[p1] Applications in various physical and biological systems


[p1-2]

A balanced Kalman Filter ocean data assimilation system with application to the South Australian Sea

Y. Li (Imperial College London) and R. Toumi (Imperial College London)

 
Abstract

In this study, a regional ocean data assimilation system is developed by combining the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). Several ensemble-based data assimilation algorithms and a wide range of observations are supported in this system. We describe the first implementation of the physical balance operators (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves introduced during the data assimilation process. The effect of assimilation with the geostrophic balance operator is compared with the original algorithm in both idealised shallow water model and ROMS model real case study. In the idealised model, the data assimilation with balance operator produces a better SSH and velocity forecast and analysis and its impact increases as the sea surface height and wind stress increase. In the real case, satellite SST and SSH are assimilated in the South Australian Sea using the Ensemble Adjustment Kalman Filter (EAKF). Assimilation with the balance operator produces a more realistic simulation of surface current. A case study with a storm affecting this region suggests that the benefit of balance operator is of particular importance under high wind stress conditions.