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| projects:hydrocolumn [2026/09/07 16:33] – ayush | projects:hydrocolumn [2026/09/12 19:33] (current) – ayush |
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| caption="Schematic of measurement setup and 1st | caption="Schematic of measurement setup and 1st |
| usable weather radar bin (~650m above radar). Adopted from Frech et al. (2017)." | usable weather radar bin (~650m above radar). Adopted from Frech et al. (2017)." |
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| src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_fig2_rime_mass.png" | src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_fig2_rime_mass.png" |
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| title="Figure 2" | title="Figure 2" |
| caption="Rime mass fraction estimated for three snow modes that were observed in birdbath scans at DWD's Hohen-peißenberg (blue and orange profiles) and Isen (pink profile) C-band radars. RMF ranges at each altitude indicate retrieval uncertainties of generally 20 to 30 %. Adapted from Gergely et al. (2022)." | caption="Rime mass fraction estimated for three snow modes that were observed in birdbath scans at DWD's Hohen-peißenberg (blue and orange profiles) and Isen (pink profile) C-band radars. RMF ranges at each altitude indicate retrieval uncertainties of generally 20 to 30 %. Adapted from Gergely et al. (2022)." |
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| A long-living supercell thunderstorm moved over Southeastern Germany on 30 April 2021 and the severe hail (hailstone diameters > 2 cm) caused substantial damage to agricultural crops and roof windows. The supercell moved directly over the Hohenpeißenberg radar, allowing for a detailed study of the radar characteristics of the supercell. Figure 3a shows the unfolded Doppler spectra that were recorded by the birdbath scan during the 5-min hail shower at the radar site. Figure 3b shows the distribution of hailstone sizes during the hail shower, determined from the Hailsens in situ sensor that estimates the hailstone diameters from the hail impact energies on a plastic disc of about 50 cm diameter, which is installed close to the ground. | A long-living supercell thunderstorm moved over Southeastern Germany on 30 April 2021 and the severe hail (hailstone diameters > 2 cm) caused substantial damage to agricultural crops and roof windows. The supercell moved directly over the Hohenpeißenberg radar, allowing for a detailed study of the radar characteristics of the supercell. Figure 3a shows the unfolded Doppler spectra that were recorded by the birdbath scan during the 5-min hail shower at the radar site. Figure 3b shows the distribution of hailstone sizes during the hail shower, determined from the Hailsens in situ sensor that estimates the hailstone diameters from the hail impact energies on a plastic disc of about 50 cm diameter, which is installed close to the ground. |
| src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_fig3_doppler_spectra.png" | src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_fig3_doppler_spectra.png" |
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| title="Figure 3" | title="Figure 3" |
| caption="(a) Profile of Doppler spectra recorded by the Hohenpeißenberg C-band radar during one birdbath scan as a supercell moved over the radar site; (b) Hail size distribution at the ground estimated from in situ hail sensor based on hailstone impact energies." | caption="(a) Profile of Doppler spectra recorded by the Hohenpeißenberg C-band radar during one birdbath scan as a supercell moved over the radar site; (b) Hail size distribution at the ground estimated from in situ hail sensor based on hailstone impact energies." |
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| Figure 3a illustrates the bimodal precipitation near the ground, consisting of both hail and rain. Additionally, hail melting and shedding (where frozen hail transitions into liquid rain) can be identified around 0 °C. Here, the 0 °C level is based on DWD's operational ICON-D2 atmospheric model (Zängl et al., 2015). Figure 3b represents one of only few hail in situ data sets where the full hail size distribution is sampled, instead of only including an estimate for a typical hail size or focusing on a single very large hailstone that is then assumed to specify the maximum hail size of the entire hail event. Here, we can fit an eponential hail size distribution to the in situ hail data with typical slope parameters of 0.2 < Λ < 0.4 mm-1. However, these automated in situ observations suggest a maximum hail size of much smaller than 2 cm, in contrast to manually performed hail size measurements of several particularly large hailstones with maximum dimensions of ≥ 2.0 cm. This suggests that there may be a systematic