443 ISSN 0001-4338, Izvestiya, Atmospheric and Oceanic Physics, 2016, Vol. 52, No. 4, pp. 443–454. © Pleiades Publishing, Ltd., 2016. Original Russian Text © A.A. Zelenko, R.M. Vil’fand, Yu.D. Resnyanskii, B.S. Strukov, M.D. Tsyrulnikov, P.I. Svirenko, 2016, published in Izvestiya Rossiiskoi Akademii Nauk, Fizika Atmosfery i Okeana, 2016, Vol. 52, No. 4, pp. 501–513. An Ocean Data Assimilation System and Reanalysis of the World Ocean Hydrophysical Fields A. A. Zelenko, R. M. Vil’fand, Yu. D. Resnyanskii, B. S. Strukov, M. D. Tsyrulnikov, and P. I. Svirenko Hydrometeorological Research Centre of the Russian Federation, Bolshoi Predtechensky per. 11-13, Moscow, 123242 Russia e-mail: zelenko@mecom.ru Received October 23, 2015; in final form, November 25, 2015 Abstract—A new version of the ocean data assimilation system (ODAS) developed at the Hydrometcentre of Russia is presented. The assimilation is performed following the sequential scheme analysis–forecast–anal- ysis. The main components of the ODAS are procedures for operational observation data processing, a vari- ational analysis scheme, and an ocean general circulation model used to estimate the first guess fields involved in the analysis. In situ observations of temperature and salinity in the upper 1400-m ocean layer obtained from various observational platforms are used as input data. In the new ODAS version, the horizon- tal resolution of the assimilating model and of the output products is increased, the previous 2D-Var analysis scheme is replaced by a more general 3D-Var scheme, and a more flexible incremental analysis updating pro- cedure is introduced to correct the model calculations. A reanalysis of the main World Ocean hydrophysical fields over the 2005–2015 period has been performed using the updated ODAS. The reanalysis results are compared with data from independent sources. Keywords: ocean, operational observations, modeling, data assimilation DOI: 10.1134/S0001433816040149 INTRODUCTION Numerical models of the ocean general and regional circulation, which historically started with the pioneer- ing works of A.S. Sarkisyan [1–4], P.S. Lineikin [5], and K. Bryan, [6], have proved to be a good tool for many practical tasks today. The application of such models is essential for the state-of-art methods in ocean forecasting, predictions of interannual variations in an ocean–atmosphere system (such as, e.g., El Niño– Southern Oscillation or North-Atlantic Oscillation), and possible climate change estimations with the help of coupled ocean–atmosphere models. A near-real time diagnostic and prognostic assess- ments of the ocean state using numerical modeling is a subject of operational oceanography, a relatively new discipline. Ocean data assimilation systems (ODASes) are one of the main component of marine information and prediction systems assuring the solution of opera- tional oceanography problems. These systems are designed for an optimal estimation of the current state of hydrophysical fields with observational and ocean gen- eral circulation model data. The ODAS development is carried out in many world oceanographic and meteoro- logical centers. The ODAS current state up to 2009 has been reviewed in, e.g., [7], and, up to 2015, in [8]. The first national operational version of ODAS was created at the Hydrometcentre of Russia and was functioning in 2006–2014 [9]. In this article a new improved version of the ocean data assimilation system is presented together with the results of its hydrophysical fields reanalysis computed for the 10-year period of 2005–2015. 1. DATA ASSIMILATION SYSTEM The essence of the data assimilation procedures is a combination (matching) of the observational data and results of a hydrodynamic model calculation used for a spatiotemporal interpolation for the areas with a lack of observational data. Both components of the ODAS— observations and modeling—have certain uncertain- ties. Eventually, the data assimilation procedure can be expressed as constructing an optimal combination of the data from these two sources taking into account the statistical structure of each of them. The thus- obtained estimation is more precise than the estimates obtained separately from either observational or mod- eling data. The success (quality of results) of any data assimilation system depends on the level of develop- ment of each component in a triad “observations– model–analysis.” 1.1. Observations Data from temperature–salinity profile measure- ments are basic input information for the ODAS. For the operational monitoring and forecasting the ocean