Bioclimatic Condition Variability in the Central Region of Poland in the Period 2001–2024
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsPlease see the attachment.
Comments for author File: 
Comments.pdf
Author Response
RESPONSES TO THE REVIEWER 1
The authors would like to thank the Reviewer for all comments and suggestions that improve the quality of the manuscript.
Comments 1. Title: The study period is 2001-2024, which represents only the early part of the
21-st century. It is therefore inaccurate to use “twenty-first century” in the title. The authors
should state the study period directly in the title. The same issue occurs at L394.
Response 1: We agree with period of this study 2001-2024 represents only early part of the 21-st century so according reviewer’s suggestion the authors have changed the title on “2001-2024”. Proposal the new title is "Bioclimatic Conditions Variability in the Central Region of Poland in the period 2001-2024”
Comments 2. L13: The regional difference in average UTCI does not seem to be significant, as
seen from Fig. 2. Whether the difference is significant or not is also not being tested statistically. The authors should present information more accurately.
Response 2: The source data - daily values od UTCI has been tested by the use of Statistica software. Shapiro-Wilk test was used and the differences are statistically significant at the level of p < 0.01.
Comments 3. L27-30: The author should use the most recent (the 6-th) IPCC report and
update the values in the first sentence accordingly. Please also spell out the full name of IPCC at first mention.
Response 3: It has been corrected and updated. The citation has been replaced on:
IPCC, 2023: Sections. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 35-115, doi: 10.59327/IPCC/AR6-9789291691647
The cited text is in original report: Global surface temperature was around 1.1°C above 1850–1900 in 2011–2020 (1.09 [0.95 to 1.20]°C), with larger increases over land (1.59 [1.34 to 1.83]°C) than over the ocean (0.88 [0.68 to 1.01]°C).
Comments 4. L40: Please spell out the full name of UTCI at first mention.
Response 4: Full name of Universal Thermal Climate Index has been supplemented.
Comments 5. L40-41: Please provide a citation to support the claim that 60% of the paper outputs are concentrated on the first two topics.
Response 5: In the first part of the sentence, a citation is given that the classification of biometeorological research and that 60% of the works concern the first two issues comes from Kruger's work (2021). For clarity, a citation of this work has been repeated at the end of the paragraph again [4].
Comments 6. L68: Quatar should be spelled as Qatar.
Response 6: It has been revised.
Comments 7. L75: “Entire multi-year” is redundant and can be removed.
Response 7: It has been deleted.
Comments 8. L27-81: The introduction lacks clarity and coherence, failing to articulate a clear research gap or the study's significance; while numerous facts and citations are included, they are disconnected and inadequately synthesized, making it difficult to discern the purpose and context of the research. To strengthen this section, the authors should ensure the introduction includes the following basic elements: a clear statement of the research problem, a concise review of relevant literature to establish the context and gap, a specific explanation of the study’s importance, and a clear outline of the research objectives or questions.
Response 8: The literature review includes an outline of the problems of biometeorology and bioclimatology, providing, among others, one of the common classifications of applications of biometeorological research. Next, they cited works from this field that appeared in recent years and concerned various climate zones, focusing on the European continent and especially the area of Poland. In the case of works concerning the area of Poland, the most important older works from the years 2012-2020 were also included. In agreement with the reviewer's comment, the "Introduction" chapter, particularly last paragraph, was reedited to press the scientific aims of the research.
Last paragraph of Introduction proposal:
The scientific objectives of the work may be specified in three aspects. (1) The research area is located in central Europe, one of the most sensitive areas vulnerable to climate change caused by global warming. The results of such an analysis can provide information on the response of bioclimatic conditions to the changing climatic conditions in recent decades. (2) This region covers the largest part of Poland and there are many cities attractive in terms of culture, business and urban tourism. The obtained results may also be used, among others, in the long-term adaptation of urban areas to climate change, as well as a tool supporting decisions in urban planning. (3) Due to the complexity of the research, the results may also be a contribution to the discussion on a new division into bioclimatic regions of Poland.
Comments 9. L83: What are the characteristics of Region IV that separate it from the other bioclimatic regions in Poland based on the classification by Kozłowska-Szczęsna? The authors need to describe them.
Response 9: Region IV is characterized by the largest spatial range and a little stimulating type of bioclimate, occurring in lowland areas. It includes the Central Polish Lowlands with a poorly diversified relief. Unlike other regions of bioclimate, a change of place of residence may only to a small extent cause the need for adaptation of the human body after arrival and readaptation after return, or even it does not require it at all. The prevailing climatic conditions are typical for Poland and the majority of the Polish population lives there.
In the Central Region (IV) there are the fewest days that are burdensome for humans in comparison to the rest of Poland. In the west, there are less than 20% of them, and in the center of the country from 20 to 30% of days a year. The mild bioclimatic conditions occur in western part of Poland that is associated with short, not very severe winters, early and warm spring and long thermal summer. In the lowland areas weather conditions (both good and bad) is more persistent, in comparison the coastal or mountains regions [31].
Comments 10. L83-93 and Fig. 1: Since the study only examine Region IV, information of the
other regions is irrelevant and should be omitted.
Response 10: Suggested part of text has been removed.
Comments 11. L92 and Fig. 1: Warsaw is used at L92 but Warsawa appears in Fig. 1. Please use
consistent spelling. The same issue is also found in Fig. 3–6.
Response 11: The spelling has been standardized.
Comments 12. L101-103: The average and maximum are written as single values, but the minimum is written in a range. Please keep consistency in this sentence.
Response 12: It has been corrected.
Comments 13. L105: Citing Wikipedia is inappropriate for a scientific manuscript. Please choose a credible source of information.
Response 13: The citation has been changed on a reliable scientific source:
- Arnfield, A. J. Köppen climate classification Encyclopedia Britannica, 2020, 11.
- Institute of Meteorology and Water Management – National Research Institute, https://klimat.imgw.pl/pl/biuletyn-monitoring/ Accessed 25 April 2025
Comments 14. L109: Please indicate the local time (CEST and CET) that correspond to 12 UTC.
Response 14: Added local time CEST and CET
Comments 15. L109-113: The description of data is insufficient. Please clarify: How many stations are included in the study? Is the data of all the weather stations in Region IV used, or only the data of the weather stations in the 6 cities are included? I assume that more than one station exists in one city. If data selection is done (i.e., not all data is used), what are the selection criteria? If the study only includes the data of the 6 cities, the findings are not representative of the entire Region IV. In this case, it is inappropriate to indicate the study area as Region IV.
Response 15: In this study, six meteorological stations were taken into account, which are located in a representative location in the administrative boundaries of the cities. These are synoptic stations and make observations to meet synoptic scale requirements. According to Guide to Instruments and Methods of Observation (WMO-No. 8) synoptic scale is equal to mesoscale i.e. 3 - 100 km. Because of homogenous conditions in lowland area the scale is greater and rather reaches few dozen kilometers than a several ones. If the data was not to be representative of the studied area, many works concerning similar problems and base on 1 station in the region would have to be questioned.
Some of this information was added as text in the manuscript in section 2.
Comments 16. L113-114: “Mean radiation temperature” should be written as “mean radiant
temperature”. Please correct. In addition, the calculation of mean radiant
temperature (Tmrt) is an intermediate step for obtaining UTCI, but Tmrt is not
included in any analyses. Please clarify the role of Tmrt in the study clearly in the manuscript.
Response 16: Indeed according to the reviewer's remark, Tmrt is an intermediate stage in calculating UTCI, and at any stage of the work does not include its analysis. Therefore, the authors removed information about this parameter.
Comments 17. L144-157 and Fig. 2: None of the values can be read from Fig. 2 because cities
are not specified in the figure. The authors should use distinct color or line pattern to label each city in Fig. 2. Moreover, please explain the relevance of displaying thermoneutral zone in Fig. 2. If it is retained, the authors should define it clearly in the manuscript.
Response 17: In accordance with the reviewer's suggestion regarding Fig. 2, the lines for each station in the graph have been marked with a different pattern so that the values can be read. In addition, the ‘thermoneutral zone’ marked in this figure is a comfort zone without heat load and is to make it easier for the reader to quickly determine and find it in the figure. But In accordance with the reviewer's suggestion, it was removed for the of clarity of this figure.
Comments 18. Fig. 2: The variation in minimum UTCI across cities in any month is much larger than those of average and maximum. Please explain the cause of such a difference in variation between average, maximum, and minimum UTCI.
Response 18: The UTCI index is a kind of the reflection of the air temperature. For the winter months and actually for the cold half-year (from October to March) the minimum values for Warsaw and Łódź - stations located in the eastern part of the region are lower compared to other locations. In turn, for the Zielona Góra station the minimum values are the highest. The big difference between the UTCI index values, especially in the cold half-year, can be associated with the fact that during the winter, the polar and arctic continental air masses inflow over eastern part of the Polish Lowland more frequently bringing frosty air and more severe winters. In the west, on the other hand, polar maritime air mass mentioned in the description of the region, covers the region more often, mitigating the course of winter. In warm half period of the year the differences are smaller than cold but also bigger than for the average and maximum values.
Comments 19. Fig. 3: There are several caveats in this analysis and its visualization:
(1) Even though the time series of maximum and minimum are non-linear, the original time
series should be shown as a comparison, and it can verify the fitted curve.
(2) The justification of fitting the time series of maximum and minimum UTCI using polynomial of 5-th or 6-th degree is unclear. If there is not a trend in the associated time series, simply report it without manipulation. Moreover, fitting a time series with such a high-degree polynomial could potentially cause overfitting. If it is important to find a best-fit line based on R2 value, why is the
same not done to the average UTCI time series? The authors need to reconsider why fitting to maximum and minimum UTCI time series is needed.
(3) The subplots should be laballed (i.e. Fig. 3a, 3b, 3c, etc.). Moreover, the current arrangement of the subplots lacks clarity. Please arrange them in 2 columns and 3 rows, with each column showing subplots of different cities, and each row showing subplots of different parameters (average, maximum, and minimum).
(4) The lack of axes and tickmarks at both axes makes it difficult to read the figure. Please add axes and tickmarks like Fig. 4.
Response 19:
Ad.(1) The original time series have been supplemented on the chart.
Ad.(2) The trend analysis showed that for each case (for different stations, for the mean, maximum and minimum value), the best trend line equation is of a different type. For the means these are linear equations, which are slightly better than polynomial ones (the coefficient of determination is slightly higher). In turn, for extreme values (maximum and minimum), polynomials from 3rd to 6th degree are definitely better than linear ones. In the final version of the paper, the authors decided to give unified equations that at the same time well reflect the trend of the studied series of results, statistical parameters are sufficient good (determination coefficient, significance). Polynomial equations of 3rd degree meet these conditions. The graph of the 3rd degree function has one inflection point and does not contain divergences between the trend line and the real values particularly at the beginning and at the end of the series, as is the case with higher degree polynomials.
Ad.(3) and (4) The remarks concerning the clarity of the charts have been taken into account.
Comments 20. L165: Consider replacing 10 years with decade when it is used in unit, where appropriate. The same happens throughout the manuscript.
Response 20: The term “10 years” has been replaced by a “decade” as suggested.
Comments 21. Fig. 4: The order of categories in the figure in inconsistent with the text (L190- 196). It makes readers difficult to follow. Please align figure layout in Fig. 4 with the order of discussion. Furthermore, please add label to each subplot.
Response 21: Changed the order of categories in the figures to match the text. Added a label to each subplot.
Comments 22. Caption of Fig. 4: The figure shows the annual number of days for each
category, not average. Please correct it.
Response 22: It has been corrected.
Comments 23. L197: Should this line be part of the figure caption of Fig. 3? Also, it should be written as “significant at 95% confidence level”. Please revise.
Response 23: It’s probably about line 187. This line is a part of the figure description. Changed according to the remark.
Comments 24. L189-190: Please clarify whether the trend of all 24 time series in Fig. 4 are statistically significant. If only some of them exhibit a significant trend, please specify them. Moreover, it should be p < 0.05 instead of p = 0.05. Please correct it.
Response 24: The section describing the figure 4 lists the cases (for which category and in which station) of significant trends (p < 0.05).
Comments 25. L192-193: The authors said that categories -1 and 0 do not show any trend, which contradict the statement at L189-190. Please resolve this inconsistency.
Response 25: The sentence in line L193 the statement ‘does not show a trend’ refers to the category ‘comfort’ (0) only.
Comments 26. L199: it should be “decrease” instead of “increase” for category -2. Please correct it.
Response 26: It has been corrected.
Comments 27. L205-207: For completeness, the authors should show the time series for
extreme heat load, even if a trend line cannot be determined due to limited sample size.
Response 27: For the completeness, time series for extreme heat load is added on two additional figures.
Comments 28. L240: Should this sentence belong to the caption of Fig. 4? Moreover, when you conduct a Student’s t-test for the trend line in this analysis, you are testing whether the slope of the regression line is zero or not, but not R2. Please correct this sentence.
Response 28: The sentence The coefficients of determination shown are significant at a statistical level of 0.05 belong to the Figure 4 explanation. It has been corrected.
Comments 29. L241-392: The subject under examination in this analysis is not (absolute) frequency, but relative frequency or percentage of each category. Please correct it in the text, Figs. 5-8, and their caption.
