RETHINKING SNOWSTORMS AS SNOW EVENTS a Regional Case Study from Upstate New York

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RETHINKING SNOWSTORMS AS SNOW EVENTS A Regional Case Study from Upstate New York

BY DAVID A. CALL

Whether predicting or planning for snowstorms, forecasters, government, and the general public should consider both meteorological and human-caused variations inherent in snow events.

n March 1888, an epic snowstorm disrupted nor- Why did these two significant snowstorms have mal life in much of the Northeastern United States. such dramatically different effects on society? In I The Blizzard of 1888 dumped more than 3 ft (91 1993, factors such as massive government interven- cm) of snow in much of the Hudson Valley and tion, cooperative behavior by the general public, and Connecticut, while winds as high as 36 m s–1 created advances in forecasting ability and forecast dissemi- drifts of more than 20 ft (6 m); (Kocin 1983; Cable nation allowed for adequate preparation, appropri- 1988). One hundred and five years later, another ate actions during the storm, and efficient cleanup epic blizzard struck the Northeast. The Blizzard of operations afterward (Uccellini et al. 1995). While 1993 was equally impressive, with incredible snow the mitigating influence of these factors may seem accumulation—such as 42 in. (107 cm) in Syracuse, intuitive, surprisingly few researchers—either within New York —strong winds, and a paralyzing impact. or outside the meteorological community—have However, despite the larger area and greater popula- examined how nonmeteorological factors affect a tion affected by this storm, fewer human fatalities snowstorm’s impact. Although, Hart and Grumm were attributed to the Blizzard of 1993 than to the (2001) and Zielinski (2002) have devised scales rating Blizzard of 1888. Furthermore, within a few days winter storms, only Rooney (1967) and Kocin and after the Blizzard of 1993 ended, many businesses Uccellini (2004b) have created snowfall scales that and schools resumed normal operations. incorporate any nonmeteorological factors. Rooney’s five-category scale focused on snow’s effects on transportation networks, while Kocin and Uccellini AFFILIATION: CALL—Department of Geography, Syracuse considered population in their Northeast snowfall University, Syracuse, New York impact scale. CORRESPONDING AUTHOR: David Call, 144 Eggers Hall, Dept. This author agrees with Kocin and Uccellini of Geography, Syracuse University, Syracuse, NY 13244 (2004b) that creating an easily understood scale that E-mail: [email protected] DOI:10.1175/BAMS-86-12-1783 incorporates the range of snowstorm variability may be difficult. Nonetheless, an understanding of In final form 18 July 2005 ©2005 American Meteorological Society the significant factors that affect a snowstorm’s impact—both meteorological and nonmeteorological

AMERICAN METEOROLOGICAL SOCIETY DECEMBER 2005 | 1783 sified under four metafactors: meteorological variations, governmental response, actions of the general public, and meteorologists and the media. A sum- mary table grouping the factors into major or minor categories will also be presented. Finally, this article will conclude with a call to action for both forecasters and the community at large. Ultimately, meteorologists and broader society should revise the concept of snowstorms into one of snow events, a richer term that reminds us that not only are meteorological factors responsible for variations in snowstorm impacts, but numerous human-created factors also play a role. In other words, while the Blizzards of 1888 and 1993 were both significant snowstorms, they were dramatically different snow events. FIG. 1. Locations of the case study cites within New York State. METHODOLOGY. Snowstorms that occurred in four major cities in Upstate New York—Buffalo, ones—will aid those who wish to create such a scale. Rochester, Syracuse, and Albany—between 1888 and Furthermore, an awareness of such factors benefits 2003 were studied to evaluate the significance of all affected by snowstorms, especially those charged factors influencing snow events. Figure 1 shows the with warning government and the general public. locations of the four cities within New York State. This article will introduce the various factors that These cities were selected because of their similar influence the impact of snowstorms and illustrate their significance. While numerous factors account TABLE 2. Dates, amounts (in.), and a qualitative for variation in snowstorm impacts, most can be clas- assessment of the disruption for the case study storms for Rochester. Note that disruption—a measure of the snow event—is not correlated with TABLE 1. Dates, amounts (in.), and a qualitative amount. assessment of the disruption for the case study Date(s) of storm Amount Disruption storms for Buffalo. Note that disruption—a measure of the snow event—is not correlated with 28 Feb–Mar 1900* 43.5 Medium amount. Question mark indicates a lack of suffi- 11–12 Dec 1944 21.5 High cient data. 15–19 Feb 1958 30.2 Medium Date(s) of storm Amount Disruption 14 Feb 1960 18.4 Medium 21–22 Jan 1902 17.4 Low? 19–20 Feb 1960 21.6 Medium 17 Mar 1936 19.0 High 23 Jan 1966 18.2 High 14–16 Dec 1945 36.0 Low 30–31 Jan 1966 26.7 High 28–29 Nov 1955 19.9 Medium 5 Dec 1977 10.8** High 29-30 Dec 1961 24.5 Low 6–7 Feb 1978 25.0 Low 30 Nov–2 Dec 1976 39.8 Low 8–10 Dec 1981 25.1 None 28–30 Jan 1977 * Extreme 28 Feb–1 Mar 1984 29.0 Medium 30 Nov–Dec 1979 22.4 Medium 11–12 Mar 1992 21.9 Low 10–11 Jan 1982 28.8 Low 13–14 Mar 1993 23.2 Low 27–29 Feb 1984 28.3 Medium 3 Jan 1996 23.0 Low 19–21 Jan 1985 33.2 High 12–15 Jan 1999 29.2 Medium 9–10 Dec 1995 41.2 Medium 4 Mar 1999 22.3 High 18–20 Nov 2000 38.9 High 6 Mar 1999 18.4 Medium 24 Dec 2001–1 Jan 2002 81.6 High *Two-day storm; no 29 Feb 1900. *Amount of accumulation unkown. **Another 13.1 in. fell 6–9 Dec 1977.

