the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Feb 2024
Advantages of G-band radar in multi-frequency, liquid phase microphysical retrievals
Abstract. Radar based microphysical retrievals of cloud and droplet properties are vital for informing model parameterisations of clouds and precipitation but these retrievals often do not capture the details of small droplets in light rain or drizzle. A state-of-the-art G-band radar is used here to demonstrate improvements to microphysical retrievals in a case study featuring light rain. Improvements are seen, as compared to W-band radar, in the retrieval of vertical wind speed, due to the location of Mie minima at smaller droplet sizes with the G-band radar. This, in turn, has an impact on the retrieval of the drop size distribution, allowing for better accuracy in the retrieval of the characteristic drop diameter and improvements in the retrieval of the number of concentration of small droplet sizes. The differential Doppler velocity between Ka- and G-bands shows increased dynamic range compared to the Ka-W pairing, particularly for instances presenting small characteristic drop diameters. The increased attenuation experienced at G-band enables improved retrievals of liquid water content and precipitation rate when paired with W-band or Ka-band as compared to the W-band and Ka- band pairing. This is particularly noticeable in periods of light rain where the W-band and Ka-band radars receive negligible attenuation while the attenuation at G-band is much greater.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-205', Anonymous Referee #1, 06 Mar 2024
Summary of paper:
The authors are showing novel G-Band radar observations. In this contribution they are investigating if the addition of a G-Band radar improves multi-frequency retrievals of liquid microphysical properties. They are comparing the retrieval of the drop size distribution (DSD), median mass diameter (Dm) and vertical wind speed using different methods and combinations of Ka-Band, W-Band and the novel G-Band measurements. The addition of the G-Band radar improves the retrieval of the DSD and vertical wind speed, as the G-Band radar observes one or more Mie-notches in the Doppler spectra more frequently than the W-Band radar. Also, the Ka-G dual-wavelength ratio (DWR) is sensitive to much smaller particle sizes than DWR at Ka-W, allowing more accuracy in retrieving small droplet sizes. The larger liquid attenuation at G-Band compared to W or Ka-Band further allows a more accurate retrieval of the LWC.
General comments:
My main concerns arise from your frequent statements that the G-Band “improves clearly” the retrieval of various microphysical properties, while you are most of the time not showing any comparisons with in-situ observations or other independent measurements or you are not showing the retrieved quantity from both the Ka-G and Ka-W combination.
While I do agree that the G-Band likely improves the accuracy of the retrieval of the drop size distribution (DSD), the example you provide in the paper in my opinion does not show that the inclusion of the G-Band actually improves the accuracy of the retrieved DSD. Yes, the forward simulated spectra look more similar when you include the G-Band, however, that does not mean that the retrieved DSD is actually “more correct”. You have DSD measurements from the disdrometer, could you compare the DSD measurements with the retrievals? Or perhaps you could compare the forward simulated Doppler spectrum to the Doppler spectrum of a fourth, independent radar at a different wavelength which is not used in the retrieval if you have access to another radar.
Also, in your example using DDV to retrieve Dm, you are showing a comparison of Dm retrieved and Dm measured by the disdrometer, however, here I am missing a comparison to the retrieved Dm from the Ka-W DDV to actually show any improvements in comparison with the lower frequency pair. So my main point is: I do not think that you have shown clearly that the addition of the G-Band radar improves the retrieval of the DSD (or Dm), you have just shown that it can retrieve a DSD (which does not need to be accurate) and that the Dm you retrieve with the G-Band is rather accurate, however, you don’t show that the one retrieved from Ka-W is less accurate. I think the paper would benefit greatly if you include a more detailed comparison of the DSD with in-situ (or other) observations and if you compare the retrieved Dm not only with in-situ observations but also with the one retrieved from Ka-W.
Specific comments:
Line 32: what is the smallest D0 you can retrieve with W-Band? Please specify in the text.
Line 47: please specify what you mean with DDV (probably dual-doppler velocity)
Line 52: perhaps you could elaborate on why there may be double solutions for the DDV retrieval using two radar wavelengths?
Line 65: Do you mean above the freezing level? Below the freezing level ice can cause significant attenuation. Or do you mean below the freezing level in respect to the height? Then you should clarify that.
Line 80: remove “to this radiation”
Line 112: remove the second “the sensitivity”
Line 114-115: could you elaborate more on why there are small variations in the success of the G-Band detecting a Mie-notch?
