the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jan 2024
An evaluation of atmospheric absorption models at millimetre and sub-millimetre wavelengths using airborne observations
Abstract. Accurate gas absorption models at millimetre and sub-millimetre wavelengths are required to make best use of observations from instruments on board the next generation of EUMETSAT polar-orbiting weather satellites, including the Ice Cloud Imager (ICI), which measures at frequencies up to 664 GHz. In this study, airborne observations of clear-sky scenes between 89 and 664 GHz are used to evaluate two state-of-the-art absorption models by performing radiative closure calculations. Observed brightness temperatures are compared to simulated values from the Atmospheric Radiative Transfer Simulator (ARTS) for both upward and downward-looking viewing directions. It is shown that uncertainties in the atmospheric water vapour profile can have a significant impact on individual comparisons, but these errors can be reduced by averaging across multiple flights. For upward looking views, which have the greatest sensitivity to the absorption model, the mean differences between observed and simulated brightness temperatures are generally close to, or within, the estimated spectroscopic uncertainty. For downward-looking views, which more closely match the satellite viewing geometry, the mean differences were generally less than 1.5 K, with the exception of window channels at 89 and 157 GHz, which are significantly influenced by surface properties. These results suggest that both of the absorption models considered are sufficiently accurate for use with ICI.
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RC1: 'Comment on egusphere-2024-229', Anonymous Referee #1, 12 Mar 2024
The manuscript provides an evaluation of two different complete atmospheric absorption models using in radiative transfer simulation for instrument such as Ice Cloud Imager (ICI). Airborne observations were compared to the brightness temperatures simulated using different source of profiles such as in-situ, NWP, sound and retrieved from observations. The manuscript is well written, it provides a systematic validation of the complete absorption models. The manuscript is rich of information. I think the manuscript is ready for publication after some minor revisions that might help clarifying a couple of points:
- Line 100. Why not compare the complete models with a line-by-line model?
- Line 209. In the case of wide antenna beams, does the use of a one-dimensional atmospheric model produce errors due to atmospheric and surface inhomogeneities, and how can this be considered?
- Line 221. Does best-estimate refer to the profile formed by the values obtained from the aircraft's in-situ measurement? What is the lowest altitude of the profile?
- Line 252. Isn't the small difference due to the fact that they are less affected by water vapor?
- Line 268. When using the OEM retrieval, the simulated values are undoubtedly fitted to the observed values, so the difference of the O-B values using the retrieval profiles is small. However, how to show that the retrieval profile is accurate?
Citation: https://doi.org/10.5194/egusphere-2024-229-RC1 -
RC2: 'Comment on egusphere-2024-229', Anonymous Referee #2, 27 Mar 2024
Comment on "An evaluation of atmospheric absorption models at millimetre and sub-millimetre wavelengths using airborne observations'' by S. Fox et al.
Overview:
The paper describes the application of two gas absorption models to simulate observations of airborne measurements in the millimeter and sub-millimeter range. Simulations have been done in close connection to several airborne measurements with upward and nadir looking geometry. The method presented is based on n radiative closure, comparing observed and simulated observations in terms of brightness temperature. The simulations are based on different temperature and humidity profiles, that all are applicable, such as drop sondes, collocated radiosonde observations and temperature and humidity profiles from high resolved numerical weather forecasts.
The different sources of the profiles used for simulating measurements show clear differences and the authors adress this issue with clear analytical methods and assumptions that ensure that the comparisons with the measurements are sound and reasonable.
The authors clearly show that the results of the radiative closure show differing results for different channels and adress the reasons for these with good arguments.The article is important for the future work with data in this spectral range. As described in the paper, these methods will provide the basis for the upcoming validation campaigns of future satellite missions. The publication will help to these methods n order to correctly compare different observations and simulations for validation purposes.
The artiocle is very well written and it is clear what the authors did.
The article covers and describes all important aspects required.
I recommend this article for publication after some minor revisions.It was a pleasure to read this article. It is well written and all aspects that are required to understand the methods and procedures are
described in a clear and concise way.
Specific Comments:Page 6 line 149 :
What is meant by vertical profiles of upward looking brightness temperatures?
Do you refer to different observation angles and thus sensitivity to different altitudes? This sentence is a little bit unclear and needs some clarification.
Page 10, Line 205:
What is does top-hat response mean? I am not familiar with that term, so I am wondering.
Page 11, line 245:
You refer to the standing wave effects that affect the results of the comparison. How do they look like? Is it correct that these are systematic but varying from flight to flight?.Page 11 Line 232 ff:
You refer to the spectroscopic uncertainties at several places. What do these uncertainties refer to? It would be especially interesting for the window channels that show quite large error bars related to the spectroscopic uncertainties.Page 12 line 267:
I like the approach to retrieve profiles and then simulations based on these retrieved profiles. and apparently this improves the result, which is not really surprising the retrieval is based o the observed radiometric measurements. I am wondering, how realistic the retrieved profiles are. From the text, I get the impression that H2O and T are retrieved simultaneously. Is this the case? As the H2O retrieval is depending on the T retrieval and, e.g. for water lines the Temperature profile is affected by the H2O, it would be interesting to see if the retrieved profiles are reasonable.
Are the profile retrievals based on single measurements or on averaged measurements?
