| Issue |
EPJ Web Conf.
Volume 376, 2026
6th International Conference on Recent Advances in Mechanical Engineering and Nanomaterials (ICRAMEN 2026)
|
|
|---|---|---|
| Article Number | 06003 | |
| Number of page(s) | 8 | |
| Section | Recent Advances in Science & Engineering | |
| DOI | https://doi.org/10.1051/epjconf/202637606003 | |
| Published online | 01 July 2026 | |
https://doi.org/10.1051/epjconf/202637606003
Projecting future precipitation in Northern Iraq applying CMIP6 ensembles and LARS-WG model: A case study of Aqra Region
1 Civil Department, College of Engineering, Wasit University, Wasit 52001, Iraq
2 College of Engineering, University of Warith Al-Anbiyaa, Karbala 56001, Iraq
3 Technical Engineering College, Al-Ayen University, Thi-Qar, Iraq
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 1 July 2026
Abstract
This investigation examines the consequences of climate change on the future precipitation patterns in Aqra City, Northern Iraq, using reliable statistical downscaling techniques. The main goal is to match the rainfall on a daily basis until the near future (2021-2040) using LARS-WG 8.0 stochastic weather generator. Calibration and validation were carried out with historical daily precipitation records taken from NASA, for the baseline interval 1985 - 2015. To account for uncertainties synonymous with the model and prospective socioeconomic pathways, ensemble outputs from General Circulation Models (GCMs), part of the CMIP6 initiative, using Shared Socioeconomic Pathways SSP245 and SSP585, were included in the analysis (six GCMs). Validation results show that the LARS-WG framework has a good fidelity in terms of reproduction of statistical signatures of the observed climate, in terms of good correlations in monthly means and standard deviations, as well as the ability to capture the seasonal wet and dry oscillations typical of this region. Forward-looking exhibits different variabilities in precipitation regimes, but exhibits large inter-model coherences in the set of GCMs selected for the analyses.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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