Oceanography has entered a realm of big data in recent decades, prompting an increased need for data curation and uncertainty quantification. This session will focus on best practices for the derivation, communication, and utilization of the uncertainties of in-situ, derived, and modeled ocean products. Participants will discuss how uncertainty quantification can be incorporated into analyses, observing system design, data assimilation, and other user applications.
We should train ocean observers and modelers in statistical terminology and techniques for the purpose of uncertainty quantification.
Building on existing efforts, we should produce a series of peer-reviewed and open-access documents that define and recommend strategies and best practices for uncertainty quantification in ocean observing.
Research programs should require and fund routine uncertainty estimates on ocean observations and derived products, and should fund dedicated efforts to develop freely available resources (software and databases) for uncertainty quantification.