Line 175: possibly “bad” data should be replaced with “unsuited” data
Line 177: why do you restrict the vertical wind speed to a maximum of 1.5m/s?
Line 182: Perhaps it would be better to call this section “Optimal estimation retrieval”, since OE has not been introduced yet
Line 188: is the G-Band 20 or 30 m away from the others? In the Methods section you said 20 m, here 30
Line 243: replace bad with another adjective
Figure 7c: why is the forward simulated W-band spectrum fitting so badly to the observed spectrum? Is the OE not working properly?
Line 268: I do not see clearly how the G-Band improves the differential Doppler velocities. Perhaps it would be helpful to show Ka-W in addition to Ka-G?
Line 273: why is the G-Band affected less by non-Rayleigh scattering in the ice phase? Ice particles do grow rather large and cause significant non-Rayleigh scattering already in W-Band right?
Figure 9: why do you not show the Dm retrieved from Ka-W? I thought that was the whole point of the paper, to show the benefits the addition of the G-Band could have compared to just having lower frequency radars
Line 284: Much better fit compared to what?
Line 303 and following: is there a way you can actually show that the LWC retrieved from the G-Band is more accurate than from the W-Band? I agree that it has a larger potential because the absolute values of PIA are larger, but does that actually make such a big difference?
Figure 10: could you please add units to the PIA and Dm in the plots?
All your Figures: it is probably a matter of taste, but I would rather have a label on the colorbar than having to search the figure caption for the description of what is plotted here. So I would suggest that you include colorbar labels
Citation: https://doi.org/10.5194/egusphere-2024-205-RC1 - AC1: 'Reply on RC1', Ben Courtier, 22 May 2024
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RC2: 'Comment on egusphere-2024-205', Anonymous Referee #2, 12 Mar 2024
The manuscript illustrates the advantage of including G-band radar measurements at 200GHz to retrievals of vertical wind speed and droplet size distribution (DSD) parameters. The authors describe the theoretically expected potential of including G-band measurements; introduce three different retrieval approaches (vertical wind; optimal estimation technique for DSD; Dm through differential Doppler velocity DDV), and evaluate the advantages based on one test case previously described in Courtier et al, 2022. While the presented case study of G-band measurements offers a lot of exciting material for the different retrievals presented, the main messages of the paper need to be strengthened to underline the advantages of the G-band.
General comments:
-GC1: The authors mention often throughout the text that including the G-band to their retrievals improves the retrievals compared to the KaW combination. Yet, I do not think that this message is underlined enough by the presented analysis and choice of figures. I would suggest two things: i) retrieved results including G-band should be compared in more depth to retrieved results using only Ka or W-band; ii) independent measurements should be taken into account to serve as “truth”. If independent measurements are not directly available, retrieval results using the different radars could also be compared to each other in forward simulated radar space.
-GC2: The authors base some of their results on the very powerful optimal estimation retrieval tool. Yet, not the full potential is exploited in the current analysis. I would suggest to analyse the advantages of including G-band by making use of eg the aposteriori errors and information content, and to compare these to the setup using conventional Ka-/W-band retrieval. These results should be illustrated in additional figures (also see specific comment on Fig 7 below).
-GC3: All analysis is based on a case study with light rain of 45 minutes in total. The different retrievals are applied to different times within the covered measurement phase. In my opinion, the advantage of including the G-band could be highlighted more by using all three retrievals for the same selected time stamp. This ‘golden case’ could be used as a synthesis bringing the different retrievals and advantage of the G-band together. It would also be interesting to include two different time stamps with different rainfall intensities to illustrate when the retrieval techniques (and advantages) are most or least beneficial.
Specific comments:
- This might be a matter of taste, but I would encourage the authors to embed subsections 1.1-1.3 in the overall introduction text without subsections. Strengths and drawbacks of the different retrievals introduced here should be sharpened to clarify the motivation for the study. The state-of-the-art for optimal estimation applications to retrieve DSDs needs to be added to the introduction.
- Sec 3.2: The presentation of the numerous different retrievals with each different inputs would benefit from an overview table summarizing each retrieval’s method, input measurement, output retrieved variable, reference to each method.
