P8.15 A Method of Estimating Snow Accumulation on ASOS using 1-Minute Observations

Wednesday, 6 October 2004
Charles G. Wade, NCAR, Boulder, CO

Accumulating snow causes delays in airport operations and affects the ability of people to get to or from the airport. At many airports there are no recorded observations of snowfall, while at others the observation is made only periodically. Better and more frequent observations of the amount and rate of snowfall can be useful in improving airport operations, and in helping forecasters provide better short term forecasts.

This paper will describe a new method of estimating the rate of snowfall and the total accumulation of snow using the 1-minute data that is available from ASOS stations.

Each ASOS has a Present Weather sensor used to determine precipitation type (rain or snow) and intensity (light, moderate, heavy). The Present Weather sensor on ASOS is an optical device called LEDWI (Light-Emitting Diode Weather Identifier). The raw 1-minute “engineering” data from LEDWI are recorded on each ASOS station and are retained for a period of 12 hours. As precipitation falls through the LEDWI’s infrared beam it generates signals in 3 channels: Low, High, and Particle. When it is raining the value in the High channel is proportional to rain rate. When it is snowing the value in the Low channel is proportional to the rate of snowfall accumulation. Integrating the snowfall rate over time gives an estimate of the potential snow accumulation that has occurred. The technique appears to work equally well for wet or dry snow, and fails only when the surface temperature is sufficiently warm to melt the snow. In this event a modification could be made to account for a warm surface. The LEDWI rates and accumulations are also independent of wind speed, although at speeds greater than 15 knots the Low channel values need to be modified slightly due to a “tuning fork” vibration that begins to occur. The rates and accumulations derived from LEDWI are also independent of settling or compacting. Thus, the best time to compare the LEDWI estimate of depth with independent observations is during the snowfall, or very shortly after the snow has stopped.

This paper will describe the LEDWI sensor and show how the Low channel data can be used to estimate snowfall rates and accumulation. Comparisons between the LEDWI estimate and human observations will be presented.

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