Machine Learning for Climate Change Forecasting Case Studies and Real-World Impact

Authors: Ravi Kumar Perumallapalli

Country: USA

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Abstract: Accurate forecasting techniques are becoming more and more important as the effects of climate change become more widespread. Because machine learning (ML) can process large and complicated environmental datasets, it has become a viable technique for anticipating trends in climate change. This study examines several case studies—from urban energy performance to flood risk assessment—where machine learning techniques have been used to forecast climate change and assess their practical implications. Previous studies, such as those on the energy performance of urban buildings on the danger of flood disaster in China's Yangtze River Delta, have shown the efficacy of machine learning in environmental predictions. Used a variety of data sources, including news alerts and internet searches, to demonstrate the value of machine learning in real-time forecasting during the COVID-19 outbreak. Unveiled a deep learning framework for spatiotemporal environmental data prediction, whereas used machine learning models to predict water levels in temperate lakes. Insights on large-scale machine learning systems, emphasizing the difficulties and solutions in practical industrial applications. In this publication, these findings are summarized and a methodology for incorporating machine learning into climate forecasting is proposed. We demonstrate the potential of machine learning to generate increasingly precise climate change projections, supporting international mitigation and adaptation initiatives, by evaluating their achievements and drawbacks.

Keywords: Forecasting climate change, Machine learning, CNN-LSTM Model, Co2 emissions forecasting, Temperature prediction, Deep learning in climate science, Climate prediction accuracy, Real- time climate forecasting.

Paper Id: 231516

Published On: 2020-01-09

Published In: Volume 8, Issue 1, January-February 2020

Cite This: Machine Learning for Climate Change Forecasting Case Studies and Real-World Impact - Ravi Kumar Perumallapalli - IJIRMPS Volume 8, Issue 1, January-February 2020.

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