the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Aug 2023
Water Vapor Measurements inside clouds and storms using a Differential Absorption Radar
Abstract. NASA’s Vapor In-cloud Profiling Radar (VIPR) is a tunable G-band radar designed for in-cloud and precipitation humidity remote sensing. VIPR estimates humidity using the differential absorption radar (DAR) technique. This technique exploits the difference between atmospheric attenuation at different frequencies (“on” and “off” an absorption line) and combines it with the ranging capabilities of the radar to estimate the absorbing gas concentration along the radar path.
We analyze the VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on East Coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, the High altitude Lidar Observatory – HALO) measurements. We discuss a comparison with dropsondes launched during these campaigns as well as an intercomparison against the ERA5 reanalysis fields. Thus, this study serves as an additional evaluation of ERA5 lower tropospheric humidity fields. In addition, we show a smooth transition in water vapor profiles between the in-cloud and clear-sky measurements obtained from VIPR and HALO respectively, which highlights the complementary nature of these two measurement techniques for future airborne and space-based missions.
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Preprint
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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-2023-1807', Anonymous Referee #1, 24 Sep 2023
The comments of “egusphere-2023-1807 Water Vapor Measurements inside clouds and storms using a Differential Absorption Radar” by Millán et al.
This article mainly uses the Differential absorption radar to measure the water vapor content in clouds and storms, the authors analyze the VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on East Coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, HALO) measurements. The comparison with the reanalysis data is also discussed. The results of this paper are undoubtedly of great significance for the measurement of the water vapor content in the cloud. The paper language expression is also good. Nevertheless, there are still some issues that need to be revised or clarified. Specific comments are as follows:
(1) The definition of differential absorption technology in the abstract can be considered into the introduction or section 2, because the differential absorption technology is relatively familiar to most professional readers of atmospheric measurement technology, and the quantitative research conclusions can be added in the abstract to clarify the scientific results of this work.
(2) In the first paragraph of the introduction, the discussion on the progress of water vapor measurement is lacking. It is suggested to increase the new technical progress and existing problems in this aspect, and the reference of response should be added.
(3) The second paragraph of the introduction on the scientific objectives of these two projects (NASA two field campaigns) and the issues to be addressed in this paper need to be strengthened.
(4) Table 1, The technical parameters required to increase the response such as signal to noise ratio, lowest detection line, detection distance and detection sensitivity, and suggest add a physical physical picture VIPR system and Hardware composition diagram.
(5) Figure 1 What is the basis of setting the flight trajectory?
(6) Figure 3. Shows the Power spectrum examples at 167.12 GHz for a clear sky and a cloudy scene, Do the other two frequencies (158.6, 174.74 GHz) have a similar conclusion and use the same data processing method?
(7) Where the Equation 3 comes from?
(8) In section 3 Retrieval methodology and datasets used for comparisons, recommended to add a flow chart.
(9) section 4 Vapor Profile Results, personal feeling it is a bit like an experimental report, rather than a scientific research paper, it is suggested to increase the regularity of the conclusion or the discovery of the elaboration, to improve the academic nature of the paper.
Citation: https://doi.org/10.5194/egusphere-2023-1807-RC1 - AC1: 'Reply on RC1', Luis Millan, 22 Nov 2023
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RC2: 'Comment on egusphere-2023-1807', Anonymous Referee #2, 23 Oct 2023
This study presents airborne measurements collected by the VIPR instrument during two recent field studies, IMPACTS and SOA2RSE. The authors describe the retrieval to derive water vapor profiles and partial column estimates by using the Differential Absorption Radar technique, accounting for differential hydrometeor scattering by including a third frequency. Water Vapor estimates are compared to dropsondes and ERA5 fields. The complementing nature of DAR and DIAL is illustrated in examples from the SOA2RSE flights.
