HR: 1400h
AN: H53B-05    [Abstracts]
TI: Rainfall Sampling Uncertainties: A Rain Gauge Perspective
AU: * Villarini, G
EM: gabriele-villarini@uiowa.edu
AF: The University of Iowa, 300 South Riverside Drive, Iowa City, IA 52242, United States
AU: Mandapaka, P V
EM: pmandapa@engineering.uiowa.edu
AF: The University of Iowa, 300 South Riverside Drive, Iowa City, IA 52242, United States
AU: Krajewski, W F
EM: witold-krajewski@uiowa.edu
AF: The University of Iowa, 300 South Riverside Drive, Iowa City, IA 52242, United States
AB: Rain gauge networks provide rainfall measurements with high degree of accuracy at specific locations but, in most of the cases, these networks are too sparse to accurately capture the high spatial and temporal variability of the precipitation systems. Radar and satellite remote sensing of rainfall has become a viable approach for effective addressing of this problem. However, among other sources of uncertainties, the remote-sensing based rainfall products are unavoidably affected by sampling errors that need to be evaluated and characterized. Using a large (seven years) dataset of rainfall measurements by a highly dense rain gauge network (50 gauges in about 140 km2) deployed in the Brue catchment (south-west part of England), this study sheds some light on the temporal and spatial sampling uncertainties: the former are defined as the errors resulting from temporal gaps in rainfall observations, while the latter as the uncertainties due to the approximation of an areal estimate with a point measurement. As far as the temporal sampling uncertainties are concerned, it will be shown that they increase with the sampling interval according to a scaling law and decrease with increasing pixel size with no strong dependence on local orography. On the other hand, the spatial sampling uncertainties tend to decrease for increasing accumulation time, with no apparent dependence on location of the gauge within the pixel or on the gauge elevation. Additionally, results pertaining to their dependence on the rainfall intensity will be presented.
DE: 1840 Hydrometeorology
DE: 1854 Precipitation (3354)
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: 2007 Joint Assembly