A novel nested flood model (MSN_Flood) is applied to simulate complex coastal-fluvial urban flooding in order to critically examine the model's capability to forecast evolution of urban inundation. The model demonstrates high accuracy of outputs without incurring the computational expense of high spatial resolution over the entire model domain. MSN_Flood provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

High precipitation quantiles tend to rise with air temperature, following the so-called Clausius–Clapeyron scaling. This CC-scaling relation breaks down, or even reverts, for very high temperatures. In our study, we verify this reversal using a 60-year period of summer data in Germany. One of the suggested meteorological explanations is limited moisture supply, but our findings indicate that this behavior could also originate from simple undersampling.

Lightning is one of the major threats to multimegawatt wind turbines and a concern for modern aircraft due to the use of lightweight composite materials. Both wind turbines and aircraft can initiate lightning, and very favorable conditions for lightning initiation occur in winter thunderstorms. Moreover, winter thunderstorms are characterized by a relatively high production of very energetic lightning. This paper reviews the different types of lightning interactions and summarizes the well-known winter thunderstorm areas.

Researchers present a percentile-based calibration of the Canadian Forest Fire Weather Index (FWI) System for the United Kingdom (UK), developed from numerical weather prediction data, and evaluate it using historic wildfire records. The Fine Fuel Moisture Code, Initial Spread Index and final FWI component of the FWI system show the greatest predictive skill for UK wildfires. The findings provide useful insights for any future redevelopment of the current operational UK fire danger rating system.

Most climate change impacts manifest in the form of natural hazards. Damage assessment typically relies on damage functions that translate the magnitude of extreme events to a quantifiable damage. In practice, the availability of damage functions is limited due to a lack of data sources and a lack of understanding of damage processes. The study of the characteristics of damage functions for different hazards could strengthen the theoretical foundation of damage functions and support their development and validation.

The destruction caused by tropical cyclone (TC) Pam in March 2015 is considered one of the worst natural disasters in the history of Vanuatu. It has highlighted the need for a better understanding of TC impacts and adaptation in the Southwest Pacific (SWP) region. Therefore, the key aims of this study are to (i) understand local perceptions of TC activity, (ii) investigate impacts of TC activity and (iii) uncover adaptation strategies used to offset the impacts of TCs.

Heat waves and the consequent heat stress of urban populations have a growing relevance in urban risk management and strategies of urban adaptation to climate change. In this context, social science studies on subjective experiencing of heat as stress by urban citizens are a new emerging field. To contribute to the understanding of self-reported subjective heat stress and its major determinants in a daily life perspective, we conducted a questionnaire survey with 323 respondents in Karlsruhe, Germany, after heat waves in July and August 2013.

Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either a fluvial or pluvial flood hazard, studies of a combined fluvial and pluvial flood hazard are hardly available.

The clustering of severe European windstorms on annual timescales has substantial impacts on the (re-)insurance industry. Our knowledge of the risk is limited by large uncertainties in estimates of clustering from typical historical storm data sets covering the past few decades. Eight storm data sets are gathered for analysis in this study in order to reduce these uncertainties.

Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the Damagescanner-Jakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability.