TY  - JOUR
A1  - Ahrens, Bodo
T1  - Distance in spatial interpolation of daily rain gauge data
T2  - Hydrology and earth system sciences discussions, 2.2005, S. 1893-1923
N2  - Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. The spatial density of available data sites is often changing with time. This paper investigates the application of statistical distance, like one minus common variance of 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 an actually available coarse observation network yields more robust interpolation results at sites of a denser network with actually lacking observations. The performance enhancement is in or close to mountainous terrain. This has the potential to 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.
Y1  - 2005
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/29474
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-294747
SN  - 1812-2116
N1  - © Author(s) 2005. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
VL  - 2
SP  - 1893
EP  - 1923
PB  - European Geophysical Society
CY  - Katlenburg-Lindau
ER  -