the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparative experimental validation of microwave hyperspectral atmospheric soundings in clear-sky conditions
Abstract. Accurate observations of atmospheric temperature and water vapor profiles are essential for weather forecasting and climate change detection. Hyperspectral radiance measurements afford a useful means to retrieve these thermodynamic variable fields, by harnessing the rich information contained in the electromagnetic wave spectrum of the atmospheric radiation. Compared to infrared radiometry, microwave radiometry holds the ability to penetrate clouds and potentially achieve an all-sky thermodynamic retrieval. Recent technological advancements have enabled the development of a hyperspectral microwave radiometer, the High Spectral Resolution Airborne Microwave Sounder (HiSRAMS), which we employ in this study to retrieve the atmospheric temperature and water vapor profiles under the clear-sky condition, in comparison with an infrared hyperspectrometer, the Atmospheric Emitted Radiance Interferometer (AERI). HiSRAMS and AERI measurements under different viewing geometries have been acquired and compared for atmospheric retrieval. When both instruments are placed on the ground to acquire zenith-pointing measurements, the infrared hyperspectral measurements exhibit higher information content and greater vertical resolution for temperature and water vapor retrievals than the microwave hyperspectral measurements. A synergistic fusion of HiSRAMS and AERI measurements from the air and ground, respectively, is tested. This “sandwich” sounding of the atmosphere takes advantage of the complementary information contents of the two instruments and is found to notably improve retrieval accuracy.
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RC1: 'Comment on egusphere-2024-1045', Chung-Chi Lin, 23 Jun 2024
Please see the attached document for my comments!
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AC1: 'Reply on RC1', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC1-supplement.pdf
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AC1: 'Reply on RC1', Lei Liu, 03 Oct 2024
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RC2: 'Comment on egusphere-2024-1045', Anonymous Referee #2, 16 Aug 2024
This is a well written paper. The analysis is thorough and supports the conclusions made. The presentation quality is good. The authors first conduct AERI and HiSRAMS retrievals for ground-based observations of clear sky only, which compares the capability of the two instruments in terms of information content on temperature and water vapor. Then they demonstrate a joint retrieval between ground-based AERI and air-borne HiSRAMS clear sky and show the benefit of combining the two instruments. I don't think this paper delivers new science, but it does present a retrieval algorithm for atmospheric temperature and water vapor sounding from IR and MW. I have the following comments for authors to consider:
1. The value of this paper is on combining air-borne microwave and ground-based infrared sounding measurements, not much on whether or not the MW and IR combined could provide a better "all-sky" retrievals. I think it is better to point this out in your title, abstract, and literature survey, and center them on your major findings.
2. The retrieved profiles agree with the radiosonde surprisingly well, but clear differences with the first guess can be seen. Are these results all for a single case? How does the algorithm perform in general? It is hard to reach conclusions based on a single case.
3. The retrieval bias around the sharp vertical features is very large, which is due to the lack of vertical resolution. This could be demonstrated by calculating the bias by comparing retrievals with the radiosondes that are vertically smoothed by the averaging kernel. Perhaps it is more interesting to ask what kind of instrument designs could resolve such feature, new channels, lower measurement error, etc.
Citation: https://doi.org/10.5194/egusphere-2024-1045-RC2 -
AC2: 'Reply on RC2', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC2-supplement.pdf
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AC2: 'Reply on RC2', Lei Liu, 03 Oct 2024
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RC3: 'Comment on egusphere-2024-1045', Anonymous Referee #3, 27 Aug 2024
This paper is well written, with good explanations of the OEM
methodology and analysis that supports the conclusions. One could
argue that the Optimal Estimation methodology is well known, but the
paper has practical examples that accompany the explanations.
Having said that, not much new or unexpected conclusions are in this
paper, but it can find a place in an Atmospheric Measurements and
Techniques paper if some fixes are made.
1) Line 470 : it is very hard to tell if the results presented truly
are statistical N >> 1, or if only one case is done for the
instruments alone on the ground, and one other case is done for the
HISRAMS/AERI synergy. Your conclusions are too general if only one
case is considered, especially since what you find is not surprising
(AERI and HISRAMS together give "better" results (closer to truth)
than one instrument alone, and a top/bottom sandwich brings a good
deal of information together).
2) Similarly, are you really doing an clear-sky retrieval. How do you
know there are no clouds? Your paper gets confusing at the beginning
when you mention "clear sky" in the title and then talk about the use
of HISRAMS in allsky conditions. Can you clarify?
3) Figure 2,6 : Please show mean(observations - calculations) and
std(observations - calculations) for both instruments. You could be
getting great results while having poor spectral fits (ie the bias and
std. dev are larger than the NeDT of the instruments).