Response 29: It has been revised.
Comments 30. L264-267: Why Wroclaw’s relatively large size lead to its lowest percentage of comfortable conditions and a higher percentage of “strong heat stress” in summer? This relationship is not evident. The authors should clarify.
Response 30: After analyzing the statement, the Authors has come to the conclusion that the location of Wrocław in the warmest region of Poland causes the frequency of the comfort zone is lower in favor of strong heat stress.
Comments 31. L327: Please remove “last years”.
Response 31: It has been removed.
Comments 32. L339: The year after 2018 is incomplete. Please correct it.
Response 32: It has been corrected.
Comments 33. L341: Please put the percentage (0.3%) inside parenthesis.
Response 33: It has been supplemented.
Comments 34. L324-341: What are the objectives and key takeaways from this analysis? I also
cannot understand the necessity of singling out particular years in this analysis.
Response 34: Figure 7 shows another way of the results visualization. It shows similar results to those included in Figure 4, which shows trend lines of the number of days in individual thermal load categories. In this case the frequencies for individual stations are presented. On the Figure 7, the variability of the occurrence of each category in individual years can be seen closely, the fluctuations from year to year of the frequencies of individual categories can be seen, warmer and colder years can be identified. Trends can also be : the frequency of the "strong heat stress" category (marked in orange) remains at a similar level, the frequency of the "moderate heat stress" category (yellow) increases slightly and the frequency of the "strong cold stress" category decreases (blue).
Comments 35. L349-350: I suggest to rewrite this sentence to “Our last analysis examined the annual cycle of heat load category percentages for each city (Fig. 8).”
Response 35: The sentence was rewritten.
Comments 36. Fig. 8: The subplots of Wroclaw and Torun cannot be seen. The authors should make sure that all figures are clearly visible.
Response 36: It has been corrected.
Comments 37. The analyses associated with Figs. 5, 6, and 8 are redundant. Fig. 6 is just the seasonal average of Fig. 8, while Fig. 5 is the overall average. Therefore, merging the 3 analyses can improve the clarity of the manuscript.
Response 37: The authors tried to combine the analysis of the results presented in Figures 5, 6 and 8. However, the characteristics of the results are different, so combining them does not reduce the content of the text. To improve the flow, the authors also considered adding secondary heading.
Comments 38. L419-420: I don’t agree that there is a “possibility of thermal stress (transition) from extreme cold stress to very strong heat stress”. Seasonal transitions are gradual, not abrupt. In Fig. 8, we cannot see category -4 and category 3 appear in any consecutive months, and it shows that the aforementioned statement is invalid. Please revise this sentence accordingly.
Response 38: The authors did not mean a sudden transition between extreme categories, but rather a range of thermal load fluctuations from extreme cold stress to very strong heat stress. This sentence has been precised.
Comments 39. Sections 4 and 5 contain overlapping content. Consider merging them for better flow.
Response 39: The authors have reedited the conclusions and tried to separate the information included in the summary and conclusions. Although the conclusions result from the summary are compensed and presented in points.
Comments 40. The findings across cities are very similar in some analyses (e.g., Figs 5-8), while differences across the cities can be observed in other (e.g. minimum UTCI in Fig. 2). The authors should explain why sometimes discrepancies exist among cities, but similarities are observed in other cases.
Response 40: The explanation both similarities and differences is the geographical location and which factors have a greater impact on the course of meteorological conditions. If macro-scale factors dominate, there are similarities at all studied stations, if meso-scale factors – there are some differences. Poland is located in the intermediate temperate climate zone, and in the area of the Polish Lowland, features of a continental climate are visible – in the east and maritime in the west. The warmest area of Poland is the south-western region and the coldest is the north-eastern one. Figure 5 shows a clear similarity in the frequency of the UTCI index at all analyzed stations. In the case of a more detailed analysis of the frequency, including the partition into the seasons (Fig. 6), differences already occur. In winter, at stations located in the east Warsaw and Łódź, the frequency of cold stress from categories (-2) and (-3) occurs more often and category (-4) appears. This is the result of more frequent inflowing of cold continental polar and continental arctic air masses over Poland at this time of year. A similar course is for Poznań, which may indicate the influence of continental features also in this region. It is also seen in Fig. 8, in which the temporal frequency distributions seem generally similar, but in the more detailed analysis for Warszawa, Łódź and Poznań stations, the ranges of occurrence of cold stress categories for the winter months are larger and the category (-4) also appears.
