the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Jul 2025
Improving Forecasts of Persistent Contrails through Ice Deposition Adjustments
Abstract. Aviation-induced clouds, especially persistent contrails, contribute significantly to anthropogenic climate forcing, often surpassing the short-term impact of aviation CO2 emissions. These clouds form in ice-supersaturated regions, where they trap longwave radiation and warm the climate. On 25 November 2023, widespread ice-supersaturated layers over eastern Canada and the USA led to extensive contrail formation, confirmed by GOES-16 satellite imagery and ground-based photography. Atmospheric conditions were characterized using ceilometer data from Toronto Pearson Airport and radiosonde soundings.
High-resolution simulations were conducted using the Global Environmental Multiscale (GEM) model with the Predicted Particle Properties (P3) microphysics scheme. The Contrail Avoidance Tool (CoAT), incorporating Schmidt-Appleman Criteria and a wake vortex model, simulated persistent contrail formation and properties. Sensitivity tests adjusting ice depositional growth rates evaluated their impact on ice supersaturation. Results indicate that the control (CNTL) simulation underestimated relative humidity over ice (RHi), a common limitation where moisture is depleted too rapidly. Reduced depositional growth rates improved RHi forecasts and contrail-forming regions. However, GEM-CoAT underestimated contrail depth and ice number concentration in very shallow high-RHi layers. CoAT simulations also revealed that SAC alone is insufficient, as wake vortex dynamics can induce adiabatic warming, leading to ice particle sublimation.
Further analysis examined contrail formation for two aircraft types (A321 and B747). The B747 generated deeper wake vortices, enhancing adiabatic heating and reducing contrail ice number concentrations by 27 % in sensitivity simulations and 78 % in the CNTL simulations. Adjusting depositional growth rates allowed GEM-CoAT to accurately simulate contrail formation and persistence.
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RC1: 'Comment on egusphere-2025-3007', Anonymous Referee #1, 31 Jul 2025
Review of "Improving Forecasts of Persistent Contrails through Ice Deposition Adjustments" by Zane Dedekind et al..
The formation of persistent contrails in ice-supersaturated regions impacts the radiation budget of the Earth and may cause possibly a faster and stronger climate warming of the troposphere than the co-emitted CO2. The processes involved are complex and not fully understood, so worth of further investigation.
The authors study contrail formation using a high-resolution simulation version of a global (? see question below?) atmospheric model (GEM) and discuss its ice microphysics scheme. Contrails are simulated in this model using a special contrail model (CoAT), incorporating the thermodynamic Schmidt-Appleman Criterium and an existing wake vortex model. Sensitivity tests are performed to investigate the impact of ice deposition for a domain over the Great Lakes region near the US-Canada border, where they have satellite observations of cirrus cloudiness (including contrails) and humidity. Basically, this is an interesting study. However, the paper is hard to read.
The topic of the deposition or accommodation coefficient has been discussed often in the literature. The accommodation factor is certainly a relevant parameter. However, there are also other effects which could be important: This includes, e.g., the number of ice particles (ice nucleation) and assumptions on sub-grid scale variability.
In respect to the SAC criterium I have a specific remark: The paper concludes among others that the “CoAT simulations revealed that SAC alone is insufficient”. It is not clear for what part of the SAC criterium this applies. Please note: It is well known that the SAC criterium does not guarantee the persistence of the contrail. It only decides on contrail formation. So, any warming of the ambient air, e.g. by sinking in the wake vortex, affects the survival of the contrail. This is not an issue of the SAC criterium. This part needs to reformulated.
Otherwise, I had huge difficulties to understand this paper.
Is the GEM (as the name suggests) a global model? Or is it a limited area model (as indicated by the information on page 7, lines 148 ff)?
The description of P3 uses the term “property-based approach” (line 157). I do not know what an property based approach is. So, it seems, I have to read all the references given?
Line 164 says “with prognostic liquid fraction off” – does this mean the model works without treating liquid water? Why is this a critical assumption for this application and why did you need to menton it?
The P3 model within GEM is applied using 3 ice categories (line 164). Which are these categories?
How are the outputs of CoAT (lines 218/219) related to these ice categories?
Why is figure B1 in an appendix, which contains nothing else than just this figure? In this figure, the various radiosonde contributions are hard to distinguish. I see red and blue colors but the rest is just in a color mix which I cannot discriminate.
Moreover, the figure is hard to read because I am unfamiliar with the various Radiosonde names and their positions (GRB etc.). Which radiosonde shows the results for the airport of Toronto? Where in your map (Fig 1 a) is Toronto?
By the way, Fig 1a is not referenced in the text.
Line 253 says the “largest contribution to the underestimation is GEM’s is its inability to capture the DTC sounding (Fig- B1)”. I cannot understand this by only looking to the figure B1. Please provide further explanations (without abbreviations).
Why do you need to average over a 5 km x 5 km domain around the soundings. I thought the sounding positions are recorded (by GPS) during the radiosonde measurements versus time and, hence, known?
A caption like “3.1.2 The outlier: DTX sounding” implies that the reader already knows what a DTX sounding is. Where can I see the DTX sounding position?
Line 280:do you mean Fig 4? Line 283: do you mean Fig 5?
Fig 5 is insufficiently explained. There are 8 panels which are grouped into 4 subpanels. The various panels are not explained. What do they show? The upper parts of these panels show color pots. What do the colors mean?
Fig 6 is also hard to digest. The axes are not explained. What is CINC (cm-3)? How can a reader digest headings like ”Soundings for APX A321 aircraft”?
I simply do not understand what you want to show.
Fig 7: What is ice particle survival (in percent)? How is it computed, and why is it important?
I stop review here, because the paper needs to be brought into a reviewable shape first.
I am ready to look at it again after major revision.
Citation: https://doi.org/10.5194/egusphere-2025-3007-RC1 - RC2: 'Comment on egusphere-2025-3007', Anonymous Referee #2, 26 Aug 2025
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