Time-Varying Bivariate Modeling for Predicting Hydrometeorological Trends in Jakarta Using Rainfall and Air Temperature Data

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents a bivariate modeling of the dependence between precipitation and temperature in a non-stationary context, using the Jakarta area as a case study.

The authors use various Archimedean copulas with different combined methods for parameter estimation.

I have the following major observations:

The degree of originality of the analysis should be highlighted in more detail, since the methods applied are already established, and the novelty lies rather in their application to the Jakarta dataset.

The literature review on the applicability and use of univariate probability distributions needs to be improved. Recently, important contributions have been made on the applicability of these distributions in the analysis of extreme events such as precipitation and maximum discharges (https://doi.org/10.1029/2019WR026535; https://doi.org/10.3390/cli13070152 etc.).

Please provide relevant references regarding the stationarity test used.

The data used are impressive in length, but raise issues of homogeneity and consistency, having different sources. No detailed homogeneity analysis is presented (standard tests such as Pettitt, Buishand). In addition, the strong urbanization of Jakarta may introduce systematic discontinuities in the series that are not discussed in depth.

The choice of Clayton, Gumbel and Frank copulas is justified by their ability to capture dependencies in different queues, but it is not justified why other more flexible families were not included.

The marginal parameters are taken from a previous study, which reduces the methodological independence of this work. A recalibration of the marginals in this study would have been more robust.

The results indicate a weak dependence between precipitation and temperature. So what benefits does bivariate analysis bring over a separate univariate analysis?

The climatic interpretation of the results is superficial. For example, the implications for the frequency of extreme events (floods, droughts) are only mentioned generically.

Author Response

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Reviewer 2 Report

Comments and Suggestions for Authors

This study presents a case analysis on Time-varying bivariate modeling for predicting hydrometeorological trends in jakarta using long-term in-situ observations. The topic is relevant to the special issue “Trends and Variations in Hydroclimatic Variables: 2nd Edition” and has some practical significance for understanding hydrometeorological risks in Jakarta. However, the manuscript currently reads more like a case report with excessive details and datasheets. From a scientific perspective, it requires restructuring and refinement to better highlight the key findings and research contributions.

Major Comments

1. Please simplify and streamline Methods and Results sections. Only the essential figures and tables should be retained. For example, Table 1 is unnecessary since only the 5% significance level is used; values for other levels add no meaning. The paper should not read like a manual or textbook.
2. The Discussion should be clearly separated from the Results to emphasize the main findings and compare them with existing studies.
3. Equations: Equations (3) and (4) lack comments on the parameter σ. In addition, Equation (11) appears redundant and may be removed.
4. Definitions: Abbreviations such as Am (line 106) and IFM (line 265) should be fully defined at first mention.
5. Figure 9 is interesting, but it is unclear how the future 2030 data are generated. It is strongly recommended to use CMIP6 climate model outputs for future projections, which would enhance the scientific value and impact of the study. Also, please enlarge the axis labels on all figures for readability.
6. The implications of the findings for drought and extreme rainfall (line 856) should be further elaborated. This would strengthen the relevance of the study.
7. At line 890, it is unclear why data were obtained from two different websites. Are these from two separate stations? Please clarify.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

The article is relevant because it addresses climate variables that allow for the assessment of climate change, such as total annual precipitation and air temperature, which are primary indicators of changes in hydrometeorological regimes. The study develops a statistical assessment by processing time series data, which allows for the identification of significant trends and patterns of variability in the Jakarta region. The methodology applied provides solid quantitative support, contributing to the understanding of the impacts of climate change and facilitating the generation of useful inputs for urban planning, water resource management, and the formulation of mitigation and adaptation policies. I suggest improving Figure 1 by placing the conventions on the map and locating the weather stations used on the map. In addition, improve the quality of the graphs presented in the document.

Author Response

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Reviewer 4 Report

Comments and Suggestions for Authors

The article is titled "Time-Varying Bivariate Modeling for Predicting Hydrometeorological Trends in Jakarta Using Rainfall and Air Temperature Data." The aim of this study is to select the best stationary and non-stationary dome model and to visualize and analyze the relationship between rainfall and air temperature to predict hydrometeorological trends. The analysis was conducted solely based on data from a single measurement station located in Jakarta.

My comments are as follows:

- The introduction is correct.

- The purpose of the study is unclear. Using only a single measurement station raises concerns. - The description of the study area needs to be expanded. A map should be presented showing the terrain, river network, building density, and the locations of the measurement stations. Information about the data should be moved to a different subsection.

- The data used in the study should be described in detail. There is no comparison of whether both stations are located at the same elevation and have similar conditions. Reference should be made to historical measurements and the method of measurement accuracy.

- The research methodology is unclear. A flowchart of the research should be presented. - There is no discussion of the obtained results with studies by other authors. The reliability of the obtained results should be indicated, and reference should be made to the increase in built-up areas with rising air temperature.

- The entire article requires a reorganization of the content; the sections/subsections are disproportionate. Some sections/subsections are only a few sentences long, while others are. Technical comments:

- Figure 1 requires corrections; the map legend, scale, north direction, and measurement stations are missing.

- Data on air temperature and precipitation should be provided to one decimal place, e.g., 0.1 instead of 0.0001.

- The literature is very sparse.

 

Author Response

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Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

No further comments.

Author Response

Dear Reviewer,

Thank you for your response: No further comments.

Best regards,

Reviewer 2 Report

Comments and Suggestions for Authors

The revision has mostly addressed my comments, and it is now suitable for publication.

Author Response

Dear Reviewer:

Thank you for your positive response: 

The revision has mostly addressed my comments, and it is now suitable for publication.

Best regards,

Reviewer 4 Report

Comments and Suggestions for Authors

I believe the authors only partially improved the article. The changes introduced are not marked in the text, making it impossible to quickly verify what has been corrected. My comments are as follows:

- keywords require improvement; they should identify with the article; abbreviations that are not explained should preferably be avoided.

- figure 2 requires improvement. The points representing the measurement station are invisible on the map, and the map representing the entire Indonesian area is too dark.

- the diagram representing the workflow should be presented in subsection 2.2 or 2.3.

- subsection 3.1. requires a different name; the data analysis was already in the methodological section; trends are discussed here.

- in the discussion, the authors should refer to other studies conducted in Indonesia, as the results obtained for a single station may be completely random. It is recommended that the authors add studies by other authors from Indonesia to this section.

Author Response

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