The above remarks will be formulated in the work as a contribution to the discussion on the new bioclimatic clasiffication of Poland.
Comments 41. Figs. 3 and 4 show the trend in UTCI and categories, while Fig. 7 shows the
change in relative frequency with time. Do these findings reflect any signal of
global warming? This important aspect should also be discussed explicitly.
Response 41:
Yes, all charts of the time course of the analyzed elements (Fig. 3, 4 and 7) indicate an increasing tendency in air temperature in central Poland (Region IV), which can be related to global warming. The figure of the UTCI values course (Fig. 6) shows an increasing trend in all cases – for average, maximum and minimum values. For minimum values, there is greater spatial (comparison of values at individual stations) and temporal (from year to year) differentiation, but the authors tried to explain this in the answer on remark number 18. In the case of graph 4 presenting the number of days in individual thermal stress categories, it can be seen that for the heat stress category (1), (2) there is an upward trend, i.e. the number of days in a given category increases, for category (0) it is difficult clearly to determine, for Warsaw and Łódź it increases and for the others stations it decreases slightly. In turn, in the case of the cold stress category, for categories (-2) and (-3) there is a decreasing trend, especially visible for category (-3). The only category of cold stress for which an increasing trend is clear is category (-1). However, this increase can be explained by a shift in the number of days from the lower categories (-2) and (-3) to category (-1), which would also confirm warming in the studied period of 2001-24. A similar trend can be seen in Fig. 7 presenting Frequency (%) of thermal stress categories according to UTCI index at 12 UTC in particular years. Increase in frequency in the categories of heat stress (1) and (2) and decrease in frequency in the categories of cold stress (-3) and (-4). This Fig. 7 also shows one interesting detail. In the middle of the study period, in the years about 2010-13, there was a slight cooling, which translates into an increase in the frequency of cold stress and cases of the occurrence of category (-4). Such a time course additionally shows that the selection of a third-degree polynomial as a trend line for the years 2001-24 has its substantiation.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe study fills a gap in the long-term changes of UTCI in central Poland, combining spatial analysis and multiple time scales (annual, seasonal, monthly), which is innovative. This study has several problems as follows.
In Materials and Methods, the latitude and longitude location of Figure 1 need to be clarified. The weather stations located in a suburban or highly urbanized area also need to be addressed. Because the difference in all meteorological data between suburban and urban areas is more significant.
The tools or formulas used to calculate the UTCI, are described in detail, which is important for the accuracy of the results.
Are the UTCI ranges and pressure categories in Table 1 consistent with local climate zones? The authors need to test and correct for this.
Figure 3 contains lots of information, which makes it very confusing, and it is recommended that the authors present the information one by one.
The results section is informative, but it is recommended that secondary headings such as 3.1, 3.2, and 3.3 be added to enhance the logic of the results and discussion sections.
It is recommended to add a description of the limitations of this study and specific policy recommendations based on the findings to achieve regional UTCI optimization.
Comments on the Quality of English LanguageAuthors are advised to modify and embellish the language of the article.
Author Response
RESPONSES TO THE REVIEWER 2
The authors would like to thank the Reviewer for all comments and suggestions that improve the quality of the manuscript.
Comments 1. In Materials and Methods, the latitude and longitude location of Figure 1 need to be clarified. The weather stations located in a suburban or highly urbanized area also need to be addressed. Because the difference in all meteorological data between suburban and urban areas is more significant.
Response 1: In this study, 6 meteorological stations were taken into account, which are located in a representative location in the administrative boundaries of the cities. They are not urban stations but the synoptic ones and make observations to meet synoptic scale requirements. According to Guide to Instruments and Methods of Observation (WMO-No. 8) synoptic scale is equal to mesoscale i.e. 3 - 100 km. Because of homogenous conditions in lowland area the scale is greater and rather reaches few dozen kilometers than a several ones.
Comments 2. The tools or formulas used to calculate the UTCI, are described in detail, which is important for the accuracy of the results. Are the UTCI ranges and pressure categories in Table 1 consistent with local climate zones? The authors need to test and correct for this.
Response 2: The Universal Thermal Climate Index (UTCI) and its ranges used in our research have been tested by many scientists - creators of this index, for whom the main assumption and purpose of this was its universal application in various climate zones. A lot of studies from both the temperate zone (to which our research concerns) and other climate zones confirm its universality and the application of the categories presented in Table 1, as well as the possibility of comparing these results of different climate zones.
Comments 3. Figure 3 contains lots of information, which makes it very confusing, and it is recommended that the authors present the information one by one.
