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Atmospheric Research

Publication date: 2017-01-01
Volume: 200 12
Publisher: Elsevier Science Publishers

Author:

Hosseinzadehtalaei, Parisa
Tabari, Hossein ; Willems, Patrick

Keywords:

Rainfall, IDF, Extremes, Climate change, Climate models, EURO-CORDEX, Science & Technology, Physical Sciences, Meteorology & Atmospheric Sciences, Extreme precipitation, Future IDF curves, Climate model resolution, Quantile perturbation downscaling, Variance decomposition, Uncertainty analysis, REGIONAL CLIMATE MODELS, STATISTICAL DOWNSCALING METHODS, EXTREME PRECIPITATION, RAINFALL EXTREMES, PERFORMANCE, IMPACTS, PROJECTIONS, MANAGEMENT, SCENARIOS, 0299 Other Physical Sciences, 0401 Atmospheric Sciences, 3701 Atmospheric sciences, 3702 Climate change science, 4104 Environmental management

Abstract:

An ensemble of 88 regional climate model (RCM) simulations at 0.11° and 0.44° spatial resolutions from the EURO-CORDEX project is analyzed for central Belgium to investigate the projected impact of climate change on precipitation intensity–duration–frequency (IDF) relationships and extreme precipitation quantiles typically used in water engineering designs. The rate of uncertainty arising from the choice of RCM, driving GCM, and radiative concentration pathway (RCP4.5 & RCP8.5) is quantified using a variance decomposition technique after reconstruction of missing data in GCM ×RCM combinations. A comparative analysis between the historical simulations of the EURO-CORDEX 0.11° and 0.44° RCMs shows higher precipitation intensities by the finer resolution runs, leading to a larger overestimation of the observations-based IDFs by the 0.11° runs. The results reveal that making a temporal stationarity assumption for the climate system may lead to underestimation of precipitation quantiles up to 70% by the end of this century. This projected increase is generally larger for the 0.11° RCMs compared with the 0.44° RCMs. The relative changes in extreme precipitation do depend on return period and duration, indicating an amplification for larger return periods and for smaller durations. The variance decomposition approach generally identifies RCM as the most dominant component of uncertainty in changes of more extreme precipitation (return period of 10 years) for both 0.11° and 0.44° resolutions, followed by GCM and RCP scenario. The uncertainties associated with cross-contributions of RCMs, GCMs, and RCPs play a non-negligible role in the associated uncertainties of the changes.