Satellite observations of seasonality and long-term trend in cirrus cloud properties over Europe: Investigation of possible aviation impacts

Li, Qiang; Groß, Silke

doi:https://doi.org/10.5194/egusphere-2022-628

Preprints

https://doi.org/10.5194/egusphere-2022-628

Preprints

20 Jul 2022

| 20 Jul 2022

Satellite observations of seasonality and long-term trend in cirrus cloud properties over Europe: Investigation of possible aviation impacts

Qiang Li and Silke Groß

Abstract. Aircrafts emit exhaust gases and soot into the atmosphere, which may increase global cirrus cloudiness and as well change the properties of already existing cirrus. In the first COVID-19 lockdown in Europe, changes in cirrus cloud occurrence and properties were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO₂ emissions and flight densities in Europe. In the current study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed. The Linear contrails and contrail cirrus induced by global aviation have long been known to contribute to climate change by warming the atmosphere. Besides increasing global cirrus cloudiness, aviation may change the properties of the natural cirrus clouds by soot emissions which leads to increased heterogeneous freezing. In the first COVID-19 lockdown in Europe, changes in cirrus cloud properties and occurrence were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO₂ emissions and flight densities in Europe. In this study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed to determine the seasonality and long-term trends in cirrus clouds as well as their correlations with the ambient temperatures and air traffic. Cirrus clouds follow a distinct seasonal cycle in their occurrence rate (OR) and particle linear depolarization ratio (PLDR) δ_p. Cirrus clouds appear within a broader altitude range in winter than in summer and they are characterized by larger OR and δ_p values in winter than in summer. The monthly medians of δ_p as well as the deseasonalized time series of them in the 10-year period before COVID show both positive trends which are statistically significant according to the Mann-Kendall (MK) significance test. However, the cirrus occurrence shows a negative trend, which might be connected with the background meteorological conditions. Since the cirrus δ_p strongly depends on the ambient temperatures in cirrus, we further remove the contributions induced by temperatures from the cirrus δ_p with a simple linear regression model. The derived residuals show significant positive trends with the MK test. To compare the cirrus δ_p and the air traffic densities, the deseasonalization of the data have previously been conducted since the seasonal cycles in both are not consistent. The deseasonalized time series of the cirrus δ_p and CO₂ emissions from aviation both show an increasing trend and their correlation coefficients are r = 0.54 at the confidence level above 99.5 %. Finally, the comparisons between the cirrus δ_p and aviation in every season were carried out and revealed a strong correlation in other seasons than in summer.

Received: 12 Jul 2022 – Discussion started: 20 Jul 2022

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Journal article(s) based on this preprint

20 Dec 2022

Satellite observations of seasonality and long-term trends in cirrus cloud properties over Europe: investigation of possible aviation impacts

Qiang Li and Silke Groß

Atmos. Chem. Phys., 22, 15963–15980, https://doi.org/10.5194/acp-22-15963-2022,https://doi.org/10.5194/acp-22-15963-2022, 2022

Short summary

Qiang Li and Silke Groß

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-628', Anonymous Referee #1, 05 Oct 2022

In this work 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed to determine inter and intra annual variability and trends of their occurrence and optical characteristics, namely depolarization. Correlation with atmospheric temperatures and air traffic are also explored.

A seasonal cycle was detected both in occurrence and optical properties, with larger values of both parameters in winter A positive trend in the deseasonalized depolarisation time serie and a negative trend in the deseasonalized occurrence rate time serie were also demonstrated.

As the author claims that there exists a positive trend in air temperature at cirrus altitude, and since depolarization is temperature dependent to a certain extent, they remove such effect from the depolarization time series. This is done by applying a linear regression model on the depolarization-temperature dependence and subtracting the model from the depolarization time series. The time series of the depolarization residuals again shows a positive trend. The author link this positive trend to an increase of air traffic over the time window of the dataset, this latter estimated from the increase in its contribution in CO2 emissions.

The work is interesting and important and certainly deserves to be published. However, there are two aspects that, in my opinion, need further study before publicaton.

First, I must note that the work it is not fully convincing in studying the interannual trend of air temperatures. In fact, while the seasonal trend of temperatures is clear, a decadal trend is not. I think this is the biggest problem of the work, which otherwise demonstrates a sufficient maturity to ensure its publication. For this reason, I encourage the authors to dwell more on the study of the decadal trend of the air temperature, to accompany their findings with any supporting literature or otherwise to make their claims on such topic less assertive.

