the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation and Correction of Precipitation Types Measured by a PARSIVEL2 Disdrometer in a Tropical Glacier Environment
Abstract. Precipitation characteristics in high-mountain regions with complex terrain remain poorly understood because observational networks are sparse and robust instrumentation is rarely deployed. This study evaluates precipitation type measurements from a PARSIVEL2 optical disdrometer installed at 4709 m a.s.l., approximately 2.5 km from the Huaytapallana tropical glacier in the Peruvian Andes. The instrument measures the equivalent diameter and fall velocity from particle shadows crossing its laser beam; it then computes precipitation intensity (mm h−1) and classifies hydrometeor types at 1 min resolution. Based on one year of observations, we identified seven precipitation types: rain, drizzle, drizzle with rain, snow, hail, soft hail, and mixed rain drizzle with snow. The original PARSIVEL2 classification indicated that drizzle with rain was the most frequent type (30.57 %), followed by snow (26.15 %). We identified 70 precipitation events (duration ≥10 min) and compared the corresponding accumulations against a Pluvio2 weighing rain gauge (threshold ≥0.25 mm). The PARSIVEL2 systematically overestimated precipitation, especially during mixed-phase events (98.5 %, 3.92 mm bias) and solid precipitation events (84.1 %, 7.09 mm bias), whereas liquid precipitation events showed minimal bias (15.7 %, 0 mm bias). The largest discrepancies occurred during extreme events (>10.6 mm and >1 h) dominated by snow, soft hail, and hail, which we attribute to misclassification of coexisting particle types and systematic deviation of the instrument’s internally calculated density values. We developed a correction methodology that combines velocity diameter reclassification criteria based on established empirical relationships with site specific density optimization. For solid precipitation, RMSE decreased from 13.05 to 4.4 mm; for mixed precipitation, the scope value improved from 1.936 to 1.004. The corrected classification identified wet snow (29.3 %) and graupel (15 %) as dominant precipitation types, whereas pure snow represented only 3.7 %. These results demonstrate the need for post processing corrections of disdrometer measurements in tropical glacier environments and provide an improved characterization of mixed-phase precipitation processes relevant to glacier mass balance assessments.
- Preprint
(15178 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-2705', Anonymous Referee #1, 30 Jul 2026
-
RC2: 'Comment on egusphere-2026-2705', Anonymous Referee #2, 30 Sep 2026
* general comments
Optical disdrometers, especially commercial products are often used without examining the internal data processing. It is important to evaluate the output of optical disdrometer, that is, the main topic of this paper. The referee think that this problem is commonly recognized in cloud physics community currently and publishing this paper is expected to be timely. The title of this paper is attractive to the reviewer.
Characteristics of measurement of PARSIVEL2 is well considered. This paper carefully presents measurement error of PARSIVEL2 and a correction method including the limitation of the method. Especially, Figure 3 is impressive to the reviewer.
The result of analysis and validation are also carefully described. Adequate description of possible errors are also shown. This paper can be recommended to the researchers and observers who use internally processed variables of commercial optical disdrometers.
There are many sentences concatenating phrases using "," or ";". Some of this type of sentences were not clear to the reviewer. Dividing those sentences may improve the clarity of the manuscript. Typos were sometimes found. The reviewer checked technical errors of the manuscript at first, though skipped later, because they were too many. Checking technical errors of the whole manuscript is recommended.
There are mismatches between Figures and main text. Sometimes, referred figure number in the main text was wrong. Some values in the main text and in the corresponding figure were different. Axis labels of figure panels should be checked, for example, both "m s-1" and "m/s" are seen and "1/m^3 mm" is ambiguous.
Overall technical (format) check of citation in the main text and reference list is necessary.
* specific commentsAbstract:
Line 11, Line 12: What is the meaning of percentage in the parentheses.
Lines 18-19 "These results demonstrate the need for post processing corrections of disdrometer measurements": I agree this point from my own experience.
1 IntroductionLine 23: Referred papers are researches on the tropical Andes regions. "in the tropical Andes regions" would be more appropriate than "in tropical regions". Otherwise, papers on the other tropical high-altitude regions should be added.
Arrangement of chapters should be written in the last part of Introduction. It will help the readers, especially, to know that Sections 4.1 and 4.2 describe on PARSIVEL2 built-in hydrometeor classification, and that Sections 4.3 and 4.4 describe the correction method developed in this paper.
2 Site and data
2.1 Area of studyLine 63: I could not catch whether the "transition" is "temporal transition" or "spatial transition".
Line 79: Was the same maximum value of 15 recorded in several months? Or, the measured values were truncated at 15?