bias of the Hailsens calibration or that the Hailsens misses large hailstones due to sampling effects. | Figure 3a illustrates the bimodal precipitation near the ground, consisting of both hail and rain. Additionally, hail melting and shedding (where frozen hail transitions into liquid rain) can be identified around 0 °C. Here, the 0 °C level is based on DWD's operational ICON-D2 atmospheric model (Zängl et al., 2015). Figure 3b represents one of only few hail in situ data sets where the full hail size distribution is sampled, instead of only including an estimate for a typical hail size or focusing on a single very large hailstone that is then assumed to specify the maximum hail size of the entire hail event. Here, we can fit an eponential hail size distribution to the in situ hail data with typical slope parameters of 0.2 < Λ < 0.4 mm-1. However, these automated in situ observations suggest a maximum hail size of much smaller than 2 cm, in contrast to manually performed hail size measurements of several particularly large hailstones with maximum dimensions of ≥ 2.0 cm. This suggests that there may be a systematic bias of the Hailsens calibration or that the Hailsens misses large hailstones due to sampling effects. |
| src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_doppler_polarization.png" | src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:hydro_column_doppler_polarization.png" |
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| caption="(a) Summary of Doppler spectra in one polarization channel from birdbath scan recorded with the MOHp C-band radar during a winter precipitation event; (b) isolated weather signal, based on polarimetric characteristics and the developed machine-learning algorithm; horizontal dashed line indicates (c) one example of a bimodal Doppler spectrum, with peak intervals found by UniDip clustering and with final mode limits for calculating quantitative (multi)modal properties and uncertainty estimates." | caption="(a) Summary of Doppler spectra in one polarization channel from birdbath scan recorded with the MOHp C-band radar during a winter precipitation event; (b) isolated weather signal, based on polarimetric characteristics and the developed machine-learning algorithm; horizontal dashed line indicates (c) one example of a bimodal Doppler spectrum, with peak intervals found by UniDip clustering and with final mode limits for calculating quantitative (multi)modal properties and uncertainty estimates." |
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| Owing to the high flexibility in operating the MOHp C-band radar, e.g., for testing scan strategies or modifying range sampling intervals, we were able to carry out a combined measurement campaign of radar measurements and airborne in situ observations provided by the German Aerospace Center (DLR) Falcon research aircraft during the BLUESKY campaign (Voigt et al. 2021) within the PROM phase-1 POLICE project (Trömel et al. 2021). Figure 2 summarizes results from this campaign: high-resolution quasi-vertical profiles of polarimetric variables, vertically pointing Doppler measurements, short-term predicitions from the operational COSMO-D2 model (replaced by ICON-D2 in February 2021), and particle images collected in flight within a horizontal distance of about 20 km from the radar site and within 15 min of the radar measurements. Clearly, the polarimetric measurements already provide a great amount of information; the region of maximum ZDR and increasing Zh toward the ground approximately between altitude levels L3 and L4, for example, faithfully indicates the increased amount of preferentially horizontally oriented two-dimensional dendritic or plate-like frozen precipitation particles visible in the particle images around these levels. In the low-ZDR region sourrounding level L6, however, the polarimetric fingerprint alone does not provide a clear indication of whether the dominant precipitation process is aggregation or riming. Here, the Doppler measurements add valuable information, because the enhanced values up to about 1.8 m s<sup>-1</sup> indicate a transition from aggregates to moderately rimed particles. The particle images tend to confirm increasing riming of polycrystals and aggregates, especially when comparing them to the level L5. Finally, we can see in Figure 2c that transitions between regions of characteristic features in the radar data also correspond to changes in (thermo)dynamic variables obtained from COSMO-D2, e.g., the transition to low ZDR is also marked by a spike in Doppler spectra standard deviation and a change in the atmospheric wind speed and direction around -7 °C. | Owing to the high flexibility in operating the MOHp C-band radar, e.g., for testing scan strategies or modifying range sampling intervals, we were able to