The Effects of Ice Habit Models on Passive Microwave Snowfall Rate Retrievals

Details

• Journal Title:
  Geophysical Research Letters
• Personal Author:
  Hong, Yulan ; Meng, Huan ; Fan, Yongzhen ; Dong, Jun ; Ren, Tong ; Yang, Ping
• NOAA Program & Office:
  NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; CISESS (Cooperative Institute for Satellite Earth System Studies)
• Description:
  This work examines the impact of ice habit models on snowfall rate (SFR) derived from spaceborne passive microwave observations. SFR retrieval is highly sensitive to ice habit assumptions. Comparisons of the SFRs based on Cloud Profiling Radar, ERA5, and National Oceanic and Atmospheric Administration Stage IV indicate that dense and sphere‐like particles tend to overestimate SFR, whereas most non‐spherical particles underestimate it. SFR biases differ by more than 200% between the most extreme cases. Although several ice habits perform well globally, an optimal choice of ice habit is environmentally dependent: A hollow bullet rosette works well in moist and warm conditions, whereas a solid ice sphere excels in cold and dry conditions. A machine learning model integrates multiple ice habits into the SFR algorithm by adjusting their contributions based on environmental conditions. This multi-habit approach improves statistical metrics by ~10% overall (by 40% in deep clouds) compared to the single ice habit method.
• Keywords:
  Hydrologic Cycle Microwaves Snow Hydrologic Cycle Ice Habit Models Microwave Observations Snowfall Rate Snowstorms
• Source:
  Geophysical Research Letters, 52, e2025GL116853
• DOI:
  https://doi.org/10.1029/2025GL116853
• Format:
  PDF
• Document Type:
  Journal Article
• Funding:
  Grant no. NA19NES4320002 ; Grant no. NA24NESX432C0001
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:945728c16cf4ae5331eee22a1bfe1bbb66223e52712a18248de70b55241b6b2b193f7e1f823e77295f8eae75a066233da3e8736fa2cf33fe6090b09e20ad0e62
• Download URL:
  https://repository.library.noaa.gov/view/noaa/73456/noaa_73456_DS1.pdf
• File Type:
  [PDF - 1.35 MB ]