1784 | DECEMBER 2005 size and attributes, such as climate, elevation, and of how a single storm differentially impacted multiple economy. Another reason these cities were selected cities were rarely done. was to examine differences between lake-effect For each case study, newspaper accounts from versus synoptic-scale snow events. Largely due to two days before the storm began until news cover- variations in lake-effect snow, average annual snow- age ended were read; most storms disappeared from fall ranges from 63 in. (160 cm) in Albany to 120 in. news coverage within a week after the last flakes fell. (305 cm) in Syracuse. Prior to 1888, these cities had To learn more about governmental response to snow, little involvement in snow mitigation and gener- the author interviewed “Commissioners of Snow” ally waited for warmer weather to alleviate snow in Buffalo, Rochester, and Syracuse, and examined problems. Thus, the first case study in the sample budgets and expense reports for all four cities. Finally, was the Blizzard of 1888. However, because sparse local broadcast meteorologists were asked to respond news coverage and weak governmental response to a set of interview questions. This was done to get hampered efforts to study storms early in the sam- a sense of both their involvement in snow events and pling period, most of the cited examples are from their beliefs about the influence of the meteorology the 1930s through 2003. community. For each city, a list of the largest snowstorms within the study period was compiled; details of this METEOROLOGICAL VARIATIONS. Meteoro- process are in the appendix. The 10 largest storms and logical variations are perhaps the most obvious cause selected storms ranked 11–20 were then selected as for differences in snow events (see Changnon 1969; the case studies. Lower-ranked storms were chosen Kocin and Uccellini 2004a). This is largely because either to fill temporal gaps in data or because they oc- meteorological parameters such as total snow accu- curred very close in time to a “top 10” storm. In total, mulation are widely available and easily understood. 59 case studies, for an average of nearly 15 per city, While the total amount of snow is important, varia- were studied. Complete lists of case study storms are tions in other parameters of a snowstorm, such as shown in Tables 1–4. Because the largest snowstorms snowfall rate (intensity), snow density, air tempera- for each city were determined strictly by snowfall for that city and not in consideration of whether other TABLE 4. Dates, amounts (in.), and a qualitative cities received significant accumulation, comparisons assessment of the disruption for the case study storms for Albany. Note that disruption—a measure of the snow event—in not correlated with the amount. Question mark indicates a lack of suf- TABLE 3. Dates, amounts (in.), and a qualitative ficient data. assessment of the disruption for the case study storms for Syracuse. Note that disruption—a Date(s) of storm Amount Disruption measure of the snow event—in not correlated with the amount. Question mark indicates a lack of suf- 11–14 Mar 1888 46.7 High ficient data. 22–25 Feb 1893 18.2 Low?

Date(s) of storm Amount Disruption 14 Feb 1914 23.5 Medium 18–20 Jan 1936 17.9 Low 6–8 Mar 1932 18* Medium 8–12 Mar 1941 17.8 Low 8–9 Feb 1958 25.3 Medium 8–9 Feb 1958 21.1 Medium 16–17 Feb 1958 29.2 High 15–16 Feb 1958 17.9 Medium 30 Jan–1 Feb 1966 42.3 High 24–25 Dec 1966 18.3 Low 5–10 Dec 1977 24.2 Medium? 22 Dec 1969 12.3 Medium 28 Feb–3 Mar 1984 30.9 Low 25–28 Dec 1969 26.4 High 15–17 Dec 1989 25.2* Low 24–25 Nov 1971 22.5 None 14–21 Jan 1992 38.6 Low 15–16 Jan 1983 24.5 Low 11–15 Mar 1992 31.7 Low 13–14 Mar 1993 26.6 Medium 13–14 Mar 1993 42.0 Medium 25 Dec 2002 21.0 Medium 4-9 Jan 1994 42.2 High 3–4 Jan 2003 20.8 Medium 30–31 Dec 1997 25.9 Medium 6–7 Dec 2003 18.0 Low *Based on newspaper reports.