A second aspect that has not been sufficiently analyzed concerns the lack of an analysis if the observed trends are due to only to the increase in cirrus originated by contrail, or rather to changes in the microphysics of cirrus clouds in general. I do not know (I doubt with sole lidar data) if there is the possibility of dividing the dataset into two categories, based on the proximity of the observations to air corridors, or on the vertical and/or optical thickness of the cirrus clouds, or their horizontal (i.e. along satellite track) extent in order to identify the cirrus clouds originating from contrail with respect to the “natural” others. If such categorization were possible, the work would undoubtedly benefit from a non-aggregated analysis. In any case, I believe that the question should still be discussed.

One final note, I as a non-native English speaker, found English of the text rather tiring to read. I would suggest having the text proofread by a native English speaker.

In the following, moredetailed annotations on the text (page, line)

(1,4) “…are supposed…”

(2,56) typo “depdendence”

(3,68-69) Unclear. Could rephrase as : “The light emitted by lidar AND BACKSCATTERED BY SPHERICAL PARTICLES exhibit the same orientation of polarization as the incident light if it is scattered WHILE THE POLARIZATION CHANGES and different polarization if scattered WHEN THE LIGHT IS BACKSCATTERED by non-spherical particles such as cirrus ice crystals.”

(3,71) I would cancel , “e.g., non-spherical mineral dust particles with high values of δp“ or add other types of non-spherical aerosol that have different mean values of δp (Biomas Burning aerosol, Sea Salt, etc..)

(3,75) Pristine habits are mainly driven by the temperature at which a crystal forms and, maybe to a lesser extent, by the humidity of the air. However the internal cloud dynamics and lifetime duration and stage strongly influence the shape of crystals as well. That should be mentioned.

(4,112) Typo „difficulat“

(4,112-113) „However, there is an aviation fingerprint with two maxima during eastbound and afternoon westbound traffic in the area we are focusing on here.“ maximum of what? what is the area we are focusing on?

(4,114) „Therefore…“ the lack of clarity of the previous sentence makes its consequences unclear.

(4,116-118) This should be shifted upward.

(5,135) „extreme lower“. Lowest?

(5,139-140) Could you comment on the statistical significance of such results? At face value it does not seem high.

(5,141-144) Please discuss the statistical significance of the findings.

(5,149-153) I honestly don't think this assertion is sufficiently supported by the above analysis. Tests for the presence of trend, confidence intervals for the trend, etc. should have been performed. In the absence of such tests (which however I encourage the authors to conduct) I suggest reformulating the sentence in a less assertive form and / or recalling any studies in the literature supporting these same conclusions.

(5,156) To my knowledge, the common cruising altitude for most commercial airplanes is between 10 and 13 km . typically, aircraft fly around 10-11 km.

(6,175) “Please note…” How do you exclude deep convecton cirrus? Please specify the methodology.

(10,288-295) “Generally…temperatures.” As in the subsequent analysis the nonlinear regression models have not been used, there is no need to quote them here. Unless you provide a justification for the choice of the linear instead of the non linear one.

(13,354) See my comment on (5,149-153).

Citation: https://doi.org/10.5194/egusphere-2022-628-RC1
- AC1: 'Reply on RC1', Qiang Li, 11 Nov 2022
  
  We thank the Referee for carefully reading our manuscript and for the comments and suggestions to improve the current work. Please see the supplement for our responses in details.
  
  Citation: https://doi.org/10.5194/egusphere-2022-628-AC1
RC2:
'Comment on egusphere-2022-628', Anonymous Referee #2, 14 Oct 2022
The paper by Qiang Li and Silke Groß is highly interesting and robust.

It is relevant in showing how vertical profiles from satellites could give a better insight of the atmospheric estate, fill gaps in knowledge, and pose new scientific questions.

As general comments, I think it is detailed and many investigations are reported. The impression is that the reader can sometimes be lost in the progress of such reporting. I would suggest reducing the number of figures and focusing more on what is the main result. Figure 12 is the main message that probably authors would like to give as a take-home message, but this is somehow diluted by the presence of many analyses: these are relevant for reaching the main results but could be shortened and eventually reported as an appendix or additional material.

