Backscatter Cross-section Dependence on Ice Crystal Habit in Radar Retrieval Algorithms During STORMVEX

Kevin Hammonds University of Utah
Gerald Mace University of Utah
Sergey Matrosov University of Colorado
Tim Garrett Utah State University
Gannet Hallar Storm Peak Laboratory - Desert Research Institute
Ian McCubbin Desert Research Institute

Category: Precipitation

It is widely known that the presence of ice particles in clouds as well as snowfall and consequent snow cover at the Earth’s surface play a critical role in the Earth’s overall radiative energy budget. Determining the contribution to these radiative effects based on the specific ice particle habit, however, is much less understood. While a large part of this lack in physical understanding is due to remote sensing assumptions and parameterizations, recent progress has been made in ascertaining ice particle habit from the use of scanning W-band ARM cloud radar (SWACR) data collected during the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX) held in Steamboat Springs, Colorado, during the winter of 2010/11. Originally shown in Matrosov et al. (2012), slant linear depolarization ratios (SLDRs) calculated from SWACR scanning periods can be used to deduce an ice particle habit when referenced in combination with backscatter relationships derived from T-Matrix scattering calculations for oblate spheroid ice particles of varying aspect ratio. Extending from this most recent work and presented here, upon choosing an ice particle habit and corresponding backscatter parameterization, a comparison is made between SWACR retrievals calculated during vertical mode using a generic backscatter parameterization and scanning mode when the SLDR is being used to choose a habit-dependent backscatter parameterization. Tentative results from this study have thus far shown that radar reflectivity and hence the microphysical processes perceived to be taking place are much more sensitive to this backscatter parameterization than was perhaps previously thought. It is also expected that by choosing a more representative ice particle habit based on the SLDR, we can reduce the optimal estimation uncertainty in snow microphysics retrieval schemes as well. This assumption will be tested with measurements collected at Storm Peak Lab and by the Wyoming King Air during the Colorado Airborne Multiphase Cloud Study (CAMPS) field campaign.

http://meteo04.chpc.utah.edu:8080/stormvex/

This poster will be displayed at ASR Science Team Meeting.

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