Climate Change Forecasting Using Time Series Techniques: A Comprehensive Review

Authors

  • Hamid Ghous Department of Computer Science, Australian Scientific and Engineering Solution, Sydney, NSW, Australia
  • Aqsa Malik Vision, Linguistics and Machine Intelligence Research Lab, Multan, Pakistan
  • Zubair Ahmad Vision, Linguistics and Machine Intelligence Research Lab, Multan, Pakistan
  • Uzma Jabeen Vision, Linguistics and Machine Intelligence Research Lab, Multan, Pakistan
  • Majid Khawar Deparment of Computer Science, NFC Institutes of Engineering and Technology Multan, Pakistan

Keywords:

Time Series Techniques, Climate Change Forecasting, Machine Learning, Deep Learning

Abstract

One of the most crucial issues facing the world today is climate change, which substantially impacts ecosystems. It is necessary for stakeholders, policymakers, and academics to make decisions and have efficient adaptation plans to forecast climate change phenomena accurately. Techniques for examining time give smart data for getting trends, patterns, and future environment projections. This review paper provides a detailed overview of 42 research papers constructed on time-based analysis methods to forecast climate change. The picked publications cover a wide range of subjects, procedures, datasets, and modeling approaches utilized in environmental change research. This survey tries to shed light on the ongoing status of environmental change anticipating and suggests potential ways for additional examination by investigating, as far as possible significant findings of these investigations.

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Published

2025-04-22