Apart from this general comment, 3 are the points to be clarified /discussed/fixed in the paper:

It seems that 2 different models are used for temperature and humidity during the investigation: ECMWF and GEOS. Why this difference? Why not use the same for the 2 analyses reported? Please clarify

In the PLRD temporal behavior of fig 12, there is an anomaly in the 2010 and 2017-2019 (mainly 2018) period: is it possible that the big volcanic eruption affecting Europe in 2010 is the cause of the 2010 anomaly? Is the aerosol/cloud misclassification in VFM a potential issue then? Which could be the reason for the lower PDLR in 2017-2018? Please discuss this point

I am not a native English speaker, but the paper is somehow hard to read. I reported some revisions in the comments in the attached pdf, but these are just examples. Please revise the paper carefully in this sense.

These and more detailed points are reported as comments in the pdf file.
Citation: https://doi.org/10.5194/egusphere-2022-628-RC2
- AC2: 'Reply on RC2', Qiang Li, 11 Nov 2022
  
  We thank the Referee for carefully reading our manuscript and for the comments and suggestions to improve the current work. Please see the supplement for our responses in details.
  
  Citation: https://doi.org/10.5194/egusphere-2022-628-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-628', Anonymous Referee #1, 05 Oct 2022

In this work 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed to determine inter and intra annual variability and trends of their occurrence and optical characteristics, namely depolarization. Correlation with atmospheric temperatures and air traffic are also explored.

A seasonal cycle was detected both in occurrence and optical properties, with larger values of both parameters in winter A positive trend in the deseasonalized depolarisation time serie and a negative trend in the deseasonalized occurrence rate time serie were also demonstrated.

As the author claims that there exists a positive trend in air temperature at cirrus altitude, and since depolarization is temperature dependent to a certain extent, they remove such effect from the depolarization time series. This is done by applying a linear regression model on the depolarization-temperature dependence and subtracting the model from the depolarization time series. The time series of the depolarization residuals again shows a positive trend. The author link this positive trend to an increase of air traffic over the time window of the dataset, this latter estimated from the increase in its contribution in CO2 emissions.

The work is interesting and important and certainly deserves to be published. However, there are two aspects that, in my opinion, need further study before publicaton.

First, I must note that the work it is not fully convincing in studying the interannual trend of air temperatures. In fact, while the seasonal trend of temperatures is clear, a decadal trend is not. I think this is the biggest problem of the work, which otherwise demonstrates a sufficient maturity to ensure its publication. For this reason, I encourage the authors to dwell more on the study of the decadal trend of the air temperature, to accompany their findings with any supporting literature or otherwise to make their claims on such topic less assertive.

A second aspect that has not been sufficiently analyzed concerns the lack of an analysis if the observed trends are due to only to the increase in cirrus originated by contrail, or rather to changes in the microphysics of cirrus clouds in general. I do not know (I doubt with sole lidar data) if there is the possibility of dividing the dataset into two categories, based on the proximity of the observations to air corridors, or on the vertical and/or optical thickness of the cirrus clouds, or their horizontal (i.e. along satellite track) extent in order to identify the cirrus clouds originating from contrail with respect to the “natural” others. If such categorization were possible, the work would undoubtedly benefit from a non-aggregated analysis. In any case, I believe that the question should still be discussed.

One final note, I as a non-native English speaker, found English of the text rather tiring to read. I would suggest having the text proofread by a native English speaker.

In the following, moredetailed annotations on the text (page, line)

(1,4) “…are supposed…”

(2,56) typo “depdendence”

(3,68-69) Unclear. Could rephrase as : “The light emitted by lidar AND BACKSCATTERED BY SPHERICAL PARTICLES exhibit the same orientation of polarization as the incident light if it is scattered WHILE THE POLARIZATION CHANGES and different polarization if scattered WHEN THE LIGHT IS BACKSCATTERED by non-spherical particles such as cirrus ice crystals.”

(3,71) I would cancel , “e.g., non-spherical mineral dust particles with high values of δp“ or add other types of non-spherical aerosol that have different mean values of δp (Biomas Burning aerosol, Sea Salt, etc..)

(3,75) Pristine habits are mainly driven by the temperature at which a crystal forms and, maybe to a lesser extent, by the humidity of the air. However the internal cloud dynamics and lifetime duration and stage strongly influence the shape of crystals as well. That should be mentioned.

(4,112) Typo „difficulat“

(4,112-113) „However, there is an aviation fingerprint with two maxima during eastbound and afternoon westbound traffic in the area we are focusing on here.“ maximum of what? what is the area we are focusing on?

(4,114) „Therefore…“ the lack of clarity of the previous sentence makes its consequences unclear.

(4,116-118) This should be shifted upward.

