lightning discharge density is associated with the forest, shrub and wet, urban areas. For the altitude range 200–1000 m asl the highest lightning discharges density is associated with water (river, lakes), urban and forest areas. For the altitude range level from 1000 m asl to 2000 m asl the highest lightning discharges density is associated with the water, forest and grass types. A dense forest on the track of the flow of a moist air mass can promote the rise of air and the formation of convective clouds and lightning strokes. The effect of rives, channels and large lakes on moisture and development of thunderstorm clouds may account for impact on cloud-to-ground (CG) lightning activity. For three flat 3° x 5° areas with similar meteorological and synoptic conditions, increased CG lightning activity is possible if there is a difference in altitude between different types of landscapes. The altitude difference further contributes to the development of convective clouds producing lightning.

Changing climate conditions on Greenland influence the snow accumulation rate and surface mass balance (SMB) on the ice sheet and, ultimately, its shape. This can in turn affect local climate via orography and albedo variations and, potentially, remote areas via changes in ocean circulation triggered by melt water or calving from the ice sheet. Examining these interactions in the IPSL global model requires improving the representation of snow at the ice sheet surface. In this paper, we present a new snow scheme implemented in LMDZ, the atmospheric component of the IPSL coupled model. We analyse surface climate and SMB on the Greenland ice sheet under insolation and oceanic boundary conditions for modern, but also for two different past climates, the last glacial inception (115 kyr BP) and the Eemian (126 kyr BP). While being limited by the low resolution of the general circulation model (GCM), present-day SMB is on the same order of magnitude as recent regional model findings. It is affected by a moist bias of the GCM in Western Greenland and a dry bias in the north-east. Under Eemian conditions, the SMB decreases largely, and melting affects areas in which the ice sheet surface is today at high altitude, including recent ice core drilling sites as NEEM. In contrast, glacial inception conditions lead to a higher mass balance overall due to the reduced melting in the colder summer climate. Compared to the widely applied positive degree-day (PDD) parameterization of SMB, our direct modelling results suggest a weaker sensitivity of SMB to changing climatic forcing. For the Eemian climate, our model simulations using interannually varying monthly mean forcings for the ocean surface temperature and sea ice cover lead to significantly higher SMB in southern Greenland compared to simulations forced with climatological monthly means.