the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 May 2025
Assessment of Disdrometer Data Quality Control Methods for Precipitation Measurements Based on Wet-Bulb Temperature
Abstract. This study focuses on the reliability assessment of precipitation data calculated from drop size distribution (DSD) based on disdrometer data observations according to wet-bulb temperature (Tw). Three distinct quality control (QC) methods based on fall velocity were implemented and validated against measurements from tipping-buckets and weighing rain gauges collected from January 2020 to February 2024. The analysis indicated that all QC methods exhibited high reliability (correlation coefficient (CC) > 0.98) for rainfall conditions when Tw was above 5 °C, with a mean absolute percentage error (MAPE) of approximately 8.5 %. However, the precision of precipitation measurements exhibited a notable decline when Tw was below 2 °C, as indicated by a CC of less than 0.6 and MAPE exceeding 30 %. This reduction in accuracy can primarily be attributed to the outcomes of the QC methods, which rely on the falling velocity, given that raindrops and solid particles were observed within the specified Tw range. When considering the melting of snow particles at Tw ranging from 0 °C to 2 °C, the CC approached 0.9, suggesting enhanced measurement reliability. The findings of this study indicate that Tw is a more effective variable than air temperature (Tair) for differentiating the precipitation types. This conclusion arises from the observation that the fall velocity of hydrometeors does not reach the terminal velocity of raindrops, even within the Tair range of 1–5 °C, coupled with the broad distribution of fall velocities. The DSD shape demonstrated stability across multiple QC methods when Tw was equal to or greater than 2 °C. In contrast, considerable variations were observed at lower temperatures, where particles with diameters ranging from 1 to 2 mm exhibited irregular distribution patterns at temperatures below 1 °C. These results suggest that DSD parameters should be derived from disdrometer data obtained under conditions where Tw is above 2 °C to ensure the reliability of the findings. This study provides critical insights for improving precipitation measurement techniques and DSD analyses in regions with variable temperature conditions.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-954', Anonymous Referee #1, 01 Jun 2025
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AC1: 'Reply on RC1', Hyeon-Joon Kim, 12 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-954/egusphere-2025-954-AC1-supplement.pdf
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AC1: 'Reply on RC1', Hyeon-Joon Kim, 12 Jun 2025
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RC2: 'Comment on egusphere-2025-954', Anonymous Referee #2, 23 Sep 2025
The manuscript evaluates three data quality control methods for disdrometer measurements based on wet-bulb temperature. This work is valuable as it may promote the application of disdrometer observations across diverse types of precipitation. In current version, imprecise expressions are present throughout the manuscript, particularly in the descriptions of the figures, which hinders general readers from clearly understanding the study. There is still considerable room for improvement in the scientific expression. In addition, the rational for selecting the three quality control methods needs to be further justified, as their comparison does not reveal significant differences. Several specific comments are provided below for possible improvement.
1. The current Title may be refined to more clearly reflect the central focus of the manuscript.
2.The Introduction section occasionally presents results that should be placed in later sections, and lacks appropriate references.
For examples, in Lines 117-119: “the authors noted a tendency for PARSIVEL to overestimate the number of small droplets measuring between 0.2 and 0.4 mm and larger particles measuring 2.4 mm or more. Furthermore, the measured fall velocity of larger droplets was lower than the actual terminal velocity”. Any appropriate reference?
In Lines 129-131: “Given the diverse shapes and fall speeds of snow particles, the mixing of raindrops and snow during precipitation events may lead to an underestimation of errors when applying conventional disdrometer QC methods.” Any references?
Similar issues exist elsewhere in the manuscript. For example, in Lines 181: “numerous studies”, any citations?
3. The manuscript does not clearly describe the conventional QC methods. Please clarify what these conventional approaches are and explicitly discuss how they differ from the three QC methods selected in this study.
4. Section 3.1: The manuscript should report the proportion of disdrometer data removed by each QC method to allow for a clearer comparison of their performance. Furthermore, please clarify whether data associated with solid meteorological particles (e.g., snow, as indicated in Lines 204–205) may be removed by these methods.
5. In Equation (5), is V(D) used to calculate Videal, i.e., terminal velocity? Please clarify.
6. Is the estimation of Tw from Tair and RH in Equation (15) applicable when Tair < 0? Please clarify.
7. Figures 5-6: Is Rainfall[Gauge] the same as Rainfall[TG]? It would be better to keep consistent terminology.
It’s not easy to find the effect of QC in Figures 5-6. Please clarify the explicit differences between Methods 1 and 2 (Fig. 5b and 5c), or even Method 3 (Fig. 5d), and indicate whether these differences are significant? Including the number of datapoints in each panel would improve clarity and aid interpretation.
In Line 256, the term “overestimate” is used—please clarify whether this applies to the comparison between Figure 6a and 6d as well. Significant?
8. Many expressions throughout the manuscript lack rigor. For examples, in Lines 279-280: “However, as the temperature exceeded 0 ℃, the fall velocity for CH 4 to 18 increased under Tw conditions, 280 while the fall velocity for CH 19 to 23 increased under Tair conditions? (Fig. 7(a-b))”. Can find this result from 7a and 7b? It looks comparable between Figure 7a and 7b.
In Lines 280-282: “Notably, when the temperature rose above 1 ℃, there was a notable increase in fall velocity for CH 4 or larger? under Tw conditions, the distribution approached the terminal velocity of raindrops for CH 4 to 13?”
The statement “Under Tair conditions, the fall velocity increased when temperatures were below 1℃” is unclear. Please clarify how this statement can be determined from the presented data or figure?