General Comments
Overall, I find this paper to be a nice contribution to the newly emerging DAR G-band radar field. It is impressive to see how well the VIPR system performs from an airborne platform. The language of the paper is clear, especially the methodological part is well written, and Figures are generally clear. Yet, I think that the scientific content of the paper can be enhanced by sharpening the results sections. The analysis of the DAR-DIAL synergy in particular, a major novelty in the field, deserves a more thorough quantification and analysis.Specific Comments
- LL 1-28: the introduction should contain more references to available literature, and a more thorough introduction on the VIPR instrument, as well as available literature on ERA-5 evaluation.- L 152: are there thin clouds that the radar is insensitive to, or which are filtered out by the phase noise model? Characterizing VIPR‘s sensitivity in more detail could also be highlighted in the synergy with DIAL (see comments Sec. 6). Sensitivity information should be added to Tab 1.
- Sec. 3.1: The 2-frequency DAR method is described in detail, summarizing previous literature (Roy et al 2018, Roy et al 2020, Battaglia and Kollias 2019). The analyses in the paper highlight the benefit of using the 3-frequency DAR method to mitigate differential scattering effects on the water vapor retrieval. I would recommend to shorten the 2-frequency description as this method has been described in detail in literature, while the modifications necessary to the retrieval to embed the 3rd frequency should be highlighted, e.g. in Eq (13) and LL205-210.
- L 252: The authors should clarify why they don‘t use the results with improved precision in their analysis instead.
- L 281: I understand that ERA5 gives an hourly snapshot with a resolution of 31km; airborne data is averaged to 10km and 1min. How do the authors account for differences due to these temporal and spatial scales of the VIPR-ERA5 comparison? By interpolating the model to the airborne data, the model output gets oversampled. In order to avoid such spatial and vertical oversampling of the model pixels, the comparison should rather be performed on model resolution. This would additionally allow to quantify the model‘s sub-pixel variability. How strongly does the performance of VIPR-ERA5 depend on this variability?
- I recommend to edit the figures in Secs 2 and 3 to increase clarity and reduce the manuscript‘s length. More specifically, I would suggest to:
- combine Fig 1a and b in one panel
- drop Fig 2: readily available in literature (eg Roy et al 2018, Fig 3)
- Fig 3: add bottom row to upper panel to reduce to two panels
- reshuffle Figure 4 and 5, e.g. by adding the bottom panel of Fig 5 below Fig 4; and combining most right panel Fig 4 with three panels Fig 5.- Section 4: To tighten the argument, I would suggest to re-order the analysis presented in this Section as follows: first, evaluate the VIPR retrieval with dropsondes, highlighting differences between 2- and 3-frequency retrieval; then, assess ERA-5 with airborne measurements.
- LL295 – 312: I propose to move some of this information to the description of the flights in Tab 2, LL73, respectively, to focus on the scientific messages.
- LL313 – 348 and Fig 7 and 8: The analysis presented here, in my view, remains very descriptive. My suggestion is to pick a couple of case studies in which main caveats of the VIPR-ERA5 comparison are highlighted, even in a timeline comparison. I would suggest to plot VIPR at top, ERA5 at bottom on the same time axis to ease the visual intercomparison. A time line of VIPR‘s water vapor could instead be added to Fig 6 to give the reader a direct illustration of reflectivity and water vapor product.
It would be great to have some additional measurement overview statistics summarized in a Table, e.g.: how many dropsondes measured in cloudy, precipitating or clear conditions? How many VIPR columns were affected by attenuation part-way through the column?- Figs 6-9: adding the height of the melting layer would be an important additional piece of information.
- LL 349: the authors state the detection noise as one of the reasons for mis-matches between VIPR and ERA-5 water vapor. The lidar measurements should be used to quantify the detection noise; and to assess the impact on the comparison to ERA5.
- LL 358: The authors should motivate the chosen 10 minute averaging interval. How sensitive is the comparison to this interval? I think that the evaluation of the VIPR retrievals with respect to dropsondes should be analysed before the ERA5 assessment (see comment above) as retrieval evaluation.
