05 Aug 2022
 | 05 Aug 2022
Status: this preprint is currently under review for the journal AMT.

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

Roberto Cremonini, Tanel Voormansik, Piia Post, and Dmitri Moisseev

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.

Roberto Cremonini et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-220', Anonymous Referee #1, 19 Sep 2022
    • AC1: 'Reply on RC1', Roberto Cremonini, 02 Nov 2022
      • EC1: 'Reply on AC1', Gianfranco Vulpiani, 03 Nov 2022
    • AC2: 'Reply on RC1', Roberto Cremonini, 23 Nov 2022
  • RC2: 'Comment on amt-2022-220', Anonymous Referee #2, 24 Sep 2022
    • AC3: 'Reply on RC2', Roberto Cremonini, 23 Nov 2022

Roberto Cremonini et al.

Roberto Cremonini et al.


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Short summary
Climatology of extreme rainfalls for a certain location is crucial for several applications. This study investigates the use of weather polarimetric data to estimate annual hourly maxima in Italy and Estonia. The results demonstrate that thanks to weather radar's high spatial resolution, even a limited-time series of polarimetric weather radar observations can provide reliable estimations of extreme values distribution parameters for rainfall maxima in climatological homogeneous regions.