AMERICAN METEOROLOGICAL SOCIETY DECEMBER 2005 | 1785 ture, wind, and duration can have just as much, if not based on the meteorological data. For example, the a greater, effect on the associated snow event. Indeed, December 2001 “Superstorm” dumped more than the term blizzard implies both windy (>15 m s–1) and 80 in. (203 cm) of snow at the Buffalo airport. Because snowy conditions leading to a reduction in visibility it occurred between Christmas and New Year’s Day— (<0.4 km; Branick 1997). Timing of a storm is also when schools were closed and many workers were on important, although this is mainly because of varia- vacation—disruption for most residents of the City tions in human factors, such as traffic volume. of Buffalo and its suburbs was arguably less than that For Buffalo, Rochester, and Syracuse, intensity is of the Gridlock Monday 2000 storm. Likewise, the often more important than total snowfall amount. Blizzard of 1993 (studied in Rochester, Syracuse, and Because these cities individually average more than Albany) had a relatively small impact compared to 90 in. (229 cm) of snow per season, snow mitigation other record-setting snowstorms, such as the Blizzard operations are efficient, members of the general of 1977 in Buffalo or the Blizzard of 1996 in Syracuse, public are experienced in dealing with snow, and fore- simply because it occurred on a weekend. Even when casters are skilled at snow prediction. Thus, a large a snowstorm occurs during the hectic shopping week- but unexceptional amount of snow may not cause ends before Christmas (examples include Buffalo much disruption of the normal routine. However, if in 1995 and Syracuse in 1989), the general public the snow falls with extraordinary intensity, normal largely chooses to stay home rather than venture life can quickly grind to a halt, even if for just a few out. Conversely, all three aforementioned gridlock hours. When 25 in. (63 cm) of snow fell on “Gridlock storms occurred on weekdays. Additionally, the most Monday 2000” (20 November), thousands of Buffalo intense snow fell between 1000 and 1400 LT. Thus, in commuters and students were stranded downtown in contrast to popular opinion, storms that are intense what the Buffalo News (21 November 2000) termed at midday are often more disruptive than those that the “worst storm since . . . 1977.” In Rochester, an strike at rush hour. Midday storms cause a super–rush intense (and largely underforecast) storm depos- hour with schools and workplaces being dismissed ited more than 22 in. (56 cm) of snow on Thursday simultaneously. Comparatively, storms that peak in 4 March 1999. Local governmental authorities closed the overnight or early morning hours may compel all interstate highways because of accidents, causing workers and students to remain at home; for storms massive gridlock. Finally, when snow fell at a rate occurring late in the day, students are already home exceeding 4 in. (13 cm) h–1 on Tuesday 4 January 1994 or in the process of returning home, and worker (the Syracuse “Snowburst”), Syracuse area schools dismissals are staggered. In response to the Syracuse and offices dismissed students and workers early, Snowburst 1994 storm, the City of Syracuse and resulting in widespread gridlock. downtown businesses created a nonbinding plan to An equally significant meteorological factor is dismiss workers on a gradual basis, with the aim of when a snowstorm occurs, although timing is impor- preventing a super–rush hour and widespread grid- tant primarily because of variations in traffic volume. lock (J. Wright 2003, personal communication). Timing as an attribute influencing snow events can If two snowstorms occur close together and the be further subdivided into different scales. On the period between them is cold, the second storm is seasonal scale, early or late season snowstorms may often a more disruptive snow event. In February lead to less significant snow events because of rela- 1958, two synoptic-scale storms affected Syracuse tively warm ground, higher sun angles, and longer and Albany in just over a week’s time. Although the day length; all of these reduce snow accumulations first storm dumped more snow on Syracuse—21 in. on roadways.1 Similarly, snowstorms that occur on (53 cm) versus 17 in. (43 cm) with the second—the holidays, weekends, or during school breaks are of- second storm was more disruptive. In Albany, the ten lesser snow events than what might be expected second storm was more disruptive than expected when compared with similar storms in 1941 and 1966. 1 Early or late-season snowstorms may be problematic because Snow remaining from the first storm and equipment of the potential for downed power lines and unprepared failure largely explain why a second storm is a more motorists. However, few reported problems with downed disruptive event. When two 15-in. (38 cm) lake-effect trees and lines were observed in this study, perhaps because snowstorms affected Buffalo in 1985, more than half of the focus on cities or maybe due to a lack of case-study of the city’s snow mitigation equipment was out of storms before late November. As for unprepared motorists, service the day after the second storm (Buffalo News, their disruptive effect was also negligible, even when a storm 22 January 1985). Even if no major snowstorms occur, was the first of the season. a prolonged period of snow and cold can have increas-

