14.4
Ice Fog and Light Snow Visibility in Cold Climates: Application to Aviation and Forecasting

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Thursday, 8 January 2015: 2:15 PM
129A (Phoenix Convention Center - West and North Buildings)
Ismail Gultepe, EC, Toronto, ON, Canada; and R. M. Rabin, T. Kuhn, A. J. Heymsfield, M. J. Pavolonis, and J. Gurka

The goal of this work is to obtain ice fog and light snow visibility parameterizations for better prediction of winter weather low visibility conditions in the cold climates. Observations collected during two Arctic field projects called FRAM (Fog Remote Sensing and Modeling) and SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) that took place in the Arctic during winter of 2010-2011 and 2013-2014, respectively, were used in the analysis. Both projects had unique ground based instruments to measure extinction, visibility, ice particle spectra, aerosol spectra, light precipitation, turbulence, and infrared and shortwave radiative fluxes. In addition to surface in-situ observations, remote sensing instruments such as Lidar, Ceilometer, PMWR (Profiling Microwave Radiometer), and MRR (Microwave Rain Radar) were also used for data collection. The main microphysical sensors used for ice and aerosol particle spectra in the project were the EC GCIP (Environment Canada Ground Cloud Imaging Probe), LTU ICIP (Lulea Technological University Ice Crystal Imaging Probe), NCAR VIPS (Video Ice Particle Sampler, <500 micron), and TSI APC (Aerosol Particle Counter) and MOPC 212-2 (Met One Inc Optical Particle Counter) with sizes>0.3 micron. The spectra from these sensors cover 0.3-1000 micron size range. A laser precipitation measurement (LPM) sensor was also used to collect the observations from 100 micron up to cm size range. In this work, the results related to extinction (as well as visibility) and ice crystal spectra with sizes less than about 500 micron (usually not measured by conventional weighing gauges or optical sensors, called light snow here) for aviation applications and weather prediction will be discussed and future challenges will be emphasized.