- Fig 10: Please motivate the choice of dropsondes presented here. I would suggest to highlight attenuation effects as well as differential scattering impacts by illustrating the retrieval performance for examples of profiles with attenuation effects; with best retrieval performance; and for solid/liquid precipitation occurrence.
- LL 371: I wonder if one way around this could be to sample the dropsondes depending on the conditions at launch (cloudy, clear, precipitating) to avoid artefacts. Please also state how many dropsondes were used for the presented statistical comparison (see eg comment LL313 with suggestion to include a table).
- Section 6 is very short and vague compared to Sec 4 and 5 while it is in my opinion one of the most novel findings of the paper. The authors should thoroughly quantify the synergistic benefits of the two instruments. The following questions could guide the analyses: How well do clear-sky pCWV agree etween the two instruments? What happens at the edges from clear-sky to cloudy, when DIAL and DAR water vapor profiles follow one another temporally? How well do water vapor observations agree above cloud top (DIAL profile vs DAR pCWV)? I would suggest to add a Figure similar to Fig 13 to analyse the clear-sky pCWV.
- Fig 14: It is nice to get an overview of the different measurements and retrieved water vapor profiles, but it is hard to catch details of the instrument synergy from the current Figure. A Figure should be added, e.g. to zoom in on the DIAL and DAR-derived water vapor curtains around cloud edges to illustrate the different vertical resolutions and quality of the retrieved profiles. The authors should also comment on the performance of the synergy for the 03-04 and 03-07 flights.
- The authors should add a paragraph in the Conclusions on future perspectives available from the presented measurements and results.
Technical Corrections
- SI units should be used for water vapor and pCWV throughout the entire manuscript (kgm-2; gm-3).
- L 154: clarify where the reader should be directed to in the figure
- L 200 ff: sentence not complete.
- L 231: should read: if more than […]
- LL 380 and further, also conclusion: see above; unit should be gm-3
- L407: „shows and overestimation of up to 80%“ relative to what?
- L420: introduce LNA abbreviation
- Fig 11 caption contains multiple typos
- L479: „Thess“ should be „these“
- L492: contains multiple typosCitation: https://doi.org/10.5194/egusphere-2023-1807-RC2 - AC2: 'Reply on RC2', Luis Millan, 22 Nov 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1807', Anonymous Referee #1, 24 Sep 2023
The comments of “egusphere-2023-1807 Water Vapor Measurements inside clouds and storms using a Differential Absorption Radar” by Millán et al.
This article mainly uses the Differential absorption radar to measure the water vapor content in clouds and storms, the authors analyze the VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on East Coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, HALO) measurements. The comparison with the reanalysis data is also discussed. The results of this paper are undoubtedly of great significance for the measurement of the water vapor content in the cloud. The paper language expression is also good. Nevertheless, there are still some issues that need to be revised or clarified. Specific comments are as follows:
(1) The definition of differential absorption technology in the abstract can be considered into the introduction or section 2, because the differential absorption technology is relatively familiar to most professional readers of atmospheric measurement technology, and the quantitative research conclusions can be added in the abstract to clarify the scientific results of this work.
(2) In the first paragraph of the introduction, the discussion on the progress of water vapor measurement is lacking. It is suggested to increase the new technical progress and existing problems in this aspect, and the reference of response should be added.
(3) The second paragraph of the introduction on the scientific objectives of these two projects (NASA two field campaigns) and the issues to be addressed in this paper need to be strengthened.
(4) Table 1, The technical parameters required to increase the response such as signal to noise ratio, lowest detection line, detection distance and detection sensitivity, and suggest add a physical physical picture VIPR system and Hardware composition diagram.
(5) Figure 1 What is the basis of setting the flight trajectory?
(6) Figure 3. Shows the Power spectrum examples at 167.12 GHz for a clear sky and a cloudy scene, Do the other two frequencies (158.6, 174.74 GHz) have a similar conclusion and use the same data processing method?
