the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Feb 2024
Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights
Abstract. Cloud geometry and in particular cloud top heights can be derived from 2-D camera measurements by applying a stereographic method to data from an overflight over a scene of clouds (see e.g. Koelling et al., 2019). Although airplane overpasses are relatively fast, cloud motion with the wind is important and can result in errors in the cloud localization. Here, the impact of the wind is investigated using the method from Koelling et al. (2019) for measurements of the airborne hyperspectral imaging system specMACS (spectrometer of the Munich Aerosol Cloud Scanner). Further, a method for the cloud motion correction using model winds from ECMWF is presented. It is shown that the update is important as the original algorithm without the cloud motion correction can over- or underestimate the cloud top heights by several hundred meters dependent on the wind speed and the relative wind direction. This is validated using data from the EUREC4A campaign as well as realistic 3-D radiative transfer simulations. From the comparison of the derived cloud top heights to the expected ones from the model input an average accuracy of the cloud top heights of less than (20 ± 140) m (mean deviation and one standard deviation) is estimated for the updated method.
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RC1: 'Comment on amt-2024-19', Anonymous Referee #1, 25 Mar 2024
This study shows that triangulation from an overpass flight photography can reconstruct well cloud topography if the horizontal wind is taken into account. Since the wind is changing with height, the correction is iterative. A wind-driven height bias of up to ~200 m is replaced, when corrected for the wind, with little bias with a random height error of 140 m. This is very nice but ignores the fact that the clouds are convective, and the vertical growth rate of the clouds can be in the order of half of the horizontal wind speed of 7 m/s in this case. An interesting question is to what extent can the remaining error be caused by the cloud's vertical growth rate? This question can be answered both theoretically, and based on the simulation part.
A missing number is the simulated flight height above the simulated cloud.
Citation: https://doi.org/10.5194/amt-2024-19-RC1 - AC1: 'Reply on RC1', Lea Volkmer, 19 Jul 2024
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RC2: 'Comment on amt-2024-19', Anonymous Referee #2, 14 Jun 2024
Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights
Lea Volkmer, Tobias Kölling, Tobias Zinner, and Bernhard Mayer
General comments
The paper is well written and has an overall clear structure and figures. The topic is interesting and fits well to the aims and scopes of AMT. The paper describes an extension of an existing method from Kölling et al. (2019) to derive the cloud top heights from airplane measurements. The extension takes cloud movement into account. The goal of the paper is clearly motivated and straight forward.
In principle the approach the authors present in their paper is very valuable and have great potential to improve the cloud top height retrieval from aircraft. It is interesting and suitable for publication in AMT. It is recommended for publication after minor revisions.
Minor comments
Wind correction based on ERA5 reanalysis data
Please, add also Pcs in the text.
p. 3, line 90: “of the point on the cloud surface (Pcs)”
to Figure 1: In the printed version the clouds are quite faint.
Validation using measurements from EUREC4A campaign
Figure 2 should be enlarged, it hard to see.
p.4, line 109: “no significant change” To be more precise, a value should be given here.
Figure 3: Could you include the PDF of the WALES measurement, the comparison would be benefit from it.
Accuracy estimation using realistic simulated measurements from 3-D radiative transfer simulations
p.7, line 133. Can you add an explanation why the used wind speed in the simulations is chosen lower than the real measurement before?
Conclusion
To the conclusion: It should be mentioned that further studies with more inhomogeneous cloud state should be added. Since the correction will be even more necessary.
Citation: https://doi.org/10.5194/amt-2024-19-RC2 - AC2: 'Reply on RC2', Lea Volkmer, 19 Jul 2024
Status: closed
-
RC1: 'Comment on amt-2024-19', Anonymous Referee #1, 25 Mar 2024
This study shows that triangulation from an overpass flight photography can reconstruct well cloud topography if the horizontal wind is taken into account. Since the wind is changing with height, the correction is iterative. A wind-driven height bias of up to ~200 m is replaced, when corrected for the wind, with little bias with a random height error of 140 m. This is very nice but ignores the fact that the clouds are convective, and the vertical growth rate of the clouds can be in the order of half of the horizontal wind speed of 7 m/s in this case. An interesting question is to what extent can the remaining error be caused by the cloud's vertical growth rate? This question can be answered both theoretically, and based on the simulation part.
A missing number is the simulated flight height above the simulated cloud.
Citation: https://doi.org/10.5194/amt-2024-19-RC1 - AC1: 'Reply on RC1', Lea Volkmer, 19 Jul 2024
-
RC2: 'Comment on amt-2024-19', Anonymous Referee #2, 14 Jun 2024
Consideration of the cloud motion for aircraft-based stereographically derived cloud geometry and cloud top heights
Lea Volkmer, Tobias Kölling, Tobias Zinner, and Bernhard Mayer
General comments
The paper is well written and has an overall clear structure and figures. The topic is interesting and fits well to the aims and scopes of AMT. The paper describes an extension of an existing method from Kölling et al. (2019) to derive the cloud top heights from airplane measurements. The extension takes cloud movement into account. The goal of the paper is clearly motivated and straight forward.
In principle the approach the authors present in their paper is very valuable and have great potential to improve the cloud top height retrieval from aircraft. It is interesting and suitable for publication in AMT. It is recommended for publication after minor revisions.
Minor comments
Wind correction based on ERA5 reanalysis data
Please, add also Pcs in the text.
p. 3, line 90: “of the point on the cloud surface (Pcs)”
to Figure 1: In the printed version the clouds are quite faint.
Validation using measurements from EUREC4A campaign
Figure 2 should be enlarged, it hard to see.
p.4, line 109: “no significant change” To be more precise, a value should be given here.
Figure 3: Could you include the PDF of the WALES measurement, the comparison would be benefit from it.
Accuracy estimation using realistic simulated measurements from 3-D radiative transfer simulations
p.7, line 133. Can you add an explanation why the used wind speed in the simulations is chosen lower than the real measurement before?
Conclusion
To the conclusion: It should be mentioned that further studies with more inhomogeneous cloud state should be added. Since the correction will be even more necessary.
Citation: https://doi.org/10.5194/amt-2024-19-RC2 - AC2: 'Reply on RC2', Lea Volkmer, 19 Jul 2024
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