Validation and comparison of cloud properties retrieved from passive satellites over the Southern Ocean

Kurup, Arathy A.; Poulsen, Caroline; Siems, Steven T.; Robbins, Daniel J. V.

doi:10.5194/amt-19-1487-2026

Articles | Volume 19, issue 4

https://doi.org/10.5194/amt-19-1487-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-19-1487-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 4

Research article

|

27 Feb 2026

Research article |

| 27 Feb 2026

Validation and comparison of cloud properties retrieved from passive satellites over the Southern Ocean

Arathy A. Kurup, Caroline Poulsen, Steven T. Siems, and Daniel J. V. Robbins

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Final revised paper (published on 27 Feb 2026)
Preprint (discussion started on 19 Feb 2025)

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-209', Anonymous Referee #1, 30 Mar 2025

The Southern Ocean is an important area of cloud research and this is a worthwhile inter-comparison. The background in the Introduction is also quite thorough and does a good job of framing this study in a larger context. There are some inconsistencies with the description of the datasets, particularly PATMOS-x, and the collocation process used in Figure 7. In order to have confidence in the results of this inter-comparison these need to be addressed, and at least some of the analysis will need to be redone. Specific comments below.
Line 133: The POES satellites were operated by NOAA so I believe this would typically be NOAA Polar Operational Environmental Satellites (POES).
Line 135: It says here NOAA-19 is used for the L2 comparisons, but in Table 1 it says the cloud optical properties being compared (COD and CER) are derived from the 1.6-micron channel. Channel 3ab on the AVHRR can either measure the 1.6 or 3.75, but not at once. NOAA-19 is switched to 3b, meaning it measures the 3.75, so it shouldn’t be possible to have 1.6-micron properties for CMSAF and PATMOS-x.
Line 146: Here and elsewhere PATMOS should be PATMOS-x
Line 154: For version 6.0 ACHA uses 11 and 13.3 channels, not 11 and 12.
Line 231: I’m a little confused using the term ‘granules’ here. THE AVHRR GAC data is reported in ascending and descending orbits. Is that the meaning of granule here, or is it the global L2b data?
Line 410: retreive -> retrieve
Line 453: CMSAF and PATMOS-x both use AVHRR GAC data so they shouldn’t have different spatial resolutions for L2 products. The sampling may be different, but that’s not the same thing.
Line 603: ‘The AVHRR PATMOS sensors exhibited the lowest correlation and the highest bias in both the overall CTH and the multilayer and single-layer cases.’ The numbers reported in Figure 8 don’t seem to support this conclusion. The PATMOS-x RMSE and MBE is lower than MYD and CMSAF for the multi-layer cases and lower than CMSAF for all cases.
Figure 2.: It seems strange to me that the collocation coverage for CMSAF and PATMOS-x are different since they are derived using the same AVHRR measurements.
I suspect the odd PATMOS-x behavior in Figure 7 can be explained by a collocation problem due to an issue with how the PATMOS-x L2b global file is created. The L2b files are created by sampling orbits for a single day to a 0.1-degree global grid. Final orbits from the previous day are included because the orbit can cross from one day to another. So, if you are looking at the end of the day, and that orbit is missing, you can get a situation where the orbit used is from the previous day (this issue was addressed for recent file deliveries but still exists for most of the record). Below is a list of the orbits used in the NOAA-19 L2b ascending file from January 10^th, 2015 (this is from the ‘source’ global attribute in the file). The pertinent files have been italicized. The start and end times in the last two files show a time gap, suggesting an orbit wasn’t processed. This time gap coincides with the start and end times from the first file, which is from January 9^th. This gap coincides with the reported collocation time of 22:50 UTC in Figure 7, suggesting the PATMOS-x orbit being analyzed was from a day previous than Cloudsat, MODIS, and CMSAF.
clavrx_NSS.GHRR.NP.D15009.S2214.E0001.B3051617.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15009.S2356.E0146.B3051718.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S0140.E0335.B3051819.SV.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S0329.E0524.B3051920.WI.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S0518.E0711.B3052021.WI.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S0705.E0853.B3052122.WI.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S0847.E1029.B3052223.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S1204.E1351.B3052425.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S1345.E1531.B3052526.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S1525.E1657.B3052627.WI.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S1652.E1836.B3052728.WI.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S1830.E2025.B3052729.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S2019.E2208.B3052930.GC.hirs_avhrr_fusion.level2.nc
clavrx_NSS.GHRR.NP.D15010.S2344.E0134.B3053132.GC.hirs_avhrr_fusion.level2.nc
It's worth reiterating this is an issue with how the PATMOS-x L2b files are created and would be difficult for the authors to identify without looking at imagery to ensure the products are observing the same scenes. Regardless it brings into question the results of Figure 7, and potentially all of the L2 comparison results, depending on how frequently this issue occurs. This should be looked at more carefully.

