the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
ICE-CAMERA: a flatbed scanner to study inland Antarctic polar precipitation
- Istituto Nazionale Ottica CNR, Sesto Fiorentino, 50019, Firenze, Italy
- Istituto Nazionale Ottica CNR, Sesto Fiorentino, 50019, Firenze, Italy
Abstract. The study of precipitation at very high latitudes is challenging because of the harsh environmental conditions that limit the external activity of humans and instruments, particularly during the polar winter. I describe a device (ICE-CAMERA) for automatic imaging, measuring and classifying ice precipitation on the high plateau. From 2014 the instrument operates unattended, all year round, at Concordia Station (75° S,123° E, 3220 m altitude). The instrument provides detailed precipitation information every hour. The article describes the apparatus and its treatment software.
Massimo Del Guasta
Status: open (extended)
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RC1: 'Comment on amt-2022-62', Anonymous Referee #1, 04 Apr 2022
reply
Review of AMT-2022-62:
ICE-CAMERA: a flatbed scanner to study
inland Antarctic polar precipitation.
authored by M. Del Guasta
April 4, 2022
Global discussion
This manuscript presents the design concept and some data applications
of a smart measurement device: ICE-CAMERA. The instrument is able to
operate in an extremely harsh environment, to collect autonomously precious
data of hydrometeor type on the Antarctic plateau and to routinely perform
a calibration/focus correction procedure. The operation of an unmanned
device collecting this type of data in the environment of the Antarctic plateau
is remarkable and the data themselves are unique and precious. The paper
fits well the scope of AMT. I have a few major remarks and a certain number
of other comments that should be taken into consideration before publication.
My current recommendation is of major revision.
Major remarks
1. As mentioned, the topic fits well the scope of AMT. For this particular
journal a higher level of detail on the instrument itself (see also
minor remarks below) is needed. I believe that the author has both
data or simulation tools available to better characterize the sampling
uncertainties associated to ICE-CAMERA. I would like for example
to see statistics on the number of particles collected according to the
wind speed (I see data are available in Fig. 8) or according to humidity/
dew point which influences sublimation. The author provides interesting hints about sublimation time for individual particles in section
1.6.2. The author may apply similar techniques over a population
of particles, for example assuming a PSD (particle size distribution)
and repeat the simulations multiple times for multiple PSDs and other
parameters (temperature for example). A first approximation could be
to use a constant PSD/snowfall intensity over the measurement period
or to elaborate more realistic scenarios.This is only an idea, and the evaluation could certainly be done in
a different way but the objective is the following: by extending the
simulation to a population of particles, something more could be said
in terms of (theoretical) catching efficiency of the instrument, a key
aspect for the readership of this journal.
2. It was not clear if the main focus of the paper is the instrument or
the CNN-based classification. I recommend to clarify it. In either case
the level of detail should be increased (see my other comments). My
assumption was that the main target is the instrument so I did not
comment in much detail about the CNN.
3. The literature overview and the current state of knowledge about ice
crystal habits is not enough documented and detailed in the introduction
and more in general in the text. See minor remarks below. I
would like to see the instrument and its capabilities better put into the
context of current state of research and the known research gaps.
4. Data access. The instrument is collecting data since 2014. So there are
now 7 or 8 years of unique data collected at the Concordia station and
not yet available. The data are the real added value of each innovative
instrument. It is crucial in my opinion that as much data as as possible
is made available, behind a DOI to allow for citation and recognition, at
the time this paper will be published. I see it as a necessary complement
to allow the readers to understand the quality and the scientific impact
of the data produced by the instrument. Platforms as Zenodo, just
to cite a common choice, are easy and user friendly and they allow to
obtain a DOI and a citation for the dataset.
Minor remarks
1. In the introduction or somewhere in the text I would recommend to take
the time to explain all the difficulties and possible failures associated
to the long term operation of an instrument in such an environment.
This is briefly mentioned through the text but I am convinced that
the average reader would not get the idea of the actual and maybe less
known challenges: breaking of rubber parts, (low) humidity issues in
heated environments, etc.2. L14-19, L22-24: some references should be added to backup these scientific
statements.3. L29: 90 um → 90 μm. Same through the text
4. L34: change forms to shapes
5. L79: I believe the scanning principle should be briefly introduced before
this point. Here we read after an entire scan, but we actually do not
know yet what a scan exactly is, for this instrument.6. Fig. 3: I found this schematics not really informative. I would recommend
either to use pictures of the actual parts of the instrument (a
qualitative but illustrative way) or to provide a higher detail electrical
/ communication schematics, even as Appendix material.7. L139: what is the expected lifetime of the LEDs?
