Projections patterns of precipitation concentration under climate change scenarios

Saeideh Ashrafi, Ali Reza Karbalaee () and Muhammad Kamangar
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Saeideh Ashrafi: Zanjan University
Ali Reza Karbalaee: Kharazmi University
Muhammad Kamangar: Zanjan University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 5, No 31, 4775-4788

Abstract: Abstract Precipitation is the most important climate element in supplying Iran’s water resources. Its regular temporal distribution will guarantee the sustainability of water resources. Estimating precipitation behavior in near future will improve managing water resources. Therefore, the current study aimed to examine precipitation regulation in near future (2021–2040). To this end, five models–namely GFDL-ESM4, MPI-ESM1-2-HR, IPSL-CM6A-LR, MRI-ESM2, and UKESM1-0-LL–along with the data of 95 synoptic stations were used. Upon estimating precipitation by the use of these models, the estimated data were ensemble using a multi-model ensemble model, which was based on the correlation-weighted average. Assessing the estimation error indicated the reduction of error rate in the ensemble data. Precipitation concentration index (PCI), precipitation concentration period (PCP), and precipitation concentration degree (PCD) were used to study precipitation regulation in near future. The results suggested more precipitation regulation in the north, northwest, and northeast of Iran, while more precipitation concentration was observed in southern parts of Iran. The precipitation concentration in southern parts of Iran indicates lower precipitation regulation in this area.

Keywords: Precipitation concentration; Near future; Ensemble model; Iran (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06403-9

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