Are Türkiye’s Semi-Enclosed Seas Warming 1.5–2 Times Faster Than CMIP6 Global Projections?

Semi-enclosed seas are particularly sensitive to regional climate forcing because their exchange with the open ocean is limited. Despite this sensitivity, the magnitude of their warming relative to global climate model projections remains insufficiently constrained. This study examines both historical and future sea surface temperature (SST) changes in the Mediterranean, Aegean, Marmara, and Black Seas surrounding Türkiye using a hybrid framework that integrates in-situ observations, satellite reanalysis, and machine learning techniques.

More than three decades (1993–2023) of monthly coastal SST records from 21 stations are analysed together with Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis data. Linear trend analysis reveals statistically significant warming across all basins, with observed SST increases reaching approximately 2.0 °C since 1993. When placed in a global context, these regional warming rates are approximately 1.5–2 times higher than the CMIP6 ensemble mean global ocean warming over a comparable period.

Future SST evolution is explored using a Long Short-Term Memory (LSTM) model trained on bias-corrected SST time series and supplemented with large-scale climate indices, namely ENSO and NAO. Comparison with observations shows that the model reproduces SST variability with a high level of agreement (R² > 0.9; RMSE ≈ 0.4–0.6 °C), while the projected trajectories remain physically plausible under both SSP2-4.5 and SSP5-8.5 scenarios. The projections point to a persistent warming signal throughout the 21st century, with the strongest increases concentrated in the Mediterranean and Aegean Seas.

Taken together, these results suggest that SST warming in Türkiye’s semi-enclosed seas is higher than coarse-resolution CMIP6 ensemble mean global ocean warming estimates. This finding emphasises the importance of regionally resolved observations and data-driven analyses for coastal climate assessment. The hybrid framework applied here offers a scalable approach for monitoring semi-enclosed marine systems and for informing climate-related decision-making at regional scales.