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| Titel |
Distance in spatial interpolation of daily rain gauge data |
| VerfasserIn |
B. Ahrens |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 10, no. 2 ; Nr. 10, no. 2 (2006-04-04), S.197-208 |
| Datensatznummer |
250007982
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| Publikation (Nr.) |
 copernicus.org/hess-10-197-2006.pdf |
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| Zusammenfassung |
| Spatial interpolation of rain gauge data is important in forcing of
hydrological simulations or evaluation of weather predictions, for
example.
This paper investigates the application of statistical
distance, like one minus common variance of observation time series, between data sites
instead of geographical distance in interpolation. Here, as a typical
representative of interpolation methods
the inverse distance weighting interpolation is applied and the test data is daily
precipitation observed in Austria. Choosing statistical distance
instead of geographical distance in interpolation of available
coarse network observations to sites of a
denser network, which is not reporting for the interpolation date, yields more robust interpolation results. The most distinct
performance enhancement is in or close to mountainous terrain. Therefore,
application of
statistical distance in the inverse distance weighting interpolation or in
similar methods can parsimoniously densify the currently available observation
network.
Additionally, the success further motivates search for conceptual
rain-orography interaction models as components of spatial rain interpolation algorithms in mountainous terrain. |
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