Response 3: Figure 3 has been changed to be more readable and clear. Subsections a, b, c etc. have been made, trend equations have been removed and moved to a new table 2. In Fig. 3, the determination coefficients R2 have been remained and a description of the stations, labels in each figure have been added. A new layout of figures has been used: two columns and 3 rows, each row for one characteristic (average, maximum and minimum).
Comments 4. The results section is informative, but it is recommended that secondary headings such as 3.1, 3.2, and 3.3 be added to enhance the logic of the results and discussion sections.
Response 4: The descriptions of some results were combined, among others, at the request of one of the reviewers, which is why the results section was shortened and synthesized. Other sections do not have subsections, so in order to maintain the uniformity of all the article text, the authors decided not to divide the results chapter.
Comments 5. It is recommended to add a description of the limitations of this study and specific policy recommendations based on the findings to achieve regional UTCI optimization.
Response 5: The aspects mentioned in the review were added to the summary and conclusions
Reviewer 3 Report
Comments and Suggestions for AuthorsIn the abstract, abbreviations should be avoided. Additionally, the descriptions of the climate index placed in quotation marks make the text unnecessarily heavy.
In the following sections, the full name should be given first, with a reference, followed by the abbreviation in parentheses, which can then be used throughout the rest of the paper.
The introduction should explain why this research is important. For example, if no previous studies have addressed this topic, it is sufficient to state that clearly.
In Section 2, you should include how the initial data were obtained. This description should be detailed enough to provide the reader with a complete understanding of the methodology. This part is currently missing, even though you later mention that certain average, maximum, and minimum values were determined. If you are using specific software (e.g., Statistica), it should be clearly stated and referenced at the end.
In the results section, Figure 3 should be aligned, for example, to the left margin. Also, the content in Figure 4 appears scattered and should be organized more clearly. This comment applies to the following visual materials as well.
Line 349: Please describe how the categories you present are defined, placing their names in quotation marks.
In the conclusion, you have synthesized the research and provided certain findings. However, the application and interpretation of these results are missing. Without that, the data remain just numbers. If it is evident that the climate is warming, how could this inform improvements in urban and spatial strategies, tourism, climate policy, emergency response protocols during periods of severe heat stress, etc.? In other words, it is necessary to complete the study with practical implications. It is also important to state the limitations of your research and suggest directions for future work on this topic.
Author Response
RESPONSES TO THE REVIEWER 3
| The authors would like to thank the Reviewer for all comments and suggestions that improve the quality of the manuscript. |
Comments 1. In the abstract, abbreviations should be avoided. Additionally, the descriptions of the climate index placed in quotation marks make the text unnecessarily heavy.
Comments 2. In the following sections, the full name should be given first, with a reference, followed by the abbreviation in parentheses, which can then be used throughout the rest of the paper.
Responses 1 and 2: The remarks have been taken into account in final version of the paper.
Comments 3. The introduction should explain why this research is important. For example, if no previous studies have addressed this topic, it is sufficient to state that clearly.
Response 3: The "Introduction" chapter, particularly last paragraph, was reedited to press the scientific aims of the research. In this part three aspects of the research has been mentioned. (1) Location the research area in one of the most sensitive areas vulnerable to climate change. The results of such an analysis can provide information on the response of bioclimatic conditions to the changing climatic conditions in recent decades. (2) This region covers the largest part of Poland and there are many cities attractive in terms of culture, business and urban tourism. (3) The contribution to the discussion on a new division into bioclimatic regions of Poland.
Comments 4. In Section 2, you should include how the initial data were obtained. This description should be detailed enough to provide the reader with a complete understanding of the methodology. This part is currently missing, even though you later mention that certain average, maximum, and minimum values were determined. If you are using specific software (e.g., Statistica), it should be clearly stated and referenced at the end.
Response 4: The basic data are daily results of meteorological measurements conducted at 6 mentioned first-order synoptic stations. On the basis, the average daily values of the UTCI index were calculated. The material was statistically tested for normal distribution and significance of differences. On the basis of daily values, the average, maximum and minimum values were calculated.
Comments 5. In the results section, Figure 3 should be aligned, for example, to the left margin. Also, the content in Figure 4 appears scattered and should be organized more clearly. This comment applies to the following visual materials as well.
Response 5: The charts both in the layout, quality of visualization and descriptions has been improved.
Comments 6. Line 349: Please describe how the categories you present are defined, placing their names in quotation marks.
