the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Oct 2024
Assessment of Sentinel-3 Altimeter Performance over Antarctica using High Resolution Digital Elevation Models
Abstract. Since 2016, the Sentinel-3 satellites have provided a continuous record of ice sheet elevation and elevation change. Given the unique, operational nature of the mission, and the planned launch of two additional satellites before the end of this decade, it is important to determine the performance of the altimeter across a range of ice sheet topographic surfaces. Whilst previous studies have assessed elevation accuracy, more detailed investigations of the underlying instrument and processor performance are lacking. This study therefore examines the performance of the Sentinel-3 Synthetic Aperture Radar (SAR) altimeter over the Antarctic Ice Sheet (AIS), utilising new detailed topographic information from the Reference Elevation Model of Antarctica (REMA). Applying Singular Value Decomposition to REMA, we firstly develop new self-consistent Antarctic surface slope and roughness datasets. We then use these datasets to assess altimeter performance across different topographic regimes, targeting a number of key steps in the altimeter processing chain. We also evaluate the impact of topography upon waveform decorrelation. We find that, for 90 % of acquisitions, the point of closest approach to the satellite is successfully captured within the Level-1b range window. However, performance degrades with increasing topographic complexity, and this also affects the capacity to record all backscattered energy from within the beam footprint. We find that 24 % of the ice sheet exhibits greater topographic variance within the footprint than can be captured by the range window, and that the window placement captures a median of 90 % of the total possible topography that could be recorded. These findings provide a better understanding of the performance of the Sentinel-3 altimeters over ice sheets, and can guide the design and optimisation of future satellite missions such as the Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL).
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RC1: 'Comment on egusphere-2024-3054', Anonymous Referee #1, 28 Nov 2024
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General comments:
- This study evaluates the performance of the Sentinel-3 SAR altimeter over the Antarctic Ice Sheet using the REMA DEM. It finds that 90% of acquisitions capture the POCA within the Level-1b range window, but performance declines in complex terrain, missing 24% of topographic variance. The findings highlight limitations in capturing backscattered energy over steep or rough surfaces and provide insights to guide improvements for future missions like CRISTAL.
- The study is using REMA as a baseline for applying a SVD analysis to generate self-consistent surface slope and roughness datasets for the Antarctic Ice Sheet.The S3 altimeter performance is assessed by evaluating different topographic regimes by analysing the relationship between surface complexity and altimeter data quality. Furthermore, a waveform decorrelation analysis is made to assess the along-track impact of topography on waveform decorrelation to understand how varying terrain affects signal quality and backscattered energy capture.
- The methods and results concerning slope and roughness are well-executed and insightful.
- The research is valuable, addressing a gap in the literature. However, it’s disappointing that the authors did not utilize the latest Sentinel-3 processing (B005), which has been available for over a year and addresses some of the highlighted issues. While the conclusions might remain valid with the reprocessed dataset, the omission weakens the study, as this remains uncertain. To make the impact the manuscript deserves, I suggest redoing the study using B005; at the very least, the new processed data should be mentioned, and what impacts the new processing has on this study.
- The technical depth of the manuscript is inconsistent. For instance, the detailed reviews of retracking, REMA, and OCOG may not be necessary. In favor of the authors, they do present the topics in a clear and accessible manner, making them useful for newcomers.
Specific comments:
Principal of radar altimetry:
- Page 2-3, Lines 55-73: While textbook examples exist, the authors provide an exceptionally clear and convincing explanation. It could be highly beneficial for newcomers, though its relevance to this study should be carefully considered.
- P3: Surface Tracking: For your information, Several places over Antarctica have been changed to open-loop acquisitions in 2021 and 2024. It would be nice to see if that has had a positive impact.
- P4, L48 Retrackers: You mention OCOG as part of S3 ground segment. True, but S3 products also include the UCL ice retracker, a beta-retracker or model-fit retracker (Wingham and Wallies, 2010).
Data:
- A fundamental weakness is choosing not to use the B005 Thematic Land Ice product, released over a year ago and specifically designed for land ice. This product uses extended window processing optimized for rough or steeply sloping surfaces. Further information is available in the B005 Validation Report: https://sentiwiki.copernicus.eu/__attachments/1681931/S3MPC-STM_RP_0114%20-%20Reprocessing%20Campaign%20BC005%20Validation%20Report%202023%20-%201.1.pdf?inst-v=bd8109db-ca17-4318-bc73-caad47319d7e and the data is currently in review in Nature Scientific Data by J. Aublanc.
- Resampling REMA to 200 m, why? Have you considered using ICESat-2's gridded products?
Methodology:
- P6, L238: Results interpreted as 68% of the roughness variance. Where does this number come from?
- I am unfamiliar with the word seed waveform, but I assume it is a kind of a "first" waveform. How do you determine this seed waveform? Is it unclear if you calculate all waveforms as seed and then calculate the correlation to the 50 subsequent waveforms, or if the seed waveform is specially chosen?
