3.9A Gap-Filling Radar Observations of a Snow Squall at San Luis Valley Regional Airport

Monday, 8 January 2018: 4:00 PM
Room 16AB (ACC) (Austin, Texas)
Andrew A. Rosenow, CIMMS/Univ. of Oklahoma and NOAA/NSSL, Norman, OK; and K. W. Howard and J. Meitín

The Intermountain West of the United States is home to a number of airports. Many of these airports are located in places deficient in radar coverage to adequately observe mesoscale weather phenomena that impact airport operations and safety. On January 24, 2017, a snow squall developed from convective snow showers, moving off of the San Juan Mountains and through the San Luis Valley in southern Colorado, a region with inadequate radar coverage. This snow squall impacted San Luis Valley Regional Airport, an airport with regular commercial service. At the airport, visibility decreased from 13 km to 1.2 km in five minutes, which was coincident with winds varying in direction from easterly to northwesterly and wind gusts up to 12 m s-1. This study will examine this event using data from the dual-polarization, X-band mobile radar known as NOAA X-Pol (NOXP) deployed in Alamosa, Colorado, as part of the Upper Rio Grande Water Resource Project.
The snow squall went almost entirely unobserved by the operational WSR-88D network due to terrain blockage and distance from the radars. This lack of observations combined with the low predictability of this type of event meant that aviation interests received essentially no information about the squall's presence and potential impacts until after the squall arrived at the airport, when airport's ASOS reported the sudden drop in visibility and changing winds.
This study compares available forecasts and operational observations around the airport to the data from NOXP to show the significant improvement in detectability from adding one radar. Then, the data from NOXP are integrated into the Multi-Radar Multi-Sensor (MRMS) radar mosaic to illustrate the existing capability of merging data from gap-filling radars with the WSR-88D network to produce a more complete observation of mesoscale phenomena, allowing these data to be used in aviation decision-making.
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