Citation: https://doi.org/10.5194/egusphere-2025-209-RC1
- AC1: 'Reply on RC1', Arathy A Kurup, 28 Jul 2025
  
  Kindly refer to our detailed point-by-point response to Reviewer Comment RC1 in the attached PDF document. We sincerely thank the reviewer for their constructive feedback.
  
  Citation: https://doi.org/10.5194/egusphere-2025-209-AC1
RC2:
'Comment on egusphere-2025-209', Anonymous Referee #2, 31 Mar 2025

The paper is reasonably well organized and written. The study compares cloud properties derived from different platforms and algorithms over the Southern Ocean, which could be worthwhile if it leads to improved understanding of algorithm deficiencies and uncertainties. Unfortunately, I don’t think the paper sheds new light on these things so the purpose for the paper isn't very clear to me. Furthermore, the results are confusing, don’t make sense in some cases, and at times contradict previous findings. As a result, I find some of the results difficult to understand as presented and am concerned that the analysis may be flawed, perhaps due to collocation problems and sampling differences. I think the authors need to reevaluate and verify their methods to ensure the results are robust for all datasets.
Lines 57, 742: replace Minnis et al., 2011 with Minnis et al., 2020 as the 2020 reference is the correct one that describes the data used in the Hinkelman analysis
Minnis, P., S. Sun-Mack, Y. Chen, F.-L. Chang, C. R. Yost, W. L. Smith, Jr., P. W. Heck, R. F. Arduini, S. Bedka, Y.Yi, G. Hong, Z. Jin, D. Painemal, R. Palikonda, B. Scarino, D. A. Spangenberg, R. Smith, Q. Z. Trepte, P. Yang, and Y. Xie, 2020: CERES MODIS cloud product retrievals for Edition 4, Part 1: Algorithm changes. IEEE Trans. Geosci. Remote Sens., doi: 10.1109/TGRS.2020.3008866.
Line 133: NASA should be NOAA
Line 224: how well do MODIS along track assessments compare to the 0.25 deg resampled L3 products?
Line 265: It isn’t clear what bin the uncertain pixels were put. Please explain
Line 290-298. Check to see that the values in the text match those in the table. I think there are some discrepancies.
Line 315-316: What finding is consistent, the values or the relative differences with CALIOP? Bromwich 2012 attributed the lower CALIOP cloud fraction to sampling, right? What’s the implication for your finding here? How does this support or contradict the fact that CALIOP is more sensitive to clouds than MODIS?
Line 347: remove ‘this’
Line 355: you already stated this on line 349
Line 376: This is a great figure, but the results are suspicious, particularly for AP which looks like it may be from a different swath. You should double check this and make sure that a mistake hasn’t been made in the collocation process.
Line 381: Consider rephrasing this: “The COD shown on each product uses the passive sensors’ 1.6 μm channel.” Instead of ‘uses’, perhaps ‘was derived using’ would make more sense.
Line 394-395: Why is AC sensitive to the midlevel cloud and MODIS not sensitive? Is this possibly the result of a space/time mismatch. Did you look at the BT’s? Are you sure the sensors are viewing the same space?
Line 403-404: This statement about passive radiometers has not been proven here and is generally incorrect. It would be more appropriate to say “This suggests that the passive sensor algorithms with a single layer assumption are not well suited for distinguishing thin cirrus in some overlapping cloud conditions.” Furthermore, why is CC indicating a cloud top phase of liquid water for the clouds at 6 and 8 km? Is that trustworthy? What's the temperature at those levels?
Line 405: clouds,
Line 405-409: Here again, the results look suspicious. Why is MODIS systematically 2-3km too high. Are we learning anything here?
Line 420: convective cloud? Where is that?
Line 441: Here and elsewhere, be careful with wording that suggests active sensors serve as ground-truth for COD (e.g. passive sensors underestimate…) The lidar, radar and passive all have different sensitivities to the cloud PSD’s, and the active sensors can actually miss information in the vertical column.
Line 449-461: This section is consistent with previous sections in that the results don’t make a lot of sense and further call to question the veracity of the collocation process adopted here. Can the two AVHRR datasets have this much difference in skill? I don’t believe I’ve ever seen a MODIS hit rate this low for daytime clouds. Aren’t these results (e.g. for MODIS) also inconsistent with what you show in figure 4?
Line 473: Why would the AC algorithm be more sensitive to high thin clouds than the MODIS algorithm given how much more information is available from MODIS? Just because the AC neural net produces better mean CTH’s, it also leads to lot of height overestimates. How does this imply that AC is more sensitive to thin cirrus?
Line 475: You already stated on line 463 what Fig 8 shows.
Line 481-483: CTH ‘overestimates’ are due to inversions, where the BT matches the profile temperature at a ‘lower’ height. Do you mean higher height?
There is a good discussion of the inversion problem here (and references within):
Dong, X., P. Minnis, B. Xi, S. Sun-Mack, and Y. Chen (2008), Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site, J. Geophys. Res., 113, D03204, doi:10.1029/2007JD008438.
Line 507-540: Section lacks discussion regarding difference across algorithms with respect to CER magnitudes (i.e. why is MODIS ice Re so much higher than the others), and CER distributions (i.e. why does AC ice look like AC water, unlike AP and MODIS)
Line 549-550: Why do you think the results disagree from Frey (2018) and Palm (2010)? Their results make more sense to me from a physical standpoint and from a retrieval difficulty standpoint..
Line 570-575. I’d prefer the following convention ‘more than 20% larger', rather than 'was >20%'
Line 611-612. This is an incomplete sentence.

