Climate change impact on short-duration extreme precipitation and intensity–duration–frequency curves over Europe

Abstract

To build future climate-proof water systems and to reduce the failure risk of infrastructure, short-duration extreme precipitation design storms must be updated. However, a robust future projection of such storms on a continental scale has not been presented due to the scarcity of long, high quality sub-daily data both for observations and model simulations. To address this need, we develop current and future precipitation intensity-duration-frequency (IDF) curves for Europe for 0.5-, 1-, 3-, 6-, 12-and 24-hour durations and for different return periods ranging between 1 and 100 years derived from a Generalized Pareto Distribution (GPD). Future IDF curves are developed in the framework of the quantile perturbation downscaling method by applying climate change signals from the EURO-CORDEX RCMs on current IDF curves obtained from high-resolution remote sensing based products. Here we show that rarer sub-daily extreme precipitation events will intensify more than less rare events and that changes may depend on precipitation duration. The frequency of sub-daily extreme precipitation events of 50-and 100-year return periods will be tripled under the high-end RCP8.5 scenario. Such intensification will lead to a substantial uplift (16-27% depending on duration and return period) and steepening (17-25% depending on return period) of the IDF curves under future climate change, calling attention to the vulnerability of the existing water infrastructure systems.

Event-Based Time Distribution Patterns, Return Levels, and Their Trends of Extreme Precipitation across Indus Basin

“…This technique selects the extreme events more rationally instead of considering simply one event each year in the case of maxima method [106] as, in some years, second or higher order extremes might be larger than the annual extremes in other years [107]. The GPD became a well-known technique and has been widely used in the recent studies to deal with extreme events and their return levels [26,31,93,100,[108][109][110][111]. Therefore, the precipitation extremes for the 20 and 50-year return levels are also predicted for the NHPK using GPD.…”

Uncertainty of Rate of Change in Korean Future Rainfall Extremes Using Non-Stationary GEV Model

“…This single value will be the ensemble average no matter what method we take [2,11]. However, as shown in previous studies [10,17] and Figure 4a of this study, the future rainfall extremes estimated by the stationary frequency analysis method using future rainfall data showed a lot of variation depending on which climate model combination was applied. In other words, the inter-model variability was very high.…”

“…In most studies, including those of Hosseinzadehtalaei et al [17] and Kim et al [11], the future rainfall extremes taking into account climate change scenarios are estimated based on the ratio of rainfall quantiles under present climate conditions to rainfall quantiles under future climate conditions (i.e., rate of change). When estimating the rainfall quantile in present or future climate conditions, stationary conditions are generally assumed for each period (e.g., 1980-2010, 2021-2050, and 2071-2100).…”

“…The same goes for the quantification of future rainfall extremes. Hosseinzadehtalaei et al [17] estimated rainfall quantiles from a stationary frequency analysis using the rainfall projection output for the 30 years from 2071 to 2100. They also estimated rainfall quantiles from another stationary frequency analysis using the present-period rainfall simulation output for 30 years from 1971 to 2000.…”

Comparison of statistical downscaling methods for climate change impact analysis on drought

“…CC BY 4.0 License. Van Uytven, 2019;De Niel et al, 2019;Hosseinzadehtalaei et al, 2020). The results of SDMs are, nevertheless, often compromised with bias and limitations due to assumptions and approximations made within each method (Trzaska and Schnarr, 2014;Maraun et al, 2015).…”