A three-dimensional variational ocean data assimilation system: Scheme and preliminary results

Abstract

A new 3DVAR-based Ocean Variational Analysis System (OVALS) is developed. OVALS is capable of assimilating in situ sea water temperature and salinity observations and satellite altimetry data. As a component of OVALS, a new variational scheme is proposed to assimilate the sea surface height data. This scheme considers both the vertical correlation of background errors and the nonlinear temperature-salinity relationship which is derived from the generalization of the linear balance constraints to the nonlinear in the 3DVAR. By this scheme, the model temperature and salinity fields are directly adjusted from the altimetry data. Additionally, OVALS can assimilate the temperature and salinity profiles from the ARGO floats which have been implemented in recent years and some temperature and salinity data such as from expendable bathythermograph, moored ocean buoys, etc. A 21-year assimilation experiment is carried out by using OVALS and the Tropical Pacific circulation model. The results show that the assimilation system may effectively improve the estimations of temperature and salinity by assimilating all kinds of observations. Moreover, the root mean square errors of temperature and salinity in the upper depth less than 420 m reach 0.63℃ and 0.34 psu. Keywords: data assimilation, 3DVAR, sea surface height, ARGO floats.With the successful development of ocean buoys technique in the 1990s, the ARGO plan was proposed by the international group in 1998 and implemented in 1999. Up to now, more than 1800 ARGO floats are now in operation and delivering real-time temperature and salinity profile observations over the world oceans. By the end of 2005, ARGO will expect to provide more than 100000 temperature and salinity profiles which have a depth range of 0 m to 2000 m [1] . Apart from the ARGO plan, the GODAE high-resolution sea surface temperature pilot project (GHRSST-PP) is beginning to implement to provide high resolution in the time of 6 h and in the space of 10 km [2] sea surface temperature observation with global coverage for the operational oceanography, climate study and prediction. Except the above two new observation systems, as a successor of successful implementation of Topex/Poseidon altimeter satellite in the 1990s, the Jason-1 Mission was successfully launched in December, 2001. This observation system can provide

Testing a four-dimensional variational data assimilation method using an improved intermediate coupled model for ENSO analysis and prediction

“…For example, the 4D-Var data assimilation method pursues the analysis solutions by minimizing the distance between the model trajectory and observation time series [i.e., the so-called cost function (e.g., Tang and Hsieh, 2001;Zhang et al, 2001;Han et al, 2006Han et al, , 2015Peng and Xie, 2006;Zhang et al, 2015b)]. Compared with economic 3D-Var analysis (Derber and Rosati, 1989;Zhu et al, 2006), the 4D-Var data assimilation method is more dynamically and mathematically consistent (e.g., Dommenget and Stammer, 2004;Sugiura et al, 2008). For instance, Weaver et al (2003) assimilated in situ temperature data into an OGCM by the 3D-Var and 4D-Var methods, and demonstrated that 4D-Var is more effective than 3D-Var in producing a consistent ocean state between model solutions and observations.…”

Improving the multiannual, high-resolution modelling of biogeochemical cycles in the Baltic Sea by using data assimilation

“…For this aim, many advanced assimilation methods based on the Kalman filter (e.g. EnKF; Evensen, 2003) and variational methods (3DVAR and 4DVAR) (Zhu et al, 2006;Liu and Yan, 2010;Liu and Zhao, 2011) have widely been used in the areas of ocean and atmospheric modelling. The ensemble optimum interpolation (EnOI) method (Fu et al, 2011;Liu et al, 2013) that will be used in this study is similar to the optimum interpolation (OI) method applied for the operational ocean forecasting system at the SMHI (Pemberton and Funkquist, 2006).…”

Altimetric data assimilation by EnOI and 3DVAR in a tropical pacific model: Impact on the simulation of variability

“…In this study, the reanalysis data were produced by the Ocean Variational Analysis System (OVALS), which synthesize many currently available observed data including TAO, Expendable Bathythermographs (XBT's), satellite sea surface height (SSH), Argo, etc. (Zhu et al, 2006). The reanalysis data were used to validate model and assimilation results (Yan et al, 2007;Fu et al, 2009a).…”