Comparison of snowfall estimates from the NASA CloudSat Cloud Profiling Radar and NOAA/NSSL Multi-Radar Multi-Sensor System

Sheng Chen, Yang Hong, Mark Kulie, Ali Behrangi, Phillip M. Stepanian, Qing Cao, Yalei You, Jian Zhang, Junjun Hu, Xinhua Zhang

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


The latest global snowfall product derived from the CloudSat Cloud Profiling Radar (2C-SNOW-PROFILE) is compared with NOAA/National Severe Storms Laboratory's Multi-Radar Multi-Sensor (MRMS/Q3) system precipitation products from 2009 through 2010. The results show that: (1) Compared to Q3, CloudSat tends to observe more extremely light snowfall events (<0.2 mm/h) and snowfall rate (SR) between 0.6 to 1 mm/h, and detects less snowfall events with SR between 0.2–0.5 mm/h. (2) CloudSat identifies 69.40% of snowfall events detected by Q3 as certain snow and 10% as certain mixed. When possible snow, possible mixed, and certain mixed precipitation categories are assumed to be snowfall events, CloudSat has a high snowfall POD (86.10%). (3) CloudSat shows less certain snow precipitation than Q3 by 26.13% with a low correlation coefficient (0.41) with Q3 and a high RMSE (0.6 mm/h). (4) With Q3 as reference, CloudSat underestimates (overestimates) certain snowfall when the bin height of detected snowfall events are below (above) 3 km, and generally overestimates light snowfall (<1 mm/h) by 7.53%, and underestimates moderate snowfall (1–2.5 mm/h) by 42.33% and heavy snowfall (⩾2.5 mm/h) by 68.73%. (5) The bin heights of most (99.41%) CloudSat surface snowfall events are >1 km high above the surface, whereas 76.41% of corresponding Q3 observations are low below 1 km to the near ground surface. This analysis will provide helpful reference for CloudSat snowfall estimation algorithm developers and the Global Precipitation Measurement (GPM) snowfall product developers to understand and quantify the strengths and weaknesses of remote sensing techniques and precipitation estimation products.

Original languageEnglish (US)
Pages (from-to)862-872
Number of pages11
JournalJournal of Hydrology
StatePublished - Oct 1 2016
Externally publishedYes


  • CloudSat
  • Radar
  • Snowfall

ASJC Scopus subject areas

  • Water Science and Technology


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