Citation: https://doi.org/10.5194/egusphere-2025-209-RC2
- AC2: 'Reply on RC2', Arathy A Kurup, 28 Jul 2025
  
  Thank you for your constructive comments. Please find attached a detailed response to the comments.
  
  Citation: https://doi.org/10.5194/egusphere-2025-209-AC2
CC1:
'Comment on egusphere-2025-209', Andrew Heidinger, 03 Apr 2025

A nice topic to explore with satellite data. My criticisms are mainly about the PATMOS-x data and how its included. I think they should be addressed or PATMOS-x should be removed. I assume that this will to climate studies and wonder if you state that is your end goal for a future study?
Line 6 - There was a project called PATMOS that was part of the EOS pathfinder efforts in the 1990s. I think you are referring the PATMOS-x (PATMOS extended) project here and should make sure to clarify the terminology
Line 130: Both Cm-SAF and PATMOS-x use AVHRR GAC which does not provide data at 1.1km as you state.
Line 155: PATMOS-x uses an optimal estimation cloud height that uses multiple channels simultaneously. They way this is written, it sounds like the CO2 channels is needed for CTH and no CTH is available using 11 and 12 micron.
Figures 3-4-5. You mention that PATMOS-x is the worst but you don't show it in these figures so it is hard to comprehend or compare.
Figure 7. PATMOS-x looks out of family and this is hard to believe. Are you certain that the correct AVHRR pass was used? There are 6 per day I think at this time. Could you provide more information if people wanted to repeat this analysis.
Line 465: I don't understand why the cloud height would not be higher without the COD limit if CIRRUS are high and thin clouds. Unsure of the point of this.
Line 400: You mention that AP's clouds are too low and it has too much ice cloud compared to water cloud. These are inconsistent with each other since ice clouds are higher than water clouds.
Figure 9: AP looks off here and does not seem in family. Other publications show it to be in family - the GEWEX Cloud Assessment and I wonder if something is wrong with the AP analysis. The lack of AP data in the maps like the other data sets would remove this suspicion.
Table 9 - results tabulated here are more inline than shown in Figure 9.

Citation: https://doi.org/10.5194/egusphere-2025-209-CC1
- AC3: 'Reply on CC1', Arathy A Kurup, 28 Jul 2025
  
  Thank you for your constructive comments. A detailed point-by-point response is included in the attached document.
  
  Citation: https://doi.org/10.5194/egusphere-2025-209-AC3

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

AR by Arathy A Kurup on behalf of the Authors (07 Aug 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (22 Aug 2025) by Linlu Mei

RR by Anonymous Referee #1 (21 Nov 2025)

Suggestions for revision or reasons for rejection

I believe the manuscript is much improved. I have a handful of comments. Most are small but one or two may require effort to address.

Collocation case study:
I appreciate the author’s finding a new case study that does not suffer from the previous day issue described in the first review. It is worth noting that this issue can impact both the beginning and ending of a day, so the authors would need to exclude swaths for the first and last couple of hours of each day to be sure they removed the issue. The updated text starting at line 273 suggests they only excluded data after 22:00 UTC.