- Section titles should be chosen more consistently throughout the manuscript to facilitate the readers’ orientation. I would suggest to maintain naming the retrieval sections according to what variable is retrieved by what technique, and to keep the titles consistent between Sec. 3.2 and 4. For example, Sec. 3.2.2 could be renamed to ‘DSD retrieval using optimal estimation’. A description of the DDV retrieval method should be added to Sec. 3.2.
- L 162: what observations were used to monitor horizontal winds? At what height levels?
- Fig 5: a panel showing a flag when case studies were suitable to apply retrievals should be added (L162); and if available, a time line of IWV and maybe LWP, or at least state the IWV in the text (L168) to provide a framework of the stated attenuation. In order to compare Ka, W, and G, it would be nice to add a panel illustrating the W-band measurements for this case, and to add a sub-title to each panel clarifying which frequency is shown. Vertical lines or markers should be added at the DSD case study times chosen for Figs 7 and 10 (or the same time stamp could be picked, see GC3). Why are ice cloud features at 4km height more pronounced in G-band at 14:15 – 14:30, when attenuation is stronger in G-band?
- L 205: the text should include information on how the covariances were defined in the optimal estimation retrieval.
- L232: The authors should clarify in the text where they are pointing at in Fig 6b.
- L236 ff: This assumption should be underlined with an analysis of the existing data. The authors could show an example by eg zooming in on one time stamp (also see GC 3) to illustrate their hypothesis.
- Fig 7 b), d): It is unclear from the figure caption which radar is used for the presented retrieved DSDs. Retrieved DSDs seem to be dominated by the prior assumption, with little information from the observations. As stated in GC2, the potential that OE offers to analyse this case in more depth should be used here to clearly state the information gain by the observations compared to the prior (eg Degrees of Freedom for signal; Averaging Kernel; Jacobian), and benefits on retrieved error thanks to addition of the observations.
- Fig 9b): statistical measures of the comparison like RMSE, bias, correlation coefficient would highlight the comparison.
- Sec 4.4 and Fig 10: I would suggest to replace this figure with a plot showing the retrieved time line of LWC, LWP and rainfall (using Ka/W; and including G); or the retrieved LWC profile for a chosen time stamp (also see GC3) in order to underline the statement given in L298 and the section title. The rainfall retrieval could be evaluated with the independent observations given in Fig 5 top panel and illustrated eg in a scatter plot.
Technical details:
- labels should be added to all colorbars
- keep DSD (instead of PSD) as label for consistency throughout manuscript (eg Fig 7; L258)
- no abbreviations should be used in Section titles (Sec. 3.2.2, 4.2, 4.3)
- readability of the manuscript would benefit from shortening many sentences throughout the manuscript which stretch over multiple lines separated by commas (eg L110, 154, 161, 251).
Citation: https://doi.org/10.5194/egusphere-2024-205-RC2 - AC2: 'Reply on RC2', Ben Courtier, 22 May 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-205', Anonymous Referee #1, 06 Mar 2024
Summary of paper:
The authors are showing novel G-Band radar observations. In this contribution they are investigating if the addition of a G-Band radar improves multi-frequency retrievals of liquid microphysical properties. They are comparing the retrieval of the drop size distribution (DSD), median mass diameter (Dm) and vertical wind speed using different methods and combinations of Ka-Band, W-Band and the novel G-Band measurements. The addition of the G-Band radar improves the retrieval of the DSD and vertical wind speed, as the G-Band radar observes one or more Mie-notches in the Doppler spectra more frequently than the W-Band radar. Also, the Ka-G dual-wavelength ratio (DWR) is sensitive to much smaller particle sizes than DWR at Ka-W, allowing more accuracy in retrieving small droplet sizes. The larger liquid attenuation at G-Band compared to W or Ka-Band further allows a more accurate retrieval of the LWC.
General comments:
My main concerns arise from your frequent statements that the G-Band “improves clearly” the retrieval of various microphysical properties, while you are most of the time not showing any comparisons with in-situ observations or other independent measurements or you are not showing the retrieved quantity from both the Ka-G and Ka-W combination.
While I do agree that the G-Band likely improves the accuracy of the retrieval of the drop size distribution (DSD), the example you provide in the paper in my opinion does not show that the inclusion of the G-Band actually improves the accuracy of the retrieved DSD. Yes, the forward simulated spectra look more similar when you include the G-Band, however, that does not mean that the retrieved DSD is actually “more correct”. You have DSD measurements from the disdrometer, could you compare the DSD measurements with the retrievals? Or perhaps you could compare the forward simulated Doppler spectrum to the Doppler spectrum of a fourth, independent radar at a different wavelength which is not used in the retrieval if you have access to another radar.