Results:
- P13, L3556-358: 23.7% of echoes are not captured within 60m range window. Could you elaborate on the discussion? Could this be solved with the current S3 setup? Is it only a SWOT processing that would solve the problem? I am missing some consideration of the ability to change the on-board tracking modes for S3.
- P14, L363: It would be nice to see how data processing baseline B005 performs. or at least discuss why it would still be an issue with the new dataset.
- P15, L370: Please elaborate on what you mean about this statement
- P16, L401-403 : The results of LPCs are fine, but again this is not what was improved by S3 processing baseline B005?
- Fig 5/6(b): It would be nice if the blue and purple colors were more distinct, but it is impossible to differentiate between the colors on the map.
- A along-track correlation study demonstrates that slope and roughness impact the result. We also see this in how the elevations are having trouble wrt. REMA or IceSat-2 results in the marginal zone. What do we gain from this method? Is this method better? It sounds like it takes a large amount of computational power.
- How does S3 perform in this sense compared to other altimeter satellites?
Technical comments:
- P6, L182: the dataset name appears to be incorrect ("S2_2_LAND__"); it should be "S3_2_LAN__".
Citation: https://doi.org/10.5194/egusphere-2024-3054-RC1 -
CC1: 'Comment on egusphere-2024-3054', Benjamin Smith, 11 Jan 2025
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This is a quick and non-exhaustive review of “Assessment of Sentinel-3 Altimeter Performance over Antarctica using High Resolution Digital Elevation Models” by Phillips and McMillan, which uses the REMA mosaic to investigate how well range windows selected by the SENTINEL radar altimeters capture the surface in Antarctica. I found the manuscript to be nicely written, and thought that it gave a very good background discussion of how radar altimeters work, and that it presented its findings quite clearly.
I would like to raise one question about the scope of the study, and one about the presentation of the SVD analysis, and my only significant remaining concern relates to font sizes in the figures (hint: they’re not too large).
Question 1: Scope of the study. The study analyses the performance of the SENTINEL-3 altimeters over a range of Antarctic surfaces, and finds that in a lot of interesting places, the telemetered range window does not capture the POCA return from the surface and/or does not capture the full range of elevations illuminated by the radar beam pattern. This finding suggests that the SENTINEL missions and future missions should use a larger range window, and should consider implementing open-loop surface tracking to better position the range window relative to the surface. It would have been nice to see an explicit analysis of how these two options could be implemented- for example, the study could analyze how large the range window would need to be to consistently capture the surface, and could analyze the resolution of the on-board surface elevation model needed to consistently capture the surface.
I was left behind a bit by the discussion of topographic capture. My naïve assumption is that as long as the waveform captures the POCA point, the rest of the waveform structure is not generally interpreted. If this is the case, then perhaps section 6.2 is not needed in as much detail.
I was also unsure of the significance of the waveform decorrelation discussion. While this is interesting in the abstract, its importance for understanding the ice sheet is not as clear. Beyond this, I thought that section 6.4 would have benefitted from a little more discission of the mechanisms that determine waveform shape. I would assume that surface slope across the beam would be the most important driver of waveform shape, and that the correlation would then be more or less determined by the along-track consistency of surface slope and roughness. This seems testable using REMA.
Question 2: Presentation of the SVD.
Upon first reading, it was not at all clear to me why the SVD of the surface would give an estimate of the surface slope. I think section 5.1 would be much improved by a couple more equations describing the SVD approach. I’m not sure why the SVD is preferred over a simple least-squares calculation of the surface slope based on a the elevations within a small window on the ice sheet surface, which would in general be much easier to compute than the SVD because the matrix relating the surface elevations and the slope could be computed once and applied to every window on the ice sheet in the same way. It would also be good to define clearly the shape of the region to which the slope analysis was applied: it is not clear whether “The centre points in each region” (line 328) means the 5x5-pixel window, or some subset thereof.
Specific editorial comments:
Line 43: It is the failure of the assumptions that leads to difficulties
Line 77: low-> short
Line 145: specify “track-to-track spacing” rather than “across-track spacing”
Line 155: no hyphen between range and window
Line 221: “As such, values determined for slope and roughness calculated in this way encode each other via complex, non-linear interactions.” I don’t understand this sentence, and if I did, I think I would disagree with it.
Section 5.4: please check the tense of the first and second paragraphs. The first paragraph should be in present tense.
Lines 320-325:
Please define R
Please give an equation for the line approximating the correlation function. What are the units of the slope? It appears that they are (15 km)^(-1).
Figures:
These are nice figures, but I had to blow them up to the size of a large pizza to make out the text. The fonts need to be much larger!
Citation: https://doi.org/10.5194/egusphere-2024-3054-CC1
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