A background error covariance model of significant wave height employing Monte Carlo simulation

The quality of background error statistics is one of the key components for successful assimilation of observations in a numerical model. The background error covariance (BEC) of ocean waves is generally estimated under an assumption that it is stationary over a period of time and uniform over a domain. However, error statistics are in fact functions of the physical processes governing the meteorological situation and vary with the wave condition. In this paper, we simulated the BEC of the significant wave height (SWH) employing Monte Carlo methods. An interesting result is that the BEC varies consistently with the mean wave direction (MWD). In the model domain, the BEC of the SWH decreases significantly when the MWD changes abruptly. A new BEC model of the SWH based on the correlation between the BEC and MWD was then developed. A case study of regional data assimilation was performed, where the SWH observations of buoy 22001 were used to assess the SWH hindcast. The results show that the new BEC model benefits wave prediction and allows reasonable approximations of anisotropy and inhomogeneous errors.