the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Layer-optimized SAR processing with a mobile phase-sensitive radar for detecting the deep englacial stratigraphy of Colle Gnifetti, Switzerland/Italy
Abstract. Radio-echo sounding is a standard technique for imaging the englacial stratigraphy of glaciers and ice sheets. In most cases, internal reflection horizons (IRHs) represent former glacier surfaces and comprise information about past accumulation, ice deformation and allow to link ice core chronologies. IRHs in the lower third of the ice column are often difficult to detect or coherently trace. In the polar ice sheets, progress in IRH detection has been made by using multistatic, phase-coherent radars, enabling synthetic-aperture radar (SAR) processing. However, these radar systems are often not suitable for deployment on mountain glaciers. We present a proof-of-concept study for a lightweight, phase-coherent, and ground-based radar system, based on the phase-sensitive radio echo-sounder (pRES). To improve the detectability of IRHs we additionally adapted a layer-optimized SAR (LO-SAR) processing scheme to this setup. We showcase the system capability at Colle Gnifetti, Switzerland/Italy, and detect significantly deeper and older IRHs compared to previously deployed pulsed radar systems. Continuous IRHs are now apparent down to the base of the glacier. Corresponding reflection mechanisms for this glacier are linked to a stratified acidic impurity which was deposited at a higher rate due to increased industrial activity in the area. Possible improvements of the system are discussed. If successfully implemented, these may provide a new way to map the deep internal structure of Colle Gnifetti and other mountain glaciers more extensively in future deployments.
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Notice on discussion status
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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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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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2731', Anonymous Referee #1, 07 Feb 2024
General comments:
This paper presents interesting results from a field survey of mountain glaciers at Colle Gnifetti using a phase-sensitive radio echo-sounder (pRES). The authors obtained the results with a layer-optimized SAR processing method, which is special in that it performs coherent summation over the synthetic aperture along an optimally estimated linear slope. The echograms from pRES revealed deeper internal reflection horizons (IRHs) that were not visible in the results from previous surveys with pulsed GPR. This data set is thus valuable for studying snow accumulation, ice flow and ice core chronologies in this area. The paper also provides valuable insights into different reflection mechanisms of the glacial IRHs at different depths by comparing radar data and ice core records. The algorithm of the tailored layer-optimized processing is an important part of the paper and aims to improve the detectability of IRHs. So, it is necessary to accurately assess the effectiveness of this algorithm in terms of the improvement in IRH detectability by comparing it with other methods that people have routinely been using in radar data processing. However, this paper does not have this kind of comparison and analysis, which is my major concern. The paper will be improved well for publication if this concern can be addressed.
Specific comments, questions, and suggestions:
- For the across-saddle and upstream profiles, it is desirable to see an echogram for each profile that is generated by applying a moving averaging filter of the same aperture length on each trace in Fig. 5 (c) and Fig. 5 (e). This averaging is like unfocused SAR processing without along-track decimation, which is much faster than the proposed LO-SAR processing. Because the phase shift due to slope has been corrected in reference phase substruction and thus the corrected phase is constant along the slope, this averaging is also similar to the coherent integration performed in the reference by Castelletti et al. (2019), i.e., the summation is not along the slope. By comparing these two echograms with Fig. 5 (d) and Fig. 5 (f), the improvement on IRH detectability by the proposed LO_SAR can be qualitatively and quantitatively analyzed and discussed.
- In 5.2 for discussions on slope estimation, the authors mentioned that “strong reflections spread out over several range bins, across which the raw phase tends to be stable”, and according to Fig. 5 (b), the “inclination relative to the surface is quantified during the LO-SAR processing and attains values of about 10° at both ends”. For the aperture length of 5 meters used in the processing, this inclination corresponds to only two range bins from one end of the aperture to the other end, therefore there might be no significant difference in performing the summation along the slope and not along the slope if the reflected power does not have big difference neither within two range bins. It would be helpful to demonstrate at what aperture length and at what slope angle the improvement of SNR for IRH detectability can be expected from the proposed LO-SAR.
- The iteration range of slopes used was from −30° to 30° in steps of 0.2°, much larger than the slop range observed in the data. Some discussion about smart selection of this range may be included in section 5.2 for reducing the computation intensity of the proposed LO-SAR.
- What was the data logger sampling rate used during data collection? 40kHz as discussed in section 5.1?
Technical corrections and suggestions:
- In Fig. 2 (a), the two legends are hard to distinguish, consider changing one of them with dashed line. The two red line segments for antennas need to explicitly be mentioned either in the figure caption or in text.
- In Fig. 3, missing information flow direction arrow along the line between the block for “Pre-processed mobile pRES data” and the block for “Moving median filtering of S”.
- Revise “by the weighting the values” to “by weighting the values” at line 166 on page 8.
- It is suggested to mark the crossover between the cross-saddle profile and the GPR profile, the crossover between the cross-saddle profile and the upstream profile towards KCC, and the crossover between the upstream profile towards KCC and the GPR profile with A, B and C respectively in Fig. 1, and according to mark those vertical white lines in Fig. 5 with A, B and C. It is much easier this way to identify these crossovers.
