A method for assessing model extensions: Application to modelling winter precipitation with a microscale obstacle-resolving meteorological model (MITRAS v4.0)

Samsel, Karolin Sarah; Boettcher, Marita; Grawe, David; Schlünzen, K. Heinke; Sieck, Kevin

doi:10.5194/egusphere-2024-2464

Preprints

https://doi.org/10.5194/egusphere-2024-2464

Preprints

25 Apr 2025

| 25 Apr 2025

A method for assessing model extensions: Application to modelling winter precipitation with a microscale obstacle-resolving meteorological model (MITRAS v4.0)

Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

Abstract. The microscale, obstacle-resolving meteorological transport and stream model MITRAS has been extended with a snow cover and precipitation scheme. The performance of the model extension is assessed by comparing the results of different model versions using a method based on hit rates originally developed for assessing wind performance. For temperature, radiation and precipitation, estimates for the threshold values were derived based on computational accuracy; these are used in the hit rate calculation for these variables. The threshold values for the deviations are 0.02 ms⁻¹ (5 %) for the wind components, 0.05 K (0.02 %) for temperature, 0.5 Wm⁻² (0.5 %) and 0.5 Wm⁻² (0.2 %) for the net long and short wave radiation, and 0.001 mm (1 %) for precipitation on ground. The model extensions produce plausible results and better represent winter precipitation. This opens the opportunity to study with higher accuracy the influence of obstacles on precipitation heterogeneities.

Received: 06 Aug 2024 – Discussion started: 25 Apr 2025

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Journal article(s) based on this preprint

11 Jun 2026

A method for assessing model extensions: application to modelling winter precipitation with a microscale obstacle-resolving meteorological model (MITRAS v3.3)

Karolin S. Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

Geosci. Model Dev., 19, 4885–4906, https://doi.org/10.5194/gmd-19-4885-2026,https://doi.org/10.5194/gmd-19-4885-2026, 2026

Short summary

Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-2464', Anonymous Referee #1, 11 Jun 2025
This manuscript presents the extension of the microscale, obstacle-resolving model MITRAS to simulate winter precipitation, incorporating both rain and snow cover schemes in urban environments. This is a valuable contribution to the fields of urban meteorology and microscale modeling, particularly given the lack of obstacle-resolving models that handle precipitation processes. The model extensions are implemented incrementally and are evaluated using a plausibility-based framework, the hit rate metric, which involves comparing model outputs across different versions.

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

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.

3. Model generalization.
The 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?
Citation: https://doi.org/10.5194/egusphere-2024-2464-RC1
RC2:
'Comment on egusphere-2024-2464', Anonymous Referee #2, 13 Jun 2025
This paper summarizes an extension of the obstacle-resolved model MITRAS with a snow cover and precipitation scheme. This is of interest and can be of great potential. Overall, the MS is well written. 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.
Some specific comments.
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.

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

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

Table 3 and Fig. 11. The difference in v-wind component {\Delt v} near the ground is very large. Why don’t you set up a case witha flat ground surface?
Citation: https://doi.org/10.5194/egusphere-2024-2464-RC2
CEC1:
'Comment on egusphere-2024-2464 - No compliance with the policy of the journal', Juan Antonio Añel, 14 Jun 2025

Dear authors,

Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".

https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
in your "Code and Data Availability" statement you say that the MITRAS code that you use for your work is available upon request. We can not accept this. This is clearly forbidden by our policy, and your manuscript should have not been accepted for Discussions because of it. All the code and data used to produce a manuscript must be published openly and freely to anyone before submission to our journal.
Therefore, we are granting you a short time to solve this situation. You have to reply to this comment in a prompt manner with the information for a repository containing the MITRAS model, the version that you have used for your manuscript. The reply must include the link and permanent identifier (e.g. DOI). Also, any future version of your manuscript must include the modified section with this new information.
Please, note that if you do not fix this issue as requested, we will have to reject your manuscript for publication in our journal.
Juan A. Añel
Geosci. Model Dev. Executive Editor

Citation: https://doi.org/10.5194/egusphere-2024-2464-CEC1
- CC1:
  'Reply on CEC1', David Grawe, 20 Jun 2025
  
  Dear Executive Editor,
  
  We are keen to follow the policy of the journal and have discussed the issue prior to the open discussion phase. For reasons beyond our control and outlined in detail to the editorial team, we are unable to make the model code publicly available.
  
