Assessment of Rainfall Frequencies from Global Precipitation Datasets
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsYin et al., found similar rainfall frequencies from CRU WET and site observations, suggesting the former should be interpreted as field-scale values. Using this CRU WET as a benchmark, the authors further found that rainfall frequencies from grid datasets of GPCP and ERA5 are much larger than the corresponding field-scale values. Finally, they compare the grid-scale rainfall frequencies with the corresponding grid size and imply there are large biases in grid rainfall datasets.
Rainfall frequencies, while being less explored than long-term means, are one of the most important statistics describing the intermittency of rainfall, which are of great importance for hydrological and ecohydrological processes. Therefore, this study is potentially of great interest to the research community. However, some points need to be addressed before the publication.
The comparison of rainfall frequencies between most datasets is focused on a 2-year period (i.e., 2021 and 2022). It might be interesting to extend the periods to have decade-long mean rainfall frequencies. Or, it might be interesting to look at the inter-annual variability of rainfall frequencies in the reference dataset of CRU WET to check whether these differences are common in other historical times.
If I understand it correctly, the authors used monthly wet days in CRU WET to estimate rainfall frequencies but used daily precipitation from other datasets to estimate the rainfall frequencies. It might be useful to have an illustrative figure to present this difference.
The authors provide a brief discussion on the estimated rainfall frequencies in 272-275. One of the reasons mentioned for large rainfall frequency biases is that model calibration has often aimed to reduce biases in long-term mean rainfall rates. Please provide any suggestions on the improvement of rainfall frequency simulation in numerical models.
In regional application of hydrological models, these global datasets are often compared with site observations and the biases can be corrected. Please cite these bias correction methods and comment on whether these methods are solutions to the problems of overestimating rainfall frequency.
P151, remove “weather stations are” and add “is”
The threshold is defined as cumulated daily rainfall in Eq. (1). It should have the length unit (e.g., mm). In the text, it sometimes uses mm/day as the unit. Please have consistent units.
Author Response
See attached reply letter. Thank you!
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis study examines a critical issue in climate data - how accurately different global precipitation datasets capture rainfall frequency (how often it rains). The rainfall frequency is important because it affects plant growth, soil processes, and water resources, but has received less research attention compared to total rainfall amounts.
Major Strengths
The study presents several noteworthy contributions:
1. Methodology
Your three-tier comparative approach combining field observations, satellite data, and reanalysis products demonstrates exceptional rigor. The statistical framework effectively quantifies measurement discrepancies across different data collection methods.
2. Key Findings
The identification of systematic biases in GPCP (41.8%) and ERA5 (74.8%) represents a significant discovery. Your analysis convincingly demonstrates that these biases persist independently of grid resolution, challenging conventional assumptions about spatial scaling.
3. Practical Applications
The development of adjusted "wet day" thresholds offers immediate practical value for researchers working with these datasets. The improvements in accuracy achieved through this method are well-documented and compelling.
Areas for Enhancement
1. Temporal Resolution
Consider expanding the analysis to include sub-daily precipitation patterns. This addition would strengthen the temporal dimension of your findings and provide valuable insights for high-resolution climate modeling.
2. Ground Truth Data
While GHCN-Daily provides a solid foundation, incorporating additional regional monitoring networks would enhance the validation framework. Consider including data from local meteorological networks, particularly in regions with unique precipitation patterns.
3. Regional Analysis
The geographical variations in measurement accuracy, especially in Europe and Australia, warrant deeper investigation. We recommend:
- Developing detailed case studies examining local factors
- Analyzing the influence of topography and climate regimes
- Quantifying the impact of measurement network density
4. Threshold Optimization
Your threshold adjustment methodology shows promise, but could benefit from:
- Region-specific calibration guidelines
- Seasonal variation analysis
- Documentation of the optimization algorithm
5. Environmental Modeling Impact
To strengthen the practical implications of your findings, consider:
- Including specific case studies demonstrating impact on hydrological models
- Quantifying the propagation of frequency biases through modeling chains
- Providing guidelines for model adjustment based on dataset biases
6. Citation Framework
While your bibliography is comprehensive, consider:
· Including more recent studies (2020-2024)
· Expanding representation from diverse research groups
· Adding references from regional climate studies
7. Technical Documentation
A) The computational methodology would benefit from:
· Detailed algorithm descriptions
· Code availability statement
· Processing workflow documentation
· Recommendations for Revision
B) Near-term Additions
- Add sub-daily precipitation analysis
- Expand regional case studies
- Include model impact examples
- Provide detailed threshold optimization methods
C) Long-term Research Directions
- Develop region-specific adjustment guidelines
- Create comprehensive validation frameworks
- Investigate seasonal variation impacts
- Study topographical influence patterns
- Revise these specific sections:
- Page 4, paragraph 2: Simplify sentence structure
- Page 7, line 245: Clarify technical description
- Page 9, discussion section: Tighten phrasing
Comments on the Quality of English Language
The manuscript demonstrates strong academic writing overall, though some areas could be refined for clarity and precision.
Author Response
Please check the details in the attached reply letter. Thank you for your valuable suggestions.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe proposed paper is a study in which new approaches for estimating rainfall frequency are tested and their accuracy is compared with existing systems. The article is well written, abbreviations are appropriate and appropriate, and the writing style is very understandable
Author Response
Thank you for reviewing our manuscript. Please see attached reply letter for details.
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
Comments and Suggestions for AuthorsI would like to thank the researchers for taking the reviewers' opinions into consideration and for their responses.
