Exploring the uncertainties in the aviation soot–cirrus effect

Righi, Mattia; Hendricks, Johannes; Beer, Christof Gerhard

doi:https://doi.org/10.5194/acp-21-17267-2021

Articles | Volume 21, issue 23

https://doi.org/10.5194/acp-21-17267-2021

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the Creative Commons Attribution 4.0 License.

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https://doi.org/10.5194/acp-21-17267-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 23

Research article

|

30 Nov 2021

Research article |

| 30 Nov 2021

Exploring the uncertainties in the aviation soot–cirrus effect

Mattia Righi, Johannes Hendricks, and Christof Gerhard Beer

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Final revised paper (published on 30 Nov 2021)
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Preprint (discussion started on 18 Jun 2021)
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Interactive discussion

Status: closed

CC1:
'Comment on acp-2021-329', Bernd Kärcher, 25 Jun 2021

Obtaining robust estimates of the indirect effect of aviation soot on cirrus clouds is an important and timely issue [Lee et al., 2021]. This topic has been discussed for a number of years, mainly on the basis of global models and with conflicting results. The present paper is the latest attempt to arrive at a GCM-based solution and discusses, as a novel feature, how aspects of the model dynamics contributes, in idealized model experiments, to uncertainty in global radiative forcing from soot-cirrus interactions.
I’d like to point the authors to two publications [Marcolli et al. 2021; Kärcher et al., 2021] that offer an unprecedented opportunity to better constrain the radiative forcing from soot-cirrus interactions using the latest findings from laboratory studies and process modeling.
It is important to include atmospheric trajectories and size information of INPs in estimations of their ice activity. The authors are aware that (i) cloud processing has been found to be crucial to render aircraft-emitted soot particles ice-active and (ii) their ice-forming abilities are strongly size-dependent (Fig.1). There’s also data available on the size (i.e., mobility diameter) distribution of aircraft-emitted soot particles, e.g., from recent aircraft campaigns carried out by NASA and DLR, or from recently developed soot models used in global emission inventories [see Kärcher, 2018, for references].
Stitching together these two pieces of information allows size-integrated ice-active fractions of aviation soot populations previously processed in contrails to be easily derived. In combination with soot ageing processes (i.e., the build-up of aqueous coatings and subsequent de-activation of ice formation), these fractions would allow the authors to more realistically constrain their range of RF estimates and improve on their parametric study of uncertainties due to ice nucleation properties of aviation soot particles that are superseded by new measurements and analysis [Marcolli et al., 2021].
I understand that the parameterization scheme used to estimate the ice nucleation behavior of soot INPs [Kärcher et al., 2006] does not capture the changing ice-activated INP number fractions with increasing supersaturation by assuming a sharp critical nucleation threshold. This parameterization does not allow for the INP-derived ice crystal concentrations to build up gradually over a range of supersaturation and, hence, precludes an accurate estimation of the INP impact on cirrus formation.
In spite of this situation, the relevance of the study can be increased by properly addressing the single key microphysical aspect of the simulations, whereby I recommend using more appropriate estimations of both, activated fraction and nucleation threshold. The former happens to be greatly overestimated while the latter is underestimated in the present study. In my opinion, interpretation of results is greatly aided by separating (1) the fraction of contrail-processed soot particles from (2) the fraction of soot particles that become ice-active at a given supersaturation and (3) the fraction that gets coated and is rendered inactive. (1) might be estimated from global models that track contrails and contrail cirrus as separate from other clouds. (2) follows from Marcolli et al. [2021] and Kärcher et al. [2021] for given soot particle size distributions. (3) would be estimated in the global aerosol-climate model based on the current representation of aerosol processes.

References
Lee, D. S. et al. The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018 Atmos. Environ. 244, https://doi.org/10.1016/j.atmosenv.2020.117834, 2021
Marcolli, C., Mahrt, F. & Kärcher, B.

Soot PCF: pore condensation and freezing framework for soot aggregates

Atmos. Chem. Phys., 21, https://doi.org/10.5194/acp-21-7791-2021, 2021
Kärcher, B., Mahrt, F. & Marcolli, C.

Process-oriented analysis of aircraft soot-cirrus interactions constrains the climate impact of aviation

Commun. Earth Environ., 2, 113, https://doi.org/10.1038/s43247-021-00175-x, 2021
Kärcher, B.

Formation and radiative forcing of contrail cirrus

Nat. Commun., 9, https://doi.org/10.1038/s41467-018-04068-0, 2018
Kärcher, B., Hendricks, J. & Lohmann, U.

Physically based parameterization of cirrus cloud formation for use in global atmospheric models

J. Geophys. Res., 111, https://doi.org/10.1029/2005JD006219, 2006

Citation: https://doi.org/10.5194/acp-2021-329-CC1
- AC1: 'Reply on CC1', Mattia Righi, 08 Sep 2021
  
  The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-329/acp-2021-329-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/acp-2021-329-AC1
RC1: 'Comment on acp-2021-329', Andrew Gettelman, 30 Jun 2021

Review of "Exploring the uncertainties in the aviation soot-cirrus effect" by Mattia Righi et al.