1786 | DECEMBER 2005 ingly negative effects. A record 78.1 in. (198 cm) of 1986]. Nonetheless, exceptionally strong winds, snow fell in Syracuse during January 2004. Two fatal coupled with light snow, can cause widespread drift- accidents, on two separate days, occurred late in the ing, and that is a major problem. Such was the case in month when drivers skidded across a long bridge on Buffalo with both the Blizzard of 1977, when winds Interstate 81, hit packed snow along the guardrail, gusted to 31 m s–1, and after the January 1985 storm, flew off the highway, and fell 15 m to the ground when winds gusted to 22 m s–1. below. Prior to the accidents, measurable snow had To summarize, meteorological variations in snow- fallen every day for more than 2 weeks, and although storms can greatly affect their impact and thus cause plow drivers for New York State had been salting and dramatically different snow events. However, snow plowing daily, they had not had time to physically re- events are also affected by many nonmeteorological move the snow along the guardrail. Similar incidents, factors, such as governmental response, and problems thankfully with less deadly results, occurred in Roch- in this area can create major snow events out of minor ester following a similar period in January 1999. snowstorms. Air temperature is another meteorological factor that affects snow events. Neither cold nor warm tem- GOVERNMENTAL RESPONSE. Although me- peratures are necessarily worse; instead, each presents teorological variations in snowstorms—especially in- a different set of complications for snow mitigation tensity—are important in understanding differences crews. At temperatures below –9°C, road salt is largely in snow events, social factors are equally important. ineffective (Moran et al. 1992). However, the drier As shown already, timing is significant largely be- and thus less dense snow at these temperatures is cause of social reasons, such as variations in traffic easier for plow crews to push and cars to drive over volume or holiday periods. Behavior of the govern- (P. Noto 2003, personal communication). While tem- ment is another important social factor. Smart plan- peratures near 0°C increase salt’s effectiveness, snow ning, competent workers, and reliable contractors aid has a higher water content and greater density. This government and minimize disruption, but failure in heavier and more clumpy snow puts a greater strain any of these areas can create a snow disaster. on snow mitigation equipment—assuming the equip- Effective snow mitigation begins with good leader- ment is able to break through the slush. More than ship at the highest level of local government. Thus, 161 km of Rochester streets were left impassible when when political fights spill into snow mitigation opera- seven contractors failed to clear their routes after a tions, minor snowstorms quickly become major snow storm in February/March 1984. Several interviewed events. Among the cities studied, Buffalo has experi- by the newspaper blamed the unusually dense snow enced the most politically enhanced snow events. A for causing equipment failure and their breach of budget dispute between Mayor George Zimmerman contract. One contactor termed the snow “cast iron” and Buffalo Common Council was already simmer- (Rochester Democrat and Chonicle,1 March 1984), an ing when the St. Patrick’s Day 1936 storm hit the city. appropriate metaphor for the way dense snow fuses Because the snow budget was exhausted, Zimmerman together when cold weather follows a storm. Thus, if did not order crews to begin plowing until the eve- a city is slow to respond to a storm with dense snow, ning, well after the snow was already settling into removal can become impossible. The March 1936 a dense, slushy mess. Council blamed the lack of “St. Patrick’s Day” storm dumped 19 in. (48 cm) of funds on fiscal mismanagement by the mayor, while snow and sleet on Buffalo; the precipitation mixture the mayor-appointed public works director accused had an usually low snow-to-water ratio of ~7:1. Snow the council of failing to provide sufficient funds for removal crews were called late and found frozen slush equipment (Buffalo News, 18 March 1936). Travel that was then impossible to clear, and the city was throughout the city remained at a standstill for nearly paralyzed for a week. a week until crews from adjacent Erie County and Wind is another meteorological factor that affects melting from warmer temperatures finally cleared the snow events, although its significance is less than the snow. In 1985, Mayor James “Jimmy” Griffin and might be expected. Within the cities studied, there is Buffalo Common Council were already fighting over little open space for snow to drift. Additionally, such who should direct snow removal operations when a open space is essentially constant; thus, mitigation severe storm hit. Lacking a snow mitigation plan, operations have been adjusted to give drift-prone and hampered by equipment failure, workers did an areas extra attention if needed [P. Noto 2003, personal uneven and generally poor job of snow mitigation, communication; J. Wright 2003, personal communi- causing citizens to flood council with complaints, cation; Albany (NY) Bureau of Streets Annual Report including discriminatory plowing (Buffalo News,

