Dear Anonymous Referees #1 and #2,

Thank you for taking the time to review our manuscript and to provide us with constructive comments.

In the following, quotes by Anonymous Referee # (RC1) and #2 (RC2) will be shown in italic followed by our replies.

RC1: 1. Plausibility validation and limitations:

While the paper states that direct comparisons to in-situ data are not feasible due to scale and data availability, it would be good to supplement the plausibility tests with some quantitative reasoning or reference to typical values, if possible.

Providing some context to the plausibility tests would indeed improve the manuscript. We enhanced section 6.4.4. with a few sentences on the heavy precipitation amount.

RC1: Also, it would be helpful to have a discussion of the limitations and assumptions of the hit rate-based method.

To improve the discussion of the limitations of the method, we revised the respective paragraph in section 6.3.

RC1: 2. Hit rate method:

•    The 95% threshold is adopted from VDI (2017) and WMO. While this reference is appropriate, it would be good to more explicitly explain why this threshold is suitable in the context of this study, particularly for variables related to precipitation.

Commonly used confidence levels are 99 %, 95 % and 66 %. A confidence level of 99% is a very strict threshold suitable for very controlled experiments. The confidence level of 66 % would allow for quite a lot of uncertainties when comparing different types of data like for example simulation results with measurement data. For our study, this confidence level would not be strict enough. 95 %, as suggested by VDI, is quite strict while allowing for some uncertainties. For increasing the strictness, we chose smaller threshold values instead of a higher confidence level. Therefore, using 95% fits our purposes well.

RC1:

•    In cases where hit rates are expected to be low, e.g., some cases are lower than 40%, the paper should provide more context. For example, what constitutes an acceptable range for deviations due to added processes? Any sensitivity analysis or benchmark expectations could clarify whether such a result indicates model improvement or other reasons.

In this paper we performed plausibility tests and no sensitivity analyses. Sensitivity studies can be found in a previous study (Ferner et al. 2023).

RC1: 3. Model generalization.

The model domain and test building represent a highly simplified urban environment. A general discussion of how the model might perform in larger, denser, or more heterogeneous urban areas would be useful for understanding the broader applicability of these extensions. E.g., would the added processes scale well to city domains, or would numerical stability or computational cost become limiting factors?

For model development and testing a simplified domain was chosen, where features of a more realistic urban setting like stretched grids, obstacle corners and terrain slopes are still included. Sensitivity studies for a more heterogeneous and realistic urban neighbourhood were carried out in the already mentioned previous study (Ferner et al. 2023). There, the grid was designed following the recommendations of the VDI.

However, when applying the extended model to larger domains, computational cost indeed becomes an issue. To reduce the number of grid cells, an irregular grid was used.

Numerical stability is not an issue.

RC2: But the numerous equations are not easy to follow, requiring the readers to read earlier reference papers. Some papers are very old and might not be easy to find. I would suggest improving the equations, such as explaining all symbols used in the equations. In the appendix (List of symbols), please give units for dimensional variables. Some equations might be excluded in the MS.

As you have already pointed out, the equations are taken from earlier publications. Some of them are old and/or in German. We wanted to have all equations relevant for the model extension of MITRAS to be found in the same publication.

We added units to the list of symbols.

RC2: 

1.    5, 8, 12, 13. Please double-check these equations (after they have been recalculated to SI units). I did check Eq. 5, and found the dimensions are consistent. I would suggest that the units in the equations should be removed.

Units in cloud microphysical equations have historically been quite peculiar as they are derived from empirical data. We improved the readability of the equations by using another notation, which reduces the occurrence of peculiar exponents. For example, Eq. 5 (terminal velocity of rain) is changed to v_TR=68.81 (10^-3 rho0/kgm^-3 q_1^2r/kgkg^-1)^0.1905. Removing the units altogether was not an option for us, as our editor asked us to include units. Unfortunately, we could not avoid, that the ventilation factor (Eq. 12) still includes units with an exponent. For depositional growth and melting and freezing we still reference Doms et al. 2011.

RC2:

2.    Section 6.2. Please give the boundary conditions for the domain boundaries.

We updated section 6.1 (model set-up) with the boundary conditions.

RC2:

3.    Section 6.1. It would be good to check mesh sensitivity or give comments to justify.

Mesh sensitivity is not the focus of the current paper. Here, we checked the reliability of the added processes by plausibility (see also our response to RC1’s comment on model generalization).

RC2:

4.    Table 3 and Fig. 11. The difference in v-wind component {\Delta v} near the ground is very large. Why don’t you set up a case with a flat ground surface?

A case without consideration of orography is included in Ferner et al. 2023.

References:

Ferner, K. S., Boettcher, M., and Schlünzen, K. H.: Modelling the heterogeneity of rain in an urban neighbourhood with an obstacle-resolving model, Meteorologische Zeitschrift, https://doi.org/10.1127/metz/2022/1149, 2023

Doms, G., Förstner, J., Heise, E., Herzog, H.-J., Mironov, D., Raschendorfer, M., Reinhardt, T., Ritter, B., Schrodin, R., Schulz, J.-P., and Vogel, G.: A Description of the Nonhydrostatic Regional COSMO Model Part II : Physical Parameterizations, Deutscher Wetterdienst, Offenbach, Germany, 2011