Review by Andrew Gettelman

This manuscript performs an in-depth investigation of the effect of aviation soot on aviation radiative forcing. The topic is an important uncertainty in aviation climate effects and is well suited for ACP. The manuscript is well written and should be publishable in ACP subject to some significant revisions and clarifications.

General comments:

1. The manuscript could do a bit better at highlighting the importance of the model base state of clouds for the soot effect, and the balance of homogeneous v. heterogeneous ice nucleation. This seems to be a critical factor. Maybe the EMAC-MADE3 values could be compared to other previous work (e.g. similar to figures 4 and 5 in Gettelman et al 2012)

Gettelman, A., X. Liu, D. Barahona, U. Lohmann, and C. C. Chen. 2012. “Climate Impacts of Ice Nucleation.” Journal of Geophysical Research 117 (D20201). https://doi.org/10.1029/2012JD017950.

2. It would be nice to dive into the microphysics a bit. Could you perhaps show sensitivity plots for Figure 3 (especially zonal mean mass and number concentrations) and maybe ice crystal number and mass? This would be very helpful at understanding radiative forcing.

For vertical velocity perturbations this is all buried in Figure S7, but would probably be more useful to try to put in the main text for this as well as for the different Script and f values. Maybe the relevant properties from figure S7 for each case could be reduced to a zonal mean perturbation, and then the line plot would enable all sensitivity studies to be put on one plot. Clearsky ant total water are probably not that relevant. That would leave a 6 panel figure with all the relevant information. One for W perturbations and one for the Scrit and F perturbations.

3. In addition, can you state what the contrail RF is for just H2O without aerosol perturbations? This would be a useful baseline to compare to other work (e.g., estimates in Lee et al 2021). Maybe this is in Righi et al 2020, but please state it here and note how it is similar (or not) to other work.

Specific Comments:

Page 1, L24: ‘milden’ is not an English word. Maybe ‘reduce’

Also note the pandemic did temporarily reduce the increase. See Gettelman et al 2021.

Gettelman, Andrew, Chieh-Chieh Chen, and Charles G. Bardeen. 2021. “The Climate Impact of COVID-19-Induced Contrail Changes.” Atmospheric Chemistry and Physics 21 (12): 9405–16. https://doi.org/10.5194/acp-21-9405-2021.

Page 2, L59: no statistically significant effects were reported by Gettelman…

Page 4, L119: I don’t think you mentioned this important point (or at least not sufficiently) in the introduction: that the model cloud state (humidity and water content and homo or heterogeneous nucleation dominance) may determine the response to soot as well. This has been discussed in the literature before, and should be highlighted in the introduction. See general comment above

Page 7, L178: what do these gamma values mean? Please state what autoconversion scheme is being used. Is the minimum CDNC for the autoconversion scheme or independent?

Page 7, L195: aviation soot = BCtag?

Page 9, L230: is there a timescale for the nudging or is it replacement of the model dynamical fields?

Page 14, L289: What is the overall contrail RF with and without soot (I.e. just aviation H2O)? That helps put this study in context of other work. See general comment.

Page 14, L315: I’m not quite following this logic. How does enhanced cloud lifetime mesh with reduced cloud fraction?

Page 16, L352: how does this compare to the total contrail RF?

Page 17, L363: order of tens of mWm-2

Page 18, L377: seems like the activation efficiency is key for disparity across studies. Can you intuit anything about model dynamics and cloud environment?

Page 19, L407: pair of assumptions for the ice nucleation….

Page 20, L416: so the effect jumps around with sub grid W? That seems a bit worrisome. You explanation is plausible however that the effect changes sign of sensitivity with W.

Page 23, L510: maybe you could plot homogenous IN faction? This may be a good model metric for comparison?

Can you comment any more here about the impact of the model base state on response to aircraft soot? Seems like you can draw some significant conclusions, basing the homo v. Hetero balance on your variation of w and Scrit?

Citation: https://doi.org/10.5194/acp-2021-329-RC1
RC2: 'Comment on acp-2021-329', Anonymous Referee #1, 08 Jul 2021

Please see my comments in supplement.

Citation: https://doi.org/10.5194/acp-2021-329-RC2
AC2: 'Authors' replies', Mattia Righi, 08 Sep 2021

The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-329/acp-2021-329-AC2-supplement.pdf

Citation: https://doi.org/10.5194/acp-2021-329-AC2

Peer review completion

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

AR by Mattia Righi on behalf of the Authors (08 Sep 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (19 Sep 2021) by Xiaohong Liu

RR by Anonymous Referee #1 (30 Sep 2021)

RR by Anonymous Referee #2 (03 Oct 2021)

ED: Publish as is (31 Oct 2021) by Xiaohong Liu

AR by Mattia Righi on behalf of the Authors (02 Nov 2021) Manuscript

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Short summary

A global climate model is applied to simulate the impact of aviation soot on natural cirrus clouds. A large number of numerical experiments are performed to analyse how the quantification of the resulting climate impact is affected by known uncertainties. These concern the ability of aviation soot to nucleate ice and the role of model dynamics. Our results show that both aspects are important for the quantification of this effect and that discrepancies among different model studies still exist.