Evaluation of the capability of regional climate models in reproducing the temporal clustering in heavy precipitation over Europe

Yang, Zhiqi; Villarini, Gabriele; Scoccimarro, Enrico

doi:10.1016/j.atmosres.2022.106027

Cited by 3 publications

(1 citation statement)

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“…The scalability of continental data, when properly interpreted, forms a powerful tool for water managers, who are often operating in data scarce settings. The Coordinated Regional Downscaling Experiment (CORDEX) program, which is a new leader in the climate project of the European Union that is sponsored by the World Climate Research Program (WCRP), aims at developing an improved framework for generating regional-scale climate projections for impact assessment, and it has been widely implemented worldwide, especially in the Eastern Mediterranean context for climatological studies where temporal clustering and precipitation trends are commonly analyzed [8,9]. The application of many global and regional climate models in CORDEX has helped to characterize the strength and the weaknesses of several regional climate models in terms of their climate projection capabilities for the selected basins [10,11].…”

Section: Introductionmentioning

confidence: 99%

Streamflow Estimation through Coupling of Hieararchical Clustering Analysis and Regression Analysis—A Case Study in Euphrates-Tigris Basin

Guzey,

Onoz

2023

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In this study, the resilience of designed water systems in the face of limited streamflow gauging stations and escalating global warming impacts were investigated. By performing a regression analysis, simulated meteorological data with observed streamflow from 1971 to 2020 across 33 stream gauging stations in the Euphrates-Tigris Basin were correlated. Utilizing the Ordinary Least Squares regression method, streamflow for 2020–2100 using simulated meteorological data under RCP 4.5 and RCP 8.5 scenarios in CORDEX-EURO and CORDEX-MENA domains were also predicted. Streamflow variability was calculated based on meteorological variables and station morphological characteristics, particularly evapotranspiration. Hierarchical clustering analysis identified two clusters among the stream gauging stations, and for each cluster, two streamflow equations were derived. The regression analysis achieved robust streamflow predictions using six representative climate variables, with adj. R2 values of 0.7–0.85 across all models, primarily influenced by evapotranspiration. The use of a global model led to a 10% decrease in prediction capabilities for all CORDEX models based on R2 performance. This study emphasizes the importance of region homogeneity in estimating streamflow, encompassing both geographical and hydro-meteorological characteristics.

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Section: Introductionmentioning

confidence: 99%