In order to improve the efficiency of the Ocean Variational Assimilation System （OVALS）, which has been widely used in various applications, an improved OVALS （OVALS2） is developed based on the recursive filter （RF） algorithm. The first advantage of OVALS2 is that memory storage can be substantially reduced in practice because it implicitly computes the background error covariance matrix; the second advantage is that there is no inversion of the background error covariance by preconditioning the control variable. For comparing the effectiveness between OVALS2 and OVALS, a set of experiments was implemented by assimilating expendable bathythermograph （XBT） and ARGO data into the Tropical Pacific circulation model. The results show that the efficiency of OVALS2 is much higher than that of OVALS. The computational time and the computer storage in the assimilation process were reduced by 83% and 77%, respectively. Additionally, the corresponding results produced by the RF are almost as good as those obtained by OVALS. These results prove that OVALS2 is suitable for operational numerical oceanic forecasting.
A dataset of surface current vectors with error estimate from 1999 to 2007 is derived from the trajectories of the Array for Real-time Geostrophic Oceanography (Argo) drifting on surface over the global ocean. The error of the estimated surface currents is about 4.7 cm s-1 which is equivalent to the accuracy of the currents determined from the surface drifters. Geographically, the Argo-derived surface currents can fill many gaps left by the Global Drifter Program due to the greater number of floats, and can provide a complementary in situ observational system for monitoring global ocean surface currents. The surface currents from the Argo floats are compared with the surface drifter-derived currents and the Tropical Atmosphere Ocean program (TAO) measurements. The comparisons show good agreement for both the current amplitude and the direction of surface currents. Results indicate the feasibility of obtaining ocean surface currents from the Argo array and of combining the surface currents from Argo and the ocean surface drifters for in situ mapping of the global surface currents. The authors also make the dataset available to users of interest for many types of applications.
