the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Augmenting the German weather radar network with vertically pointing cloud radars: implications of resolution and attenuation
Abstract. A beam-aware columnar vertical profile (BA-CVP) methodology that incorporates data of the national German operational radar network with the aim of augmenting vertically pointing cloud radars is introduced. The method uses polarimetric radar data collected in plan position indicator (PPI) scans of multiple operational radars and considers the contributions of each operational radar in a beam-aware manner. The results of the method are paired with measurements of a vertically pointing cloud radar located in range of the operational radars and compared to measurements of dedicated scanning radars collected in range height indicator (RHI) scans for two different case studies. The combination of side-looking operational radars in the BA-CVP format with a vertically pointing cloud radar allows the simultaneous exploitation of polarimetric multi-frequency observations including radar variables like the differential reflectivity, the dual-wavelength ratio, Doppler fall speed and linear depolarisation ratio measurements to study the microphysical properties of hydrometeors while not having to rely on the availability of dedicated scanning radars. The extracted BA-CVPs based on operational data deliver good results with respect to resolving finer details in radar reflectivity and differential reflectivity when compared to measurements of dedicated radars. Usage of differential phase measurements is discussed as marker for high hydrometeor attenuation affecting the measurements of radars far from the point of interest. For future use of this method, the coverage of the national German operational radar network is studied and recommendations for locations with potential for additional vertically pointing cloud radars are pointed out.
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RC1: 'Comment on egusphere-2025-691', Anonymous Referee #1, 09 Apr 2025
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AC1: 'Reply on RC1', Christian Heske, 27 May 2025
Dear Reviewer,
on behalf of all co-authors of this paper, I would like to express my gratitude and thank you for taking the time to evaluate the manuscript. Your valuable feedback has helped a lot to improve the paper. Please find our replies to your comments in the attachement.
Kind regards,
Christian Heske
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AC1: 'Reply on RC1', Christian Heske, 27 May 2025
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RC2: 'Comment on egusphere-2025-691', Anonymous Referee #2, 18 Apr 2025
This study introduces a beam-aware columnar vertical profile (BA-CVP) method that enhances the utility of Germany's operational weather radar network by integrating its PPI (plan position indicator) data with vertically pointing cloud radar observations. The aim is to improve microphysical analysis of hydrometeors—especially in areas where scanning radars are unavailable. The paper is generally well written and I only have a few comments require clarification.
Line 215-217, I’m a bit confused here as the C-band radar resolution is 50 m and the moving average window size is also 50 m?
Line 221, please elaborate on the reasoning as to why all dual-pol variables require Z based weighting? And how is done?
Line 300, for this paragraph, I’m not sure if I understand the BV-CVP extraction for PPI data. The traditional QVP/CVP method consider distance compared with center point of selection. Can you please demonstrate how the new BV-CVP differs from traditional CVP in this point? Most importantly, at higher elevations, the available scans are sparse, do you mean the BV-CVP can fill the gaps? But this can only be true in this study’s set up when you have more than one radar doing PPI scans nearby right?
Line 355-370, more clarification is needed here, how is hydrometeor induced attenuation is done? By only Z? Please elaborate on this.
Figure 8. Can you please add the difference between BV-CVP vs MIRA? Also, please extend this to Zdr, Kdp, and CC as well. In particular, a vertical profile of mean difference and their standard deviation are needed to quantify the difference.
Figure 11, for the 2nd case, it seems the higher resolution MHP are overly smoothed to lower resolution as in ISN and MEM, please justify the resolution degradation here.
Citation: https://doi.org/10.5194/egusphere-2025-691-RC2 -
AC2: 'Reply on RC2', Christian Heske, 27 May 2025
Dear Reviewer,
on behalf of all co-authors of this paper, I would like to express my gratitude and thank you for taking the time to evaluate the manuscript. Your valuable feedback has helped a lot to improve the paper. Please find our replies to your comments in the attachement.
Kind regards,
Christian Heske
-
AC2: 'Reply on RC2', Christian Heske, 27 May 2025
Status: closed
-
RC1: 'Comment on egusphere-2025-691', Anonymous Referee #1, 09 Apr 2025
-
AC1: 'Reply on RC1', Christian Heske, 27 May 2025
Dear Reviewer,
on behalf of all co-authors of this paper, I would like to express my gratitude and thank you for taking the time to evaluate the manuscript. Your valuable feedback has helped a lot to improve the paper. Please find our replies to your comments in the attachement.
Kind regards,
Christian Heske
-
AC1: 'Reply on RC1', Christian Heske, 27 May 2025
-
RC2: 'Comment on egusphere-2025-691', Anonymous Referee #2, 18 Apr 2025
This study introduces a beam-aware columnar vertical profile (BA-CVP) method that enhances the utility of Germany's operational weather radar network by integrating its PPI (plan position indicator) data with vertically pointing cloud radar observations. The aim is to improve microphysical analysis of hydrometeors—especially in areas where scanning radars are unavailable. The paper is generally well written and I only have a few comments require clarification.
Line 215-217, I’m a bit confused here as the C-band radar resolution is 50 m and the moving average window size is also 50 m?
Line 221, please elaborate on the reasoning as to why all dual-pol variables require Z based weighting? And how is done?
Line 300, for this paragraph, I’m not sure if I understand the BV-CVP extraction for PPI data. The traditional QVP/CVP method consider distance compared with center point of selection. Can you please demonstrate how the new BV-CVP differs from traditional CVP in this point? Most importantly, at higher elevations, the available scans are sparse, do you mean the BV-CVP can fill the gaps? But this can only be true in this study’s set up when you have more than one radar doing PPI scans nearby right?
Line 355-370, more clarification is needed here, how is hydrometeor induced attenuation is done? By only Z? Please elaborate on this.
Figure 8. Can you please add the difference between BV-CVP vs MIRA? Also, please extend this to Zdr, Kdp, and CC as well. In particular, a vertical profile of mean difference and their standard deviation are needed to quantify the difference.
Figure 11, for the 2nd case, it seems the higher resolution MHP are overly smoothed to lower resolution as in ISN and MEM, please justify the resolution degradation here.
Citation: https://doi.org/10.5194/egusphere-2025-691-RC2 -
AC2: 'Reply on RC2', Christian Heske, 27 May 2025
Dear Reviewer,
on behalf of all co-authors of this paper, I would like to express my gratitude and thank you for taking the time to evaluate the manuscript. Your valuable feedback has helped a lot to improve the paper. Please find our replies to your comments in the attachement.
Kind regards,
Christian Heske
-
AC2: 'Reply on RC2', Christian Heske, 27 May 2025
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