the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 May 2025
Modelling contrail cirrus using a double-moment cloud microphysics scheme in the UK Met Office Unified Model
Abstract. Contrail cirrus is the largest contributor to aviation effective radiative forcing (ERF), but remains highly uncertain (∼70 %). Recent research has highlighted the critical role of cloud microphysical schemes in contrail cirrus climate modelling. In this study, we implement a contrail parameterisation in the double-moment cloud microphysics scheme, Cloud AeroSol Interacting Microphysics (CASIM), within the regional configuration of the UK Met Office Unified Model (UM). We first investigate a contrail cluster model experiment, showing that the simulated contrails retain a high ice crystal number concentration for several hours before declining. Ice water content increases during the early stage of the lifecycle before gradually decreasing. In addition, as the contrail cluster gradually sediments below flight levels, there is an increase in both contrail ice number concentration and water content. We also perform regional simulations over a European domain, estimating a regional annual mean contrail cirrus ERF of 0.93 W m-2, within the range of previous climate modelling estimates. Using a range of initial contrail width, depth and ice crystal size based on contrail observations, we estimate an annual mean European regional contrail cirrus ERF range of 0.19 W m-2 to 2.80 W m-2. Our study highlights the critical need for double-moment cloud microphysics in global climate models to realistically simulate contrail impacts. Future work should extend the simulation globally and investigate how the use of alternative fuels affects contrail microphysical properties, contrail lifetime, and climate impact.
- Preprint
(1649 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2025-2045', Anonymous Referee #1, 25 Jun 2025
This manuscript presents an implementation and evaluation of a contrail parameterization within the double-moment microphysics scheme (CASIM) of the UK Met Office Unified Model (UM), focusing on regional simulations over Europe. The study addresses an important gap in contrail cirrus climate impact modeling by leveraging more advanced microphysics, and provides new regional estimates of contrail cirrus effective radiative forcing (ERF).
The paper is well-organized, clearly written, and provides a thorough overview of the current state of contrail cirrus modeling. The methodology is sound, and the results are relevant for both the modeling and aviation climate impact communities.
Suggestions for Improvement
While the manuscript mentions comparison with observations and other models, more quantitative evaluation of the model’s performance (e.g., ice water content, number concentration, cloud fraction) against available satellite or in-situ observations would strengthen the study.
If possible, include statistical metrics (e.g., bias) for key variables.
The manuscript discusses uncertainties in contrail ERF, but does not provide a detailed sensitivity analysis of the model’s key parameters (e.g., initial ice crystal size, number concentration, ambient humidity).
Consider adding a section or at least a discussion on how sensitive your results are to these parameters.
Please clarify the rationale for selecting 70 vertical levels and the vertical resolution profile, especially in the context of representing contrail processes in the UTLS.
Indicate how the chosen vertical and horizontal resolutions impact the simulation of contrail lifecycles and radiative effects.
The discussion could be expanded to address the limitations of regional modeling (e.g., boundary effects, lack of global feedbacks) and how these might affect the generalizability of the results. Consider elaborating on the implications for global-scale modeling and policy.
Ensure that all figures are clear, with appropriate legends and axis labels.
Provide time series or spatial maps of key variables (e.g., contrail coverage, ERF) to illustrate model behavior.
Minor comments
Some references to previous studies could be updated or expanded, particularly regarding recent advances in contrail observation and modeling.
Double-check for typographical errors and ensure consistency in units and notation throughout the manuscript.
For Figure 2, I recommend providing the linear regression equation, including both the intercept and slope, either in the figure panel or the caption. Including this information would enhance the quantitative interpretation of the relationship shown, and allow readers to compare your results with those from other studies more easily. This is a common practice in the field and would further strengthen the clarity and reproducibility of your analysis.
While the introduction provides a solid overview of the current state of contrail cirrus research and cites several recent studies, I recommend including a reference to the recent review by Singh et al. (2024). This comprehensive review synthesizes the latest developments and ongoing challenges in contrail modeling and climate impacts. It would further strengthen the background section by providing readers with a broader context and up-to-date summary of the field.
This manuscript presents a valuable contribution to the field of contrail cirrus modeling and is suitable for publication after minor to moderate revisions. Addressing the points above, particularly regarding model evaluation and uncertainty analysis, will further strengthen the paper.
Citation: https://doi.org/10.5194/egusphere-2025-2045-RC1 -
AC1: 'Reply on RC1', Weiyu Zhang, 09 Sep 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2045/egusphere-2025-2045-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Weiyu Zhang, 09 Sep 2025
-
RC2: 'Comment on egusphere-2025-2045', Anonymous Referee #2, 26 Jun 2025
Review of "Modelling contrail cirrus using a double-moment cloud microphysics scheme in the UK Met Office Unified Model" by Weiyu Zhang et al.
This manuscript describes the implementation of a contrail parameterization in a regional version of the UK Met Office Unified Model (UM). It describes the implementation and integration with the cloud physics, and then assesses regional simulations over Europe to estimate contrail radiative effects. The manuscript is well written and generally a good description of the work. The work is appropriate for ACP. The manuscript should be publishable with minor revisions as noted below and clarification of a few points.
As a general comment, it would be good if the manuscript could present some temporal evolution and variation of the contrail radiative forcing. You have fine scale temporal detail, and you show the evaluation of the 'idealized' case, but I would like to see some use of temporal variation of the longer runs: a diurnal cycle if possible but at least an annual cycle of contrail properties and radiative forcing.
Specific Comments:
Page 3, L69: might need to write out the model acronyms (at least for CAM).
Page 4, L118: what is the depositional water in the volume? Everything above supersaturation? I guess that’s what in equation 4?
Page 6, L174: I think it should be “young contrail properties…”
Page 8, L204: “as contrail ice crystals sediment into these drier layers…”
Page 8, L213: does that mean the area is too large?
Page 8, L216: is the cloud fraction magnitude expected just the contrail width? At 200m in a 4km grid box it;s 0.05 right?
Page 9, L220: What if you just assigned the increase in cloud fraction when the contrail is initialized based on the initial width?
Page 10, L244: does this imply the density of small ice in CASIM is too low? 200 kg m-3 seems very small for small ice crystals….
Page 10, L264: define QCF in figure 5b title. Is that the model variable for ice water content?
Page 10, L270: is figure 5e just change in water vapor? Or is it change in mass above supersaturation? The latter is a function of temperature change as well, so not as clear. Suggest better to show just r water vapor change.
Page 12, L290: is figure 6 all 12 x 10-day periods averaged? Please state what time range is being shown.
Page 12, L304: This seems high given that it is near the peak of the contrail # concentration in figure 5a after 30 min.
Page 14, L340: Figure 8. It would be useful to note what time period this represents. An annual average? What does the annual cycle look like?
Page 15, L379: what about the annual or diurnal cycle of contrail forcing? What frequency of AEDT inventory did you use (e.g. you can get it hourly). I assume at least monthly variation to do an annual cycle.
Citation: https://doi.org/10.5194/egusphere-2025-2045-RC2 -
AC2: 'Reply on RC2', Weiyu Zhang, 09 Sep 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2045/egusphere-2025-2045-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Weiyu Zhang, 09 Sep 2025
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 373 | 64 | 13 | 450 | 9 | 20 |
- HTML: 373
- PDF: 64
- XML: 13
- Total: 450
- BibTeX: 9
- EndNote: 20
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1