PCLM-D-25-00262

Regional Heterogeneity and Warming Dominance in the United States

PLOS Climate

Dear Dr. Rivas,

Thank you for submitting your manuscript to PLOS Climate. After careful consideration, we feel that it has merit but does not fully meet PLOS Climate’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Ahmed Kenawy, Ph.D.

Academic Editor

PLOS Climate

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Climate’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Climate does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I thank the authors for their original scientific research, which represents a strong scientific methodology and strong thinking.

My observations on the work are as follows:

The figures and maps are of poor quality and need to be improved and better formatted.

In the abstract, you mentioned statistical results but did not explain the probability of the results or link them physically. Please link them or explain the probability more deeply.

I see in the introduction that the references are good, but they focus entirely on the statistical aspect. Please also address physical climate references, as the current indications are superficial and not in-depth.

From the research results, 44% of the states may not show a statistically significant increase using the average temperature, while the largest percentage, 84%, show warming when evaluating different quantities of the distribution. This highlights that relying on the average can mask the significant warming occurring in specific parts of the temperature range.

In the methodology, why were the classification results not compared with other alternatives, such as nonlinear fits or others?

Why was the statistical analysis period not divided into two periods? For example, the first period was from 1950 to 1990, as You mentioned that there was little change, while the period from 1990 to 2021 saw more dramatic change, so the outcome may have changed in the end.

The discussion focused on quantitative values more than concrete impacts, such as health and agricultural issues, etc.

The recommendations are very general and must take regional diversity into account.

Reviewer #2: I must acknowledge the significant effort expended in the current draft before sharing some general comments on it.

The quantitative approach is technically sound, innovative, and well-suited for statistical testing. It moves beyond the analysis of average temperatures to uncover hidden warming patterns across the spatially and climatically diverse regions of the United States. This highlights the method's versatility and significance.

The paper's finding that warming could be detected in 84% of US states when considering different quantities, compared to only 44% when using the average, is an interesting result, revealing important nuances often overlooked by traditional approaches.

This methodology offers valuable regional insights by identifying distinct warming patterns across various states. For example, it highlights uniform warming, stronger warming in the lower percentiles, and stronger warming in the upper percentiles, which together contribute to a precise, state-level understanding of climate change. Such details are essential for informing policymakers and shaping regional adaptation strategies.

The proposed concept of "warming dominance" provides a testable framework for comparing the intensity of warming across different regions, which the reviewer considers a strong conceptual contribution.

The use of robust and testable linear regression formulas for analysis, along with the consideration of the full temperature distribution, is statistically sound and comprehensive, providing a strong empirical basis for the research.

While the selection and representativeness of the data across all 50 states may be crucial to the research, a significant concern persists regarding the spatial density of the chosen climate stations. There is a question of whether the data adequately captures the variability in areas that are less populated or sparsely monitored.

The concept of "warming dominance" raises questions about its interpretation and the potential for oversimplification. Therefore, what are the political implications of one state's "warming dominance" over another's, especially if it does not account for factors such as vulnerability, population density, or economic impact?

Is it currently possible (under political pressure) to attribute the dominance of warming to increased human activities and the demand for emissions reductions in the United States?

Regarding warming patterns, what are the potential physical mechanisms (e.g., land-use changes, atmospheric circulation patterns, and urban heat island effects) that lead to the observed variability across the United States? Could this be a potential area for future research?

Has the climate dataset used in the current study been compared with other climate datasets to enhance data reliability and quality?

Has the robustness and accuracy of the data been tested, particularly with regard to the choice of quantiles, the potential impact of data quality issues, and potential biases resulting from spatial distribution and the variability of the number of stations over time?

The draft requires a more detailed discussion of how policymakers at the state and federal levels might use these results practically to design more efficient and targeted mitigation and adaptation strategies.

Can the methodology be easily applied to other climate variables (e.g., precipitation, sea level rise) or at different spatial scales?

What are the practical limitations and potential adaptations needed for broader application?

The manuscript focuses primarily on temperature variation. A more comprehensive analysis should consider the interaction of temperature changes with other climate variables, such as precipitation or extreme weather events, as a potential area for future research.

What are the similarities and differences between the current research paper and the published paper entitled "Climate Change Heterogeneity: A New Quantitative Approach" published earlier this year in terms of the nature of the study, the quantitative method, the set of climate data used, the results, and the case study?

Despite its importance, the introduction to the current study should be concise, transferring its findings and comparisons to the discussion section.

A conclusion section should be included.

The discussion section should be rewritten and improved, avoiding repetition, as repeated sentences were observed in the introduction.

Reviewer #3: PCLM-D-25-00262: statistical review

SUMMARY. This paper proposes a quantitative approach to describe and compare warming processes across different regions with an application to the United States. The main novelty relies on the use of multiple quantiles to compare distributions of temperatures over time and across regions. While I fully agree with the authors that quantiles have an enormous potential in the analysis of climate change, I have to remark that the statistical methods exploited by the authors are not fully appropriate. See the major issue below.

MAJOR ISSUE.

1. Quantiles are analyzed by a least squares regression model. This is not correct, as estimating a quantile requires the minimization of a loss function that is not the sum of squared residuals. Likely, though, statistical modelling of quantiles is nowdays well developed and methods of quantile regression are available in most statistical platforms. See for example the quantreg R library or qreg in Stata.

Quantile regression not only provides a rigorous framework to estimate equations (1) and (3), which are the main equations of the paper, but it also helps interregional comparisons, by including a regional dummy variable as a predictor. I would therefore recommend to re-do the statistical analysis by relying on quantile regression methods. In this way, findings would be based on a state-of-the-art, rigorous ground, enhancing paper solidity. This comment should be viewed as a constructive suggestion: quantile regression is easy to implement and it shouldn't require too much time.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Regional Heterogeneity and Warming Dominance in the United States

PCLM-D-25-00262R1

Dear Dr. Rivas,

We are pleased to inform you that your manuscript 'Regional Heterogeneity and Warming Dominance in the United States' has been provisionally accepted for publication in PLOS Climate.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow-up email from a member of our team.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Climate.

Best regards,

Ahmed Kenawy, Ph.D.

Academic Editor

PLOS Climate

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Additional Editor Comments (if provided):

The manuscript can be accepted for publication in its present form.

Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Does this manuscript meet PLOS Climate’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

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4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Climate does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I see that it was done as he wanted.

Reviewer #2: The authors have adequately addressed all the changes and comments I requested from them, and I believe the manuscript in this form is suitable for publication.

Reviewer #3: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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