8. L162: add a reference or a statement about the expected maximum
height of blowing snow in Concordia.9. L177 (and related section):
• Could you show data evidence of partial sublimation bias in the
collected images? A caveat that you mention also later on in the
manuscript.
• The role of relative humidity should be discussed here. If relative
humidity is higher, sublimation rate will be lower.
10. Fig 8: I see some clear patterns / clusters / populations in the data. I
recommend to try to explain why such patterns appear. I suspect they
are related to individual events/seasons, but they may be related to
more interesting physical aspects or technical issues.
Also, I would try to produce similar scatterplots but including relative
humidity, which should be routinely available in Concordia.11. L294 (and related section): a flow-chart could help to present the processing
steps rather than a bullet list. The text of this section should
be edited to be descriptive rather than a simple enumeration of steps.12. L331: how often does this situation occur?
13. L352: Why this approach end up to be unreliable for your instrument?
14. L363: does this imply that the images collected have to be resized?
(down or upscaled?) Is the resolution of the instrument constant?15. Fig 14: can spheroidal particles actually be supercooled liquid water?
It would be good to have some size reference in this image.16. L402: about trigonal plates. This statement here seems to be contradicted
by the results of Fig. 17, and in fact this is highlighted in L471.
I would either remove the statement here or remove this class from all
the analysis of the paper.17. L407: a good idea actually.
18. L560-561: I maybe missed it, but are there statistics on the total
amount of data collected since the instrument is operational?19. L565: I would recommend to clarify explicitly the content of the governmental
policies mentioned here. Nowadays most of the institutions promote
FAIR policies (https://www.go-fair.org/fair-principles/), so this
Code and Data availability statement may be sounding strange for some
readers. Secondly, only the CNN and a test dataset is mentioned here.
The paper, as the title suggests, is not about the CNN but about the
instrument. I would expect to see a data statement about access to
the data collected so far by the instruments and maybe some link to
relevant technical documentation of the instrument itself.
20. Plot quality: the quality of some plots seems very low (for example
Fig. 5)-
AC1: 'Reply on RC1', Massimo Del Guasta, 08 Apr 2022
reply
Thanks for your useful suggestions
About your major remarks:
1) I will easily add a picture about the number of particles collected vs wind speed. More tricky is the use of humidity , especially at temperatures much below -40°C. Unfortunately, the most reliable , standard meteo station collecting 'menaingful' humidity values is located 500 m away from the ICE-CAMERA site, and is 2 meters lower than ICEcamera. Moreover ice-camera is placed on the top of a heated shelter, and temperatures/humidities are sligthly different from free air . The reliability of any humidity sensor in DomeC during winter is also disputable. For these reasons I prefer to use not measured humidity data in this type of work. But I will try to manage something about this topic
The use of a PSD as suggested by the referee was welcome! I already made the simulation of PSD evolution with sublimation, starting from a 'flat' PSD in the range 50-1000 um.
2)The focus of the paper is the instrument considered as a 'whole'. That is, both hardware and software. So, the image processing and the CNN are as important as the scanning system itself in order to provide automatically , as an output, pre-processed segmented ice grain images and useful data
3) I am rewriting the introduction in order to cite the papers (available to me) related with crystal habits vs temperature. Any suggestion from the referee will be welcome
4) The paper focuses on the instrument and its capabilities, not on data analysis. As stated in the text, data analysis and statistics is a topic for a second paper, with different co-authors ,and where the combined use of ICEcamera and other instruments is adopted . For this reason the ICE-CAMERA data set will not be published together with the present paper, just devoted to the instrument description. I can publish the CNN , instead , as it is actually part of this work, together with a (limited) database of samples of ice-camera images for the 14 classes. Detailed technical data about the instrument can also be released on the suggested platform
About the minor remark, I will ll try to follow all the precious referee suggestions
Best regards
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AC1: 'Reply on RC1', Massimo Del Guasta, 08 Apr 2022
reply
Massimo Del Guasta
Massimo Del Guasta
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