Supervisor
Dr. Muhammed Iqbal
Programme
MSc in Data Analytics
Subject
Computer Science
Abstract
The Atlantic Meridional Overturning Circulation (AMOC) plays a key role in regulating climate across the North Atlantic, including Ireland. This study analyses AMOC variability using RAPID, ODYSSEA, and MÉRA datasets to examine relationships between subsurface ocean conditions, sea surface temperatures, and air temperature. ARIMA/SARIMA models identify trends and correlations, while a Long Short-Term Memory (LSTM) neural network forecasts future climate changes. Results show rising sea surface temperatures, moderate links between salinity and temperature, and seasonal air temperature patterns with a slight upward trend. The LSTM model outperforms traditional statistical approaches in capturing complex patterns, highlighting the value of machine learning for climate prediction and adaptation planning.
Date of Award
2025
Full Publication Date
2025
Access Rights
open access
Document Type
Capstone Project
Resource Type
thesis
Recommended Citation
Whyte, C.
(2025) Predictive Analysis of Atlantic Meridional Overturning Circulation AMOC and Its Climatic Implications on Ireland Using Advanced Machine Learning Techniques. CCT College Dublin.
DOI: https://doi.org/10.63227/652.299.116