Reliable wave forecasts are essential for maritime safety, port operations, and hazard warnings. In areas such as the Oman Sea, where in-situ observations are scarce, validating and improving numerical wave models remains a challenge. This study examines the performance of the WAVEWATCH III model in predicting wave height and period under limited-data conditions.
The model was forced with surface wind fields from ECMWF and regional bathymetry. Its results were compared with satellite observations and the few available buoy records. Statistical measures, including RMSE, BIAS, and Scatter Index, were used to evaluate accuracy. Findings show that the model performs well under normal conditions but tends to lose accuracy during extreme events such as monsoon storms. The quality of wind input data was also found to strongly influence model performance.
Overall, the study indicates that combining satellite data, numerical modeling, and statistical correction techniques can enhance wave forecasts in data-sparse regions. These insights are useful for maritime agencies, port managers, and policymakers in Iran and the Persian Gulf, and underline the importance of improving observational networks and early warning systems.

Reliable wave forecasts are essential for maritime safety, port operations, and hazard warnings. In areas such as the Oman Sea, where in-situ observations are scarce, validating and improving numerical wave models remains a challenge. This study examines the performance of the WAVEWATCH III model in predicting wave height and period under limited-data conditions.
The model was forced with surface wind fields from ECMWF and regional bathymetry. Its results were compared with satellite observations and the few available buoy records. Statistical measures, including RMSE, BIAS, and Scatter Index, were used to evaluate accuracy. Findings show that the model performs well under normal conditions but tends to lose accuracy during extreme events such as monsoon storms. The quality of wind input data was also found to strongly influence model performance.
Overall, the study indicates that combining satellite data, numerical modeling, and statistical correction techniques can enhance wave forecasts in data-sparse regions. These insights are useful for maritime agencies, port managers, and policymakers in Iran and the Persian Gulf, and underline the importance of improving observational networks and early warning systems.