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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-517
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Oct 2018

Research article | 11 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Assessment of spatial uncertainty of heavy local rainfall using a dense gauge network

Sungmin O1,2,a and Ulrich Foelsche1,2,3 Sungmin O and Ulrich Foelsche
  • 1Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics (IGAM/IP), NAWI Graz, University of Graz, Austria
  • 2FWF-DK Climate Change, University of Graz, Austria
  • 3Wegener Center for Climate and Global Change (WEGC), University of Graz, Austria
  • anow at: Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany

Abstract. Hydrology and remote-sensing communities have made use of dense rain-gauge networks for studying rainfall uncertainty and variability. However, in most regions, these dense networks are only available at sub-pixel scales and over short periods of time. Just a few studies have applied a similar approach, employing dense gauge networks, to local-scale areas, which limits the verification of their results in other regions. Using 10-year rainfall measurements from a network of 150 rain gauges, we assess spatial uncertainty in observed heavy rainfall events. The network is located in southeastern Austria over an area of 20km×15km with no significant orography. First, the spatial variability of rainfall in the region was characterised using a correlogram at daily and sub-daily scales. Differences in the spatial structure of rainfall events between wet and dry seasons are apparent and we selected heavy rainfall events, the upper 10% of wettest days during the wet season, for further analyses because of their high potential for causing hazard risk. Secondly, we investigated uncertainty in estimating mean areal rainfall arising from a limited gauge density. The number of gauges required to obtain areal rainfall with >20% accuracy tends to increase roughly following a power law as time scale decreases. Lastly, the impact of spatial aggregation on extreme rainfall was examined using gridded rainfall data with horizontal grid spacings from 0.1° to 0.01°. The spatial scale dependence was clearly observed at high intensity thresholds and high temporal resolutions. Quantitative uncertainty information from this study can guide both data users and producers to estimate uncertainty in their own observational datasets, consequently leading to the rational use of the data in relevant applications. Our findings are generalisable to other plain regions in mid-latitudes, however the degree of uncertainty could be affected by regional variations, like rainfall type or topography.

Sungmin O and Ulrich Foelsche
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Status: open (until 06 Dec 2018)
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Sungmin O and Ulrich Foelsche
Sungmin O and Ulrich Foelsche
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Short summary
We analyse heavy local rainfall to address questions regarding the spatial uncertainty due to the approximation of areal rainfall using point measurements. 10-years rainfall data from a dense network of 150 rain gauges in southeastern Austria are employed, which permits robust examination of small-scale rainfall at various horizontal resolutions. Quantitative uncertainty information from this study can guide both data users and producers to estimate uncertainty in their own rainfall datasets.
We analyse heavy local rainfall to address questions regarding the spatial uncertainty due to...
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