We are grateful to referee #1 for the constructive and encouraging comments on the original version of our manuscript. We took all comments into account and revised the manuscript accordingly. Here are our replies:

• Comment: This study presents the ACCF 1.0 to describe the climate impact of aviation emissions. ACCF 1.0 takes the atmospheric conditions as input to calculate the climate impact, mainly through the average temperature response over 20 years (ATR20). The emissions include, (via and), vapour, and contrail-cirrus. The study is valuable as it provides an integrated model to assess the environmental impact of non-CO₂ I have a few comments below:

            Reply: We thank referee #1 for these positive comments. We have addressed all the comments as follows.

• Comment: The ACCF 1.0 model is based on the aCCF, which was proposed by the earlier project REACT4C2 for researching the climate change caused by emissions. ACCF works as a submodel of the global atmospheric-chemistry model EMAC. What new features/functions are developed should be discussed.

            Reply: As the reviewer might have noticed in Figure 1 of this manuscript, there are three stages of work leading to the current version of algorithmic climate change functions (aCCFs by short), which is the core of the ACCF submodel presented in this manuscript.

           Stage one: In REACT4C, the original Climate Change Functions (CCFs by short) were developed and implemented for climate optimized flight trajectories, including the effects from CO₂, NO_x, H₂O, and contrail cirrus (Grewe et al., 2014a). The various case studies showed the effectiveness of using CCFs to achieve flight routings with minimum climate impact (Grewe et al. 2014b; Grewe et al. 2017b). The main challenge is that CCFs cannot be directly implemented in trajectory planning tools since generating CCFs requires a heavy computational load.

           This brought the work to the second stage to develop algorithmic CCFs in a previous EU project ATM4E (van Manen and Grewe, 2019; Matthes et al., 2017). aCCFs are simplified response models for estimating the climate impact of various aviation emissions (e.g., CO₂, H₂O and NO_x)/effect (day/night contrails). Though the inputs to aCCFs are the original CCFs, the step from CCFs to aCCFs is innovative and essential, as unlike CCFs, aCCFs can be directly implemented in flight planning tools to obtain climate optimized flight trajectories quickly. The aCCFs for NO_x and H₂O estimating has been well documented by van Manen and Grewe (2019). The approach of developing contrails aCCFs is only made available in the current ACCF v1.0 manuscript as a supplement.

           While continuing to the third stage of implementing the aCCFs in the current ACCF V1.0 (FlyATM4E scope), we noticed inconsistencies between the NO_x/H₂O aCCFs and contrails aCCFs due to different approaches in calculating radiative forcing and the emission scenarios concerned to develop the response models (Pulse vs. future increasing emissions). For details, please see the discussion in section 2 of this manuscript. Therefore, one significant effort in the current manuscript is to diagnose and correct the previous aCCFs models to be consistent.

           Long story short, the novelty of the current paper is that we, for the first time, publish: 1) the contrail aCCFs development; 2) a consistent set of aCCFs models in terms of fuel scenario, metric, and efficacy for all species.

• Comment: The application simulation of existing trajectory is conducted to show the climatology impact. They also used the calculation model to optimize the trajectory, from which they draw the conclusion that climate-optimized trajectories considering non-CO₂ effects fly lower altitudes to reduce the impact of the total NO_x, H₂O, and contrails. The scalability of the tool for large-scale problems should be discussed.

            Reply: The application study in section 5 is based on a daily simulation. Accordingly, climate-optimized flights tend to reduce their flight altitudes driven by NO_x and contrail effects. Regarding the tool's scalability, the quality check in section 4 can be seen as a scalability check of aCCFs models themselves. For instance, in section 4.1, we compared the climatological aCCFs with the literature to confirm that the pattern of aCCFs matches the previous studies. Furthermore, in general, NO_x’s climate impact decreases at low altitudes and high latitudes due to shorter residence time or inactive atmospheric chemistry process of NO_x. The climate impact of H₂O reduces with altitude as well. The effect of contrails is vital in a narrow altitude band following the tropopause height. Following such behavior, we expect the flights with lower climate impact will favor a lower flight altitude than cost-optimal flights. We are performing work based on a year simulation to quantify the mitigation gains regarding climate impact.

• Comment: However, in their scenarios, the CO₂-related environmental impact is considered to be lower than the non-CO₂ impact, which may limit the possible subsequent applications of the ACCF. Maybe discuss futural models, which can provide a comprehensive assessment of climate impact caused by aviation emissions.

            Reply: We agree that the lower CO₂ impact estimated from the aCCFs model requires further diagnosis and new developments if required. During our current work, we performed intensive studies to understand the mechanism, and we suspect the reasons could be in the following aspects:

            1) Metrics: when we convert the metrics to 100 years’ time horizon instead of 20 years in this paper, we observed an increase in  CO₂ contribution for the same set of flights.

            2) Radiation scheme for developing the original CCFs.

            3) Geographical representative: the current research is mainly on European regions. Ongoing research is investigating whether  CO₂ and non-CO₂ relative importance are globally consistent, and this will help us understand better the local representation of  aCCFs as well.

             We have added one paragraph on page 24 Line 505-508, for this discussion. Please see the track change in the resubmission.

Reference

• Grewe, V., Frömming, C., Matthes, S., Brinkop, S., Ponater, M., Dietmüller, S., Jöckel, P., Garny, H., Tsati, E. and Dahlmann, K. (2014a). "Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1. 0)." Geoscientific Model Development, 7(1): 175-201. DOI: https://doi.org/10.5194/gmd-7-175-2014.
• Grewe, V., Champougny, T., Matthes, S., Frömming, C., Brinkop, S., Søvde, O. A., Irvine, E. A. and Halscheidt, L. (2014b). "Reduction of the air traffic's contribution to climate change: A REACT4C case study." Atmospheric Environment, 94: 616-625. DOI: https://doi.org/10.1016/j.atmosenv.2014.05.059.
• Grewe, V., Matthes, S., Frömming, C., Brinkop, S., Jöckel, P., Gierens, K., Champougny, T., Fuglestvedt, J., Haslerud, A., Irvine, E. and Shine, K. (2017b). "Feasibility of climate-optimized air traffic routing for trans-Atlantic flights." Environmental Research Letters, 12(3): 034003. DOI: 10.1088/1748-9326/aa5ba0.
• van Manen, J. and Grewe, V. (2019). "Algorithmic climate change functions for the use in eco-efficient flight planning." Transportation Research Part D: Transport and Environment, 67: 388-405. DOI: https://doi.org/10.1016/j.trd.2018.12.016.
• Matthes, S., Grewe, V., Dahlmann, K., Frömming, C., Irvine, E., Lim, L., Linke, F., Lührs, B., Owen, B., Shine, K., Stromatas, S., Yamashita, H. and Yin, F. (2017). "A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories." Aerospace, 4(3): 42.

Thank you for the efforts in reviewing our paper. We addressed all the comments in the paper revision! Please also find the point-to-point reply in the supplement.