Correlations between Analyses and Forecasts of Banded Heavy Snow Ingredients and Observed Snowfall

Abstract

North American Mesoscale (NAM) model forecasts of the occurrence, magnitude, depth, and persistence of ingredients previously shown to be useful in the diagnosis of banded and/or heavy snowfall potential are examined for a broad range of 25 snow events, with event total snowfall ranging from 10 cm (4 in.) to over 75 cm (30 in.). The ingredients examined are frontogenetical forcing, weak moist symmetric stability, saturation, and microphysical characteristics favorable for the production of dendritic snow crystals. It is shown that these ingredients, previously identified as being critical indicators for heavy and/or banded snowfall in major storms, are often found in smaller snowfall events. It is also shown that the magnitude, depth, and persistence of these ingredients, or combinations of these ingredients, appear to be good predictors of event total snowfall potential. In addition, a relationship is demonstrated between temporal trends associated with one of the ingredients (saturated, geostrophic equivalent potential vorticity) and event total snowfall.Correlations between forecast values of these ingredients and observed snowfall are shown to decrease substantially as forecast lead time increases beyond 12 h. It is hypothesized that model forecast positioning and timing errors are primarily responsible for the lower correlations associated with longer-lead forecasts. This finding implies that the best forecasts beyond 12 h may be produced by examining the diagnostics of heavy snow ingredients from a single, high-resolution model to determine snowfall potential, then using ensemble forecasting approaches to determine the most probable location and timing of any heavy snow.

Using the 21 June 2008 California Lightning Outbreak to Improve Dry Lightning Forecast Procedures

“…11. Frontogenesis can be seen at 0600 UTC 21 August off the coast of northwest California, with weak F n vector convergence over the coast ranges of northern California and western Oregon and immediately offshore corresponding to upward vertical motions associated with frontogenesis (Evans and Jurewicz 2009). A similar band of low-level frontogenesis can also be seen associated with the Washoe zephyr (Clements et al 2006) over western Nevada.…”

Comparison of Ensemble Kalman Filter–Based Forecasts to Traditional Ensemble and Deterministic Forecasts for a Case Study of Banded Snow

“…Despite having a more convective appearance, the accumulated precipitation in D3 is similar to that in D12. Such results are discouraging as higher-resolution forecasts are presumed to provide more accurate QPFs (Novak et al 2008;Evans and Jurewicz 2009). Such may be the case when deterministic forecasts capture the convection and structure of the precipitation system in question, but such was not the case for this event.…”

“…Note that multiple forms of instability may simultaneously be present (Schultz and Knox 2007;Novak et al 2010;Schumacher et al 2010). Other ingredients one may consider are whether a u e ridge exists at midlevels (Moore and Blakley 1988;Weisman 1996;Jurewicz and Evans 2004;Moore et al 2005), the relative humidity (RH), and whether temperatures are in the dendrite-growth zone [255-261 K; Rogers and Yau (1989); Evans and Jurewicz (2009)]. Evans and Jurewicz (2009) evaluated operational North American Mesoscale Model (NAM; Janjić et al 2005) forecasts of several banded snow events and found that the forecast accuracy of the ingredients degrades substantially for lead times of 12 h and beyond, a result that suggests that deterministic forecasting may be unreliable for this type of event.…”

“…Other ingredients one may consider are whether a u e ridge exists at midlevels (Moore and Blakley 1988;Weisman 1996;Jurewicz and Evans 2004;Moore et al 2005), the relative humidity (RH), and whether temperatures are in the dendrite-growth zone [255-261 K; Rogers and Yau (1989); Evans and Jurewicz (2009)]. Evans and Jurewicz (2009) evaluated operational North American Mesoscale Model (NAM; Janjić et al 2005) forecasts of several banded snow events and found that the forecast accuracy of the ingredients degrades substantially for lead times of 12 h and beyond, a result that suggests that deterministic forecasting may be unreliable for this type of event. Ensemble-mean forecasts generally show improved skill over deterministic forecasts for many applications because small-scale error growth is not usually reflected in the mean fields (e.g., Leith 1974;Wandishin et al 2001;Roebber et al 2004).…”

“…Ensembles also provide a direct measure of probability, which is useful for assigning a degree of confidence to the forecast, assuming the model and analysis error are properly accounted for (e.g., Roebber et al 2004). Novak et al (2006) and Evans and Jurewicz (2009) recommend the use of ensembles for banded snow forecasting.…”