Also, related to the question above, what do the brightness temperatures observed at all altitudes mean? Does this refer to the flight altitude?Page 17 Fig 6:
I think in the caption could be noted that this is for the upward looking cases.Page 19 tab 3:
As for Fig 6, you could mention that this refers to the upward looking geometry.About section 5.2:
Did you consider to apply the retrieval approach even for the down-looking observation?Citation: https://doi.org/10.5194/egusphere-2024-229-RC2 -
RC3: 'Comment on egusphere-2024-229', Anonymous Referee #3, 14 Apr 2024
The paper evaluates the performance of two state-of-the-art absorption models using airborne brightness temperature (TB) measurements at high frequencies in light of upcoming satellite missions. Both absorption models are integrated into the radiative transfer (RT) simulator ARTS, and atmospheric profiles are used to simulate TBs. A previous publication by several of the authors (Gallucci et al. 2023) has thoroughly investigated the uncertainties of one of the absorption models introduced imposed on simulated TB. The confrontation of simulated and observed TB shows that both absorption models agree with observation within the large uncertainties imposed by insufficient knowledge of the atmospheric state, measurement uncertainties and/or matching.
General Comments:
1. As mentioned above, the (non-negligible) discrepancies between observed and simulated TBs might have different reasons, though I agree with the authors that the most likely reason is the lack of knowledge on water vapor. In fact, the major finding of the manuscript for me is the difficulty of getting the atmospheric state right and not on the absorption models. Therefore, the discussion should be extended to make this clear, and also it should be reflected in the abstract as a call to the community to work on this highly relevant topic.
2. The title emphasizes the intercomparison of both absorption models. Thus a Table comparing the different ingredients would be very helpful, and easier to comprehend than the text I section 2. Also the work by Galluci et al on uncertainties should be mentioned here. At the end of Section 5.1. the authors conclude that both have similar performance but the interesting question is whether this is because they are similar in their settings or whether compensating effects exist? That there are differences becomes clear in Fig. 6 for the innermost channels of the 183 and 448 lines – this needs to be understood better (see my point 1)
3. The comparison includes two state-of-the-art absorption models. But these are not the ones that are most used in the community today. Though AMSUTRAN is going to be the basis for the next version of RTTOVS, the more important question is how the current version behaves (at least for 89 and 183 GHz channels)? Or the ones that have been used for the generation of ERA5 or other frequently used models (Liebe93, etc)? I completely understand if the authors don’t want to include this in full detail but some rough estimation and general statement would be important for many readers.
4. The paper is relatively poor with respect to “open science” issues and the reproducibility of the results. Maybe the authors can reconsider data publication of drop sondes and radiometer measurements. As no scripts are made available some details on data processing might be given in an appendix. E.g. hardly any information is available on the retrieval scheme.
5. I am rather irritated by the explicit figure captions in the text and the missing descriptions in the figure caption. I typically read the text without looking at the figures, as they should only be the proof for the statements in the text. Such detailed descriptions of different lines strongly disturb the flow of the paper. I didn’t check AMT but most journals give guidelines to avoid this and also say that the captions should be explicit enough that the reader can understand the significance of the illustration without reference to the text.
Specific Comments:
Abstract: l4-6: The text can be misinterpreted – suggest
“In this study, airborne observations of clear-sky scenes between 89 and 664 GHz are used to evaluate two state-of-the-art absorption models, both integrated into the Atmospheric Radiative Transfer Simulator (ARTS). Radiative closure calculations for both upward and downward-looking viewing directions…”
Introduction: The “sister” paper by Gallucci et al. (2023) is quite important for understanding but not introduced in the beginning.
P2, l29 “The brightness temperatures for cloudy scenes are generally reduced compared to the equivalent clear-sky value due to scattering from the ice crystals in the cloud” – make clear that this holds for (thick) ice clouds only
P2l95: Say that they are integrated in ARTS. What is the uncertainty of using this model?
P6l163: identifying regions of enhanced brightness temperature is very vague – I understand you want to be conservative
P7/P8 Dropsonde description is short. Do you use the ASPEN software for corrections. Do you calculate variability in atmospheric to filter for homogeneous scenes? What is the imact of the 15 % humidity correction.
L215 delete blank before .
Section 4: I would have preferred the description of the setup for the RT – construction of the atmospheric state in this section instead of lines 220 (5.1) onwards as this holds for both up and downward looking geometry.
Lines 227 to 238: Figure caption and different lines should not be described in the text, but the content of the plot. The same comment hold for several figures, which I don’t mention later on
L250: 20 K are very large – here, you need to show how much change in water vapor can explain this discrepancy (and whether this is reasonable) before just drawing the conclusion. My gut feeling is that this is the case but there needs to be more detail….especially as you say later (l275) “..that the atmosphere is sufficiently homogenous
L357: Why forecast and not (re)analysis?
L390: Also reanalysis – in the conclusion you could also discuss specific experiment settings
Section 5.2: I am missing information on the surface dependence. Do you get better agreement for calmer sea surfaces?
Figure 2: Horizontal scale needed
Figure 4: What does “partial column” mean – is it just the flight altitude
Fig. 7: Why do you show nadir if (as mentioned in the text anmd also shown in Fig.8 the interest is on 53 deg?
Table 3. Why not show biases?
Supplement: I am missing figure captions – or at least an obvious not of their difference.
Supplement Fig.4: At first glance, the figure might be misleading as the large shaded range at high water vapor points at large differences. I suggest using the second axis and the lower (empty) space to include the number of measurements per water vapor bin to (hopefully show that the majority of measurements have low differences.
Citation: https://doi.org/10.5194/egusphere-2024-229-RC3
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