The Development of a Snow-To-Liquid Ratio Technique for the National Blend of Models and for the National Weather Service's Graphical Forecast Editor (54)

Andrew Just, National Weather Service, Kansas City, MO

Chauncy Schultz, National Weather Service

Joshua Barnwell, National Weather Service

Bruce Veenhuis, National Weather Service

Michael Dutter, National Weather Service

 

Abstract:

The Development of a Snow-To-Liquid Ratio Technique for the National Blend of Models and for the National Weather Service's Graphical Forecast Editor

Andrew Just (NWS CRH, Kansas City, MO), Chauncy Schultz (NWS Bismarck, ND), Joshua Barnwell (NWS Nashville, TN), Bruce Veenhuis (NWS WPC, College Park, MD), Michael Dutter (NWS Wakefield, VA), Eugene Petrescu (NWS ARH, Anchorage, AK), Phil Shafer (NWS MDL Silver Spring, MD), Brian Brong (NWS Reno, NV), Matthew Foster (NWS OPG, Kansas City, MO), Chris Gibson (NWS Missoula, MT)

When forecasting snowfall amounts, one of the most important factors to consider is the density, or snow-to-liquid ratio (SLR), of the snow. For the same amount of precipitation, a wetter snow versus a drier snow can result in vastly different snowfall amounts and impacts. Historically, a simple ten to one ratio has been used as a rule of thumb to predict snowfall. However, more recently, numerous techniques have been developed to forecast SLR. Examples of these dynamic SLR techniques include the Cobb (Cobb and Waldstreicher 2005) and Roebber (Roebber 2007) methods and others based on thickness and temperature aloft. Each of these techniques has advantages and disadvantages. Additionally, some techniques have limitations depending on the available vertical level data.

In the National Weather Service's (NWS) Graphical Forecast Editor and in the National Blend of Models (NBM), a scientific approach was needed to calculate SLR. A group of NWS personnel volunteered for this task. Each method was examined for its scientific validity. Following in line with the consensus approach to operational forecasting, which verifies well on average (Baars and Mass 2005), the same concept was applied to SLR. The group recognizes that the consensus technique approach could have problems in extreme events, where a forecaster would need to examine and modify for those given scenarios. However, early results suggest that in general the consensus SLR approach helps produce more accurate snowfall forecasts that are also consistent spatially across NWS geographic domains.

The presentation will describe the various SLR techniques that were included into the consensus, and the challenges that go into the verification process.