An uncertainty model for snowfall rate retrievals from the GPM DPR

Abstract:

In this presentation, a simple version of the operational GPM DPR retrieval algorithm will be used to explore uncertainties in snowfall rate retrievals using single-frequency and dual-frequency retrieval methods. This model will be used to quantify uncertainties in retrieval of the profile of snowfall rate within the column as well as at the surface below clutter ranges.

The DPR uncertainty model will use data from GPM-GV field campaigns including C3VP (Canadian CloudSat/CALIPSO Validation Programme, conducted in 2007 near Barrie, Ontario, Canada) and GCPEx (Global Precipitation Measurement mission Cold Season Precipitation Experiment, conducted in 2012 near Barrie, Ontario, Canada) to gather a priori microphysical assumptions from surface disdrometer and aircraft data. These assumptions will be used to explore the impact of varying a priori assumptions on measured dual frequency radar profiles observed in snowfall from the ground, aircraft, and spaceborne radars to ascertain sensitivities and key parameters which cause the snowfall rate retrievals to vary in the profile and at the surface. The variability in snowfall parameters the near surface bins within spaceborne radar measurements will also be examined, and suggestions for the treatment of these bins in algorithms will be addressed.