AMERICAN METEOROLOGICAL SOCIETY DECEMBER 2005 | 1787 26 January 1985). Despite these complaints and compared to the past (based on city budgets; P. Noto similar ones following a snowstorm in January 1984, 2003, personal communication; J. Wright 2003, Mayor Griffin was reelected three times. Although personal communication). there have been some examples to the contrary, such Finally, outside aid—in the form of Disaster as Mayor John Lindsey in New York City in 1969 Declarations and National Guard assistance—is (see McKelvey 1995), problems with snow mitiga- more common today than in the past. While such tion are not always fatal to political careers—even assistance is rarely available until after a snow event in Buffalo. is well underway, the extra labor and governmental Regardless of political leadership, without compe- funds help people in cities resume normal activities tent workers and the proper equipment, snow mitiga- more quickly. tion operations will fail. Nonetheless, it appears that the workers are rarely a problem—both newspapers ACTIONS OF THE GENERAL PUBLIC. and Commissioners of Snow consistently praise them Equally significant to governmental response are the as being dedicated and capable. For example, Joseph actions of the general public. Most important are car- N. Giambra, Commissioner of Snow for Buffalo, related actions, both in terms of parking and driving. termed his employees “super” and noted that “they’ll Parked cars impede plowing operations, while cars work 16 hours for you and not hesitate about coming in driving lanes—especially if stalled, abandoned, in the next morning” (2003, personal communica- or gridlocked—get in the way. More generally, indi- tion). Additionally, the size of the workforce is almost vidual decisions by members of the general public to always sufficient. One notable exception occurred remain at home or venture out can collectively affect in Rochester in December 1944, when a labor short- a snow event. age due to World War II exacerbated snow removal The greatest problem that cities face in dealing difficulties initially caused by poor leadership (the with snow is parked cars. One commissioner claimed workers were called late). Although most cities that parked cars were his city’s “biggest nemesis,” since then have employed enough workers, having a while another twice referred to them as a “nightmare” sufficient quantity of working snow removal equip- (P. Noto 2003, personal communication; J. Wright ment is another story. In all four cities studied, old 2003, personal communication). Unlike adjacent equipment was used well beyond its life expectancy, suburbs, which almost always ban nighttime parking and breakdowns hampered operations. Examples of during the snow season, the cities studied are ham- this include snowstorms in Buffalo 1936, 1945, and pered by old neighborhoods with a shortage of off- 1985; Albany in 1958; and Syracuse in 1958 and 1966. street parking. At best, cars parked on the street slow However, thanks to improvements in snow removal down plows and restrict curb-to-curb clearing opera- technology, equipment problems today are less com- tions. At worst, they can block plows from entering mon and less severe than those in the past. narrow streets. Problems are not limited to residential In all four cities, contractors are an important areas, either; illegal downtown parking created many component of the snow mitigation force. Use of con- problems encountered in the mid–twentieth century tractors allows cities to save money on equipment (see storms from Rochester, 1966; Syracuse, 1958; purchases and labor, yet they can still increase their and Albany, 1958). Because of parking problems in workforce when an extraordinary storm occurs. the past, the cities studied have instituted large fines, Unfortunately, contractors sometimes fail to appear strong enforcement, and consistent parking regula- or fail to use adequate equipment for clearing heavy, tions. For example, Syracuse drivers may park on compacted snow. Historically, Rochester has relied on only one side of the street based on whether the date contractors more than the other cities, and in both is odd or even; the actual weather is irrelevant. As a 1977 and 1984 no-show contractors slowed recov- result of these parking policy changes, problems with ery after major storms. In these cases, the problem parked cars are less substantial today, although they was exacerbated by the city’s lack of trucks small are still significant. enough to squeeze down narrow residential streets. Motorists also disrupt snow removal efforts. Consequently, Rochester today has a larger number Whether cars are moving, idling, stalled, or aban- of small trucks than in the past, and contractors doned, they slow traffic flow—including snow are required to bring their equipment to the Public plows. In worst-case scenarios, traffic can become Works Garage for inspection annually (P. Noto 2003, completely gridlocked (e.g., Buffalo Gridlock Monday personal communication). More generally, all of the 2000 storm). Nonetheless, traffic today seems to have cities studied are less reliant on contractors today a less visible effect than it did in the past. For example,

1788 | DECEMBER 2005 commuters’ return to work following major storms job. An early example of this was a lake-effect storm in the 1950s and 1960s caused massive traffic jams in that struck Buffalo in December 1961; the magnitude every city for every storm studied during this time. of the snow event was minimal. The Buffalo News Return-to-work traffic jams do not occur today in credited Weather Service, Inc., with notifying the the case-study cities. The cause for this change is Streets Division early enough for adequate prepara- unclear; however, the author believes it is probably a tion (30 December 1961). Similarly, good forecasts combination of population declines, job losses, and greatly aided snow mitigation operations in Syracuse improvements in parking regulation. during and after the Blizzard of 1993—and this was Finally, the general public influences snow events despite one of the largest snow totals on record (J. simply by choosing whether or not to remain at home. Wright 2003, personal communication). People staying home during the Blizzard of 1993 Meteorologists also influence actions of the gen- have been credited with assisting mitigation efforts eral public. Again, the Blizzard of 1993 is a prime (Albany Times-Union, 15 March 1993). On the other example of a storm that had a lesser impact because of hand, police blamed violators of a driving ban for a well-prepared general public (Albany Times-Union, slowing down cleanup and removal operations fol- 15 March 1993). In Rochester, the February/March lowing the January 1985 storm in Buffalo (Buffalo 1984 storm, despite occurring during the middle of News, 23 January 1985), and sightseers from the sub- the workweek, had a relatively minor impact initially urbs hindered operations following the 1969 storms because of the general public’s preparation (although in Albany (Albany Times-Union, 30 December 1969). problems with no-show contractors ultimately made Finally, looters caused an extra burden by distracting this a very disruptive storm). police (who often are needed to ticket illegally parked Conversely, if meteorologists’ forecasts are incor- cars prior to towing) following storms in Syracuse rect, ire descends from the public. For example, an (1966) and Buffalo (1977 and 1985). early December 1977 storm in Syracuse was much less significant than predicted, prompting the edito- METEOROLOGISTS AND THE MEDIA. rial board of the Syracuse Post-Standard to blame Although meteorologists and the media do not con- “misleading” weather reports and “fearsome” film trol the weather, drive snowplows, or have a large clips for the unnecessary closing of 50 local school collective effect as do members of the general public, districts (10 December 1977). On the other end of the they do have an indirect influence on snow events by spectrum, when a forecasted minor storm became a altering the behavior of the government and general major storm on Thursday 4 March 1999, a massive public. Meteorologists influence behavior by issuing traffic jam resulted in Rochester. forecasts and warnings; the media influence behavior Corresponding to the rise in meteorologists’ influ- through their coverage of storm preparations, the ence is an increase in the general public’s knowledge storm itself, and storm aftermath. It should be noted and understanding of meteorology. All five meteo- that since many meteorologists are employed by rologists interviewed agreed with this statement and media companies their influences are intertwined; cited reasons such as advances in technology (e.g., furthermore, additional media that do not employ Doppler radar) and easier access to information or contract meteorologists also disseminate weather through sources such as The Weather Channel® and information. World Wide Web. However, they cautioned that The power of meteorologists to affect behavior members of the general public have increasingly high has grown with time. For the case study storms that expectations due to promotion and use of such tech- occurred before approximately 1980, it was rare to see nology. Furthermore, most broadcast meteorologists an newspaper article about the storm before it actu- interviewed by the author complained of insufficient ally began. Since then, however, newspaper articles on-air time for a complex discussion of weather pos- warning of an impending storm or discussing storm sibilities and uncertainties. Some speculated that preparations have become commonplace. Poststorm communication problems may stem from closer to evaluations of governmental response and meteoro- home due to an in-house disconnect between them logical forecasts are not uncommon either. and their respective news departments. Meteorologists affect governmental response The media also reflect and influence public by providing warnings in advance of a snowstorm. opinion. Newspapers use both editorials and news When a well-forecast storm strikes a well-prepared articles to illustrate their belief in the ability, or city, the streets may have been presalted, plows are ineptitude, of government. If government fails to gassed up and ready to go, and city workers are on the properly mitigate snow, news coverage takes a nega-

