Impacts of multi-layer overlap on contrail radiative forcing

Sanz-Morère, Inés; Eastham, Sebastian D.; Allroggen, Florian; Speth, Raymond L.; Barrett, Steven R. H.

doi:https://doi.org/10.5194/acp-21-1649-2021

Articles | Volume 21, issue 3

https://doi.org/10.5194/acp-21-1649-2021

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

https://doi.org/10.5194/acp-21-1649-2021

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

Articles | Volume 21, issue 3

Research article

|

09 Feb 2021

Research article |

| 09 Feb 2021

Impacts of multi-layer overlap on contrail radiative forcing

Inés Sanz-Morère, Sebastian D. Eastham, Florian Allroggen, Raymond L. Speth, and Steven R. H. Barrett

Download

Final revised paper (published on 09 Feb 2021)
Supplement to the final revised paper
Preprint (discussion started on 05 May 2020)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review', Anonymous Referee #1, 25 May 2020
RC2: 'Effect of contrail overlap on radiative impact attributable to aviation contrails', Anonymous Referee #2, 29 Jun 2020
SC1: 'Some comments including more information on GCM overlap treatment', Michael Ponater, 30 Jun 2020
AC1: 'Response to referee and community comments', Sebastian Eastham, 31 Jul 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Sebastian Eastham on behalf of the Authors (31 Jul 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (24 Aug 2020) by Michael Pitts

RR by Anonymous Referee #1 (08 Sep 2020)

RR by Anonymous Referee #2 (05 Oct 2020)

Suggestions for revision or reasons for rejection

The paper was significantly improved by a clearer definition of the goals of the paper, sharpening the arguments and a major rewrite of the parts summarizing the background literature. The paper in its current form is very interesting and contains useful information that adds to our understanding of contrail RF. Some parts of the paper still contain parts/sentences from the prior paper version that the authors agreed in their answers to remove or wording that needs to be corrected. A few small corrections should be made to the paper before it can be published.
Comments:
1. You say that ‘Contrail contrail overlap can likely be neglected’. But you actually only look at whether it can be neglected when estimating the radiative response. Contrails forming in older contrails, which seems to be part of your contrail-contrail overlap, may still have a significant impact microphysically. It should be specified that contrail contrail overlap can likely be neglected radiatively which leaves it open if it might have an impact microphsically.
2. You may want to cite the new Lee et al. (2020) assessment instead of Lee et al. (2009) as this has been published recently in Atmospheric Environment
3. Page 9: Burkhardt and Kärcher (2011) and Bock and Burkhardt (2016) do not use the approach of Ponater et al. (2002) who simulates line-shaped contrails. Instead they use a very different, process-based contrail cirrus parameterization based on Burkhardt and Kärcher (2009). Please correct this.
4. Page 19 line 422-424: contrail-contrail overlap is mostly assumed to occur with maximum-random (and not random) overlap in climate models (see your table 3). What does ‘true maximum overlap’ mean? How do you know what is the truth? I thought we agreed that maximum overlap is an extreme assumption.
5. Page 21 Line 470-471: How would it be possible to capture the effect of changes in natural cloudiness due to the presence of contrails in observational data while not including the contrails themselves? Either you have a data set of natural clouds plus contrails which will include the natural cloud adjustments to contrails or you may choose only situations in which you believe no contrails can be present and then the data won’t include cloud adjustments or contrails.
6. Page 21 Line 483-484: How can a nonlinearity be representative of a bias? Additionally, according to your answers to my last review we agree that your study does not give an estimate of the bias of the radiative forcing estimates in the literature. You should remove this sentence together with the sentence on page 24 line 535-536.
7. In section 4.2 and 4.3.1 it should be mentioned at the beginning of those sections that you assume maximum overlap.
8. You still use often the word ‘interaction’ instead of ‘overlap’. You should go through the whole paper and make sure that you use the correct word.
9. Page 44, line 1012: the overlap of contrails and clouds could only be calculated (instead of making overlap assumptions) if the model resolution gets close to a few km and fractional cloud cover schemes are not needed anymore. As soon as you need a fractional cloud cover scheme you do not know which part of a model grid box is cloudy and which part is cloud free. This means that you cannot calculate overlap without making overlap assumptions. Furthermore, it is necessary to prescribe real flight movements connected with a particular synoptic situation as flight tracks depend on and clouds vary with meteorology.
10. The section of ‘Priorities for future work’ should include improvements in the temporal resolution of cloud data. If the temporal resolution is not improved then the correlation of contrail and natural clouds and therefore their overlap cannot be captured.
11. Page 45, line 1028-1029: I agree that the results in this paper improve our understanding of the factors which contribute to global contrail RF, but I do not agree that the work helps us improve estimates of contrail RF – I thought we had agreed on that. I also cannot find any further mention of a resulting improvement of the current estimates in the conclusions. If you are talking about CERM not having considered overlap with clouds before then please say that the work improves estimates made by CERM.

