Artificial Intelligence Applications in Climate Change Prediction and Management

Mikko Kolehmainen

Artificial Intelligence Applications in Climate Change Prediction and Management

Author(s)	Mikko Kolehmainen
Country	United States
Abstract	Climate change has become one of the most complex global challenges due to increasing temperature variations, extreme weather events, environmental degradation, and uncertainty in climate patterns. Traditional climate prediction and management approaches often depend on statistical models and historical observations, which may have limitations in processing complex environmental interactions and large-scale climate datasets. Artificial intelligence (AI) has emerged as an advanced technological approach capable of improving climate prediction accuracy, environmental analysis, and climate management decision-making. This study examines artificial intelligence applications in climate change prediction and management by analysing their contribution to climate forecasting accuracy, risk detection capability, predictive efficiency, and environmental decision support. The research explores key AI technologies including machine learning algorithms, deep learning models, neural networks, predictive analytics, remote sensing intelligence, and climate data processing systems. A simulation-based analytical framework is developed to compare conventional climate prediction methods with AI-driven approaches using evaluation indicators including prediction accuracy, climate risk identification, forecasting efficiency, and management effectiveness. The findings demonstrate that AI-based climate systems significantly improve climate prediction and management capabilities by enabling advanced data analysis, pattern recognition, and predictive modelling. The results indicate that artificial intelligence provides effective solutions for identifying climate risks, forecasting environmental changes, and supporting proactive climate management strategies. However, successful implementation requires addressing challenges related to data availability, computational requirements, model transparency, infrastructure development, and policy integration.
Keywords	Artificial Intelligence, Climate Change Prediction, Machine Learning, Climate Management, Predictive Analytics, Environmental Intelligence, Climate Modelling
Field	Engineering
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-02

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American International Journal of Research and Innovation

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Artificial Intelligence Applications in Climate Change Prediction and Management

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