Section 3.2
I have concerns about the Level 2 collocated data. Typically a comparison of an imager and lidar would best be done for simultaneous nadir overpasses (SNO), the ‘nadir’ being an important part of that. In this case there is no mention of sensor zenith angle criteria being applied for the collocations. I don’t believe they could be, because to get collocations close to nadir they would need to be farther poleward than the Southern Ocean. This creates a challenge, as imagers viewing clouds at oblique angles can impact cloud height, fraction, and optical depth retrievals, when compared to nadir observations of the same clouds. I think a section describing this challenge and how it could impact the results is warranted.

Figures 7 and 9:
Labels still reads PATMOS instead of PATMOS-x

Figure 8:
The caption says MODIS is the top row and CMSAF is the middle row. I think this should be switched. I’m also having trouble reconciling numbers in Figure 8 and Table 6 with the conclusions and abstract of the article:

“In the case of the CTH analysis, a mean absolute bias of 0.65 km (AVHRR CMSAF), 1.02 km (MODIS), and 1.28 km (AVHRR PATMOS-x) was observed for single-layer cloud scenes cases. This mean bias increased to 1.85 km (AVHRR CMSAF), 3.23 km (MODIS), and 3.30 km (AVHRR PATMOS-x) for multilayered cloud scenes. Hence, we can conclude that the passive sensor MAE against the active sensor for multilayer cases is 3 to 4 times the corresponding MAE for single-layer cases and 2 times MAE for the overall year. The bias can also be attributed to the retrieval algorithm differences, COD of the layers, and sensitivity of sensors to the cloud.”

This (and text beginning at line 737) suggests CMSAF performed significantly better for single- and multi-layer cases than PATMOS-x or MODIS, but the stats in Figure 8 show CMSAF has noticeably larger MBE and RMSE than the other two for multi-layer cases. Rereading the description, it seems the conclusions are based on comparisons with no COD threshold, but Figure 8 applies a COD threshold of 0.5. This makes more sense, but I am curious why the threshold of 0.5 was chosen, and why are the conclusions based on no threshold? Looking at Figure 8, one could reasonably conclude that MODIS performed best for single-layer clouds and PATMOS-x performed best for multi-layered clouds. I’ve seen similar comparisons where a COD threshold of 0.1 was chosen to filter out sub-visible cloud that a lidar may detect but an imager would not. Using 0.5 would filter out some pretty thick clouds. Is this based on a previous study?

Referee Report: PDF

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RR by Anonymous Referee #3 (21 Nov 2025)

Suggestions for revision or reasons for rejection

The paper has been well revised according to the reviewers’ comments and each point has been well discussed. The authors have done a great job revising the manuscript and updating the entire case study. I recommend that the paper be accepted pending minor revisions, detailed below.

General comments:

Many of the figures have writing that is too small for the reader.

Lines 8 : "... AVHRR CMSAF showed higher cloud cover over mid-latitudes and lower cloud cover over land ..."

Ligne 9-10 : suggestion "... against CALIOP indicates that AVHRR CMSAF tends to overestimate, whereas MODIS tends to underestimate the liquid cloud fraction. The magnitude of the difference varies with the latitude and season."

Lines 32-33: I don't really understand the sentence, suggestion "The new finding that contradicts previous studies may result from the difficulty of retrieving cloud optical depth over ice using the retrieval algorithms."

Line 72: "They observed a bias of -10 W/m2 in LWCRE and concluded that the factors contributing to this bias include ..."

Line 74 -75: "... were evaluated AGAINST CALIOP observations by Yost et al. (2023) and the reevaluation showed that multilayer clouds are one of the main contributors to errors in cloud top
height retrieval."

Line 86: "... are found that mixed-phase clouds..."

Line 91: add a "," after "instruments"

Line 93: add a "," after "which".

Lines 97-102: You could perhaps specify the chapter number for each step described in this paragraph, if possible.

line 127-128: "LIDAR and RADAR for understanding cloud vertical profileS, cloud classification and cloud properties, such as cloud top height (CTH)..." (remove cloud layer top).

Line 129: Remove the "," after "product".

Line 138: If "the data" is plural --> remove the "s" at the end of includes ("the data include"). In the previous sentence data is plural.

Line 140: "The L2 data consist of..." without "s".

Line 149-150: "The latest AVHRR has six channels, out of which only five can be transmitted at any given time." is already mentioned in line 146. You could modify your first sentence to include all information about the channels.

Line 154: add provided --> "AVHRR instrument, providing clouds, suface albedo...". I don't understand what you mean with provided cloud? what from clouds? cloud properties?

Line 156: "...and the time-period available.."