In particular could you indicate the surface channels of the HISRAMS
when showing the biases?
4) The paper could be much better organized. For example instead of
"sandwich" you could use the more traditional "synergy" term.
5) Figures S5 - S8 are ..?
6) Lines 155-162, and lines 174-180, should be combined together
rather than being separated. Then again line 189 the n_{level} is
mentioned.
7) Similarly lines 434 to 439 could be moved to the conclusionCitation: https://doi.org/10.5194/egusphere-2024-1045-RC3 -
AC3: 'Reply on RC3', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC3-supplement.pdf
-
AC3: 'Reply on RC3', Lei Liu, 03 Oct 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-1045', Chung-Chi Lin, 23 Jun 2024
Please see the attached document for my comments!
-
AC1: 'Reply on RC1', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Lei Liu, 03 Oct 2024
-
RC2: 'Comment on egusphere-2024-1045', Anonymous Referee #2, 16 Aug 2024
This is a well written paper. The analysis is thorough and supports the conclusions made. The presentation quality is good. The authors first conduct AERI and HiSRAMS retrievals for ground-based observations of clear sky only, which compares the capability of the two instruments in terms of information content on temperature and water vapor. Then they demonstrate a joint retrieval between ground-based AERI and air-borne HiSRAMS clear sky and show the benefit of combining the two instruments. I don't think this paper delivers new science, but it does present a retrieval algorithm for atmospheric temperature and water vapor sounding from IR and MW. I have the following comments for authors to consider:
1. The value of this paper is on combining air-borne microwave and ground-based infrared sounding measurements, not much on whether or not the MW and IR combined could provide a better "all-sky" retrievals. I think it is better to point this out in your title, abstract, and literature survey, and center them on your major findings.
2. The retrieved profiles agree with the radiosonde surprisingly well, but clear differences with the first guess can be seen. Are these results all for a single case? How does the algorithm perform in general? It is hard to reach conclusions based on a single case.
3. The retrieval bias around the sharp vertical features is very large, which is due to the lack of vertical resolution. This could be demonstrated by calculating the bias by comparing retrievals with the radiosondes that are vertically smoothed by the averaging kernel. Perhaps it is more interesting to ask what kind of instrument designs could resolve such feature, new channels, lower measurement error, etc.
Citation: https://doi.org/10.5194/egusphere-2024-1045-RC2 -
AC2: 'Reply on RC2', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Lei Liu, 03 Oct 2024
-
RC3: 'Comment on egusphere-2024-1045', Anonymous Referee #3, 27 Aug 2024
This paper is well written, with good explanations of the OEM
methodology and analysis that supports the conclusions. One could
argue that the Optimal Estimation methodology is well known, but the
paper has practical examples that accompany the explanations.
Having said that, not much new or unexpected conclusions are in this
paper, but it can find a place in an Atmospheric Measurements and
Techniques paper if some fixes are made.
1) Line 470 : it is very hard to tell if the results presented truly
are statistical N >> 1, or if only one case is done for the
instruments alone on the ground, and one other case is done for the
HISRAMS/AERI synergy. Your conclusions are too general if only one
case is considered, especially since what you find is not surprising
(AERI and HISRAMS together give "better" results (closer to truth)
than one instrument alone, and a top/bottom sandwich brings a good
deal of information together).
2) Similarly, are you really doing an clear-sky retrieval. How do you
know there are no clouds? Your paper gets confusing at the beginning
when you mention "clear sky" in the title and then talk about the use
of HISRAMS in allsky conditions. Can you clarify?
3) Figure 2,6 : Please show mean(observations - calculations) and
std(observations - calculations) for both instruments. You could be
getting great results while having poor spectral fits (ie the bias and
std. dev are larger than the NeDT of the instruments).
In particular could you indicate the surface channels of the HISRAMS
when showing the biases?
4) The paper could be much better organized. For example instead of
"sandwich" you could use the more traditional "synergy" term.
5) Figures S5 - S8 are ..?
6) Lines 155-162, and lines 174-180, should be combined together
rather than being separated. Then again line 189 the n_{level} is
mentioned.
7) Similarly lines 434 to 439 could be moved to the conclusionCitation: https://doi.org/10.5194/egusphere-2024-1045-RC3 -
AC3: 'Reply on RC3', Lei Liu, 03 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1045/egusphere-2024-1045-AC3-supplement.pdf
-
AC3: 'Reply on RC3', Lei Liu, 03 Oct 2024
Data sets
Clear-sky retrieval of atmospheric temperature and water vapor using microwave and infrared hyperspectrometers Lei Liu, Natalia Bliankinshtein, and Yi Huang http://doi.org/10.17632/524hj3w6r8
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