  However, following case two of the "Code and Data Policy", we have archived the code in restricted repositories for the editor and reviewers:
  
  MITRAS version 3.0:
  
  DOI:10.5281/zenodo.15705546
  
  https://doi.org/10.5281/zenodo.15705546
  
  MITRAS version 3.1:
  
  DOI: 10.5281/zenodo.15705664
  
  https://doi.org/10.5281/zenodo.15705664
  
  MITRAS version 3.3:
  
  DOI: 10.5281/zenodo.15705608
  
  https://doi.org/10.5281/zenodo.15705608
  
  We will be happy to include these persistent references in an updated version of the manuscript.
  
  David Grawe
  
  Citation: https://doi.org/10.5194/egusphere-2024-2464-CC1
  - CEC2: 'Reply on CC1', Juan Antonio Añel, 20 Jun 2025
    
    Dear authors,
    Many thanks for your reply. I have requested access to the repositories that you have mentioned to check the storage of the MITRAS code. Also, I have seen that in your comments to the Topical Editor you have stated that the University of Hamburg has not been able of getting the copyright from previous authors of parts of the MITRAS code. Regarding this, please, could you clarify how it is possible that if the university does not have the rights on the code, it is possible that you are using it? The situation regarding the copyright, license and distribution of MITRAS does not seem clear from the information that you have provided. Thanks.
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2024-2464-CEC2
    
    AC2: 'Reply on CEC2', Karolin Samsel, 18 Aug 2025
    
    Dear Executive Editor,
    the university has the right to use the model, but not to publish the code.
    Karolin Samsel
    
    Citation: https://doi.org/10.5194/egusphere-2024-2464-AC2
AC1: 'Reply on RC1 and RC2', Karolin Samsel, 18 Aug 2025

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

Citation: https://doi.org/10.5194/egusphere-2024-2464-AC1

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-2464', Anonymous Referee #1, 11 Jun 2025
This manuscript presents the extension of the microscale, obstacle-resolving model MITRAS to simulate winter precipitation, incorporating both rain and snow cover schemes in urban environments. This is a valuable contribution to the fields of urban meteorology and microscale modeling, particularly given the lack of obstacle-resolving models that handle precipitation processes. The model extensions are implemented incrementally and are evaluated using a plausibility-based framework, the hit rate metric, which involves comparing model outputs across different versions.

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

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.

3. Model generalization.
The 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?
Citation: https://doi.org/10.5194/egusphere-2024-2464-RC1
RC2:
'Comment on egusphere-2024-2464', Anonymous Referee #2, 13 Jun 2025
This paper summarizes an extension of the obstacle-resolved model MITRAS with a snow cover and precipitation scheme. This is of interest and can be of great potential. Overall, the MS is well written. 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.
Some specific comments.
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.

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

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

Table 3 and Fig. 11. The difference in v-wind component {\Delt v} near the ground is very large. Why don’t you set up a case witha flat ground surface?
Citation: https://doi.org/10.5194/egusphere-2024-2464-RC2
CEC1:
'Comment on egusphere-2024-2464 - No compliance with the policy of the journal', Juan Antonio Añel, 14 Jun 2025

Dear authors,

Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".

