Improved estimates of the dynamical state of the North Pacific Ocean from a 4 dimensional variational data assimilation

Abstract

A 4‐dimensional variational data assimilation system has been used to better define the mean seasonal state of the North Pacific. The synthesis of available observational records and a sophisticated general circulation model produces a dynamically consistent time‐varying dataset which exhibits realistic features of the global ocean circulation and requires no artificial sources or sinks for the temperature and salinity fields. The dataset enables us to clarify the water mass formation and movement processes. A sensitivity experiment using our system reveals that the origin of the North Pacific Intermediate Water can be traced back to the Okhotsk and Bering Seas in the subarctic region and to the subtropical Kuroshio region further south, consistent with recent observational findings. This result illustrates that the ocean state derived from our data assimilation has greater information and forecast potential than that obtained from earlier methods.

Development of a four‐dimensional variational coupled data assimilation system for enhanced analysis and prediction of seasonal to interannual climate variations

“…This preliminary setting of the required parameter regime is favorable for 4D-VAR experiments because the accuracy of the corrections obtained from the adjoint calculation are greatly dependent upon the performance of the model [e.g., Fukumori et al, 2004;Masuda et al, 2003]. Since the Green's function method is an efficient means of optimization with a low degree of freedom, the adjustment of these 7 parameter values is expected to contribute to an enhanced model climatology fit to observed data such as the WOD's oceanic temperature and salinity climatologies and the SSM/I 10 m sea wind values.…”

“…The ocean reanalysis data set was also used to create the initial conditions for the first-guess fields. The error covariance matrices for the observational data were assumed to be diagonal and were determined from the temporal changes of the corresponding variables in each model grid point [Stammer et al, 2002;Masuda et al, 2003]. Although the background terms for initial conditions are not involved explicitly in the cost function, a sequential input of the ocean reanalysis data set as an assimilation element mentioned above is expected to help maintain the covariance structure because of use of the same OGCM.…”

Possible link between interannual variation of neon flying squid (Ommastrephes bartramii) abundance in the North Pacific and the climate phase shift in 1998/1999

“…In this study, we used ENT as a proxy for the nutrient-rich water supply entering the mixed layer. This dataset provides an accurate estimate of water mass formation and distribution in the subsurface layer, including the ENT processes across the mixed layer, as the 4D-VAR method can create a dynamically self-consistent dataset requiring no artificial sources or sinks for the temperature and salinity fields (Masuda et al, 2003). In fact, the obtained reanalysis field shows good agreement with observations (Masuda et al, 2010;Kouketsu et al, 2011).…”

“…This provided the best time-trajectory fit to observations and created a dynamically self-consistent dataset. The assimilation system was developed by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and Kyoto University (Masuda et al, 2003(Masuda et al, , 2006(Masuda et al, , 2010Kouketsu et al, 2011), and is based on a global oceanic general circulation model (OGCM), specifically, version 3 of the Geophysical Fluid Dynamics Laboratory (GFDL; NOAA, USA) Modular Ocean Model (MOM) (Pacanowski and Griffies, 2000). The horizontal resolution is one degree of latitude and longitude, with 46 vertical levels.…”

“…Recent studies have focused on obtaining an optimal synthesis of observational data and model results by data assimilation techniques for better descriptions of the ocean state (Fukumori and Wunsh, 1991). In particular, a four-dimensional variational (4D-VAR) approach, based on strong constraint formalism, has become one of the most attractive assimilation methods for practical use (Masuda et al, 2003). Masuda et al (2010) successfully developed a highly accurate ocean data assimilation system based on a 4D-VAR adjoint approach and obtained a comprehensive four-dimensional reanalysis dataset from the sea surface to the ocean bottom for all major ocean basins between 1967 and 2006.…”