Predicting the next decade of sea surface temperatures in the Mediterranean Sea using hybrid deep learning models
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Abstract
The Mediterranean Sea plays a crucial role in regulating regional climate, supporting biodiversity, and sustaining coastal economies, making its temperature an essential factor for environmental stability. This study presents a forecast of sea level temperatures in the Mediterranean Sea for the next 10 years using historical data from the European Centre for Medium-Range Weather Forecasts (ECMWF), spanning from 1940 to 2024. Two hybrid deep learning models, CNN-LSTM and CNN-GRU, are employed to predict future temperature trends. The models are evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) as primary accuracy metrics. The results will provide valuable insights into the potential impacts of climate change on the Mediterranean region’s sea level temperatures, contributing to better understanding and future planning efforts.
Keywords: Climate Change, Forecasting, Mediterranean, Deep Learning, Hybrid Deep Learning
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