2020Unpublished venueOpen access

Use of dual-polarization weather radar quantitative precipitation estimation for climatology

Tanel Voormansik, Roberto Cremonini, Piia Post, Dmitri Moisseev

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Abstract

Abstract. Accurate, timely and reliable precipitation observations are mandatory for hydrological forecast and early warning systems. In the case of convective precipitations, traditional rain gauges networks often miss precipitation maxima, due to density limitations and high spatial variability of rainfall field. Despite several limitations like attenuation or partial beam-blockings, the use of C-band weather radar has become operational in most of European weather services. Traditionally, weather radar-based quantitative precipitation estimation (QPE) are derived by horizontal reflectivity data. Nevertheless, dual-polarization weather radar can overcome a number of shortcomings of the legacy horizontal reflectivity based estimation. For the first time, the present study analyses one of the longest datasets from fully operational polarimetric C-band weather radars; those ones are located in Estonia and in Italy, in very different climate conditions and environments. The study focuses on long-term observations of summertime precipitation and their quantitative estimations by polarimetric observations. From such derived QPEs accumulations for 1 hour, 24 hours and one month durations are calculated and compared with reference rain gauges to quantify uncertainties and evaluate performances.

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Abstract. Accurate, timely and reliable precipitation observations are mandatory for hydrological forecast and early warning systems. In the case of convective precipitations, traditional rain gauges networks often miss precipitation maxima, due to density limitations and high spatial variability of rainfall field. Despite several limitations like attenuation or partial beam-blockings, the use of C-band weather radar has become operational in most of European weather services. Traditionally, weather radar-based quantitative precipitation estimation (QPE) are derived by horizontal reflectivity data. Nevertheless, dual-polarization weather radar can overcome a number of shortcomings of the legacy horizontal reflectivity based estimation. For the first time, the present study analyses one of the longest datasets from fully operational polarimetric C-band weather radars; those ones are located in Estonia and in Italy, in very different climate conditions and environments. The study focuses on long-term observations of summertime precipitation and their quantitative estimations by polarimetric observations. From such derived QPEs accumulations for 1 hour, 24 hours and one month durations are calculated and compared with reference rain gauges to quantify uncertainties and evaluate performances.

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Available abstract

Abstract. Accurate, timely and reliable precipitation observations are mandatory for hydrological forecast and early warning systems. In the case of convective precipitations, traditional rain gauges networks often miss precipitation maxima, due to density limitations and high spatial variability of rainfall field. Despite several limitations like attenuation or partial beam-blockings, the use of C-band weather radar has become operational in most of European weather services. Traditionally, weather radar-based quantitative precipitation estimation (QPE) are derived by horizontal reflectivity data. Nevertheless, dual-polarization weather radar can overcome a number of shortcomings of the legacy horizontal reflectivity based estimation. For the first time, the present study analyses one of the longest datasets from fully operational polarimetric C-band weather radars; those ones are located in Estonia and in Italy, in very different climate conditions and environments. The study focuses on long-term observations of summertime precipitation and their quantitative estimations by polarimetric observations. From such derived QPEs accumulations for 1 hour, 24 hours and one month durations are calculated and compared with reference rain gauges to quantify uncertainties and evaluate performances.

Key concepts: Quantitative precipitation estimation, Weather radar, Radar, Precipitation, Environmental science, Rain gauge, Meteorology, Polarimetry

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