Estimation of extreme precipitations in Estonia and Italy using dual-pol weather radar QPEs

crossref(2022)

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摘要
Abstract. Climatology of extreme rainfalls for a certain location is commonly taken into account designing stormwater management systems. Rain gauge data have often been used to estimate rainfall intensity for a given return period. However, the poor spatial and temporal resolution of operational gauges is the main limiting factor. Several studies have used rainfall estimates based on weather radar horizontal reflectivity (Zh), but they come with a significant caveat: while proven reliable on low or moderate rainfall rates, they are subject to major errors in extreme rainfall and convective cases. It is widely known that C-band weather radar can both underestimate precipitation intensity due to signal attenuation or overestimate it due to hail and clutter contamination. This study circumvents these shortcomings by using specific differential phase (Kdp) data from dual-polarization C-band weather radars. The rain intensity estimates based on specific differential phase are immune to attenuation and affected less by hail contamination. This study aims to estimate depth-duration-frequency (DDF) curves computed using polarimetric weather radar data using quantitative precipitation estimations (QPEs) based on Kdp data and to compare the results with the DDF curves derived using rain-gauge data. Only the warm period of the year is here considered, as most of the extreme precipitation events take place at this time. Limiting the dataset to warm period also allows us to use the radar-based rainfall quantitative precipitation estimates, which are more reliable than the snowfall ones. Single C-band polarimetric weather radar site data are used both from Italy and Estonia. This study demonstrates that polarimetric weather radar observations can provide reliable QPEs compared to rain gauges and, that even relatively short time series can provide a reliable estimation of the rainfall return periods in climatological homogeneous areas.
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