Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

Abstract

Abstract. Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.

Comparison of the impacts of urban development and climate change on exposing European cities to pluvial flooding

“…Several empirical and theoretical methods have been developed to describe infiltration characteristics during precipitation of varying intensities, these being the key engines controlling overland run-off generation in hydrological models (Tomicic, 2015). Some of the most widely applied methods include Horton's equation, the Green-Ampt method and the Soil Conservation Service method (Horton, 1933;Green and Ampt, 1911;USDA, 1986).…”

“…Extreme value analyses are carried out for both present-day (1986-2005) and future (2081-2100) time slices for maximum hourly precipitation (within one day) to estimate the intensities for return periods of 5 to 100 years (RP 5, RP 10, RP 20, RP 50 and RP 100). The extreme value series are derived from the two time slices using a partial duration series (PDS) based on an average of three extreme events per year, following Sunyer et al (2015b). A generalized Pareto distribution (GPD) is then fitted to the derived extreme value series to estimate the intensities for different return periods.…”

“…The impact of climate change on extreme precipitation intensities is represented using a change factor (CF) methodology, i.e. by estimating the relative difference between climate model outputs (extreme precipitation intensities) for future and present-day conditions respectively (Willems et al, 2012;Sunyer et al, 2015b). Extreme value analyses are carried out for both present-day (1986-2005) and future (2081-2100) time slices for maximum hourly precipitation (within one day) to estimate the intensities for return periods of 5 to 100 years (RP 5, RP 10, RP 20, RP 50 and RP 100).…”

Contributions of different bias‐correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes

“…We then conducted the three-way analysis of variance (ANOVA) with simple interactions (RCPxGCM, RCPxBC, and GCMxBC) for each of two 40 year periods according to earlier work [Bürger et al, 2013;Sunyer et al, 2015]. The 40 year periods were 2021-2060 and 2061-2100.…”

Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

“…Hydrological applications of climate change impact analysis often assume that the precipitation change factors, defined as the relative change from historical to future climate conditions, can be obtained from GCM or RCM simulations and applied for impact analysis at finer spatial scales. This is the case for any delta change or perturbation based statistical downscaling method (e.g., Ntegeka et al, 2014;Sunyer et al, 2015). In this study, the validity of this hypothesis is investigated by comparing the climate change signals between the high and coarse scale resolution models.…”