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An impact of weather on road accidents has been identified in several studies with a focus mainly on monthly or daily accident counts. We study hourly probabilities of road accidents caused by adverse weather conditions in Germany on the spatial scale of administrative districts. Meteorological predictor variables from radar-based precipitation estimates, high-resolution reanalysis and weather forecasts are used in logistic regression models. Models taking into account temperature and hourly precipitation sums reach the best predictive skill according to different metrics. By introducing meteorological variables, the models hit rate is increased from 0.3 to 0.7, while keeping the false alarm rate constant at 0.2. Accident probability has a non-linear relationship with precipitation. Given an hourly precipitation sum of 1 mm, accident probabilities are about 5 times larger at negative temperatures compared to positive temperatures. Based on ensemble weather forecasts skilful predictions of accident probabilities of up to 21 hours are possible; the loss of skill compared to a model using radar and reanalysis data is negligible. The findings are relevant in the context of impact based warnings for both road users, road maintenance and traffic management authorities, as well as rescue forces.

The effect of weather on public transport usage in Berlin is analysed. The number of single and day tickets sold is used as a proxy for the number of occasional public transport users. Analysing more than three years of hourly ticket sale data, it is shown that the most important factor influencing ticket sales is temperature. Temperatures below −5°C lead to an increase in ticket sales by up to 30% on working days, while on hot days (> 28°C) passenger numbers drop by up to 5%. Precipitation increases the number of sales on working days by up to 5%. On weekends, the lowest ticket-sale numbers are associated with wet and either very cold or very hot conditions. Another factor influencing ticket sales is sunshine duration, while wind and snowfall do not seem to play a role for ticket sales in Berlin. It is demonstrated that it is possible to predict ticket sales depending on date, time and weather conditions using a statistical model. On designated public transport routes the effect of weather on passenger numbers can be much stronger than the district average. This is shown for the example of a bus route to a public beach. With each degree of temperature increase, passenger numbers on this line go up by approximately 30%.

The sensitivity of the October 1996 medicane in the western Mediterranean basin to sea surface temperatures (SSTs) is investigated via 24-member ensembles of regional climate model simulations. Eleven ensembles are created by uniformly changing SSTs in a range of −4 K to +6 K from the observed field, with a 1 K step. By using a modified phase space diagram and a simple compositing method, it is shown that the SST state has a minor influence on the tracks of the cyclones, but a strong influence on their intensities. Increased SSTs lead to greater probabilities of tropical transitions, to stronger low- and upper-level warm cores, and to lower pressure minima. The tropical transition occurs sooner and lasts longer, which enables a greater number of transitioning cyclones to survive landfall over Sardinia and to re-intensify in the Tyrrhenian Sea. The results demonstrate that SSTs influence the intensity of fluxes from the sea, which leads to greater convective activity before the storms reach their maturity. These results suggest that the processes at steady-state for medicanes are very similar to tropical cyclones.

Regional climate models (RCMs) are used to add the effects of nonresolved scales to coarser resolved model simulations by using a finer grid within a limited domain. We identify large-scale secondary circulations (SCs) relative to the driving global climate model (GCM) in an RCM simulation over Europe. By applying a clustering technique, we find that the SC depends on the large-scale flow prescribed by the driving GCM data. Evidence is presented that the SC is caused by the different representations of orographic effects in the RCM and the GCM. Flow modifications in the RCM caused by the Alps lead to large-scale vortices in the SC fields. These vortices are limited by the RCM boundaries, causing artificial boundary-parallel flows. The SC is associated with geopotential height and temperature anomalies between RCM and GCM and has the potential to produce systematic large-scale biases in RCMs.