Weighted multi-model ensemble projection of extreme precipitation in the Mediterranean region using statistical downscaling

Keupp, Luzia; Hertig, Elke; Kaspar-Ott, Irena; Pollinger, Felix; Ring, Christoph; Paeth, Heiko; Jacobeit, Jucundus

doi:10.1007/s00704-019-02851-7

Cited by 8 publications

(10 citation statements)

References 83 publications

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“…An infinite number of performance metrics can be defined: quality assessment metrics such as correlation, root mean square error, and bias for example (Baumberger et al, 2017 andCardoso et al 2019), spatial performance assessment metrics such as SPAtial EFficiency metric (SPAEF) or Fractions skill score (FSS) (Ahmed et al 2019;Koch et al 2018) or any other quality scores comparing the model to observations. However, the choice of an appropriate performance metric is quite challenging (Keupp et al 2019;Knutti et al 2010Knutti et al , 2018Weigel et al 2010).…”

Section: Discussionmentioning

confidence: 99%

“…This relationship (usually established through some form of regression across models) can then be used to estimate a constrained projection that is relatively independent of the underlying models (Boé et al 2009;Cox et al 2013;Mahlstein et al 2012). This method is, however, highly susceptible to the quality of the observed data, the understanding of the physical processes, and sometimes the subjective decisions of the researcher (Keupp et al 2019). As shown in Caldwell et al (2018), recent studies using emergent constraints on equilibrium climate sensitivity have pointed out several limitations of this method.…”

Section: Discussionmentioning

confidence: 99%

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Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco

et al. 2021

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Internal variability, multiple emission scenarios, and different model responses to anthropogenic forcing are ultimately behind a wide range of uncertainties that arise in climate change projections. Model weighting approaches are generally used to reduce the uncertainty related to the choice of the climate model. This study compares three multi-model combination approaches: a simple arithmetic mean and two recently developed weighting-based alternatives. One method takes into account models’ performance only and the other accounts for models’ performance and independence. The effect of these three multi-model approaches is assessed for projected changes of mean precipitation and temperature as well as four extreme indices over northern Morocco. We analyze different widely used high-resolution ensembles issued from statistical (NEXGDDP) and dynamical (Euro-CORDEX and bias-adjusted Euro-CORDEX) downscaling. For the latter, we also investigate the potential added value that bias adjustment may have over the raw dynamical simulations. Results show that model weighting can significantly reduce the spread of the future projections increasing their reliability. Nearly all model ensembles project a significant warming over the studied region (more intense inland than near the coasts), together with longer and more severe dry periods. In most cases, the different weighting methods lead to almost identical spatial patterns of climate change, indicating that the uncertainty due to the choice of multi-model combination strategy is nearly negligible.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco

et al. 2021

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“…The Mediterranean precipitations result from the interaction of dynamic and thermodynamic processes (Keupp et al 2019 ). Therefore, common predictors of reanalysis were determined from the studies by Chen et al ( 2010 ), Nasseri et al ( 2013 ), Beecham et al ( 2014 ), Bettolli and Penalba ( 2018 ), Yang et al ( 2018 ), Keupp et al ( 2019 ), and Jafarzadeh et al ( 2021 ) that achieved successful results in predicting daily and heavy precipitations (Table 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…And therefore, climate change will impact local or global precipitation and hydrological regime (IPCC 2013 ; Rashid et al, 2015 ). The Mediterranean region, including Turkey, is among the areas that will be most affected by climate change (Diffenbaugh and Giorgi 2012 ; Keupp et al 2019 ; IPCC 2021 ). It is necessary to develop an effective policy for analyzing and understanding the current and possible future climate changes and adaptation to climate change (Noor et al 2020 ).…”

Section: Introductionmentioning

confidence: 99%

“…Besides, the choice of predictors is also essential in affecting heavy precipitation (Keupp et al 2019 ). The Susurluk Basin in Turkey, having mountain and semi-arid Mediterranean climates, was chosen as the study area because the interplay of dynamic and thermodynamic processes has given rise to the Mediterranean precipitations reported by Keupp et al ( 2019 ). The importance of variable selection for the SD models is even more significant in the Susurluk Basin.…”

Section: Introductionmentioning

confidence: 99%

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Daily precipitation performances of regression-based statistical downscaling models in a basin with mountain and semi-arid climates

Şan

Nacar

Kankal

et al. 2022

Stoch Environ Res Risk Assess

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The impacts of climate change on current and future water resources are important to study local scale. This study aims to investigate the prediction performances of daily precipitation using five regression-based statistical downscaling models (RBSDMs), for the first time, and the ERA-5 reanalysis dataset in the Susurluk Basin with mountain and semi-arid climates for 1979–2018. In addition, comparisons were also performed with an artificial neural network (ANN). Before achieving the aim, the effects of atmospheric variables, grid resolution, and long-distance grid on precipitation prediction were holistically investigated for the first time. Kling-Gupta efficiency was modified and used for holistic evaluation of statistical moments parameters at precipitation prediction comparison. The standard triangular diagram, quite new in the literature, was also modified and used for graphical evaluation. The results of the study revealed that near grids were more effective on precipitation than single or far grids, and 1.50° × 1.50° resolution showed similar performance to 0.25° × 0.25° resolution. When the polynomial multivariate adaptive regression splines model, which performed slightly higher than ANN, tended to capture skewness and standard deviation values of precipitations and to hit wet/dry occurrence than the other models, all models were quite well able to predict the mean value of precipitations. Therefore, RBSDMs can be used in different basins instead of black-box models. RBSDMs can also be established for mean precipitation values without dry/wet classification in the basin. A certain success was observed in the models; however, it was justified that bias correction was required to capture extreme values in the basin. Supplementary Information The online version contains supplementary material available at 10.1007/s00477-022-02345-5.

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Spatiotemporal analysis of transition probabilities of wet and dry days under SSPs scenarios in the semi-arid Susurluk Basin, Türkiye

Şan,

Nacar,

Kankal

et al. 2024

Science of The Total Environment

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Weighted multi-model ensemble projection of extreme precipitation in the Mediterranean region using statistical downscaling

Cited by 8 publications

References 83 publications

Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco

Changes in mean and extreme temperature and precipitation events from different weighted multi-model ensembles over the northern half of Morocco

Daily precipitation performances of regression-based statistical downscaling models in a basin with mountain and semi-arid climates

Spatiotemporal analysis of transition probabilities of wet and dry days under SSPs scenarios in the semi-arid Susurluk Basin, Türkiye

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