(5,135) „extreme lower“. Lowest?

(5,139-140) Could you comment on the statistical significance of such results? At face value it does not seem high.

(5,141-144) Please discuss the statistical significance of the findings.

(5,149-153) I honestly don't think this assertion is sufficiently supported by the above analysis. Tests for the presence of trend, confidence intervals for the trend, etc. should have been performed. In the absence of such tests (which however I encourage the authors to conduct) I suggest reformulating the sentence in a less assertive form and / or recalling any studies in the literature supporting these same conclusions.

(5,156) To my knowledge, the common cruising altitude for most commercial airplanes is between 10 and 13 km . typically, aircraft fly around 10-11 km.

(6,175) “Please note…” How do you exclude deep convecton cirrus? Please specify the methodology.

(10,288-295) “Generally…temperatures.” As in the subsequent analysis the nonlinear regression models have not been used, there is no need to quote them here. Unless you provide a justification for the choice of the linear instead of the non linear one.

(13,354) See my comment on (5,149-153).

Citation: https://doi.org/10.5194/egusphere-2022-628-RC1
- AC1: 'Reply on RC1', Qiang Li, 11 Nov 2022
  
  We thank the Referee for carefully reading our manuscript and for the comments and suggestions to improve the current work. Please see the supplement for our responses in details.
  
  Citation: https://doi.org/10.5194/egusphere-2022-628-AC1
RC2:
'Comment on egusphere-2022-628', Anonymous Referee #2, 14 Oct 2022
The paper by Qiang Li and Silke Groß is highly interesting and robust.

It is relevant in showing how vertical profiles from satellites could give a better insight of the atmospheric estate, fill gaps in knowledge, and pose new scientific questions.

As general comments, I think it is detailed and many investigations are reported. The impression is that the reader can sometimes be lost in the progress of such reporting. I would suggest reducing the number of figures and focusing more on what is the main result. Figure 12 is the main message that probably authors would like to give as a take-home message, but this is somehow diluted by the presence of many analyses: these are relevant for reaching the main results but could be shortened and eventually reported as an appendix or additional material.

Apart from this general comment, 3 are the points to be clarified /discussed/fixed in the paper:

It seems that 2 different models are used for temperature and humidity during the investigation: ECMWF and GEOS. Why this difference? Why not use the same for the 2 analyses reported? Please clarify

In the PLRD temporal behavior of fig 12, there is an anomaly in the 2010 and 2017-2019 (mainly 2018) period: is it possible that the big volcanic eruption affecting Europe in 2010 is the cause of the 2010 anomaly? Is the aerosol/cloud misclassification in VFM a potential issue then? Which could be the reason for the lower PDLR in 2017-2018? Please discuss this point

I am not a native English speaker, but the paper is somehow hard to read. I reported some revisions in the comments in the attached pdf, but these are just examples. Please revise the paper carefully in this sense.

These and more detailed points are reported as comments in the pdf file.
Citation: https://doi.org/10.5194/egusphere-2022-628-RC2
- AC2: 'Reply on RC2', Qiang Li, 11 Nov 2022
  
  We thank the Referee for carefully reading our manuscript and for the comments and suggestions to improve the current work. Please see the supplement for our responses in details.
  
  Citation: https://doi.org/10.5194/egusphere-2022-628-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Qiang Li on behalf of the Authors (11 Nov 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to minor revisions (review by editor) (14 Nov 2022) by Matthias Tesche

AR by Qiang Li on behalf of the Authors (21 Nov 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (22 Nov 2022) by Matthias Tesche

AR by Qiang Li on behalf of the Authors (22 Nov 2022) Manuscript

Journal article(s) based on this preprint

20 Dec 2022

Satellite observations of seasonality and long-term trends in cirrus cloud properties over Europe: investigation of possible aviation impacts

Qiang Li and Silke Groß

Atmos. Chem. Phys., 22, 15963–15980, https://doi.org/10.5194/acp-22-15963-2022,https://doi.org/10.5194/acp-22-15963-2022, 2022

Short summary

Qiang Li and Silke Groß

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The IPCC report identified that cirrus clouds have significant impacts on the radiation balance comparable to the CO₂ effects, which, however, are still hard to parameterize. The current study aims to investigate the possible aviation impact on cirrus properties based on the analysis of 10-year lidar measurements of CALIPSO. The results reveal that there is a significant positive trend in cirrus depolarization ratio in the last 10 years before COVID, which is strongly correlated with aviation.


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