Supercooled cloud and precipitation water droplets cause in-flight icing of aircraft lifting and control surfaces and
thus constitute a safety hazard to aviation. There is a growing interest in the development of remote sensors to warn
of the danger zones. A known characteristic of these zones is that they are spatially and temporally variable, hence
the need for real time detection. We have tested in two coordinated field experiments the DREV multiple-fieldof-
view (MFOV) lidar as a means of characterizing icing conditions. The required information is the temperature,
the phase, the liquid water content arid the droplet size of clouds and precipitation. The last three quantities are
obtainable, within limits, with the MFOV lidar. The paper briefly describes the MFOV measurement and solution
methods, and reports on sample retrieval results of liquid water content and droplet effective diameter. These data
are directly applicable to the remote characterization of in-flight icing conditions. The accuracy of these lidar solutions
is currently estimated at 30-40%.
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