Articles | Volume 24, issue 7
https://doi.org/10.5194/nhess-24-2481-2024
https://doi.org/10.5194/nhess-24-2481-2024
Research article
 | 
19 Jul 2024
Research article |  | 19 Jul 2024

Revisiting regression methods for estimating long-term trends in sea surface temperature

Ming-Huei Chang, Yen-Chen Huang, Yu-Hsin Cheng, Chuen-Teyr Terng, Jinyi Chen, and Jyh Cherng Jan

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Latest update: 22 Nov 2024
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Short summary
Monitoring the long-term trends in sea surface warming is crucial for informed decision-making and adaptation. This study offers a comprehensive examination of prevalent trend extraction methods. We identify the least-squares regression as suitable for general tasks yet highlight the need to address seasonal signal-induced bias, i.e., the phase–distance imbalance. Our developed method, evaluated using simulated and real data, is unbiased and better than the conventional SST anomaly method. 
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