Response 6: The categories of thermal load was defined according to the value of UTCI index. The main assumption and purpose of this index was its universal application in various climate zones. A lot of studies from both the temperate zone (to which our research concerns) and other climate zones confirm its universality and the application of the categories. The categories, their names and ranges of UTCI values are presented in Table 1.
Comments 7. In the conclusion, you have synthesized the research and provided certain findings. However, the application and interpretation of these results are missing. Without that, the data remain just numbers. If it is evident that the climate is warming, how could this inform improvements in urban and spatial strategies, tourism, climate policy, emergency response protocols during periods of severe heat stress, etc.? In other words, it is necessary to complete the study with practical implications. It is also important to state the limitations of your research and suggest directions for future work on this topic.
Response 7: The aspects mentioned in the review were added to the summary and conclusions
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsSee attachment.
Comments for author File: Comments.pdf
See attachment.
Author Response
ROUND 2 RESPONSES TO THE REVIEWER 1
The authors thank the Reviewer for valuable comments and suggestions. The changes and corrections in the manuscript are marked in green.
Comments 1. Response 2: The authors used a wrong statistical test. Shapiro-Wilk test is a test for normality, but not a test for statistically significant differences between the monthly average UTCI values of different cities. The authors should use one-way ANOVA, which compare the means of two or more independent groups. After conducting ANOVA, please report the p-value in the manuscript.
Response 1. The authors corrected the statistical testing and applied the appropriate statistical test of one-way ANOVA analysis between monthly average UTCI values for different cities. The test did not draw statistical significacy. However, the same one-way ANOVA test was carried out on the source data (daily data) and statistically significant relationships were obtained at the level of p < 0.01.
Comments 2. Response 11: Both Warsaw and Warszawa are still being used throughout the manuscript. Please standardize the city name. I recommend Warsaw, which is the name most widely recognized by a general international audience.
Response 2. Response 11: The spelling has been standardized and corrected to Warsaw.
Comments 3. Response 14: “CEST” and “CET” are added to Line 116, but the local time (13 CET and 14 CEST) that corresponds to 12 UTC is not written.
Response 3. Response 14. Both times have been added.
Comments 4. Response 15: Thank you for clarifying that the study uses six synoptic stations located within the cities. While these stations are appropriate for capturing regional or large-scale climate patterns, synoptic stations are typically positioned to reduce the impact of local urban microclimate effects (like UHI). The authors also noted that “In most cities in the region urban heat island UHI take place” (Lines 105-106). Therefore, please add a clear statement in the data description section acknowledging that the data from these synoptic stations is used to represent the large-scale climate conditions in Region IV but may not fully capture the variability at the urban or local scale, particularly the potentially more extreme conditions within dense urban areas.
Response 4. Response 15. The Urban Heat Island is a phenomenon that occurs commonly in larger agglomerations. The statement "In most cities in the region urban heat island UHI take place - typical phenomenon for large urban-industrial areas [31, 32, 33]", which was included in the article, is a general statement that does not refer to the scope of research in this paper nor to the type of the stations. In the fragment in lines L 120 - 124 it is written that the stations are located "within the administrative boundaries of the city"; however, these are not urban stations but synoptic stations representing the large-scale climate conditions.
Comments 5. Response 18: Please add the explanation (the cause of the difference in variation between average, maximum, and minimum UTCI) to the manuscript. In addition, does your response imply that the UTCI in Region IV is dominated by air temperature, while the other underlying factors (humidity, radiation, and wind speed) are secondary? Please also clarify your perspective on the relative importance of these meteorological parameters for UTCI in Region IV in the manuscript, wherever appropriate.
Response 5. The statement “the UTCI in Region IV is dominated by air temperature” has not been so much about the “dominance” of temperature, but the influence of thermal differentiation on the “differentation of UTCI”. All meteorological parameters taken into account when calculating UTCI are important. If this were not the case, the UTCI index would not be needed and the thermal sensation would be determined based only on temperature. However, in the case of the Polish Lowland, which is covered by Region IV, the spatial distributions of solar radiation, air humidity and wind speed are similar. In this a case, the variability of the index is most influenced by the parameter whose variability is the biggest.
In addition, greater differences in maximum and minimum values may be a confirmation of the nature of climate change in the first decades of the 21st century. One of the effects of climate change is the intensification of extreme phenomena, the occurrence of greater interannual differences in the course of air temperature or amounts of precipitation, etc. Therefore, the minimum and maximum values of the UTCI index have bigger differentiation, which is not noticed in the course of the average values.