Line 85: Was the same maximum value of 15 recorded in several months? Or, the measured values were truncated at 15?
Caption of Figure 2: The meaning of error bars in (a) and (b) should be described.
Figure 2 and corresponding part of the main text are not well related.
2.2 Instruments and data
2.2.1 Weighing Precipitation GaugeLine 96: Shown as "Fig. 1d" is not the Pluvio2. I guess that the facility next to PARSIVEL2 might be the Pluvio2. Figure 2 needs correction.
Line 102 "added": "used to calculate" ? I guess that the difference of weight would be converted to the increase of precipitation.
Line 109: The correction of wind-induce catch loss is described in Section 2.2.4. Adding "(Section 2.2.4)" would be kind to the readers.
On the Pluvio observation: Was the countermeasure to the evaporation loss (for example, an oil layer on the water in the collecting container) applied? If so, it should be described.
On the Pluvio observation: How was the countermeasure to the snow capping on the facility?
2.2.4 Quality ControlCaption of Table 1: The sentence below the table needs improvement and should be included in the caption. Is each line of the table indicates the result of filtering for 1-month of data?
3 Methods
3.2 Spectrum of precipitationLine 156: Is it possible to add the reference on the description "(30 mm - Di/2)"? This definition is seen in some literature without reference.
3.3 Precipitation estimates correction
3.3.2 Hydrometeor types segmentationTable 2: Both "Hailstones" and "Hail" would be a single category "Hail".
Line 208 "most large frozen particles were reclassified as soft hail rather than hard hail in Fig. 11b.": Is this description corresponds to the upper three lines in Fig. 4f?
4 Results
4.3 Application and Results of the Correction MethodCaption of Figure 12: It is necessary to mention that this figure is on the values by the PARSIVEL2 internal algorithm.
* technical correctionsUppercase/lowercase of the section title words should be checked.
1 Introduction
Line 34: The reference should be "(Löffler-Mang and Joss, 1999)". Reference list should also be corrected.
2 Site and data
2.1 Area of studyLine 75, Line 76 "Fig. 2d": Should be "(Fig. 2d)"
Line 85: A value of "0.30 m s-1" is not found in Figure 2b.
2.2 Instruments and data
2.2.1 Weighing Precipitation GaugeLine 95 "HydroMet, 2019": See comment on Line 690.
Line 107: Typically, this author is referred simply as "Goodison et al. (1998)".
Line 109: The Referring description should be checked.
Lines 124-125: A sentence "The instruments .." need some commas.
3 Methods
3.1 Type Precipitation Identification
→ Precipitation type identification3.2 Spectrum of precipitation
Line 156: "(raw_data)" appear only once here. It is better to delete it.
3.3 Precipitation estimates correction
3.3.2 Hydrometeor types segmentationLine 191 "Footec and Toit (1969)": Usually, this literature is referred to as "Foote and du Toit (1969)"
Table 2 "C and J": May be "Knight and Heymsfield".
Line 199 - Line 214: "Fig. 11" may be "Fig. 4".
Figure 4b: Shading of rain area is very light and cannot be distinguished from the white background.
Figure 4b: What is "*C" of the equation of v.
Line 203 "tha": "the"
4 Results
4.1 Precipitation characterization according to PARSIVEL2Line 270: In Figure 5, the amount is "30.6%".
Line 275 "2.4 m s-1": -> "3.4 m s-1"
4.2 Performance evaluation and error quantification
4.2.1 Assessment of the PARSIVEL2Caption of Figure. 9 "(black asterisk)", "(black dot)": I guess "black" is not necessary, because the colors are attributed to the type of hydrometeor.
5 Discussion
5.1 Hydrometeor characterization and physical implicationsLine 544 " .. intensity.A finding .. ": " .. intensity; a finding .. " ?
Code and data availability.Lines 614,615: "Perez (2026b)": -> "(Perez, 2026b)."
ReferencesLine 650: The author name is not correctly written.
Line 690 "HydroMet, O.": "OTT HydroMet" is the name of a company, not surname and family name. So, "HydroMet, O." is strange.
Line 741: Ro et al. published in 2023, however, it is included in the journal volume of "Vol. 120 (2024)". I guess that this paper should be referred to as Ro et al. (2024).
Citation: https://doi.org/10.5194/egusphere-2026-2705-RC2
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 240 | 131 | 37 | 408 | 40 | 34 |
- HTML: 240
- PDF: 131
- XML: 37
- Total: 408
- BibTeX: 40
- EndNote: 34
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Please see attached PDF.