Ida Bülow Gregersen

Potential future increase in extreme one-hour precipitation events over Europe due to climate change.

In this study the potential increase of extreme precipitation in a future warmer European climate has been examined. Output from the regional climate model (RCM) HIRHAM4 covering Europe has been analysed for two periods, a control period 1961-1990 and a scenario 2071-2100, the latter following the IPCC scenario A2. The model has a resolution of about 12 km, which is unique compared with existing RCM studies that typically operate at 25-50 km scale, and make the results relevant to hydrological phenomena occurring at the spatial scale of the infrastructure designed to drain off rainfall in large urban areas. Extreme events with one- and 24-hour duration were extracted using the Partial Duration Series approach, a Generalized Pareto Distribution was fitted to the data and T-year events for return periods from 2 to 100 years were calculated for the control and scenario period in model cells across Europe. The analysis shows that there will be an increase of the intensity of extreme events generally in Europe; Scandinavia will experience the highest increase and southern Europe the lowest. A 20 year 1-hour precipitation event will for example become a 4 year event in Sweden and a 10 year event in Spain. Intensities for short durations and high return periods will increase the most, which implies that European urban drainage systems will be challenged in the future.

Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems

Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems provides a state-of-the-art overview of existing methodologies and relevant results related to the assessment of the climate change impacts on urban rainfall extremes as well as on urban hydrology and hydraulics. This overview focuses mainly on several difficulties and limitations regarding the current methods and discusses various issues and challenges facing the research community in dealing with the climate change impact assessment and adaptation for urban drainage infrastructure design and management. ISBN: 9781780401256 (Print) ISBN: 9781780401263 (eBook)

Regional frequency analysis of short duration rainfall extremes using gridded daily rainfall data as co-variate

A regional partial duration series (PDS) model is applied for estimation of intensity duration frequency relationships of extreme rainfalls in Denmark. The model uses generalised least squares regression to relate the PDS parameters to gridded rainfall statistics from a dense network of rain gauges with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour, the mean intensity is significantly correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark, a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both increases and decreases are seen. A subsample analysis is conducted to evaluate the impacts of non-stationarities in the rainfall data. The regional model includes the non-stationarities as an additional source of uncertainty, together with sampling uncertainty and uncertainty caused by spatial variability.

Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change

Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

Climate Change Impacts on Rainfall Extremes and Urban Drainage: a State-of- the-Art Review

Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review (Willems et al., 2012) considers the following aspects: - Analysis of long-term historical trends due to anthropogenic climate change; - Analysis of long-term future trends due to anthropogenic climate change; - Implications for urban drainage infrastructure design and management. A summary is provided in this paper.

A regional and nonstationary model for partial duration series of extreme rainfall

Regional extreme value models for estimation of extreme rainfall intensities are widely applied, but their underlying assumption of stationarity is challenged. Many recent studies show that the rainfall extremes worldwide exhibit a non-stationary behavior. This paper presents a spatio-temporal model of extreme rainfall. The framework is built on a Partial Duration Series approach with a non-stationary, regional threshold value. The model is based on Generalized Linear Regression solved by Generalized Estimation Equations. It allows a spatial correlation between the stations in the network and accounts furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by Generalized Least Squares are used to validate and discuss the results of the full spatio-temporal model. The model is applied on data from a large Danish rain gauge network for four durations ranging from 10 minutes to 24 hours. The observation period differs between stations, and the number of stations with more than 10 years of observations has increased over the years. A spatio-temporal model for the threshold is suggested, applying the Mean Annual Precipitation and time as the explanatory variables in the regional and temporal domain, respectively. Further analysis of Partial Duration Series with non-stationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found to be constant. This article is protected by copyright. All rights reserved.