Machine Learning Enhances Flood Resilience Measurement  in a Coastal Area – Case Study of Morocco

Satour, N.; Benyacoub, Badreddine; Moçayd, Nabil El; En-Naimani, Zakariae; Niazi, Sarfaraz K.; Kassou, Nadia; Kacimi, Ilias

doi:10.3808/jei.202300497

Cited by 2 publications

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“…The Paris Agreement aims to hold the average increase in global warming to well below 2°C and to pursue efforts to limit it to 1.5°C (Gillett et al, 2021;Zhao et al, 2024). The risks of extreme climate events accompany the trajectory of global warming, with extreme precipitation emerging as a representative consequence, yielding profound impacts (Baydaroğlu et al, 2023;Satour et al, 2023;W. Zhang & Zhou, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Mounting evidence reveals a robust link between human activities and extreme precipitation (Amanatidou et al, 2023;Donat et al, 2016). This link is particularly pronounced for anthropogenic greenhouse gas (GHG) emissions, serving as the primary driver of the observed increases in the intensification of extreme precipitation at the global scale (Satour et al, 2023;Tan et al, 2023). Despite this, time series of extreme precipitation typically manifest small signals and high variability, especially at smaller scales, hindering regional-scale attribution (Baydaroğlu et al, 2023;Sarojini et al, 2016;Solovey et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

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Interactions Between Anthropogenic Greenhouse‐Gas and Aerosol Emissions Will Shape Extreme Precipitations Over the Qinghai‐Tibet Plateau

Tang,

Huang,

et al. 2024

Geophysical Research Letters

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Attributing intensification extreme precipitation to anthropogenic factors on the regional scale is challenging, given the large fluctuations and the complexity of quantifying interactions among these anthropogenic factors. Here, we propose a new variance‐based method to investigate the roles of human‐induced greenhouse gas (GHG), aerosol (AER), and their interactions (GA) in shaping extreme precipitation on the Qinghai‐Tibet Plateau (QTP) at stational scale. In terms of contribution, GHG has the greatest impact on total wet‐day precipitation and simple daily intensity. In terms of significance, GA, and AER exert significant effects on all 10 extreme indices (P; < 0.05) over 48.3% and 44.8% of all stations, while GHG affects less (25.9%). Overall, GHG is not the only dominant factor, and GA and AER are expected to play vital roles in intensifying extreme precipitation over the QTP under SSP2‐4.5. These findings challenge the conventional insights that GHG is the primary anthropogenic driver of extreme precipitation.

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