Line 158: Suggestion "The data used in the analysis have a spatial resolution of 5 km."

Line 166:"The climate data record covers a period of 44 years..."

Line 170:"In this study, the ACHA CTH algorithm uses 11..."

Line 176: "Validation of the cloud products over the SO has been mostly performed using monthly data."

Line 178: "... compared against CALIOP..."

Lines 178-180: Separate the sentence in 2 sentences --> "...1km CALIPO product. In the case of..."

Line 183: "They observed that the smallest mean CTH differences ..."

Line 188: "... with biases increasing as COD decreasing..."

Line 190: ".... during the polar winter."

Line 192: Which polar region? polar regions or southern/northern polar region.

Line 206: Multilayer clouds detection? or detection of what?

Line 209: Chen et al is written 3 times.

Line 216: Remove the "," after "instruments".

Line 224: Li et al. is written 3 times.

Line 251: replace "contained" with "contains"

Line 252: add a "," before "such as".

Line 268: In the literature, ML is also used to designate the melting layer, which could be misleading or confusing for the reader.

Lines 289-290: I don't understand the sentence --> Is cloudy used twice in the classification?

Line 313: add a "," after "factors" --> "factors, such as..."

Lines 313-314: You could combine sensitivity and resolution --> "differences in sensor sensitivity and resolution,..."

Line 317: Replace "and" with "to" "ranging from 0.36 ... TO 0.32 ...".

Line 319: The sentence concerning the MBE is unclear

Line 326-328: Add MBE before ">" --> "with MBE>1 km", "MBE± 0.5 km", MBE>1km" and "MBE>1.5km" so that the reader understands what you mean. I would suggest applying this throughout your manuscript wherever you use the >, <, or ± symbols.

Lines 337: This contradicts what you state in lines 304–308; could you please explain why?

Line 339: "for the active and passive sensor data"

Line 399: You could write the date in the title. Suggestion: "case study on the 19.10.2015 at 08:37 UTC". It could help the reader.

Line 400: A brief sentence describing the case study and what it was used to observe before introducing the Figure 6 would be appreciated.

Line 406: Change "see" in "observe".

Lines 406-408: I don't understand the sentence. Suggestion: "Although all three sensors observed a similar high cloud pattern around 50°S: AC retrieves the CTH at around 11km height, while MYD and AP retrieve the CTH at around 9 km height. Finally, AP has a significant region of cloud with CTHs at around 5 km Height located at 40°S and 80°E, while AC and MYD observed low clouds with CTHs at around 2 Km height for the same region."

Line 423: suggestion "...over thick lower-level clouds"

Line 425: You can add "height" after "km" if you speak about altitude of clouds.

Line 431: "lower-level cloud" or "lower layer cloud"?

Line 444-447: Please reorganize the sentence which is not very clear. You could rephrase it in 2 sentences. Suggestion: "...temperature profiles. Indeed, the CTH can vary substantially, particularly at high altitude and altitude, and depends on the difficulty in identifying the inversion at the tropopause..."

Lines 448+451: "Figure 7aiii shows a region of boudary layer clouds around 41.5°S"

Line 457: The second panel of which Figure do you mean? 7b?

Line 461: "active sensors" --> Is there only one active sensor (CALIOP) or several?

Line 472: You can move ",particularly where ice clouds detected are quite different" (remove the first "are") to the end of the sentence after "in general". Add "of" before AP CER" --> "the vaues OF AP CER".

Line 485: "in Sect. 4.2.4"?

Lines 576-577: You can remove this part of the sentence "for example, MYD has five phase categories, while AC has eight, including a supercooled water class" because it is already shown with the Table 7.

Lines 650-673: The paragraph appears twice: you can delete the text from lines 662 to 673.

Line 706: Change "biases" in "bias".

Line 741-742: "..the cloud thermodynamic phase...", remove the "s" at the end of thermodynamic.

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ED: Publish subject to minor revisions (review by editor) (30 Nov 2025) by Linlu Mei

AR by Arathy A Kurup on behalf of the Authors (20 Dec 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (04 Jan 2026) by Linlu Mei

AR by Arathy A Kurup on behalf of the Authors (18 Jan 2026) Manuscript

Short summary

Southern Ocean (SO) clouds are crucial in defining the Earth's radiation budget. They are primarily observed by satellites, due to a lack of surface observations. This study validated cloud top height and cloud mask and compared the microphysics products from 3 satellite cloud datasets over the SO. The study revealed significant differences in cloud property retrievals between the sensors. Multilayer clouds play a major role in the differences when validated with active satellite measurements.