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Tipping bucket mechanical errors and their influence on rainfall statistics and extremes.
Barbera P La1, L G Lanza, L Stagi
1Department of Environmental Engineering, University of Genova, Italy.
Summary
Systematic mechanical errors in tipping bucket rain gauges bias rainfall extreme statistics. An equivalent sample size index helps engineers assess these errors
Area of Science:
- Hydrology
- Environmental Engineering
- Meteorology
Background:
- Tipping bucket rain gauges are widely used for rainfall measurement.
- Systematic mechanical errors can affect data accuracy.
- Accurate rainfall data is crucial for hydrological and hydraulic engineering.
Purpose of the Study:
- To quantify the bias introduced by systematic mechanical errors in tipping bucket rain gauges.
- To define an index for assessing the influence of these errors on hydrological practice.
- To discuss the consequences for data reconstruction and climate trend analysis.
Main Methods:
- Laboratory tests on operational rain gauges from the Liguria region network.
- Quantification of error figures and bias in rainfall extreme statistics.
- Definition and application of an equivalent sample size index.
Main Results:
- Systematic mechanical errors significantly bias the estimation of rainfall extremes and return periods.
- The proposed equivalent sample size index effectively measures the influence of these errors.
- Potential for artificial climate trends and data reconstruction issues were identified.
Conclusions:
- Mechanical errors in rain gauges necessitate careful data quality control.
- The equivalent sample size index provides a practical tool for engineers.
- Addressing these errors is vital for reliable hydrological design and climate change studies.