A novel and simple mathematical model was developed in this study to enhance the capacity of a reduced-order model based on eigenvectors (RMEV) to predict sea surface temperature (SST) in the northwest portion of the Indian Ocean, including the Persian and Oman Gulfs and Arabian Sea. Developed using only the first two of 12,416 possible modes, the enhanced RMEV closely matched observed daily optimum interpolation SST (DOISST) values. Spatial distribution of the first mode indicated the greatest variations in DOISST occurred in the Persian Gulf. Also, the slightly increasing trend in the temporal component of the first mode observed in the study area over the last 34 years properly reflected the impact of climate change and rising DOISST. Given its simplicity and high level of accuracy, the enhanced RMEV can be applied to forecast DOISST in oceans, which the poor forecasting performance and large computational-time of other numerical models may not allow.
Estuarine Coastal and Shelf Science – Elsevier
Published: Oct 15, 2017
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