Comments 6. Response 19: Is the purpose of using the polynomial fit for demonstrating that the trend in a city and parameter is not linear? If it is true, the authors can simply use linear fit because the slope should be very small when a linear trend does not exist. To show “more complex behaviors in temporal thermal stress distribution” as stated on Lines 569-570, the raw time series are sufficient as large interannual variability is evident. The polynomial fitting lines do not add any value. If the authors insist on the role of polynomial fit, please explicitly and clearly express the scientific purpose and added value in the manuscript.
Response 6. Response 19: The intention of trend analysis was to show whether it exists or not. Only in the case of the UTCI index values, for all values - average, minimum and maximum, a better fit was obtained for the polynomial function, which can be seen by comparing e.g. Table 2 from the previous (first version of the manuscript) with the present one. In the case of trend analysis of annual number of days with thermal stress categories, the best-fitting function was the linear function. The explanation of why the authors decided to use the polynomial trend is also in the response to comment no. 19 in the first round of review: "In the final version of the paper, the authors decided to give unified equations that at the same time well reflect the trend of the studied series of results, statistical parameters are sufficiently good". Finally, agreeing with the Reviewer to show a linear trend, which in the case of no existing the slope of the function is very small the authors analyzed the linear trend in the mauscript.
Comments 7. Response 30: The authors concluded that “the location of Wrocław in the warmest region of Poland causes the frequency of the comfort zone is lower in favor of strong heat stress.” I would assume that “relatively large size” is no longer one of the reasons. However, the related statement in the manuscript (Line 286) remains unchanged. The authors should clarify: does the relatively large size of Wrocław lead to its lowest percentage of comfortable conditions and a higher percentage of “strong heat stress” in summer? Or is the unchanged statement on Line 286 an error?
Response 7: Response 30: It is a mistake. The statement „ and its relatively large size” will be removed from this sentence.
Comments 8. Method: In the method section, please describe all the statistical tests used in the study and the analyses in which a test is applied.
Response 8: It has been supplemented. The one-way ANOVA test was used to check for statistically significant differences between the monthly average UTCI values of different cities. In case od the basic daily data the significance was confirmed at the level of p < 0.01, but for average monthly values was not.
Comments 9. Lines 125, 548, 573: Please remove the full name of UTCI as it has been defined in Line 40.
Response 9. It has been removed.
Comments 10. Lines 144-152 (method): Why do the authors apply polynomial fit to average/minimum/maximum UTCI (Fig. 3), but not the number of days of the occurrence of each thermal stress category (Fig. 4)?
Response 10: In the first version of the manuscript it was assumed that the best-fitting trend equation would be presented. In the case of UTCI values (average, maximum and minimum) they were polynomial equations and in the case of the number of days they were linear ones. Accordingto the Reviewer's comment (number 19 in first round of the reviews) in the current version it has been changed and in the cases of both analyzed elements a linear trend is analysed. Although mention of the fact that such an analysis was carried out was found in the text. The explanation is also provided in the response to comment number 6.
Comments 11. Lines 181-182:
(a) The authors stated that “The rate of average value of UTCI increase were determined according to linear trend, not presented in the table this paper”. Does this statement refer to 0.6d egC/decade in Poznań and Toruń to 1.8 degC/decade in Wrocław and Warsaw?
(b) What about the maximum (Lines 177-178) and minimum (Lines 178-180) of UTCI? How are these values calculated?
(c) What are the reasons for reporting the linear trend first and then fit the time series using polynomial? This part is very confusing.
Response 11:
(a)&(b): This part of the results description has been corrected. In accordance with the reviewer's suggestion in remerk 6, only the fragments concerning the results of the linear trend analysis remain in the manuscript. Although mention of the fact that other type of equation (polynomial) were analysed has been carried out was found in the text
(c) The explanation is provided in the response to comment number. 6.
Comments 12. Line 192: Remove “the” before “Figure 3”.
Response 12. It has been removed.
Comments 13. Line 193: “All equations for” should be written as “The trends of”.
Response 13. It has been corrected.
Comments 14. Line 532: Please clarify what “(applied in this work)” mean here.
Response 14. The paragraph in question raises the issue of the new bioclimatic classification of Poland, based on different criteria. The authors wanted to remind that in this work the research area (Region IV Central) was adopted based on the existing classification of Szczęsna-Kozłowska modified by Błażejczyk. The statement "(applied in this work)" will be replaced with "(used in work)". However, if the Reviewer believes that such a statement is also misleading, it will be removed.
Author Response File: Author Response.pdf