AMERICAN METEOROLOGICAL SOCIETY DECEMBER 2005 | 1789 tive tone (some representative case studies include creations— allows us to better understand why Buffalo 1936 and Rochester 1944). In Albany, persis- similar snowstorms often have dramatically differ- tent problems with snow removal in late 1969 turned ent impacts on society. Tables 5 and 6 summarize news coverage from relatively neutral to antagonistic. the factors that affect snow events; Table 5 shows News headlines best illustrate this change: while factors that directly influence a snow event, while initial headlines expressed awe at the magnitude of Table 6 shows indirect influences. All factors shown the snow problem, such as “Wow, We Are Snowed!” in Table 5 are grouped underneath the meta-fac- (Albany Times-Union, 23 December 1969), later head- tors of meteorological variations, governmental lines expressed increasing frustration, such as “Area response, or actions of the general public. Factors in Remains Paralyzed: Another Storm is on the Way” Table 5 are further separated by whether variations (ibid., 29 December 1969). in them generally have a major or minor influence The combined influence of meteorologists and the in affecting the magnitude of a snow event’s dis- media is most evident in a phenomenon termed by ruption. Several factors not previously discussed, this author as the mad rush. Mad rushes occur when such as the clearing of fire hydrants and sidewalks, members of the general public mob grocery and hard- generally had little effect on snow events in the case ware stores in search of the essentials, such as bread, study cities (Call 2004), however, these may have milk, toilet paper, and snow shovels, in advance of an more significance in other cities or noncity areas. impending snowstorm. In this study, the first mad Indeed, budget-related problems can be especially rushes were observed in the 1990s, suggesting that significant for smaller municipalities, such as towns better forecasts and media dissemination are at least (ibid., p. 35). Table 6 includes factors relating to the partially responsible for such behavior. The mad rush metafactor of meteorologists and the media, as well also varies spatially. Although eight case study storms as several factors that are either relatively constant, affected Buffalo and Rochester in the 1990s and such as a city’s climate, or difficult to measure, such 2000s, none of them triggered a mad rush. However, as residents’ level of experience. Because of the in- mad rushes were common in Albany during this direct nature of the factors in this table, no further time; mad rushes have also been observed elsewhere grouping was attempted. While climate and city in the Northeast corridor and also in connection with layout and terrain have a small influence, at least for hurricanes. Ironically, mad-rush behavior is generally the case study cities (Call 2004), future researchers unnecessary in regard to snowstorms. With two ex- may wish to determine the importance and relative ceptions—both in Buffalo—no recent storm has para- influence of the other factors shown in Table 6. lyzed any portion of any city studied for more than Two important limitations of this study are its few days. Although vulnerable groups of the general regional focus and its emphasis on cities. Rooney public, such as the elderly or residents of rural areas, (1967), for example, found significant regional dif- could be stuck in place for several days, it is unlikely ferences between snow events in the Upper Midwest that most urban and suburban residents could face and those in the western Great Plains, and this study such a predicament from all but the worst of storms. found significant differences even among four similar Unanswered questions regarding the spatial variation cities. For example, Buffalo has had the most politi- in the mad rush outside of Upstate New York and more general ques- TABLE. 5 Factors directly affecting snow events in the cities studied. tions about why this behavior Meteorological Governmental Actions of the occurs suggest a need for further variations response general public research. Finally, one reviewer of this paper suggested that the mad Major • Amount of snow • Equipment • Parked cars rush may actually benefit cities • Intensity of snow • Preparation • Motorists by lessening the need for people • Timing • Use of Contractors • Choosing to stay to travel during a snowstorm. • Temperature • Politics home, or not Future researchers may also want (snow density) to examine this supposition. Usually • Wind • Labor • Adherence to driving minor • Duration • Outside aid bans CONCLUSIONS. Thinking • Criminal behavior of snowstorms—meteorologi- • Budget • Clearing of hydrants cal happenings—in the larger and sidewalks context of snow events—social

