A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration

Liu, Yibo; Zhao, Zichen; Zhang, Zhe; Yang, Yi

doi:10.3390/rs17101681

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A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration

¹

College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China

²

Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province, Lanzhou 730000, China

³

Center for Weather Forecasting and Climate Prediction of Lanzhou University, Lanzhou 730000, China

⁴

School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2025, 17(10), 1681; https://doi.org/10.3390/rs17101681

Submission received: 24 March 2025 / Revised: 5 May 2025 / Accepted: 8 May 2025 / Published: 10 May 2025

(This article belongs to the Special Issue Artificial Intelligence and Big Data for Oceanography (2nd Edition))

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Abstract

Sea surface temperature (SST) is crucial for weather forecasting, climate modeling, and environmental monitoring. This study proposes a novel prediction model that achieves a 60-day forecast with a root mean square error (RMSE) consistently below 0.9 °C. The model combines the nonlinear feature extraction of a deep belief network (DBN) with the high-precision regression of support vector regression (SVR), enhanced by spatiotemporal secondary calibration (SSC) to better capture SST variation patterns. Using satellite-derived remote sensing data, the DBN-SVR model outperforms baseline methods in both the Indian Ocean and North Pacific regions, demonstrating strong applicability across diverse marine environments. This work advances long-term SST prediction capabilities, providing a reliable foundation for extended-range marine forecasts.

Keywords: deep belief network; support vector regression; sea surface temperature prediction; spatiotemporal secondary calibration; deep learning

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MDPI and ACS Style

Liu, Y.; Zhao, Z.; Zhang, Z.; Yang, Y. A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration. Remote Sens. 2025, 17, 1681. https://doi.org/10.3390/rs17101681

AMA Style

Liu Y, Zhao Z, Zhang Z, Yang Y. A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration. Remote Sensing. 2025; 17(10):1681. https://doi.org/10.3390/rs17101681

Chicago/Turabian Style

Liu, Yibo, Zichen Zhao, Zhe Zhang, and Yi Yang. 2025. "A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration" Remote Sensing 17, no. 10: 1681. https://doi.org/10.3390/rs17101681

APA Style

Liu, Y., Zhao, Z., Zhang, Z., & Yang, Y. (2025). A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration. Remote Sensing, 17(10), 1681. https://doi.org/10.3390/rs17101681

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A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration

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