article · 2025

Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction

Manik Rakhra, Harjeet Kaur, Sanjeev Kumar, Tiyas Sarkar, Amanpreet Singh, Sourav Kumar

Cited by 0Abstract and details only

Abstract

The research investigates the tricky field of meteorological forecasting on binary classification to forecast the occurrence of snow. High-level machine learning approaches such as Logistic Regressions, Support Vector Machine (SVM), and Decision Tree classifiers are applied towards the modelling and decode latent patterns which exist within a weather dataset of London climatic records. The dataset includes a full variety of atmospheric features such as temperature variations, precipitation level, cloud density, and amount of sunlight that occurred, and the binary target variable indicates snow-covered or clear conditions. The experimental framework will include preprocessing steps that will be done systematically with anomaly detection, imputation, normalization, and feature transformation. Further stages presuppose the training of supervised learning models and the comparison with each other based on performance indicators. These models are evaluated thoroughly against set of evaluation metrics- accuracy, precision, recall and F1-score, to break down the robustness and reliability of their classification in real scenario meteorological situations. Decision boundaries and predictive relevance of each of the models are also improved by confusion matrix interpretation and determination of feature importance ranking. The empirical evidence can provide a rather fine-grained view on the dynamics of the model presented in conditions subjected to different meteorological circumstances and, eventually, help create a more realistic and situational snow prediction framework.

Cite this paper

APA 7

Rakhra, M., Kaur, H., Kumar, S., Sarkar, T., Singh, A., & Kumar, S. (2025). Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction. https://doi.org/10.1109/icec2nt65402.2025.11379934

MLA 9

Rakhra, Manik, et al. “Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction.” 2025, pp. 1–6, https://doi.org/10.1109/icec2nt65402.2025.11379934.

Chicago

Rakhra, Manik, Harjeet Kaur, Sanjeev Kumar, Tiyas Sarkar, Amanpreet Singh, and Sourav Kumar. 2025. “Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction.” https://doi.org/10.1109/icec2nt65402.2025.11379934.

Harvard

Rakhra, M. et al. (2025) ‘Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction’. Available at: https://doi.org/10.1109/icec2nt65402.2025.11379934.

BibTeX

@article{rakhra2025machine,
  title = {{Machine Learning-Driven Snowfall Forecasting: Unraveling Spatiotemporal Meteorological Patterns for Enhanced Precision Weather Prediction}},
  author = {Rakhra, Manik and Kaur, Harjeet and Kumar, Sanjeev and Sarkar, Tiyas and Singh, Amanpreet and Kumar, Sourav},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/icec2nt65402.2025.11379934}
}

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