(7) Where the Equation 3 comes from?
(8) In section 3 Retrieval methodology and datasets used for comparisons, recommended to add a flow chart.
(9) section 4 Vapor Profile Results, personal feeling it is a bit like an experimental report, rather than a scientific research paper, it is suggested to increase the regularity of the conclusion or the discovery of the elaboration, to improve the academic nature of the paper.
Citation: https://doi.org/10.5194/egusphere-2023-1807-RC1 - AC1: 'Reply on RC1', Luis Millan, 22 Nov 2023
-
RC2: 'Comment on egusphere-2023-1807', Anonymous Referee #2, 23 Oct 2023
This study presents airborne measurements collected by the VIPR instrument during two recent field studies, IMPACTS and SOA2RSE. The authors describe the retrieval to derive water vapor profiles and partial column estimates by using the Differential Absorption Radar technique, accounting for differential hydrometeor scattering by including a third frequency. Water Vapor estimates are compared to dropsondes and ERA5 fields. The complementing nature of DAR and DIAL is illustrated in examples from the SOA2RSE flights.
General Comments
Overall, I find this paper to be a nice contribution to the newly emerging DAR G-band radar field. It is impressive to see how well the VIPR system performs from an airborne platform. The language of the paper is clear, especially the methodological part is well written, and Figures are generally clear. Yet, I think that the scientific content of the paper can be enhanced by sharpening the results sections. The analysis of the DAR-DIAL synergy in particular, a major novelty in the field, deserves a more thorough quantification and analysis.Specific Comments
- LL 1-28: the introduction should contain more references to available literature, and a more thorough introduction on the VIPR instrument, as well as available literature on ERA-5 evaluation.- L 152: are there thin clouds that the radar is insensitive to, or which are filtered out by the phase noise model? Characterizing VIPR‘s sensitivity in more detail could also be highlighted in the synergy with DIAL (see comments Sec. 6). Sensitivity information should be added to Tab 1.
- Sec. 3.1: The 2-frequency DAR method is described in detail, summarizing previous literature (Roy et al 2018, Roy et al 2020, Battaglia and Kollias 2019). The analyses in the paper highlight the benefit of using the 3-frequency DAR method to mitigate differential scattering effects on the water vapor retrieval. I would recommend to shorten the 2-frequency description as this method has been described in detail in literature, while the modifications necessary to the retrieval to embed the 3rd frequency should be highlighted, e.g. in Eq (13) and LL205-210.
- L 252: The authors should clarify why they don‘t use the results with improved precision in their analysis instead.
- L 281: I understand that ERA5 gives an hourly snapshot with a resolution of 31km; airborne data is averaged to 10km and 1min. How do the authors account for differences due to these temporal and spatial scales of the VIPR-ERA5 comparison? By interpolating the model to the airborne data, the model output gets oversampled. In order to avoid such spatial and vertical oversampling of the model pixels, the comparison should rather be performed on model resolution. This would additionally allow to quantify the model‘s sub-pixel variability. How strongly does the performance of VIPR-ERA5 depend on this variability?
- I recommend to edit the figures in Secs 2 and 3 to increase clarity and reduce the manuscript‘s length. More specifically, I would suggest to:
- combine Fig 1a and b in one panel
- drop Fig 2: readily available in literature (eg Roy et al 2018, Fig 3)
- Fig 3: add bottom row to upper panel to reduce to two panels
- reshuffle Figure 4 and 5, e.g. by adding the bottom panel of Fig 5 below Fig 4; and combining most right panel Fig 4 with three panels Fig 5.- Section 4: To tighten the argument, I would suggest to re-order the analysis presented in this Section as follows: first, evaluate the VIPR retrieval with dropsondes, highlighting differences between 2- and 3-frequency retrieval; then, assess ERA-5 with airborne measurements.
