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| Titel |
Sea-ice extent and its trend provide limited metrics of model performance |
| VerfasserIn |
D. Notz |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 8, no. 1 ; Nr. 8, no. 1 (2014-02-14), S.229-243 |
| Datensatznummer |
250116019
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| Publikation (Nr.) |
 copernicus.org/tc-8-229-2014.pdf |
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| Zusammenfassung |
| We examine how the evaluation of modelled sea-ice coverage against reality is
affected by uncertainties in the retrieval of sea-ice coverage from
satellite, by the usage of sea-ice extent to overcome these uncertainties, and
by internal variability. We find that for Arctic summer sea ice, model biases
in sea-ice extent can be qualitatively different from biases in sea-ice area.
This is because about half of the CMIP5 models and satellite retrievals based
on the Bootstrap and the ASI algorithm show a compact ice cover in summer
with large areas of high-concentration sea ice, while the other half of the
CMIP5 models and satellite retrievals based on the NASA Team algorithm show a
loose ice cover. For the Arctic winter sea-ice cover, differences in grid
geometry can cause synthetic biases in sea-ice extent that are larger than
the observational uncertainty. Comparing the uncertainty arising directly
from the satellite retrievals with those that arise from internal
variability, we find that the latter by far dominates the uncertainty
estimate for trends in sea-ice extent and area: most of the differences
between modelled and observed trends can simply be explained by internal
variability. For absolute sea-ice area and sea-ice extent, however, internal
variability cannot explain the difference between model and observations for
about half the CMIP5 models that we analyse here. All models that we examined
have regional biases, as expressed by the root-mean-square error in
concentration, that are larger than the differences between individual
satellite algorithms. |
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