carry out a combined measurement campaign of radar measurements and airborne in situ observations provided by the German Aerospace Center (DLR) Falcon research aircraft during the BLUESKY campaign (Voigt et al. 2021) within the PROM phase-1 POLICE project (Trömel et al. 2021). Figure 2 summarizes results from this campaign: high-resolution quasi-vertical profiles of polarimetric variables, vertically pointing Doppler measurements, short-term predicitions from the operational COSMO-D2 model (replaced by ICON-D2 in February 2021), and particle images collected in flight within a horizontal distance of about 20 km from the radar site and within 15 min of the radar measurements. Clearly, the polarimetric measurements already provide a great amount of information; the region of maximum ZDR and increasing Zh toward the ground approximately between altitude levels L3 and L4, for example, faithfully indicates the increased amount of preferentially horizontally oriented two-dimensional dendritic or plate-like frozen precipitation particles visible in the particle images around these levels. In the low-ZDR region sourrounding level L6, however, the polarimetric fingerprint alone does not provide a clear indication of whether the dominant precipitation process is aggregation or riming. Here, the Doppler measurements add valuable information, because the enhanced values up to about 1.8 m s<sup>-1</sup> indicate a transition from aggregates to moderately rimed particles. The particle images tend to confirm increasing riming of polycrystals and aggregates, especially when comparing them to the level L5. Finally, we can see in Figure 2c that transitions between regions of characteristic features in the radar data also correspond to changes in (thermo)dynamic variables obtained from COSMO-D2, e.g., the transition to low ZDR is also marked by a spike in Doppler spectra standard deviation and a change in the atmospheric wind speed and direction around -7 °C. |
| src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:summary_of_data.png" | src="https://www2.meteo.uni-bonn.de/spp2115/lib/exe/fetch.php?media=projects:summary_of_data.png" |
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| title="Figure 2" | title="Figure 2" |
| caption="Summary of data collected during a spring precipitation event over MOHp C-band radar. (a) high-resolution quasi-vertical profiles (25° elevation scans) of polarimetric variables; (b) summary of birdbath scan with profiles of derived radar reflectivity (Zh), mean velocity, and standard deviation indicated by blue, yellow, and black lines, respectively; (c) several variables indicating the atmospheric (thermo)dynamics according to COSMO-D2 model short-term predictions; (L1-L9) particle images collected at altitudes indicated in panel a (modified from Trömel et al. 2021)." | caption="Summary of data collected during a spring precipitation event over MOHp C-band radar. (a) high-resolution quasi-vertical profiles (25° elevation scans) of polarimetric variables; (b) summary of birdbath scan with profiles of derived radar reflectivity (Zh), mean velocity, and standard deviation indicated by blue, yellow, and black lines, respectively; (c) several variables indicating the atmospheric (thermo)dynamics according to COSMO-D2 model short-term predictions; (L1-L9) particle images collected at altitudes indicated in panel a (modified from Trömel et al. 2021)." |
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| We have planned several upcoming combined measurement campaigns with DLR aircraft in situ observations where we will further investigate the co-variability of radar variables and weather forecast model outputs specifying the atmospheric (thermo)dynamics to characterize a more diverse set of precipitation conditions. Here, we also intend to build on first results for retrieving the rime mass fraction from the mean Doppler velocity (Kneifel and Moisseev 2020). In collaboration with TROPOS Leipzig, we continue to analyze the potential of using spectrally resolved C-band polarimetric measurements collected at various elevation angles for quantitative microphysical retrievals. | We have planned several upcoming combined measurement campaigns with DLR aircraft in situ observations where we will further investigate the co-variability of radar variables and weather forecast model outputs specifying the atmospheric (thermo)dynamics to characterize a more diverse set of precipitation conditions. Here, we also intend to build on first results for retrieving the rime mass fraction from the mean Doppler velocity (Kneifel and Moisseev 2020). In collaboration with TROPOS Leipzig, we continue to analyze the potential of using spectrally resolved C-band polarimetric measurements collected at various elevation angles for quantitative microphysical retrievals. |