High-Resolution Air Temperature Forecasts in Urban Areas: A Meteorological Perspective on Their Added Value

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript evaluates the effectiveness of high-resolution air temperature forecasts in urban areas, focusing on the coupled AROME and SURFEX-SA modeling systems. The study addresses critical issues such as the urban heat island effect and assesses model accuracy against observational data from various urban environments in Austria. It emphasizes the advantages of fine-scale modeling and highlights the performance of SURFEX-SA under extreme thermal conditions, though some limitations persist compared to the coarser AROME system. The manuscript is well-structured and presents significant contributions to urban climate modeling; however, several areas need attention to enhance its clarity and scientific rigor. Below are detailed comments for improvement:

 

1. Verify and ensure the proper formatting of references (e.g., ref. 28 and 60).

 

2. Address missing axis labels and units across various figures (e.g., x and y axes in Figures 3, 4, and 5; units in Figures 6, 11; x-axis units in Figures 7, 8, 9, 10, 12, 14, 15, and 20; and labels in Figure 13).

 

3. Split the sets of figures in Figure 18 to represent results by location for better interpretability.

 

4. Provide detailed interpretations for complex figures such as Figures 18 and 20 to help readers grasp their significance.

 

5. Incorporate sensitivity analyses to quantify the dependence of SURFEX-SA results on AROME inputs. This will provide a clearer understanding of their interaction and limitations.

 

6. Clarify the preparation of boundary conditions and input data, such as land-use parameters and meteorological states, for both systems.

 

7. Highlight the problem statements and novelty in both the abstract and introduction to underline the unique contributions of the study.

 

8. Identify and condense sections with repetitive ideas or results, particularly in the results and discussion sections, to improve readability and focus.

 

9. Emphasize critical comparisons between AROME and SURFEX-SA by linking key findings to the underlying physical processes.

 

10. Explain the advantages or disadvantages of each system in the context of the study’s objectives.

 

11. Ensure precise language throughout the manuscript. Avoid ambiguities in describing methodologies and results.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

work prepared correctly. However, Fig. 5 should be improved, the description of the X axis is missing

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Authors,

In your study, you have developed and evaluated a high-resolution modeling system to predict the urban heat island effect and the resulting thermal stress in urban environments. By integrating AROME and SURFEX-SA models, you have examined the capability to predict air temperatures with resolutions ranging from 2.5 km to 100 m across four Austrian cities (Vienna, Linz, Klagenfurt, and Innsbruck). The use of locally enriched land-use maps has significantly strengthened the foundation of your work. Furthermore, analyzing model performance across various scenarios, such as seasonal extremes, rural/urban settings, and extreme thermal conditions, has allowed you to highlight the strengths and weaknesses of each system in detail. This comprehensive approach offers new perspectives in urban thermal stress prediction.

While your study is well-prepared overall, certain major and minor revisions are required for further improvement. Below, you will find the suggested revisions itemized:

Major Concerns

• Conclusion Section:
  Your manuscript lacks a Conclusion section. For a study involving such comprehensive analyses and original findings, it is essential to summarize the key results under a dedicated Conclusion section. Presenting these findings in bullet points would be more effective.
• Discussion Section:
  Although your analysis visualization and interpretation are well-executed, the Discussion section falls short in comparing your results with similar studies in the current literature. A more detailed comparison, highlighting similarities, differences, strengths, weaknesses, and novel aspects, is necessary. This section should include more references and avoid simply reiterating the results.
• Figures and Tables:
  Your manuscript includes a substantial number of visual elements (20 figures and 3 tables), some of which could be consolidated. Additionally, several figures lack essential details such as axis labels, which must be included. While captions provide explanations, basic information (e.g., axis names, units) should appear on the figures themselves. Maps must include a north arrow and scale bar. Units should also be added to numerical values where applicable.

Minor Concerns

• The abstract contains several unexplained abbreviations. Each abbreviation (e.g., AROME, SURFEX-SA, NETATMO) should be defined upon its first use in both the abstract and the introduction.
• What is the rationale behind specifically choosing the years 2019, 2023, and 2024? Please clarify.
• Materials and Methods:
• Figure 1: Why are the map dimensions inconsistent? While you mention that the stations are represented by green points, these points are not visible. Consider increasing their size. Latitude-longitude details, a north arrow, and a map scale bar must be included for each map.
• Table 1: What criteria were used to determine threshold values (e.g., Tmax > 298.2 K for summer days, 303.2 K for hot days)? Please specify.
• Why did you choose Heidke Skill Score, Brier Score, and Fraction Skill Score for your analysis? Could more fundamental metrics, such as the Critical Success Index (CSI), have been considered?
• Some Figures:
• Figure 3: What do the numerical values on the axes represent? Additionally, the map outlines below the grayscale plots should be more prominent for better interpretation. The same issue applies to Figure 4. It may be more suitable to combine Figures 3 and 4 into a single figure.
• Figure 5: What information is presented on the x-axis? This should be explicitly labeled. Similarly, in Figure 6, does the y-axis represent time in hours, days, or minutes? Please specify.
• Figure 7: Does "Lead Time 00" refer to local time or UTC? This needs to be clarified.
• Figures 8, 9, and 10: These figures could be consolidated into a single figure for better presentation.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you.