NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109

Spurred by the sustained operation and new development of satellite and in-situ observing systems, global ocean state estimation efforts that gear towards climate applications have flourished in the past decade. A hierarchy of estimation methods is being used to routinely synthesize various observations with global ocean models. Many of the estimation products are available through public data servers. There have been an increasingly large number of applications of these products for a wide range of research topics in physical oceanography as well as other disciplines. These studies often provide important feedback for observing systems design. This white paper describes the approaches used by these estimation systems in synthesizing observations and model dynamics, highlights the applications of their products for climate research, and addresses the challenges ahead in relation to the observing systems. Additional applications to study climate variability using an ensemble of state estimation products are described also by a white paper by Stammer et al.

Analyzing ocean variability, understanding its importance for the climate system, and quantifying its socio-economic impacts are among the primary motivations for obtaining ongoing global ocean observations. There are several possible approaches to address these tasks. One with much potential for future ocean information services and for climate predictions is called ocean synthesis, and is concerned with merging all available ocean observations with the dynamics embedded in an ocean circulation model to obtain estimates of the changing ocean that are more accurate than either system alone can provide. The field of ocean synthesis has matured over the last decade. Several global ocean syntheses exist today and can be used to investigate key scientific questions, such as changes in sea level, heat content, or transports. This CWP summarizes climate variability as “seen” by several ocean syntheses, describes similarities and differences in these solutions and uses results to highlight developments necessary over the next decade to improve ocean products and services. It appears that multi-model ensemble approaches can be useful to obtain better estimates of the ocean. To make full use of such a system, though, one needs detailed error information not only about data and models, but also about the estimated states. Results show that estimates tend to cluster around methodologies and therefore are not necessarily independent from each other. Results also reveal the impact of a historically under-sampled ocean on estimates of inter-decadal variability in the ocean. To improve future estimates, we need not only to sustain the existing observing system but to extend it to include full-depth ARGO-type measurements, enhanced information about boundary currents and transports through key regions, and to keep all important satellite sensors flying indefinitely, including altimetry, gravimetry and ice thickness, microwave SST observations, wind stress measurements and ocean color. We also need to maintain ocean state estimation as an integral part of the ocean observing and information system.