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| Titel |
Spatial patterns of linear and nonparametric long-term trends in Baltic sea-level variability |
| VerfasserIn |
R. V. Donner, R. Ehrcke, S. M. Barbosa, J. Wagner, J. F. Donges, J. Kurths |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 19, no. 1 ; Nr. 19, no. 1 (2012-02-13), S.95-111 |
| Datensatznummer |
250014167
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| Publikation (Nr.) |
 copernicus.org/npg-19-95-2012.pdf |
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| Zusammenfassung |
| The study of long-term trends in tide gauge data is important for
understanding the present and future risk of changes in sea-level variability
for coastal zones, particularly with respect to the ongoing debate on climate
change impacts. Traditionally, most corresponding analyses have exclusively
focused on trends in mean sea-level. However, such studies are not able to
provide sufficient information about changes in the full probability
distribution (especially in the more extreme quantiles). As an alternative,
in this paper we apply quantile regression (QR) for studying changes in
arbitrary quantiles of sea-level variability. For this purpose, we chose two
different QR approaches and discuss the advantages and disadvantages of
different settings. In particular, traditional linear QR poses very
restrictive assumptions that are often not met in reality. For monthly data
from 47 tide gauges from along the Baltic Sea coast, the spatial patterns of
quantile trends obtained in linear and nonparametric (spline-based)
frameworks display marked differences, which need to be understood in order to
fully assess the impact of future changes in sea-level variability on coastal
areas. In general, QR demonstrates that the general variability of Baltic
sea-level has increased over the last decades. Linear quantile trends
estimated for sliding windows in time reveal a wide-spread acceleration of
trends in the median, but only localised changes in the rates of changes in the lower and
upper quantiles. |
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