1790 | DECEMBER 2005 Tom DiVecchio, Don Paul, and Wayne Mahar, the discus- TABLE 6. Factors indirectly affecting snow events in the cities studied. sion of meteorologists’ influence on snow events would not have been possible. Similar thanks are in order to the Meteorologists and the Additional factors Commissioners of Snow: Joseph N. Giambra, Paul Noto, media and Jeff Wright. Thanks also to Steve McLaughlin for his • Accuracy of forecasts • Climate assistance in defining severe snowstorms and perspective • Lead time • City layout and terrain on NWS procedures. Finally, appreciation is extended to • Tone of coverage • Credibility of government, all six reviewers of this article—their comments greatly • Amount of coverage meteorologists, and media strengthened my argument. • Experience with past events APPENDIX: CREATING THE LISTS OF CASE STUDY STORMS. Creating the lists of case study storms was a surprisingly problematic task. cally enhanced events, while Rochester has had the Although snow events are determined by much more most problems with contractors. Nonetheless, the than snow amounts, using daily snow data to develop author believes that the metafactors introduced here the lists was easier and faster than more complex could be applied to cities elsewhere in the United methods [such as those used Branick (1997)]. For States. An awareness of the nonmeteorological fac- Albany, the local National Weather Service Forecast tors affecting the impact of snowstorms could be Office maintains a list of the largest snowstorms from especially valuable in regions less accustomed to 1888 through the present on its Web site; this list was snow, because the actions of the government, general sufficient for this study. For the other three cities, lists public, meteorologists, and media can significantly of storms had to be constructed. Some information reduce the disruption of snow events. Finally, this was available for Buffalo and Rochester, such as a list study focused on cities, and caution should be used of the greatest 24-h snowfalls since 1980 and a list of when applying the findings to suburban or rural ar- the greatest daily snowfalls since 1943, respectively. eas. Although the author believes that the factors are Although these provided a useful starting point, be- transferable, the significance of them changes greatly cause long duration but less intense storms did not because of dramatic differences in the suburban and appear on the lists, the daily snow record also had to rural landscape. For example, suburban areas near be examined. For Syracuse, no list of any type was the case study cities have overnight on-street parking available. Thus, for Buffalo, Rochester, and Syracuse, bans, a lower street density, large drainage ditches, simple objective criteria defining a severe snowstorm and other differences that greatly aid plows and had to be created; then these had to be applied to lessen problems with cars (Rochester Democrat and daily snow accumulation data to create lists of severe Chronicle, 3 March 1984). In rural areas, wind causes snowstorms. significant drifting, and residents can be isolated for Unfortunately, no official criteria define severe long periods, behooving them to purchase extra sup- snowstorms. Although 6 in. (15.2 cm) of snow is plies before a storm. generally the minimum criterion for heavy snow in To end, this study has shown the importance of the Northern United States (Changnon 1967; Branick considering nonmeteorological factors as well as 1997), that amount is fairly common in the case study meteorological ones when studying snow events. region. More problematically, snow falls nearly daily Whether preparing forecasts and warnings for clients in lake-effect snow regions during winter, and it is or the general public, forecasters should consider the difficult to tell if snowfall from consecutive days is role of both social and meteorological factors and from one or multiple snowstorms. Thus, a working adjust the tone of their pronouncements accordingly. definition was created as follows: at least 1 in. (2.5 cm) Ultimately, improvements in the tone and emphasis of of snow per day with a minimum of 10 in. (25.4 cm) forecasts will increase the ability of the meteorologi- in total. Because no list of any type was available for cal community to provide valuable information for Syracuse, this initial definition was used to create the the government and the general public. list of severe snowstorms shown in Table 3. After studying these storms, it was discovered ACKNOWLEDGMENTS. I wish to thank Anne that most long-duration storms with relatively low Mosher, Mark Monmonier, and Susan Millar for their guid- amounts per day (such as 14–22 January 1992) had ance and suggestions during this study. Without the honest almost no impact, probably because the snow inten- and insightful responses of Tom Atkins, Steve Caporizzo, sity never strained the city’s capacity. As a result,

