Methods and applications of ocean synthesis in climate research

The past 20 years have provided us with an unprecedented ability to observe, monitor, and forecast the oceans. In situ and remotely sensed ocean observations in combination with ocean general circulation models using data assimilation and state estimation methods underpin climate applications. State estimation aims to provide a dynamically consistent estimation of ocean fields, of errors of these fields, and of certain model parameters such as mixing coefficients. Conversely, data assimilation tools have been developed predominantly for ocean prediction applications and ocean reanalyses. This chapter describes approaches used by state estimation and data assimilation systems in synthesizing observations and model dynamics. We highlight some applications, including their limitations for climate research, and address the challenges ahead in relation to the ocean observing system.