Central Plains Blizzard: Snow Amounts Likely to Take Many By Surprise

A Blizzard Warning and Winter Storm Warning has been issued parts of the Southern and Central Plains, the second such blizzard in a week for some residents.  However a concept in disaster preparedness can be readily displayed with the forecast for this event.  Currently, the National Weather Service is forecasting a foot as the upper limit to the snowfall values in Kansas and 15″ as the upper limit to snowfall values in extreme Northeastern part of the Texas Panhandle.  But the highest snowfall totals for this storm could be much much higher….

Recently, the NOAA Hydrometeorological Prediction Center (HPC) began issuing probabilistic snowfall graphics (shown below) that show snowfall forecasts where snowfall values are exceeded 90%, 75%, 50%, 25% and 10% of the time.


HPC 50th Percentile Snow Forecast
(Click for larger image)


HPC 90th Percentile Snow Forecast
(Click for larger image)

Essentially a 50th percentile snow forecast is the forecast that 50% of the time the amounts will be higher and 50% of the time, the amounts will be lower.  For planning purposes, this is the likely amount forecasted if you’re going to play the middle of the road.

However the 90th percentile forecast is quite different.  It shows the amounts that will be exceeded only 10% of the time.  While many people want to forecast snow amounts accurately, the 10% probability event is a great resource to “Plan for the worst” and the 50% probability event is “hoping for the best”.

The wild card in events like this is thunder snow. Essentially, areas where thunder snow occurs can receive locally higher snowfall amounts. The snow probabilities point to this potentiality, although the bands of intense snowfall will not cover the entire area. Depending on where the most intense bands set up, it will dramatically impact the amounts of snow received in those areas. This again points to the importance of the 10% exceedance threshold. Most people will receive snow amounts closer to the 50th percentile amount, but there will be pockets where people receive substantially higher amounts.


Comparison between NWS forecast (left) and HPC 90th percentile / 10% exceedance forecast (right) Current as of 0800CT on 2/24/2013

You may be saying right now, “that’s great but I hate math and hate probabilities”.  Communicating potential risk, especially in low probability, high impact events is critical for anticipating the worst and taking protective action while hoping for the best.  If there was a 10% chance of an intruder in your house, going after you and your family, would you take protective action?  If there was a 1 in 10 chance that you could lose your job, would you start developing a backup plan?

We’ll see how this specific event unfolds, but the current forecast (left in map above) isn’t even at the levels depicted in the 50th percentile event (likely underestimating snow  amounts).  Between that and the incredible disparity between the forecast and 10% potential snowfall amounts, this is a classic example where people can and likely will be caught surprised by the event.

The Age of Unnamed Storms is Over

In the meteorological community, hurricanes were given names in the mid 20th century.  In an article earlier this year titled how hurricanes are named, “Names are presumed to be far easier to remember than numbers and technical terms,” the World Meteorological Organization explains on its website. “Many agree that appending names to storms makes it easier for the media to report on tropical cyclones, heightens interest in warnings and increases community preparedness.”

But there are times when storms are not named by official channels.  Continue reading

There are Cat 3 Hurricanes & EF-3 Tornadoes, But Do Winter Storms Get Categories Too???

Many people are aware of the Enhanced Fujita (EF) Scale for tornadoes.  Most also know about the Saffir-Simpson Hurricane Wind Scale.  However there is also a rating scale for Winter Storms that fewer people know about. In 2004, Paul Kocin and Louis Uccellini from the National Weather Service (Kocin and Uccellini, 2004) developed the Northeast Snowfall Impact Scale (NESIS).    Below is a description from the National Climate Data Center (NCDC) website for NESIS:

“The index differs from other meteorological indices in that it uses population information in addition to meteorological measurements. Thus NESIS gives an indication of a storm’s societal impacts. This scale was developed because of the impact Northeast snowstorms can have on the rest of the country in terms of transportation and economic impact.

NESIS scores are a function of the area affected by the snowstorm, the amount of snow, and the number of people living in the path of the storm. The diagram below illustrates how NESIS values are calculated within a geographical information system (GIS). The aerial distribution of snowfall and population information are combined in an equation that calculates a NESIS score which varies from around one for smaller storms to over ten for extreme storms. The raw score is then converted into one of the five NESIS categories. The largest NESIS values result from storms producing heavy snowfall over large areas that include major metropolitan centers. Continue reading