- LL295 – 312: I propose to move some of this information to the description of the flights in Tab 2, LL73, respectively, to focus on the scientific messages.
- LL313 – 348 and Fig 7 and 8: The analysis presented here, in my view, remains very descriptive. My suggestion is to pick a couple of case studies in which main caveats of the VIPR-ERA5 comparison are highlighted, even in a timeline comparison. I would suggest to plot VIPR at top, ERA5 at bottom on the same time axis to ease the visual intercomparison. A time line of VIPR‘s water vapor could instead be added to Fig 6 to give the reader a direct illustration of reflectivity and water vapor product.
It would be great to have some additional measurement overview statistics summarized in a Table, e.g.: how many dropsondes measured in cloudy, precipitating or clear conditions? How many VIPR columns were affected by attenuation part-way through the column?- Figs 6-9: adding the height of the melting layer would be an important additional piece of information.
- LL 349: the authors state the detection noise as one of the reasons for mis-matches between VIPR and ERA-5 water vapor. The lidar measurements should be used to quantify the detection noise; and to assess the impact on the comparison to ERA5.
- LL 358: The authors should motivate the chosen 10 minute averaging interval. How sensitive is the comparison to this interval? I think that the evaluation of the VIPR retrievals with respect to dropsondes should be analysed before the ERA5 assessment (see comment above) as retrieval evaluation.
- Fig 10: Please motivate the choice of dropsondes presented here. I would suggest to highlight attenuation effects as well as differential scattering impacts by illustrating the retrieval performance for examples of profiles with attenuation effects; with best retrieval performance; and for solid/liquid precipitation occurrence.
- LL 371: I wonder if one way around this could be to sample the dropsondes depending on the conditions at launch (cloudy, clear, precipitating) to avoid artefacts. Please also state how many dropsondes were used for the presented statistical comparison (see eg comment LL313 with suggestion to include a table).
- Section 6 is very short and vague compared to Sec 4 and 5 while it is in my opinion one of the most novel findings of the paper. The authors should thoroughly quantify the synergistic benefits of the two instruments. The following questions could guide the analyses: How well do clear-sky pCWV agree etween the two instruments? What happens at the edges from clear-sky to cloudy, when DIAL and DAR water vapor profiles follow one another temporally? How well do water vapor observations agree above cloud top (DIAL profile vs DAR pCWV)? I would suggest to add a Figure similar to Fig 13 to analyse the clear-sky pCWV.
- Fig 14: It is nice to get an overview of the different measurements and retrieved water vapor profiles, but it is hard to catch details of the instrument synergy from the current Figure. A Figure should be added, e.g. to zoom in on the DIAL and DAR-derived water vapor curtains around cloud edges to illustrate the different vertical resolutions and quality of the retrieved profiles. The authors should also comment on the performance of the synergy for the 03-04 and 03-07 flights.
- The authors should add a paragraph in the Conclusions on future perspectives available from the presented measurements and results.
Technical Corrections
- SI units should be used for water vapor and pCWV throughout the entire manuscript (kgm-2; gm-3).
- L 154: clarify where the reader should be directed to in the figure
- L 200 ff: sentence not complete.
- L 231: should read: if more than […]
- LL 380 and further, also conclusion: see above; unit should be gm-3
- L407: „shows and overestimation of up to 80%“ relative to what?
- L420: introduce LNA abbreviation
- Fig 11 caption contains multiple typos
- L479: „Thess“ should be „these“
- L492: contains multiple typosCitation: https://doi.org/10.5194/egusphere-2023-1807-RC2 - AC2: 'Reply on RC2', Luis Millan, 22 Nov 2023
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Luis F. Millan
Matthew D. Lebsock
Ken B. Cooper
Jose V. Siles
Robert Dengler
Raquel Rodriguez Monje
Amin Nehrir
Rory A. Barton-Grimley
James E. Collins
Claire E. Robinson
Kenneth L. Thornhill
Holger Vömel
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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