Sarkar et al. (2026) A Review on Smart Weather Prediction Using Machine Learning Approaches

Identification

• Journal: Lecture notes in networks and systems
• Year: 2026
• Date: 2026-01-01
• Authors: Kaushik Sarkar, Abira Sengupta, Sarbani Palit, Rajat Kumar Pal
• DOI: 10.1007/978-981-96-8998-9_4

Research Groups

• University of Calcutta, Kolkata, West Bengal, India
• Bengal Institute of Technology, Techno India Group, Kolkata, West Bengal, India
• University of Otago, Dunedin, New Zealand
• Indian Statistical Institute, Kolkata, West Bengal, India

Short Summary

This review paper provides a chronological overview of the integration of Machine Learning (ML) into weather and climate modeling, highlighting its transformative impact on prediction accuracy and reliability. It serves as a foundational guide by explaining key ML concepts, methodologies, ethical considerations, and future research directions in this field.

Objective

• To provide a comprehensive review of the evolution, applications, methodologies, ethical considerations, and future directions of Machine Learning in weather and climate modeling.

Study Configuration

• Spatial Scale: Not applicable for a literature review.
• Temporal Scale: Not applicable for a literature review; covers the chronological evolution of ML applications in weather and climate modeling from early studies to recent advancements.

Methodology and Data

• Models used: Not applicable for a review paper, as this is a literature review of models used by others.
• Data sources: Literature review of existing scientific papers, conference proceedings, and academic publications focusing on Machine Learning applications in weather prediction.

Main Results

• The integration of Machine Learning has significantly improved the accuracy and reliability of weather forecasts compared to traditional methods.
• The review chronologically traces the development and application of various ML techniques in weather and climate modeling.
• It provides concise explanations of fundamental ML concepts, diverse methodologies, and ethical considerations pertinent to weather prediction.
• The paper identifies and explores promising avenues for future research in the domain of ML-enhanced weather and climate forecasting.

Contributions

• Offers a foundational guide for researchers and model developers seeking to understand and apply ML in weather and climate modeling.
• Provides a structured, chronological overview of ML's evolution in this field, from early studies to the latest advancements.
• Synthesizes key ML concepts, methodologies, and addresses ethical considerations, which are crucial for responsible development.
• Highlights unexplored areas and promising directions for future research, stimulating further innovation.

Funding

• Host institutions provided the necessary computing environment and supported the authors' work.

Citation

@article{Sarkar2026Review,
  author = {Sarkar, Kaushik and Sengupta, Abira and Palit, Sarbani and Pal, Rajat Kumar},
  title = {A Review on Smart Weather Prediction Using Machine Learning Approaches},
  journal = {Lecture notes in networks and systems},
  year = {2026},
  doi = {10.1007/978-981-96-8998-9_4},
  url = {https://doi.org/10.1007/978-981-96-8998-9_4}
}