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Skill Assessment in Ocean Biological Data AssimilationThere is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.
Document ID
Document Type
Preprint (Draft being sent to journal)
Gregg, Watson W. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Friedrichs, Marjorie A. M. (Virginia Inst. of Marine Science Gloucester Point, VA, United States)
Robinson, Allan R. (Harvard Univ. MA, United States)
Rose, Kenneth A. (Louisiana State Univ. LA, United States)
Schlitzer, Reiner (Alfred-Wegener Inst. for Polar and Marine Research Germany)
Thompson, Keith R. (Dalhousie Univ. Halifax, Nova Scotia, Canada)
Doney, Scott C. (Woods Hole Oceanographic Inst. MA, United States)
Date Acquired
August 25, 2013
Publication Date
May 2, 2008
Subject Category
Distribution Limits