Evaluation of the microphysical assumptions within GPM-DPR using ground-based observations of rain and snow

Randy J. Chase, Stephen W. Nesbitt, Greg M. McFarquhar

Research output: Contribution to journalArticlepeer-review


The Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) provides an opportunity to investigate hydrometeor properties. Here, an evaluation of the microphysical framework used within the GPM-DPR retrieval was undertaken using ground-based disdrometer measurements in both rain and snow with an emphasis on the evaluation of snowfall retrieval. Disdrometer measurements of rain show support for the two separate prescribed relations within the GPM-DPR algorithmbetween the precipitation rate (R) and themassweightedmean diameter (Dm) with a mean absolute percent error (MAPE) on R of 29% and 47% and a mean bias percentage (MBP) of-6% and-20% for the stratiform and convective relation, respectively. Ground-based disdrometer measurements of snow show higher MAPE and MBP values in the retrieval of R, at 77% and 52%, respectively, compared to the stratiform rain relation. An investigation using the disdrometer-measured fall velocity andmass in the calculation of R and Dm illustrates that the variability found in hydrometeor mass causes a poor correlation between R and Dm in snowfall. The results presented here suggest that R-Dm retrieval is likely not optimal in snowfall, and other retrieval techniques for R should be explored.

Original languageEnglish (US)
Article number619
Issue number6
StatePublished - Jun 1 2020


  • Radar retrievals
  • Rainfall rate
  • Snowfall rate

ASJC Scopus subject areas

  • Environmental Science (miscellaneous)


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