We haven’t had any snow in Boston yet this season, but it won’t be long now; forecasters have already been using the “S” word. We can take a few inches in stride, but a major Northeast snowstorm, or worse—a series of them as we had in 2015—can have serious economic impacts.
While most snowstorms do not have the sudden catastrophic impact of hurricanes or tornadoes, they still can bring a potent combination of wind, low temperatures, and heavy snow. At temperatures near freezing, snow can have high water content, producing gravity (downward) loads that can stress building connections or even lead to roof collapses. Severe snowfall can place enormous stresses on civil governments and business operations, causing costly travel disruptions and damage to power and communication networks that can bring everyday life to a standstill.
As a society, we rely on rating or relative impact scales as a practical means for assessing the severity of various events. In atmospheric science, the most familiar impact scales are those developed for tornadoes (Fujita) and hurricanes (Saffir-Simpson). Did you know that there is also a rating scale for Northeast snowstorms?
Paul Kocin of The Weather Channel® and Louis Uccellini of the National Weather Service developed the Northeast Snowfall Impact Scale (NESIS) to quantify the impact of these storms on populations. NESIS provides a relative measure of Northeast winter storm impact based on total snowfall amount, its geographic distribution, and population density. The National Climatic Data Center (NCDC) computes NESIS values when a significant snowstorm hits the 13-state Northeast region—defined as West Virginia, Virginia, and northeastward through New York and the New England states. To capture the entire storm history, NESIS values are computed using total snowfall distributed east of the Rocky Mountains.
About a week after the event, preliminary values are calculated using a geographic information system (GIS) and posted to the NCDC website. These values are often refined after additional quality checks or as more observations become available and final NESIS estimates are released at the end of the winter season.
The wide range in the severity of winter storms typically results in NESIS values between 1 and 13, corresponding to one of five categorical assignments: (1) Notable, (2) Significant, (3) Major, (4) Crippling, and (5) Extreme (Table 1).
The NESIS scale was calibrated based on an analysis of 30 Northeast snowstorms that occurred from 1956 to 2000, using the average area covered by at least 10 inches or more of snowfall accumulation and the average population (as of the 2000 census) within the affected area. The mean NESIS value for these calibration events is 5.0 (Category 3). The ten most severe storms on record are ranked by NESIS value in Table 2.
NESIS is different from most other scales in that it takes into account population density in addition to meteorological data and can indicate a storm's societal impacts. The overall impact of a winter season can be assessed by summing the NESIS values of individual storms. A very intense winter season can be a result of a single crippling event or multiple less intense ones. For example, the Great Blizzard of 1993 holds the record for maximum NESIS value for a single storm at 13.20. In comparison, the seasonal NESIS value from 1977–78 was 12.31, but this resulted from two Category 3 events.
The NESIS scale can provide valuable information regarding the potential social and economic impacts of an impending snowstorm by comparing its projected track and intensity to similar storms in the NESIS historical database.
A more robust and reliable representation of the full spectrum of extreme winter events is provided by a well-constructed catastrophe model. Its primary benefit is to anticipate the potential impact of extreme events before they occur. Furthermore, by simulating winter storms using state-of-the-art numerical modeling techniques, regional correlation in risk is properly enforced, as is the intraseasonal “clustering” of snowfall events that has been observed on occasion.
As a final point, it is important to note that NESIS does not consider the replacement value of property. This brings into focus the value of a well-constructed industry exposure database in a catastrophe model, which—along with robust hazard simulation and expert understanding of how structures respond to snow loads—can provide a fully probabilistic assessment of potential damage and loss.