REVOLUTIONIZING NUMERICAL WEATHER PREDICTION MODELS WITH MACHINE LEARNING INNOVATIONS

Authors

  • Atagara Jayasree Rani, Dr Y.Narasimha Reddy Author

DOI:

https://doi.org/10.48047/7gy3es52

Keywords:

.

Abstract

Accurate weather forecasting is essential for disaster management, agriculture, aviation, and energy sectors, yet Numerical Weather Prediction (NWP) models often struggle with data assimilation errors, computational complexity, and inherent uncertainties. This study explores how Machine Learning (ML) techniques can revolutionize NWP models by enhancing their accuracy, efficiency, and adaptability. 

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References

Concept of a Numerical Forecast Model. Accessed: Aug. 10, 2023. [Online]. Available: http://web.kma.go.kr/aboutkma/intro/superc

om/model/model_concept.jsp

P. Davis, C. Ruth, A. A. Scaife, and J. Kettleborough, ‘‘A large ensemble seasonal forecasting system: GloSea6,’’ Dec. 2020,

vol. 2020.

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Published

2025-03-10

Issue

Vol. 54 No. 5 (2025): Year 2025 ,Volume 54 Issue 5

Section

Articles

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How to Cite

Atagara Jayasree Rani, Dr Y.Narasimha Reddy. (2025). REVOLUTIONIZING NUMERICAL WEATHER PREDICTION MODELS WITH MACHINE LEARNING INNOVATIONS . Cuestiones De Fisioterapia, 54(5), 10-18. https://doi.org/10.48047/7gy3es52