TY  - JOUR
A1  - Ahrens, Bodo
T1  - Distance in spatial interpolation of daily rain gauge data
T2  - Hydrology and earth system sciences
N2  - 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.
Y1  - 2006
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/29475
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-294757
SN  - 1802-6419
N1  - © Author(s) 2006. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
VL  - 10
SP  - 197
EP  - 208
PB  - European Geosciences Union
CY  - Katlenburg-Lindau
ER  -