Evaluation of future temperature and precipitation projections in Morocco using the ANN-based multi-model ensemble from CMIP6

Gumus, Veysel; El Moçayd, Nabil; Seker, Mehmet; Seaid, Mohammed

Abstract

In present study, values of minimum temperature, maximum temperature and precipitation at 27 observation stations in Morocco are used to implement an artificial neural network based downscaling approach in order to simulate regional climate and to investigate the impact of climate change on the country under different scenarios. For this purpose, the best models representing the country among the 15 GCMs within the scope of the CMIP6 are first identified. Then, using the artificial neural network based statistical downscaling method, a multi-model ensemble is created for each climate parameter. Following the performance evaluation based on different statistical metrics and their aggregated values, a good agreement between the observed and the predicted variables is achieved. This allows us to assess future projections of temperature and precipitation following two climate scenarios, namely the SSP2-4.5 and SSP5-8.5. Spatial as well as temporal changes are evaluated for three different time periods namely, 2025–2049, 2050–2074 and 2075–2100. Both scenarios indicate that an important increase of the minimum and maximum temperatures is expected and it can reach up to 5 °C by the end of the century in some regions of the country. Seasonal variability has also been addressed here under climate change scenarios, and consistent variations with annual changes are also reported during each season, except for the summer where the increase barely goes beyond 1.5 °C. The current analysis also includes the variation of precipitation at both seasonal and annual timescales. The country is likely to experience an important drought during the upcoming years, reaching a decrease of roughly 30% and 50% each year respectively, under the SSP2-4.5 and SSP5-8.5 scenarios by the end of the century. This change is also consistent over the seasons, especially during fall, winter and spring seasons, when Morocco receives its major amount of precipitation.

Citation

Gumus, V., El Moçayd, N., Seker, M., & Seaid, M. (2023). Evaluation of future temperature and precipitation projections in Morocco using the ANN-based multi-model ensemble from CMIP6. Atmospheric Research, 292, Article 106880. https://doi.org/10.1016/j.atmosres.2023.106880

• Journal Article Type: Article
• Acceptance Date: Jun 14, 2023
• Online Publication Date: Jun 26, 2023
• Publication Date: Sep 1, 2023
• Deposit Date: Nov 9, 2023
• Publicly Available Date: Jun 27, 2024
• Journal: Atmospheric Research
• Print ISSN: 0169-8095
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 292
• Article Number: 106880
• DOI: https://doi.org/10.1016/j.atmosres.2023.106880
• Public URL: https://durham-repository.worktribe.com/output/1903550