Citation: https://doi.org/10.5194/egusphere-2025-954-RC2 -
AC2: 'Reply on RC2', Hyeon-Joon Kim, 11 Oct 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-954/egusphere-2025-954-AC2-supplement.pdf
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AC2: 'Reply on RC2', Hyeon-Joon Kim, 11 Oct 2025
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-954', Anonymous Referee #1, 01 Jun 2025
This paper represents a significant contribution to the field by improving the accuracy and reliability of precipitation data through the evaluation of quality control methods for precipitation measurement instruments, with a particular emphasis on the impact of wet-bulb temperature. The research is of considerable value. But revisions are required before publication
Major comments:
- Line 98-101: In this part of the discussion, it is essential to include relevant references. Additionally, it is suggested that the authors polish the language of the entire text to improve its quality.
- Line 238-240：Given that the QC methods for the disdrometer were specifically designed to address rainfall, the variable Tw was employed to differentiate between rainfall and snowfall, thereby facilitating the verification of rainfall timing. I would like to know what exactly is meant by "rainfall timing." Does it refer to the start time of the rainfall or its duration? How is it verified? This issue is not mentioned in the subsequent discussion.
- Figure 9 may cause some confusion due to the presence of two dashed lines in the same color. It is recommended to make appropriate modifications to enhance the clarity and readability of the figure.
- It is recommended to include a discussion on the limitations of the methods used in this paper. When discussing the effectiveness of the QC method at different wet bulb temperatures, should it also be influenced and constrained by factors such as the measurement location?
Minor comments:
- The units of the vertical axis in Figures 13 and 14 are inconsistent with the units described in the text. The author should carefully check this.
Citation: https://doi.org/10.5194/egusphere-2025-954-RC1 -
AC1: 'Reply on RC1', Hyeon-Joon Kim, 12 Jun 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-954/egusphere-2025-954-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2025-954', Anonymous Referee #2, 23 Sep 2025
The manuscript evaluates three data quality control methods for disdrometer measurements based on wet-bulb temperature. This work is valuable as it may promote the application of disdrometer observations across diverse types of precipitation. In current version, imprecise expressions are present throughout the manuscript, particularly in the descriptions of the figures, which hinders general readers from clearly understanding the study. There is still considerable room for improvement in the scientific expression. In addition, the rational for selecting the three quality control methods needs to be further justified, as their comparison does not reveal significant differences. Several specific comments are provided below for possible improvement.
1. The current Title may be refined to more clearly reflect the central focus of the manuscript.
2.The Introduction section occasionally presents results that should be placed in later sections, and lacks appropriate references.
For examples, in Lines 117-119: “the authors noted a tendency for PARSIVEL to overestimate the number of small droplets measuring between 0.2 and 0.4 mm and larger particles measuring 2.4 mm or more. Furthermore, the measured fall velocity of larger droplets was lower than the actual terminal velocity”. Any appropriate reference?
In Lines 129-131: “Given the diverse shapes and fall speeds of snow particles, the mixing of raindrops and snow during precipitation events may lead to an underestimation of errors when applying conventional disdrometer QC methods.” Any references?
Similar issues exist elsewhere in the manuscript. For example, in Lines 181: “numerous studies”, any citations?
3. The manuscript does not clearly describe the conventional QC methods. Please clarify what these conventional approaches are and explicitly discuss how they differ from the three QC methods selected in this study.
4. Section 3.1: The manuscript should report the proportion of disdrometer data removed by each QC method to allow for a clearer comparison of their performance. Furthermore, please clarify whether data associated with solid meteorological particles (e.g., snow, as indicated in Lines 204–205) may be removed by these methods.
5. In Equation (5), is V(D) used to calculate Videal, i.e., terminal velocity? Please clarify.
6. Is the estimation of Tw from Tair and RH in Equation (15) applicable when Tair < 0? Please clarify.
7. Figures 5-6: Is Rainfall[Gauge] the same as Rainfall[TG]? It would be better to keep consistent terminology.
It’s not easy to find the effect of QC in Figures 5-6. Please clarify the explicit differences between Methods 1 and 2 (Fig. 5b and 5c), or even Method 3 (Fig. 5d), and indicate whether these differences are significant? Including the number of datapoints in each panel would improve clarity and aid interpretation.
In Line 256, the term “overestimate” is used—please clarify whether this applies to the comparison between Figure 6a and 6d as well. Significant?
8. Many expressions throughout the manuscript lack rigor. For examples, in Lines 279-280: “However, as the temperature exceeded 0 ℃, the fall velocity for CH 4 to 18 increased under Tw conditions, 280 while the fall velocity for CH 19 to 23 increased under Tair conditions? (Fig. 7(a-b))”. Can find this result from 7a and 7b? It looks comparable between Figure 7a and 7b.
In Lines 280-282: “Notably, when the temperature rose above 1 ℃, there was a notable increase in fall velocity for CH 4 or larger? under Tw conditions, the distribution approached the terminal velocity of raindrops for CH 4 to 13?”
The statement “Under Tair conditions, the fall velocity increased when temperatures were below 1℃” is unclear. Please clarify how this statement can be determined from the presented data or figure?
Citation: https://doi.org/10.5194/egusphere-2025-954-RC2 -
AC2: 'Reply on RC2', Hyeon-Joon Kim, 11 Oct 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-954/egusphere-2025-954-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Hyeon-Joon Kim, 11 Oct 2025
Peer review completion
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Hyeon-Joon Kim
Sung-Ho Suh
Jongyun Byun
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4544 KB) - Metadata XML
This paper represents a significant contribution to the field by improving the accuracy and reliability of precipitation data through the evaluation of quality control methods for precipitation measurement instruments, with a particular emphasis on the impact of wet-bulb temperature. The research is of considerable value. But revisions are required before publication
Major comments:
Minor comments: