An experiment is conducted to compare four-dimensional variational (4DVAR) and ensemble Kalman filter (EnKF) assimilation systems and their predictability in the Gulf of Mexico (GoM) using the Massachusetts Institute of Technology general circulation model (MITgcm). The quality of the ocean-state estimates, forecasts, and the contribution of ensemble prediction are evaluated. The MITgcm–Estimating the Circulation and Climate of the Ocean (ECCO) 4DVAR (MITgcm–ECCO) and the MITgcm–Data Assimilation Research Testbed (DART) EnKF (MITgcm–DART) systems were used to compute two-month hindcasts (March–April, 2010) by assimilating satellite-derived along-track sea-surface height (SSH) and gridded sea-surface temperature (SST) observations. The estimates from both methods at the end of the hindcast period were then used to initialize forecasts for two months (May–June, 2010). This period was selected because a loop current (LC) eddy (Eddy Franklin: Eddy-F) detachment event occurred at the end of May 2010, immediately after the Deepwater Horizon (DwH) oil spill. Despite some differences between the setups, both systems produce analyses and forecasts of comparable quality and both solutions significantly outperformed model persistence. A reference forecast initialized from the 1/12° Hybrid Coordinate Ocean Model (HYCOM)/NCODA global analysis also performed well. The EnKF experiments for sensitivity to filter parameters showed enhanced predictability when using more ensemble members and stronger covariance localization, but not for larger inflation. The EnKF experiments varying the number of assimilation cycles showed enhanced short-term (long-term) predictability with fewer (more) assimilation cycles. Additional hindcast and forecast experiments at other times of significant LC evolution showed mixed performance of both systems, which depends strongly on the background state of the GoM circulation. The present work demonstrates a practical application of both assimilation methods for the GoM and compares them in a limited number of realizations. The overall conclusion showing improved short-term (long-term) predictability for EnKF (4DVAR) carries an important caveat that the results from this study are specific to a few 4DVAR and EnKF LC eddy separation experiments in the GoM and cannot be generalized to conclude the relative performance of both methods, especially in other applications. However, some of the concepts and methods should carry over to other applications.
|Original language||English (US)|
|Number of pages||23|
|Journal||Quarterly Journal of the Royal Meteorological Society|
|State||Published - Mar 31 2019|