Intelligent Earth: AI As A Catalyst For Climate Action

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 4 | 01 | Page :
    By

    Mr. Achinta Kumar Palit,

  • Mr. Abhishek Panda,

  1. Asst. Prof., Dept. Of CSE, Gandhi Institute Of Excellent Technocrats, Bhubaneswar, odissa, India
  2. B. Tech, Computer Science & Engineering Gandhi Institute of Excellent Technocrats, odissa, India

Abstract

Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small — scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes and enhancements to these approaches. By identifying hidden patterns, nonlinear relationships, and trends within massive streams of data, AI supports the development of hybrid frameworks that blend empirical observations with physics — based simulations, ultimately improving predictive precision and spatial granularity. The fusion of AI with satellite remote sensing technologies has significantly strengthened the capacity for continuous, automated monitoring of environmental change. These systems can rapidly detect and quantify phenomena such as deforestation, glacial retreat, biodiversity loss, urban heat island effects, air pollution dynamics, and fluctuations in sea surface temperatures. In addition, AI — driven forecasting and early warning platforms are enhancing preparedness for extreme weather events, including hurricanes, floods, droughts, and wildfires, enabling quicker response times and more informed disaster risk management strategies. Despite its transformative promise, integrating AI into climate research is not without obstacles. Persistent issues related to data quality, representativeness, algorithmic bias, interpretability, and reproducibility require careful attention. Effective progress also depends on strong cross-disciplinary collaboration among climate scientists, computer engineers, policymakers, and local stakeholders. Ethical considerations, transparency in model development, and equitable access to technological benefits remain central to responsible deployment. As the scale and urgency of climate challenges intensify, AI is emerging as a critical enabler for evidence-based policymaking, efficient resource allocation, and long — term sustainability planning, reshaping how humanity understands  and responds to a rapidly changing planet.

Keywords: Artificial Intelligence (AI), Environmental Monitoring, Machine Learning, Deep Learning, Remote Sensing

How to cite this article:
Mr. Achinta Kumar Palit, Mr. Abhishek Panda. Intelligent Earth: AI As A Catalyst For Climate Action. International Journal of Environmental Noise and Pollution Control. 2026; 04(01):-.
How to cite this URL:
Mr. Achinta Kumar Palit, Mr. Abhishek Panda. Intelligent Earth: AI As A Catalyst For Climate Action. International Journal of Environmental Noise and Pollution Control. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijenpc/article=2026/view=238380


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Ahead of Print Subscription Review Article
Volume 04
01
Received 28/01/2026
Accepted 18/02/2026
Published 10/03/2026
Publication Time 41 Days
60

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