Also, in your example using DDV to retrieve Dm, you are showing a comparison of Dm retrieved and Dm measured by the disdrometer, however, here I am missing a comparison to the retrieved Dm from the Ka-W DDV to actually show any improvements in comparison with the lower frequency pair. So my main point is: I do not think that you have shown clearly that the addition of the G-Band radar improves the retrieval of the DSD (or Dm), you have just shown that it can retrieve a DSD (which does not need to be accurate) and that the Dm you retrieve with the G-Band is rather accurate, however, you don’t show that the one retrieved from Ka-W is less accurate. I think the paper would benefit greatly if you include a more detailed comparison of the DSD with in-situ (or other) observations and if you compare the retrieved Dm not only with in-situ observations but also with the one retrieved from Ka-W.
Specific comments:
Line 32: what is the smallest D0 you can retrieve with W-Band? Please specify in the text.
Line 47: please specify what you mean with DDV (probably dual-doppler velocity)
Line 52: perhaps you could elaborate on why there may be double solutions for the DDV retrieval using two radar wavelengths?
Line 65: Do you mean above the freezing level? Below the freezing level ice can cause significant attenuation. Or do you mean below the freezing level in respect to the height? Then you should clarify that.
Line 80: remove “to this radiation”
Line 112: remove the second “the sensitivity”
Line 114-115: could you elaborate more on why there are small variations in the success of the G-Band detecting a Mie-notch?
Line 175: possibly “bad” data should be replaced with “unsuited” data
Line 177: why do you restrict the vertical wind speed to a maximum of 1.5m/s?
Line 182: Perhaps it would be better to call this section “Optimal estimation retrieval”, since OE has not been introduced yet
Line 188: is the G-Band 20 or 30 m away from the others? In the Methods section you said 20 m, here 30
Line 243: replace bad with another adjective
Figure 7c: why is the forward simulated W-band spectrum fitting so badly to the observed spectrum? Is the OE not working properly?
Line 268: I do not see clearly how the G-Band improves the differential Doppler velocities. Perhaps it would be helpful to show Ka-W in addition to Ka-G?
Line 273: why is the G-Band affected less by non-Rayleigh scattering in the ice phase? Ice particles do grow rather large and cause significant non-Rayleigh scattering already in W-Band right?
Figure 9: why do you not show the Dm retrieved from Ka-W? I thought that was the whole point of the paper, to show the benefits the addition of the G-Band could have compared to just having lower frequency radars
Line 284: Much better fit compared to what?
Line 303 and following: is there a way you can actually show that the LWC retrieved from the G-Band is more accurate than from the W-Band? I agree that it has a larger potential because the absolute values of PIA are larger, but does that actually make such a big difference?
Figure 10: could you please add units to the PIA and Dm in the plots?
All your Figures: it is probably a matter of taste, but I would rather have a label on the colorbar than having to search the figure caption for the description of what is plotted here. So I would suggest that you include colorbar labels
Citation: https://doi.org/10.5194/egusphere-2024-205-RC1 - AC1: 'Reply on RC1', Ben Courtier, 22 May 2024
-
RC2: 'Comment on egusphere-2024-205', Anonymous Referee #2, 12 Mar 2024
The manuscript illustrates the advantage of including G-band radar measurements at 200GHz to retrievals of vertical wind speed and droplet size distribution (DSD) parameters. The authors describe the theoretically expected potential of including G-band measurements; introduce three different retrieval approaches (vertical wind; optimal estimation technique for DSD; Dm through differential Doppler velocity DDV), and evaluate the advantages based on one test case previously described in Courtier et al, 2022. While the presented case study of G-band measurements offers a lot of exciting material for the different retrievals presented, the main messages of the paper need to be strengthened to underline the advantages of the G-band.
General comments:
-GC1: The authors mention often throughout the text that including the G-band to their retrievals improves the retrievals compared to the KaW combination. Yet, I do not think that this message is underlined enough by the presented analysis and choice of figures. I would suggest two things: i) retrieved results including G-band should be compared in more depth to retrieved results using only Ka or W-band; ii) independent measurements should be taken into account to serve as “truth”. If independent measurements are not directly available, retrieval results using the different radars could also be compared to each other in forward simulated radar space.
