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| Titel |
Impact of data assimilation of physical variables on the spring bloom from TOPAZ operational runs in the North Atlantic |
| VerfasserIn |
A. Samuelsen, L. Bertino, C. Hansen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1812-0784
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| Digitales Dokument |
URL |
| Erschienen |
In: Ocean Science ; 5, no. 4 ; Nr. 5, no. 4 (2009-12-07), S.635-647 |
| Datensatznummer |
250002737
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| Publikation (Nr.) |
 copernicus.org/os-5-635-2009.pdf |
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| Zusammenfassung |
| A reanalysis of the North Atlantic spring bloom in 2007 was produced using
the real-time analysis from the TOPAZ North Atlantic and Arctic forecasting
system. The TOPAZ system uses a hybrid coordinate general circulation ocean
model and assimilates physical observations: sea surface anomalies, sea
surface temperatures, and sea-ice concentrations using the Ensemble Kalman
Filter. This ocean model was coupled to an ecosystem model, NORWECOM
(Norwegian Ecological Model System), and the TOPAZ-NORWECOM coupled model
was run throughout the spring and summer of 2007. The ecosystem model was
run online, restarting from analyzed physical fields (result after data
assimilation) every 7 days. Biological variables were not assimilated in the
model. The main purpose of the study was to investigate the impact of
physical data assimilation on the ecosystem model. This was determined by
comparing the results to those from a model without assimilation of physical
data. The regions of focus are the North Atlantic and the Arctic Ocean.
Assimilation of physical variables does not affect the results from the
ecosystem model significantly. The differences between the weekly mean
values of chlorophyll are normally within 5–10% during the summer months,
and the maximum difference of ~20% occurs in the Arctic, also
during summer. Special attention was paid to the nutrient input from the
North Atlantic to the Nordic Seas and the impact of ice-assimilation on the
ecosystem. The ice-assimilation increased the phytoplankton concentration:
because there was less ice in the assimilation run, this increased both the
mixing of nutrients during winter and the area where production could occur
during summer. The forecast was also compared to remotely sensed
chlorophyll, climatological nutrients, and in-situ data. The results show
that the model reproduces a realistic annual cycle, but the chlorophyll
concentrations tend to be between 0.1 and 1.0 mg chla/m3 too low during
winter and spring and 1–2 mg chla/m3 too high during summer. Surface
nutrients on the other hand are generally lower than the climatology
throughout the year. |
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