AI in Climate Prediction: Using Machine Learning to Model Extreme Weather Events

Kartikkumar Ashokbhai Pandya

doi:10.71097/IJSAT.v16.i4.8912

AI in Climate Prediction: Using Machine Learning to Model Extreme Weather Events

Author(s)	Mr. Kartikkumar Ashokbhai Pandya
Country	United States
Abstract	This dissertation explores the growing relevance of more frequent and intense extreme weather events think floods, droughts, and hurricanes driven by climate change. It does so through the development and evaluation of some pretty advanced machine learning models, specifically convolutional neural networks (CNNs) and long short-term memory networks (LSTMs). The focus is on using time-series data from satellites and sensors. Essentially, this work demonstrates that these machine learning models can predict extreme weather events with noticeably better accuracy compared to older, more traditional methods. In fact, we're seeing accuracy improvements of up to around 30% in predicting floods and droughts. These results really underscore the need you might even say the urgency for these predictive capabilities. They are critical for supporting timely responses to public disasters, especially considering the serious public health and safety risks that extreme weather poses to those populations that are already vulnerable. Beyond just disaster preparedness and response, machine learning offers some truly transformative prospects as the climatology community works to protect the public. Machine learning can actually enhance public health by giving healthcare providers and the wider community insights into potential, near-term extreme weather events. The dissertation proposes that these machine learning methods can sharpen immediate predictions, and pave the way for a complete transition to a "data-driven decision-making" (DDDM) approach when it comes to climate resiliency strategies. This really highlights how physical technologies intersect with social relevance as we try to tackle the diverse challenges that climate change throws our way. Ultimately, what we have here is a framework that points toward future research into refining predictive models, and forging broader collaborations across different academic fields. The goal is to lessen the burden of extreme weather events on public health around the world.
Keywords	Ai, Climate Prediction, Machine Learning, Wether, Temperature
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-10-26
DOI	https://doi.org/10.71097/IJSAT.v16.i4.8912
Short DOI	https://doi.org/g98ndb

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AI in Climate Prediction: Using Machine Learning to Model Extreme Weather Events

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