Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 106648 10.2205/2025ES001075 xxxhmn Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ” What SSP Global Climate Change Scenario is the Caspian Sea Region Following? Part 1: Air Temperature Analysis What SSP Global Climate Change Scenario is the Caspian Sea Region Following? Part 1: Air Temperature Analysis https://orcid.org/0000-0002-3363-091X Бочаров Александр Вячеславович Bocharov Aleksander Vyacheslavovich https://orcid.org/0000-0001-7441-5055 Костяной Андрей Геннадьевич Kostianoy Andrey Gennad'evich https://orcid.org/0000-0002-4976-7136 Лебедев Сергей Анатольевич Lebedev Sergey Anatol'evich

доктор физико-математических наук;

doctor of physical and mathematical sciences;

 https://orcid.org/0009-0008-6972-8805 Коломеец Людмила И. Kolomeec Lyudmila I. https://orcid.org/0000-0002-5562-7156 Кравченко Павел Н. Kravchenko Pavel N. Тверской государственный университет Tver Stare University Институт океанологии имени П. П. Ширшова РАН Россия Shirshov Institute of Oceanology, Russian Academy of Sciences Russian Federation Геофизический центр Российской академии наук Россия Geophysical Center, Russian Academy of Sciences Russian Federation Майкопский государственный технологический университет Россия Maykop State Technological University Russian Federation Институт океанологии им. П.П. Ширшова РАН P.P.Shirshov Institute of Oceanology of the Russian Academy of Science Геофизический центр Российской академии наук Россия Geophysical Center, Russian Academy of Sciences Russian Federation Майкопский государственный технологический университет Россия Maykop State Technological University Russian Federation Московский университет имени С. Ю. Витте Россия S. Yu. Witte Moscow University Russian Federation Геофизический центр Российской Академии Наук Россия Geophysical Center of Russian Academy of Sciences Russian Federation Майкопский государственный технологический университет Maikop State Technological University Национальный исследовательский университет «МИЭТ» National Research University of Electronic Technology Институт океанологии имени П. П. Ширшова РАН Россия Shirshov Institute of Oceanology, Russian Academy of Sciences Russian Federation Институт радиолокационной метеорологии Россия Institute of Radar Meteorology Russian Federation Санкт-Петербургский государственный университет Россия Saint Petersburg State University Russian Federation Российский государственный гидрометеорологический университет Россия Russian State Hydrometeorological University Russian Federation Главная геофизическая обсерватория имени Воейкова Россия The Voeikov Main Geophysical Observatory Russian Federation Институт океанологии имени П. П. Ширшова РАН Россия Shirshov Institute of Oceanology, Russian Academy of Sciences Russian Federation Московский университет имени С. Ю. Витте Россия S. Yu. Witte Moscow University Russian Federation 10 12 2025 10 12 2025 25 6 ES6006 10 09 2025 10 11 2025 https://rjes.ru/en/nauka/article/106648/view

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 (𝑅2), 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.

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 (𝑅2), 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.

 Caspian Sea air temperature weather stations SSP CMIP6 global climate models Caspian Sea air temperature weather stations SSP CMIP6 global climate models The research was done with the support of the RSF Grant 23-77- 00027 “Investigation of the climate variability of thermo-hydrodynamic regime of the Caspian Sea based on remote sensing data”, https://rscf.ru/en/project/23-77-00027/. The research was done with the support of the RSF Grant 23-77- 00027 “Investigation of the climate variability of thermo-hydrodynamic regime of the Caspian Sea based on remote sensing data”, https://rscf.ru/en/project/23-77-00027/.

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