294 A Climatology of Snow to Liquid Ratios in Southeast Alaska

Monday, 7 January 2019
Hall 4 (Phoenix Convention Center - West and North Buildings)
David E. Levin, NOAA/NWS, Juneau, AK

Snow to liquid ratios (SLR) continue to be a large source of error for forecasters in the prediction of snow amounts during the winter months. Current methods of predicting SLR in Southeast Alaska range from an empirical method based solely on surface temperatures, to using model-derived SLR. Both of these methods are limited in that numerical models parameterize many of the complex microphysical factors that drive SLR, while surface temperatures are likely insufficient as a predictor given that snow formation originates well above the surface. A climatology was developed using data from 32 COOP stations around Southeast Alaska for the period of 1950 to the present. This yielded a robust data set of 17,447 unique snowfall observations. SLR was calculated for each event following the methodology of Baxter et al. (2004) and their SLR climatology for the contiguous United States. The mean SLR for the Juneau County Warning Area was found to be much higher than the empirical method based on surface temperatures. Considerable variability was noted in both mean and median SLR values between sites located along the immediate Gulf coast and those along the more interior channels. The mean SLR for Southeast Alaska was also higher in general than those found by Baxter et al. in locations along the Pacific Northwest coast. It is hypothesized that the frequency of events where warmer marine air over-runs cold, dry arctic air from northwest Canada modulates these variations in snow to liquid ratio. Several individual cases were examined to determine the low level thermal profiles and other meteorological parameters that may have led to the observed snow ratios in order to further help give guidance to operational forecasters. Finally, the results were then analyzed on a grid using the National Weather Service Graphical Forecast Editor (GFE) and a smart tool was developed which would allow operational forecasters to use this climatology as a starting point when making a prediction of snow to liquid ratio.
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