-GC2: The authors base some of their results on the very powerful optimal estimation retrieval tool. Yet, not the full potential is exploited in the current analysis. I would suggest to analyse the advantages of including G-band by making use of eg the aposteriori errors and information content, and to compare these to the setup using conventional Ka-/W-band retrieval. These results should be illustrated in additional figures (also see specific comment on Fig 7 below).
-GC3: All analysis is based on a case study with light rain of 45 minutes in total. The different retrievals are applied to different times within the covered measurement phase. In my opinion, the advantage of including the G-band could be highlighted more by using all three retrievals for the same selected time stamp. This ‘golden case’ could be used as a synthesis bringing the different retrievals and advantage of the G-band together. It would also be interesting to include two different time stamps with different rainfall intensities to illustrate when the retrieval techniques (and advantages) are most or least beneficial.
Specific comments:
- This might be a matter of taste, but I would encourage the authors to embed subsections 1.1-1.3 in the overall introduction text without subsections. Strengths and drawbacks of the different retrievals introduced here should be sharpened to clarify the motivation for the study. The state-of-the-art for optimal estimation applications to retrieve DSDs needs to be added to the introduction.
- Sec 3.2: The presentation of the numerous different retrievals with each different inputs would benefit from an overview table summarizing each retrieval’s method, input measurement, output retrieved variable, reference to each method.
- Section titles should be chosen more consistently throughout the manuscript to facilitate the readers’ orientation. I would suggest to maintain naming the retrieval sections according to what variable is retrieved by what technique, and to keep the titles consistent between Sec. 3.2 and 4. For example, Sec. 3.2.2 could be renamed to ‘DSD retrieval using optimal estimation’. A description of the DDV retrieval method should be added to Sec. 3.2.
- L 162: what observations were used to monitor horizontal winds? At what height levels?
- Fig 5: a panel showing a flag when case studies were suitable to apply retrievals should be added (L162); and if available, a time line of IWV and maybe LWP, or at least state the IWV in the text (L168) to provide a framework of the stated attenuation. In order to compare Ka, W, and G, it would be nice to add a panel illustrating the W-band measurements for this case, and to add a sub-title to each panel clarifying which frequency is shown. Vertical lines or markers should be added at the DSD case study times chosen for Figs 7 and 10 (or the same time stamp could be picked, see GC3). Why are ice cloud features at 4km height more pronounced in G-band at 14:15 – 14:30, when attenuation is stronger in G-band?
- L 205: the text should include information on how the covariances were defined in the optimal estimation retrieval.
- L232: The authors should clarify in the text where they are pointing at in Fig 6b.
- L236 ff: This assumption should be underlined with an analysis of the existing data. The authors could show an example by eg zooming in on one time stamp (also see GC 3) to illustrate their hypothesis.
- Fig 7 b), d): It is unclear from the figure caption which radar is used for the presented retrieved DSDs. Retrieved DSDs seem to be dominated by the prior assumption, with little information from the observations. As stated in GC2, the potential that OE offers to analyse this case in more depth should be used here to clearly state the information gain by the observations compared to the prior (eg Degrees of Freedom for signal; Averaging Kernel; Jacobian), and benefits on retrieved error thanks to addition of the observations.
- Fig 9b): statistical measures of the comparison like RMSE, bias, correlation coefficient would highlight the comparison.
- Sec 4.4 and Fig 10: I would suggest to replace this figure with a plot showing the retrieved time line of LWC, LWP and rainfall (using Ka/W; and including G); or the retrieved LWC profile for a chosen time stamp (also see GC3) in order to underline the statement given in L298 and the section title. The rainfall retrieval could be evaluated with the independent observations given in Fig 5 top panel and illustrated eg in a scatter plot.
Technical details:
- labels should be added to all colorbars
- keep DSD (instead of PSD) as label for consistency throughout manuscript (eg Fig 7; L258)
- no abbreviations should be used in Section titles (Sec. 3.2.2, 4.2, 4.3)
- readability of the manuscript would benefit from shortening many sentences throughout the manuscript which stretch over multiple lines separated by commas (eg L110, 154, 161, 251).
Citation: https://doi.org/10.5194/egusphere-2024-205-RC2 - AC2: 'Reply on RC2', Ben Courtier, 22 May 2024
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Benjamin Michael Courtier
Alessandro Battaglia
Kamil Mroz
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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