https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
in your "Code and Data Availability" statement you say that the MITRAS code that you use for your work is available upon request. We can not accept this. This is clearly forbidden by our policy, and your manuscript should have not been accepted for Discussions because of it. All the code and data used to produce a manuscript must be published openly and freely to anyone before submission to our journal.
Therefore, we are granting you a short time to solve this situation. You have to reply to this comment in a prompt manner with the information for a repository containing the MITRAS model, the version that you have used for your manuscript. The reply must include the link and permanent identifier (e.g. DOI). Also, any future version of your manuscript must include the modified section with this new information.
Please, note that if you do not fix this issue as requested, we will have to reject your manuscript for publication in our journal.
Juan A. Añel
Geosci. Model Dev. Executive Editor

Citation: https://doi.org/10.5194/egusphere-2024-2464-CEC1
- CC1:
  'Reply on CEC1', David Grawe, 20 Jun 2025
  
  Dear Executive Editor,
  
  We are keen to follow the policy of the journal and have discussed the issue prior to the open discussion phase. For reasons beyond our control and outlined in detail to the editorial team, we are unable to make the model code publicly available.
  
  However, following case two of the "Code and Data Policy", we have archived the code in restricted repositories for the editor and reviewers:
  
  MITRAS version 3.0:
  
  DOI:10.5281/zenodo.15705546
  
  https://doi.org/10.5281/zenodo.15705546
  
  MITRAS version 3.1:
  
  DOI: 10.5281/zenodo.15705664
  
  https://doi.org/10.5281/zenodo.15705664
  
  MITRAS version 3.3:
  
  DOI: 10.5281/zenodo.15705608
  
  https://doi.org/10.5281/zenodo.15705608
  
  We will be happy to include these persistent references in an updated version of the manuscript.
  
  David Grawe
  
  Citation: https://doi.org/10.5194/egusphere-2024-2464-CC1
  - CEC2: 'Reply on CC1', Juan Antonio Añel, 20 Jun 2025
    
    Dear authors,
    Many thanks for your reply. I have requested access to the repositories that you have mentioned to check the storage of the MITRAS code. Also, I have seen that in your comments to the Topical Editor you have stated that the University of Hamburg has not been able of getting the copyright from previous authors of parts of the MITRAS code. Regarding this, please, could you clarify how it is possible that if the university does not have the rights on the code, it is possible that you are using it? The situation regarding the copyright, license and distribution of MITRAS does not seem clear from the information that you have provided. Thanks.
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2024-2464-CEC2
    
    AC2: 'Reply on CEC2', Karolin Samsel, 18 Aug 2025
    
    Dear Executive Editor,
    the university has the right to use the model, but not to publish the code.
    Karolin Samsel
    
    Citation: https://doi.org/10.5194/egusphere-2024-2464-AC2
AC1: 'Reply on RC1 and RC2', Karolin Samsel, 18 Aug 2025

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

Citation: https://doi.org/10.5194/egusphere-2024-2464-AC1

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

AR by Karolin Samsel on behalf of the Authors (19 Sep 2025) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (10 Feb 2026) by Simon Unterstrasser

AR by Karolin Samsel on behalf of the Authors (01 Mar 2026) Author's response Manuscript

Journal article(s) based on this preprint

11 Jun 2026

A method for assessing model extensions: application to modelling winter precipitation with a microscale obstacle-resolving meteorological model (MITRAS v3.3)

Karolin S. Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

Geosci. Model Dev., 19, 4885–4906, https://doi.org/10.5194/gmd-19-4885-2026,https://doi.org/10.5194/gmd-19-4885-2026, 2026

Short summary

Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

Supplement

https://doi.org/10.5194/egusphere-2024-2464-supplement

Karolin Sarah Samsel, Marita Boettcher, David Grawe, K. Heinke Schlünzen, and Kevin Sieck

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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A microscale, obstacle-resolving meteorological model has been extended with a snow cover and precipitation scheme making it the first model of its kind that includes rain and snow. The model allows first estimates on the influence of different city characteristics on precipitation heterogeneities. The performance of the model extension is assessed by comparing the results of different model versions. For the comparisons, threshold values were derived based on computational accuracy.


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