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Autor |
Quartly, G. D. |
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Titel |
Altimeter repeat-track analysis -- a comparison of various algorithms for producing the mean profile |
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Jahr |
1995 |
Publikation |
J. Atmos. Ocean. Technol |
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12 |
Ausgabe |
3 |
Seiten |
674-686 |
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Schlüsselwörter |
dynamical-oceanography; remote-sensing; satellite-altimetry; sea-level-measurement; geoid-; geostrophic-transport; statistical-analysis; errors- |
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Zusammenfassung |
Sea surface height may be measured by a satellite-borne altimeter and its along-track slope used to infer geostrophic currents. A major difficulty is that, in general, the local geoid and satellite orbit are not known to the accuracy desired. Thus, comparison is often made between repeat flights of an altimeter along fixed ground tracks in order to infer the changes in the currents. In practice, it is convenient to calculate a mean height profile from many repeat passes and use this as a reference, so that individual altimetric profiles yield variations about this mean. It is thus important to derive a high-quality reliable estimate of the altimetric mean in order to minimize the errors in the inferred flows for the individual repeats. This work examines various methods for deriving the mean profile. |
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1302 |
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Autor |
Walters, C. |
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Titel |
Estimation of historical stock sizes and recruitment anomalies from relative abundance time series |
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Zeitschrift, Artikel |
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Jahr |
1995 |
Publikation |
Can. J. Fish. Aquat. Sci. J. Can. Sci. Halieut. Aquat |
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Band |
52 |
Ausgabe |
7 |
Seiten |
1523-1534 |
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stock-assessment; approximation-; anomalies-; recruitment-; abundance-; growth-; survival-; algorithms-; fishery-management; marine-fisheries |
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Zusammenfassung |
Often only simple relative abundance time series and basic growth and (or) survival estimates are available for assessing impacts of fishing and environmental factors. Assessment then involves fitting production models to the series, while forcing the model with observed catch or effort series. A key uncertainty in this approach is how to deal with recruitment variations due to factors other than stock size. A dynamic programming algorithm can be used to compute maximum likelihood estimates of the recruitment anomaly sequence, given prior knowledge of growth parameters, the natural survival rate, and proportion of the variation in the relative abundance index that is due to abundance measurement errors. |
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1779 |
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