AMERICAN METEOROLOGICAL SOCIETY DECEMBER 2005 | 1791 the definition of a severe snowstorm—at least by In conclusion, because the revised definition Buffalo, Rochester, and Syracuse standards—was favors shorter but more intense storms, the author revised to include only those storms with at least believes it is a superior way to determine severe snow- 3 in. (8 cm) of snow per day and at least 14 in. (36 cm) storms. This is because intense snowstorms, at least in in total accumulation.The higher amount of snow the case study cities, are often more disruptive than per day was needed to prevent long-duration low- less intense storms with greater snow accumulations. impact snowstorms (generally lake-effect episodes) Nonetheless, as shown by the rank order changes from being considered severe. The requirement for of Syracuse storms, significant snow events may be total accumulation was made to keep the lists of excluded from study by this definition. It is likely potential case study storms manageable; as shown in that some major snow events associated with low-ac- Tables 1–4, virtually every case study storm featured cumulation storms in the other cities may have been at least 18 in. (46 cm) of accumulation. Exceptions missed in this study. The challenge of determining a were either studied before the definition was revised severe snowstorm by using a parameter such as total or were secondary storms that occurred close in time snow accumulation, or even snow intensity, under- to “top 10” storms. scores a central point of this article: the disruption Finally, the revised definition was applied to caused by a snow event is based on much more than the Syracuse climate data and the new list of severe meteorological parameters. snowstorms was compared with the original list (see Table A1). Not surprisingly, several storms dropped far in the rankings, while a few did not meet the new REFERENCES criteria. Although some of these storms were insig- Albany (NY) Bureau of Streets Annual Report, 1986: nificant, the 1994 Syracuse Snowburst and second Proceedings of the Common Council: Vol. 2: Message February 1958 storm would not have been studied of the Mayor and Reports of City Officers. V-B Print- if the revised definition had been used initially. The ing Company. [Available from Albany Public Library, revised rankings belie the major snow events associ- 161 Washington Ave., Albany, NY 12210.] ated with these storms.

TABLE A1. Largest storms, ranked from highest to lowest accumulation, that affected Syracuse based on the original definition of a severe snowstorm as having at least 1 in. (2.5 cm) of snow per day and 10 in. (25.4 cm) in total accumulation. Revised dates, amounts, and rank based on defining a severe snowstorm as having at least 3 in. (7.6 cm) per day with at least 14 in. (36 cm) in total. Numbers in italics indicate storms that were studied but would not have been studied under the revised definition. All amounts are inches.

Original Revised Original Revised Original Revised Month Year date(s) date(s) amount amount rank rank Jan–Feb 1966 30–1 30–1 42.3 42.3 1 1 Jan 1994 4–9 4–5 42.2 16.4 2 27 Mar 1993 13–14 13–14 42.0 42.0 3 2 Jan 1992 14–21 18 38.6 19.8 4 14 Mar 1992 11–15 11–14 31.7 30.1 5 4 Feb–Mar 1984 28–3 28–3 30.9 30.9 6 3 Feb 1958 15–20 16–17 29.2 16.9 7 25 Jan 1925 29–30 29–30 27.5 27.5 8 5 Feb 1958 7–10 8–5 25.3 21.1 9 10 Dec 1989 15–17 15–17 25.2* 25.2* 10 6 Dec 1997 30–31 3–31 24.8 24.8 11 7 Dec 1977 5–10 — 24.2 — 12 — Dec 1991 4–6 4–5 24.0 24.0 13.5 8 Dec 2000 23–28 26–27 24.0 15.5 13.5 29 * Amount based on newspaper reports.

1792 | DECEMBER 2005 Branick, M. L., 1997: A climatology of significant win- ——, and ——, 2004b: A snowfall impact scale derived ter-type weather events in the contiguous United from Northeast storm snowfall distributions. Bull. States, 1982–94. Wea. Forecasting, 12, 193–207. Amer. Meteor. Soc., 85, 177–194. Cable, M., 1988: The Blizzard of ’88. Atheneum, McKelvey, B., 1995: Snow in the Cities: A History of 197 pp. America’s Urban Response. University of Rochester Call, D. A. 2004: Urban snow events in Upstate New Press, 248 pp. York: An integrated human and physical geographi- Moran, V. M., L. A. Abron, and L. W. Weinberger, 1992: cal analysis. M.A. thesis, Dept. of Geography, Syra- A comparison of conventional and alternative deic- cuse University, 120 pp. ers: An environmental impact perspective. Chemical Changnon, S. A., Jr., 1969: Climatology of severe winter Deicers and the Environment, F. M. D’Itri, Ed., Lewis storms in Illinois. Illinois State Water Survey Bulletin, Publishers, Inc., 341–361. No. 53, 45 pp. Rooney, J. F., Jr., 1967: The urban snow hazard in the Hart, R. E., and R. H. Grumm, 2001: Using normal- United States: An appraisal of disruption. Geogr. ized climatological anomalies to rank synoptic- Rev., 57, 538–559. scale events objectively. Mon. Wea. Rev., 129, Uccellini, L. W., P. J. Kocin, R. S. Schneider, P. M. Sto- 2426–2442. kols, and R. A. Dorr, 1995: Forecasting the 12–14 Kocin, P. J., 1983: An analysis of the “Blizzard of ’88.” March 1993 superstorm. Bull. Amer. Meteor. Soc., Bull. Amer. Meteor. Soc., 64, 1258–1272. 76, 183–199. ——, and L. W. Uccellini, 2004a: Northeast Snow- Zielinski, G. A., 2002: A classification scheme for winter storms. Meteor. Monogr., No. 54, Amer. Meteor. storms in the eastern and central United States with Soc., 818 pp. an emphasis on Nor’easters. Bull. Amer. Meteor. Soc., 83, 37–51.

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