Sea Surface Temperature Forecasting Using Machine Learning

• Author(s): Samta Kumari; Sajid Ali; Sushant Ranjan; Dr. Ishrat Ali; Prof. (Dr.) Sanjay Pachauri
• Paper ID: 1712141
• Page: 1341-1342
• Published Date: 18-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025
• DOI: https://doi.org/10.64388/IREV9I5-1712141

Abstract

Sea Surface Temperature (SST) is a critical climate variable that influences global weather, monsoon behavior, and marine ecosystems. Traditional numerical models struggle with high computational cost and nonlinear ocean?atmosphere dynamics. This work presents a machine-learning-based framework for SST forecasting using satellite observations and reanalysis data. Models including Random Forest, LSTM, and ConvLSTM are evaluated for short- and medium-term prediction. Results show that ML models significantly outperform persistence and statistical baselines in accuracy and efficiency. The study demonstrates the potential of data-driven methods to enhance operational SST forecasting and support climate monitoring applications.

Keywords

Sea Surface Temperature (SST); Machine Learning; Deep Learning; ConvLSTM; LSTM; Climate Forecasting; Oceanography; SatelliteData; Time-Series Prediction.

Citations

IRE Journals:
Samta Kumari, Sajid Ali, Sushant Ranjan, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Sea Surface Temperature Forecasting Using Machine Learning" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1341-1342 https://doi.org/10.64388/IREV9I5-1712141

IEEE:
Samta Kumari, Sajid Ali, Sushant Ranjan, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Sea Surface Temperature Forecasting Using Machine Learning" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712141

APA:
Samta Kumari, Sajid Ali, Sushant Ranjan, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri (2025). Sea Surface Temperature Forecasting Using Machine Learning. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712141

MLA:
Samta Kumari, Sajid Ali, Sushant Ranjan, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Sea Surface Temperature Forecasting Using Machine Learning" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712141

BibTeX

@article{1712141,
author = {Samta Kumari, Sajid Ali, Sushant Ranjan, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri},
title = {Sea Surface Temperature Forecasting Using Machine Learning},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {1341-1342},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712141.pdf},
abstract = {Sea Surface Temperature (SST) is a critical climate variable that influences global weather, monsoon behavior, and marine ecosystems. Traditional numerical models struggle with high computational cost and nonlinear ocean?atmosphere dynamics. This work presents a machine-learning-based framework for SST forecasting using satellite observations and reanalysis data. Models including Random Forest, LSTM, and ConvLSTM are evaluated for short- and medium-term prediction. Results show that ML models significantly outperform persistence and statistical baselines in accuracy and efficiency. The study demonstrates the potential of data-driven methods to enhance operational SST forecasting and support climate monitoring applications.},
keywords = {Sea Surface Temperature (SST); Machine Learning; Deep Learning; ConvLSTM; LSTM; Climate Forecasting; Oceanography; SatelliteData; Time-Series Prediction.},
month = {November}
}