Assessment of Climate Change Scenarios Uncertainty in Estimating Probable Maximum Precipitation (PMP) in the Caspian Sea Coastal Provinces

Abstract

Objective: One of the most critical meteorological variables influenced by climate change is the Probable Maximum Precipitation (PMP), a key parameter in the design of high-risk water infrastructures such as dams. This study assesses the impacts of climate change on PMP across the coastal provinces of the Caspian Sea (including synoptic stations in Anzali, Rasht, Ramsar, Babolsar, Qaemshahr, and Gorgan). Methods: To generate climate change scenarios for two periods (2025-2054 and 2055-2084), the outputs of 18 AOGCM models and three greenhouse gas emission scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) were used. To reduce uncertainties in the AOGCM outputs, two methods-weighted averaging and probabilistic analysis-were employed. In the weighted averaging method, AOGCM models were ranked and weighted based on their accuracy in simulating precipitation of baseline period. In the probabilistic method, probability distributions were applied to generate precipitation scenarios at probability levels of 0.5, 0.75, and 0.90.Results: The findings revealed significant uncertainty among AOGCM outputs and emission scenarios in estimating PMP, indicating that PMP changes in the studied stations do not follow a consistent pattern. However, in the weighted averaging approach, PMP is generally expected to decrease in the first period and show a slight increase in the second period.Conclusions: For designing high-risk structures, it is recommended to utilize the results from the critical scenario with a 0.90 probability level. In this case, the increase in PMP due to climate change varies from approximately 12% at Qaemshahr station to a maximum of 48% at Gorgan station.

Keywords

• climate change
• maximum probable precipitation
• aogcm models
• greenhouse gases