- The location of the white line to the right in Fig. 5 (a) does not match with the location of the crossover between the upstream profile towards KCC and the GPR profile in Fig. 1 which is at the very end of the GPS profile.
Citation: https://doi.org/10.5194/egusphere-2023-2731-RC1 -
AC1: 'Reply on RC1', Falk M. Oraschewski, 22 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2731/egusphere-2023-2731-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2023-2731', Benjamin Hills, 21 Feb 2024
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AC2: 'Reply on RC2', Falk M. Oraschewski, 22 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2731/egusphere-2023-2731-AC2-supplement.pdf
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AC2: 'Reply on RC2', Falk M. Oraschewski, 22 Apr 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2731', Anonymous Referee #1, 07 Feb 2024
General comments:
This paper presents interesting results from a field survey of mountain glaciers at Colle Gnifetti using a phase-sensitive radio echo-sounder (pRES). The authors obtained the results with a layer-optimized SAR processing method, which is special in that it performs coherent summation over the synthetic aperture along an optimally estimated linear slope. The echograms from pRES revealed deeper internal reflection horizons (IRHs) that were not visible in the results from previous surveys with pulsed GPR. This data set is thus valuable for studying snow accumulation, ice flow and ice core chronologies in this area. The paper also provides valuable insights into different reflection mechanisms of the glacial IRHs at different depths by comparing radar data and ice core records. The algorithm of the tailored layer-optimized processing is an important part of the paper and aims to improve the detectability of IRHs. So, it is necessary to accurately assess the effectiveness of this algorithm in terms of the improvement in IRH detectability by comparing it with other methods that people have routinely been using in radar data processing. However, this paper does not have this kind of comparison and analysis, which is my major concern. The paper will be improved well for publication if this concern can be addressed.
Specific comments, questions, and suggestions:
- For the across-saddle and upstream profiles, it is desirable to see an echogram for each profile that is generated by applying a moving averaging filter of the same aperture length on each trace in Fig. 5 (c) and Fig. 5 (e). This averaging is like unfocused SAR processing without along-track decimation, which is much faster than the proposed LO-SAR processing. Because the phase shift due to slope has been corrected in reference phase substruction and thus the corrected phase is constant along the slope, this averaging is also similar to the coherent integration performed in the reference by Castelletti et al. (2019), i.e., the summation is not along the slope. By comparing these two echograms with Fig. 5 (d) and Fig. 5 (f), the improvement on IRH detectability by the proposed LO_SAR can be qualitatively and quantitatively analyzed and discussed.
- In 5.2 for discussions on slope estimation, the authors mentioned that “strong reflections spread out over several range bins, across which the raw phase tends to be stable”, and according to Fig. 5 (b), the “inclination relative to the surface is quantified during the LO-SAR processing and attains values of about 10° at both ends”. For the aperture length of 5 meters used in the processing, this inclination corresponds to only two range bins from one end of the aperture to the other end, therefore there might be no significant difference in performing the summation along the slope and not along the slope if the reflected power does not have big difference neither within two range bins. It would be helpful to demonstrate at what aperture length and at what slope angle the improvement of SNR for IRH detectability can be expected from the proposed LO-SAR.
- The iteration range of slopes used was from −30° to 30° in steps of 0.2°, much larger than the slop range observed in the data. Some discussion about smart selection of this range may be included in section 5.2 for reducing the computation intensity of the proposed LO-SAR.
- What was the data logger sampling rate used during data collection? 40kHz as discussed in section 5.1?
Technical corrections and suggestions:
- In Fig. 2 (a), the two legends are hard to distinguish, consider changing one of them with dashed line. The two red line segments for antennas need to explicitly be mentioned either in the figure caption or in text.
- In Fig. 3, missing information flow direction arrow along the line between the block for “Pre-processed mobile pRES data” and the block for “Moving median filtering of S”.
- Revise “by the weighting the values” to “by weighting the values” at line 166 on page 8.
- It is suggested to mark the crossover between the cross-saddle profile and the GPR profile, the crossover between the cross-saddle profile and the upstream profile towards KCC, and the crossover between the upstream profile towards KCC and the GPR profile with A, B and C respectively in Fig. 1, and according to mark those vertical white lines in Fig. 5 with A, B and C. It is much easier this way to identify these crossovers.
- The location of the white line to the right in Fig. 5 (a) does not match with the location of the crossover between the upstream profile towards KCC and the GPR profile in Fig. 1 which is at the very end of the GPS profile.
Citation: https://doi.org/10.5194/egusphere-2023-2731-RC1 -
AC1: 'Reply on RC1', Falk M. Oraschewski, 22 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2731/egusphere-2023-2731-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-2731', Benjamin Hills, 21 Feb 2024
-
AC2: 'Reply on RC2', Falk M. Oraschewski, 22 Apr 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2731/egusphere-2023-2731-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Falk M. Oraschewski, 22 Apr 2024
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Falk M. Oraschewski
Inka Koch
M. Reza Ershadi
Jonathan Hawkins
Olaf Eisen
Reinhard Drews
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(5510 KB) - Metadata XML