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Comparative Analysis of Microphysical Characteristics between Wet and Dry Snow in Northeast China Based on Disdrometer Observations.

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Title: Comparative Analysis of Microphysical Characteristics between Wet and Dry Snow in Northeast China Based on Disdrometer Observations.
Authors: Gong, Ying1 (AUTHOR), Yang, Sen1 (AUTHOR) yangsen@iaesy.cn, Li, Deqin1 (AUTHOR), Ma, Zhanshan2 (AUTHOR), Cheng, Xiaoping3 (AUTHOR), Pan, Xiao1 (AUTHOR), Wang, Shu1 (AUTHOR)
Source: Journal of Applied Meteorology & Climatology. Jan2026, Vol. 65 Issue 1, p109-132. 24p.
Subjects: Snowstorms, Meteorological precipitation measurement, Snowmelt, Weather, Snow chemistry, Snowflakes, Snow cover
Abstract: Northeast China experiences significant snowstorms during winter. However, the microphysics of snowfall in this area remains poorly understood. This study aims to address this gap by comparing the microphysical characteristics and related meteorological conditions of wet and dry snow in Northeast China. The results indicate that the number concentration (NC) of wet snow is approximately twice that of dry snow, contributing to the liquid-equivalent snow rate (SR) being approximately twice as high in wet snow compared to dry snow. The formation and dissipation of wet snow are primarily attributed to the sharp increase and decrease in the NC of small-size particles, respectively, while for typical dry snow, they are largely ascribed to the broadening and shrinking of the snow particle spectra along the diameter dimension. Although the intensification of snow processes usually involves both accelerated generation and growth of snow particles, wet snow is characterized by the faster generation of denser but smaller particles, while dry snowfall corresponds to faster growth of sparser but larger particles. The linear-fit line of the μ–Λ (two of the three parameters of the gamma model) relationship for wet snow mirrors that of dry snow, and both plot among the previously established linear-fit lines for rainfall, albeit with smaller μ and Λ values. The warmer, more humid, faster rising meteorological environments with higher average cloud-top heights (CTHs) during wet snow processes contribute to microphysical differences between wet and dry snow. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 191287143
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comparative Analysis of Microphysical Characteristics between Wet and Dry Snow in Northeast China Based on Disdrometer Observations.
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Gong%2C+Ying%22">Gong, Ying</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Sen%22">Yang, Sen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yangsen@iaesy.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Deqin%22">Li, Deqin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Zhanshan%22">Ma, Zhanshan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cheng%2C+Xiaoping%22">Cheng, Xiaoping</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Xiao%22">Pan, Xiao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Shu%22">Wang, Shu</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Meteorology+%26+Climatology%22">Journal of Applied Meteorology & Climatology</searchLink>. Jan2026, Vol. 65 Issue 1, p109-132. 24p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Snowstorms%22">Snowstorms</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+precipitation+measurement%22">Meteorological precipitation measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Snowmelt%22">Snowmelt</searchLink><br /><searchLink fieldCode="DE" term="%22Weather%22">Weather</searchLink><br /><searchLink fieldCode="DE" term="%22Snow+chemistry%22">Snow chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Snowflakes%22">Snowflakes</searchLink><br /><searchLink fieldCode="DE" term="%22Snow+cover%22">Snow cover</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Northeast China experiences significant snowstorms during winter. However, the microphysics of snowfall in this area remains poorly understood. This study aims to address this gap by comparing the microphysical characteristics and related meteorological conditions of wet and dry snow in Northeast China. The results indicate that the number concentration (NC) of wet snow is approximately twice that of dry snow, contributing to the liquid-equivalent snow rate (SR) being approximately twice as high in wet snow compared to dry snow. The formation and dissipation of wet snow are primarily attributed to the sharp increase and decrease in the NC of small-size particles, respectively, while for typical dry snow, they are largely ascribed to the broadening and shrinking of the snow particle spectra along the diameter dimension. Although the intensification of snow processes usually involves both accelerated generation and growth of snow particles, wet snow is characterized by the faster generation of denser but smaller particles, while dry snowfall corresponds to faster growth of sparser but larger particles. The linear-fit line of the μ–Λ (two of the three parameters of the gamma model) relationship for wet snow mirrors that of dry snow, and both plot among the previously established linear-fit lines for rainfall, albeit with smaller μ and Λ values. The warmer, more humid, faster rising meteorological environments with higher average cloud-top heights (CTHs) during wet snow processes contribute to microphysical differences between wet and dry snow. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1175/JAMC-D-25-0017.1
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 24
        StartPage: 109
    Subjects:
      – SubjectFull: Snowstorms
        Type: general
      – SubjectFull: Meteorological precipitation measurement
        Type: general
      – SubjectFull: Snowmelt
        Type: general
      – SubjectFull: Weather
        Type: general
      – SubjectFull: Snow chemistry
        Type: general
      – SubjectFull: Snowflakes
        Type: general
      – SubjectFull: Snow cover
        Type: general
    Titles:
      – TitleFull: Comparative Analysis of Microphysical Characteristics between Wet and Dry Snow in Northeast China Based on Disdrometer Observations.
        Type: main
  BibRelationships:
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      – PersonEntity:
          Name:
            NameFull: Gong, Ying
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          Name:
            NameFull: Yang, Sen
      – PersonEntity:
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            NameFull: Li, Deqin
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            NameFull: Ma, Zhanshan
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            NameFull: Cheng, Xiaoping
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            NameFull: Pan, Xiao
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            NameFull: Wang, Shu
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          Dates:
            – D: 01
              M: 01
              Text: Jan2026
              Type: published
              Y: 2026
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              Value: 15588424
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              Value: 65
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              Value: 1
          Titles:
            – TitleFull: Journal of Applied Meteorology & Climatology
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