An ensemble approach for the analysis of extreme rainfall under climate change in Naples (Italy). Issue 14 (3rd May 2019)

• Record Type: Journal Article
• Authors: Padulano, Roberta; Reder, Alfredo; Rianna, Guido
• Is Part Of: Hydrological processes. Volume 33:Issue 14(2019)
• Page Start: 2020
• Page End: 2036
• Publication Date: 2019-05-03
• Subjects: EURO‐CORDEX -- bias‐correction -- quantile delta mapping -- storm index -- intensity–duration–frequency curves -- growth factor -- early warning system -- generalized extreme value -- ensemble approach; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.13449
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: In the present paper, an ensemble approach is proposed to estimate possible modifications caused by climate changes in the extreme precipitation regime, with the rain gauge Napoli Servizio Idrografico (Naples, Italy) chosen as test case. The proposed research, focused on the analysis of extremes on the basis of climate model simulations and rainfall observations, is structured in several consecutive steps. In the first step, all the dynamically downscaled EURO‐CORDEX simulations at about 12 km horizontal resolution are collected for the current period 1971–2000 and the future period 2071–2100, for the RCP4.5 and the RCP8.5 concentration scenarios. In the second step, the significance of climate change effects on extreme precipitation is statistically tested by comparing current and future simulated data and bias‐correction is performed by means of a novel approach based on a combination of simple delta change and quantile delta mapping, in compliance with the storm index method. In the third step, two different ensemble models are proposed, accounting for the variabilities given by the use of different climate models and for their hindcast performances. Finally, the ensemble models are used to build novel intensity–duration–frequency curves, and their effects on the early warning system thresholds for the area of interest are evaluated.