4.7 Article

Enhancing the usability of weather radar data for the statistical analysis of extreme precipitation events

期刊

HYDROLOGY AND EARTH SYSTEM SCIENCES
卷 26, 期 19, 页码 5069-5084

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/hess-26-5069-2022

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  1. Federal Ministry of Education and Research (BMBF)
  2. State Office for the Environment, Measurements
  3. Nature Conservation of the Federal State of Baden-Wurttemberg (LUBW)
  4. Regierungsprasidium (governing council) Stuttgart

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Spatially explicit design storms are crucial for assessing flood risk and planning. This study presents a method to estimate these storms using statistically extended weather radar precipitation estimates. The results show that the spatial patterns of the design storms are more realistic in the weather-radar-based product, but the magnitude of the storms is generally lower. More research is needed to understand this discrepancy.
Spatially explicit quantification on design storms is essential for flood risk assessment and planning. Due to the limited temporal data availability from weather radar data, design storms are usually estimated on the basis of rainfall records of a few precipitation stations only that have a substantially long time coverage. To achieve a regional picture, these station-based estimates are spatially interpolated, incorporating a large source of uncertainty due to the typical low station density, in particular for short event durations. In this study we present a method to estimate spatially explicit design storms with a return period of up to 100 years on the basis of statistically extended weather radar precipitation estimates, based on the ideas of regional frequency analyses and subsequent bias correction. Associated uncertainties are quantified using an ensemble-sampling approach and event based bootstrapping. With the resulting dataset, we compile spatially explicit design storms for various return periods and event durations for the federal state of Baden Wurttemberg, Germany. We compare our findings with two reference datasets based on interpolated station estimates. We find that the transition in the spatial patterns of the design storms from a rather random (short-duration events, 15 min) to a more structured, orographically influenced pattern (long-duration events, 24 h) seems to be much more realistic in the weather-radar-based product. However, the absolute magnitude of the design storms, although bias-corrected, is still generally lower in the weather radar product, which should be addressed in future studies in more detail.

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