Hide

ED: Reconsider after major revisions (20 Oct 2020) by Michael Pitts

AR by Sebastian Eastham on behalf of the Authors (20 Nov 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (23 Nov 2020) by Michael Pitts

RR by Anonymous Referee #1 (29 Nov 2020)

RR by Anonymous Referee #2 (21 Dec 2020)

Suggestions for revision or reasons for rejection

As I commented already in my last review the paper is much improved. Therefore, I had only a quick look through the paper and want to comment on a couple of small mistakes and suggest slight changes. I want to congratulate the authors on this interesting paper.
Comments:
1. Table 1:
a) The Burkhardt and Kärcher estimates were calculated for air traffic of the year 2002 for both linear contrails and contrail cirrus. Please correct the year.
b) The Chen and Gettelman estimate was revisited and corrected in the Lee et al 2020 paper  From Lee et al: ‘The estimate of Chen and Gettelman (2013) was corrected by redoing the CAM simulation using a lower ice crystal radius of 7 μm and a larger contrail cross-sectional area of 0.09 km2 for the initialization of contrails at an age of about 15–20 min, in agreement with observations (Schumann et al., 2017). The resulting change in cirrus cloudiness including the adjustment in cloudiness due to the presence of contrail cirrus leads to a radiative forcing of 57 mW m− 2.’ It would be good to note this in your table.
2. Line 65: When you talk about the factors that are important for estimating the increase in contrail cirrus radiative forcing in the future you omitted ‘climate change’ as a factor. Chen and Gettelman (2016) as well as Bock and Burkhardt (2019) discuss (amongst other factors) the impact of climate change on the contrail cirrus radiative forcing for future air traffic.
3. Line 67: The impact of a reduction in initial ice crystal numbers (as resulting from a use of biofuels) on contrail properties is analyzed in detail in Burkhardt et al. (2018). They show a shortening of contrail life times and a decrease in contrail optical depth.
4. Lee et al (2020) includes a long discussion of uncertainties connected with contrail cirrus radiative forcing (see their Appendix E) discussing uncertainties in the upper tropospheric water budget, contrail cloud overlap, contrail life times and other factors.
5. Line 173: ‘These approaches’…. is a bit unclear. I suggest ‘The approaches estimating the impact of cloud overlap on contrail radiative forcing’ …
6. Line 323: ‘In several previous radiative forcing calculations in literature, clouds and contrails have been assumed to maximally overlap,‘. You have deleted the entries in table 1 which specified the overlap schemes connected with the different models, but as far as I can see all entries would have been ‘maximum random overlap’ except for the Schumann and the Spangenberg estimate. Either you state that most models use maximum random overlap or you cite exactly which models use maximum overlap.
7. Line 326: According to your table 3, two models use random overlap while four models use maximum random overlap. Therefore, most climate models assume maximum random overlap. Please correct this.
8. Line 362: Please note that Bickel et al. (2020) estimate a much stronger reaction of natural clouds to the presence of contrail cirrus.
9. Line 739: It may be of interest to compare the contrail cloud overlap in this study with the results of Bock and Burkhardt (2016) who find a large variability in the fraction of contrail coverage that leads to an increase in overall cloud coverage. On average this fraction amounts to 43% while over the Northern Atlantic and Northern Pacific this fraction is about 20%.

Chen, C.-C. and Gettelman, A.: Simulated 2050 aviation radiative forcing from contrails and aerosols, Atmos. Chem. Phys., 16, 7317–7333, https://doi.org/10.5194/acp-16-7317-2016, 2016.
Bock, L. and Burkhardt, U.: Contrail cirrus radiative forcing for future air traffic. Atmos. Chem. Phys., 19, 8163–8174, https://doi.org/10.5194/ACP-19-8163-2019.
Burkhardt, U., Bock, L., Bier, A., 2018. Mitigating the contrail cirrus climate impact by reducing aircraft soot number emissions. npj Clim. Atmos. Sci. 1, 37. https://doi.org/10.1038/s41612-018-0046-4.
Bickel, M., Ponater, M., Bock, L., Burkhardt, U., Reineke, S., 2020. Estimating the effective radiative forcing of contrail cirrus. J. Clim. 33, 1991–2005. https://doi.org/10.1175/JCLI-D-19-0467.1.

Hide

ED: Publish subject to technical corrections (23 Dec 2020) by Michael Pitts

AR by Sebastian Eastham on behalf of the Authors (28 Dec 2020) Author's response Manuscript

Download

Article (6334 KB)
Full-text XML

Short summary

Contrails cause ~50 % of aviation climate impacts, but this is highly uncertain. This is partly due to the effect of overlap between contrails and other cloud layers. We developed a model to quantify this effect, finding that overlap with natural clouds increased contrails' radiative forcing in 2015. This suggests that cloud avoidance may help in reducing aviation's climate impacts. We also find that contrail–contrail overlap reduces impacts by ~3 %, increasing non-linearly with optical depth.