What SSP Global Climate Change Scenario is the Caspian Sea Region Following? Part 1: Air Temperature Analysis

Authors:
Open Access
Publisher website
Google Scholar
Abstract
The paper’s aim is to study the impact of global and regional climate change on the state of the Caspian Sea. Determining the most probable climate scenarios for different coastal zones is an important step in predicting the change in the Caspian Sea level and developing plans for the region's adaptation to future climate change. This study assessed the Shared Socioeconomic Pathways (SSP) climate scenarios obtained using the CMIP6 global climate models (GCMs) by comparing the simulated data with actual measurements of surface air temperature (tas) at 72 weather stations in a 200-km buffer zone of the Caspian Sea. The analysis covered the period from 2015 to 2025. The research focuses on air temperature as the most reliably predicted parameter. The study used four main SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) calculated based on six climate models (AWI-CM-1-1-MR, CMCC-CM2-SR5, CNRM-CM6-1-HR, EC-Earth3, MPI-ESM1-2-HR and INM-CM5-0). The quality of the modeling was assessed using a number of indicators: mean error (ME), correlation coefficient (r), coefficient of determination ( 2), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE) and Kling–Gupta efficiency (KGE). The results showed a high degree of agreement between the models and observations for temperature, with correlation coefficients ranging from 0.85 to 0.96. However, systematic biases are observed (from −12.9 to +6.5 °C), with modeled data generally overestimated for lowland areas and underestimated for mountainous areas. The choice of the “best” SSP scenario varies depending on the metric used: based on RMSE and NSE, the most consistent with the actual mean temperature data (2015–2025) is the SSP5-8.5 scenario, while based on KGE, the SSP3-7.0 scenario better reproduces the variability and structure of the time series.

This publication has 13 references indexed in Scilit: