Skill assessment in ocean biological data assimilation
There 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 pri...
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Veröffentlicht in: | Journal of marine systems 2009-02, Vol.76 (1), p.16-33 |
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container_title | Journal of marine systems |
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creator | Gregg, Watson W. Friedrichs, Marjorie A.M. Robinson, Allan R. Rose, Kenneth A. Schlitzer, Reiner Thompson, Keith R. Doney, Scott C. |
description | There 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 data assimilation: the free-run model, data, and the assimilation model, which uses information from both the free-run model and the data. Intercomparison 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. |
doi_str_mv | 10.1016/j.jmarsys.2008.05.006 |
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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 data assimilation: the free-run model, data, and the assimilation model, which uses information from both the free-run model and the data. Intercomparison 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. 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source | ScienceDirect Journals (5 years ago - present) |
subjects | Data assimilation Fisheries data assimilation Fisheries models Marine Ocean biogeochemistry models Ocean biology models Skill assessment |
title | Skill assessment in ocean biological data assimilation |
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