Status: final response (author comments only)
Evaluation of overall quality
This manuscript presents an investigation whereby the authors use primarily CALIPSO lidar data from six years to determine the ideal sites to observe altocumulus (Ai) and cirrus (Ci) clouds with a clear line of sight with ground-based lidar systems. However, due to its sun-synchronous orbit, CALIPSO only collects data at 0130 and 1330 local time. To determine the representativeness of Ai and Ci data collected from CALIPSO, these data were compared to International Space Station-based, CATS lidar system, which collects data throughout the diurnal cycle. Results from these analysis found that CALIPSO nighttime observations were representative for at least the first 9 hours of the day and the afternoon observation is able to capture the period with the greatest anomaly, which is much more pronounced when observing the diurnal variability of cirrus clouds. The authors demonstration that when averaged overall times the global distribution of cirrus and altocumulus clouds derived from CATS and CALIPSO qualitatively compare well, despite both CALIPSO and CATS not including the same analysis period. The resultant maps of location siting for cirrus and altostratus observations is both useful and relevant, but its utility toward shorter term field campaign studies is limited because the shown maps lack any seasonality, which would be crucial for field campaign planning. In addition, the original manuscript was riddled with grammatical errors and the overall tone was at times colloquial. However, I do feel that this manuscript does fit within the mission of AMT and I would recommend the paper for publications following major revisions.
Specific Comments/Questions
Major:
Minor:
Excerpt from CALIPSO User’s Guide
Cloud / Aerosol
For cloud and aerosol layers, feature type QA is directly related to the cloud-aerosol discrimination (CAD) score, as follows:
high confidence |
= |
|CAD score| ≥ 70 |
medium confidence |
= |
50 ≤ |CAD score| < 70 |
low confidence |
= |
20 ≤ |CAD score| < 50 |
no confidence |
= |
|CAD score| < 20 |
I think that such details need to be clearly identified in the CALIPSO data and methodology section and doing would help clarify the authors assumptions and help establish any potential limitations to study’s results. While QA filtering was applied (only values larger than 5 are included), I personally feel it might also be helpful to also filter by the CAD score too to increase cloud identification confidence, which is vital for the aims of this manuscript.
Technical Corrections
General comments:
Specific comments:
Evaluation of overall quality
This manuscript presents an investigation whereby the authors use primarily CALIPSO lidar data from six years to determine the ideal sites to observe altocumulus (Ai) and cirrus (Ci) clouds with a clear line of sight with ground-based lidar systems. However, due to its sun-synchronous orbit, CALIPSO only collects data at 0130 and 1330 local time. To determine the representativeness of Ai and Ci data collected from CALIPSO, these data were compared to International Space Station-based, CATS lidar system, which collects data throughout the diurnal cycle. Results from these analysis found that CALIPSO nighttime observations were representative for at least the first 9 hours of the day and the afternoon observation is able to capture the period with the greatest anomaly, which is much more pronounced when observing the diurnal variability of cirrus clouds. The authors demonstration that when averaged overall times the global distribution of cirrus and altocumulus clouds derived from CATS and CALIPSO qualitatively compare well, despite both CALIPSO and CATS not including the same analysis period. The resultant maps of location siting for cirrus and altostratus observations is both useful and relevant, but its utility toward shorter term field campaign studies is limited because the shown maps lack any seasonality, which would be crucial for field campaign planning. In addition, the original manuscript was riddled with grammatical errors and the overall tone was at times colloquial. However, I do feel that this manuscript does fit within the mission of AMT and I would recommend the paper for publications following major revisions.
Specific Comments/Questions
Major:
Minor:
Excerpt from CALIPSO User’s Guide
Cloud / Aerosol
For cloud and aerosol layers, feature type QA is directly related to the cloud-aerosol discrimination (CAD) score, as follows:
high confidence |
= |
|CAD score| ≥ 70 |
medium confidence |
= |
50 ≤ |CAD score| < 70 |
low confidence |
= |
20 ≤ |CAD score| < 50 |
no confidence |
= |
|CAD score| < 20 |
I think that such details need to be clearly identified in the CALIPSO data and methodology section and doing would help clarify the authors assumptions and help establish any potential limitations to study’s results. While QA filtering was applied (only values larger than 5 are included), I personally feel it might also be helpful to also filter by the CAD score too to increase cloud identification confidence, which is vital for the aims of this manuscript.
Technical Corrections
General comments:
Specific comments:
This paper takes satellite measurements to evaluate regionality supporting ground-based observations of mid-level/mixed-phase and cirrus clouds. The thought here is that this study would lead to insights in supporting studies aimed at these clouds with only the least amount of low-level cloudiness that would otherwise attenuate lidar-based measurement and limit the numbers of cloud scenes available for monitoring and data collection. Methods are clear, as are images. The subject matter is suitable to consideration by AMT.
This is the first time this reviewer has read this paper.
This is a rare instance whereby I'm going to pass this through with minor revisions, but don't really have anything positive to say about this manuscript. If authors want to publish this, then sobeit. There is no hypothesis. This isn't an experiment. This is more an atlas of climatologically-driven observations to suggest where future observations may or may not take place. And, in that, authors have done a fine job, and are well within their rights to put this in the peer-reviewed literature. That said, the idea that observability might even be a consideration to how people may or may not set up ground-based observing systems for mid and upper-level clouds is really not one I'm comfortable with, and authors do nothing to suggest otherwise. Ken Sassen, speaking of cirrus clouds, once wrote that cirrus are (paraphrasing) the result of regional weather features. Therefore, if you want to study specific cloud processes or isolate convection, anything, you're going to go to the place where that sort of cloud is present. If you're limited by by 10-20%, but you're getting the data that you want? Is that a deal-breaker? I don't see it. Perhaps there are more specified observing scenarios that the authors envisioned, but don't necessarily come out in the narrative? Mixed-phase/altocumulus-type clouds are very common in the Arctic. Yet, ground infrastructure is highly limited. I don't see folks turning to observability in deploying ground-based sensors, though I acknolwedge that they ultimately could.
This paper reads like a study without a mandate. But, I cannot fault the process by which they've studied and processed their datasets, and presented their results.
I'm attaching some technical notes to help with parsing of the narrative. Of specific concern, I strongly encourage you to look at and reference the wonderful paper of S. Gedzelman, Weatherwise (1988; I believe) in talking about altocumulus.
Otherwise, I wish you good luck.