| Summary: | Dissertation (Ph.D.) University of Alaska Fairbanks, 2019 Arctic-region observations are sparse and represent only a small portion of the physical state of nature. It is therefore essential to maximize the information content of observations and bservation-conditioned analyses whenever possible, including the quantification of their accuracy. The four largely disparate works presented here emphasize observation analysis and assimilation in the context of the Arctic Ocean (AO). These studies focus on the relationship between observational data/products, numerical models based on physical processes, and the use of such data to constrain and inform those products/models to di_erent ends. The first part comprises Chapters 1 and 2 which revolve around oceanographic observations collected during the International Polar Year (IPY) program of 2007-2009. Chapter 1 validates pan- Arctic satellite-based sea surface temperature and salinity products against these data to establish important estimates of product reliability in terms of bias and bias-adjusted standard errors. It establishes practical regional reliability for these products which are often used in modeling and climatological applications, and provides some guidance for improving them. Chapter 2 constructs a gridded full-depth snapshot of the AO during the IPY to visually outline recent, previouslydocumented AO watermass distribution changes by comparing it to a historical climatology of the latter 20th century derived from private Russian data. It provides an expository review of literature documenting major AO climate changes and augments them with additional changes in freshwater distribution and sea surface height in the Chukchi and Bering Seas. The last two chapters present work focused on the application of data assimilation (DA) methodologies, and constitute the second part of this thesis focused on the synthesis of numerical modeling and observational data. Chapter 3 presents a novel approach to sea ice model trajectory optimization whereby ...
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