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    Average snowfall in the Midwest (December–March). Major cities of the region are shown.

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    Study area along with the location of major airports in the Midwest region of the United States. Each airport is identified by its International Air Transport Association (IATA) airport code.

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    Number of delayed flights per meteorological factor in the studied airports. Blue denotes large airports, while light green denotes small airports.

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    Number of days per meteorological factor in the studied airports. Blue denotes large airports, while light green denotes small airports.

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    Combined factors for (a) number of flights per factor and (b) number of days per factor.

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    Combined number of flights and number of days per factor by airport size. Flight statistics for large airports is presented in (a), daily data for large airports is in (b), flight statistics for small airports is in (c), and daily data for small airports is in (d).

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    Delays per factor in each of the large airports in the study. Flight statistics for (a) Chicago O’Hare, (b) Minneapolis, and (c) Detroit.

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    Delays per factor in each of the small airports in the study. Flight statistics for (a) St. Louis, (b) Kansas City, (c) Cleveland, (d) Indianapolis, (e) Milwaukee, and (f) Columbus.

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    Number of cancellations per storm type.

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    Days of cancellation per storm type.

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Meteorological Factors Affecting Airport Operations during the Winter Season in the Midwest

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  • 1 Department of Geography, Ball State University, Muncie, Indiana
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Abstract

During the coldest months of the year, weather systems bring a variety of winter weather to most of the continental United States in the form of snow, sleet, and freezing rain, which along with strong winds, low clouds, and reduced visibilities may create dangerous conditions. These weather conditions can result in major disruptions in air travel, leading to delays and cancellations of hundreds or thousands of flights, thus affecting the plans of millions of travelers. To assess the specific meteorological factors that prompt flight delays and cancellations in the Midwest region of the United States during wintertime, a comprehensive study was performed on nine of the largest airports (by passenger boardings) in the area.

Flight delay and cancellation data from 11 winter seasons (2005–06 to 2015–16) were collected from the Bureau of Transportation Statistics (BTS) and analyzed along with climatological data from the National Centers for Environmental Information (NCEI). A classification scheme was developed, and each flight was categorized according to the meteorological factor that could have prompted its delay. The results of the study revealed that visibility was the main meteorological factor affecting midwestern airports, with low ceilings as a close second. Blizzards were the main cause for flight cancellations.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nathan M. Hitchens, nmhitchens@bsu.edu

Abstract

During the coldest months of the year, weather systems bring a variety of winter weather to most of the continental United States in the form of snow, sleet, and freezing rain, which along with strong winds, low clouds, and reduced visibilities may create dangerous conditions. These weather conditions can result in major disruptions in air travel, leading to delays and cancellations of hundreds or thousands of flights, thus affecting the plans of millions of travelers. To assess the specific meteorological factors that prompt flight delays and cancellations in the Midwest region of the United States during wintertime, a comprehensive study was performed on nine of the largest airports (by passenger boardings) in the area.

Flight delay and cancellation data from 11 winter seasons (2005–06 to 2015–16) were collected from the Bureau of Transportation Statistics (BTS) and analyzed along with climatological data from the National Centers for Environmental Information (NCEI). A classification scheme was developed, and each flight was categorized according to the meteorological factor that could have prompted its delay. The results of the study revealed that visibility was the main meteorological factor affecting midwestern airports, with low ceilings as a close second. Blizzards were the main cause for flight cancellations.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nathan M. Hitchens, nmhitchens@bsu.edu

1. Introduction

Studies by the Federal Aviation Administration’s (FAA’s) observation network have shown that weather is the largest cause of air traffic delays in the national airspace system (NAS), accounting for 69% of all air traffic delays from 2008 to 2013 (FAA 2017a,b). Although 80% of flights are on time [Bureau of Transportation Statistics (BTS) 2017], a fraction of the remaining 20% could be delayed because of weather. The FAA defines a delayed flight as one in which an aircraft departs at least 15 min later than its originally scheduled time. Furthermore, the portion of delays caused by weather represented nearly 10 million minutes in 2013. However, if weather conditions deteriorate to such an extent that it may become dangerous for planes to fly, flights could get canceled instead of delayed. Winter is the season with the most cancellations caused by weather; in fact, during the 2010–11 winter season, between 1 November and 11 February, a total of 86 000 flights were either delayed or canceled throughout the country (BTS 2017). During the cold season, weather systems bring snow, sleet, or freezing rain to most of the continental United States, excluding extreme southern areas of Florida, Arizona, and California because of their warmer and drier climates. Even southern cities such as Atlanta, Dallas, and Memphis have recorded some type of frozen precipitation, per climate records by the National Centers for Environmental Information (NCEI 2017), but in lesser amounts than that experienced by more northern cities such as New York, Chicago, Minneapolis, or Buffalo. In this study, flight data were compared with hourly weather observations to determine the frequency by which different wintertime meteorological factors resulted in delays or cancellations of flights in major midwestern airports.

Besides summer, winter is the year’s busiest travel season because schools and some businesses take a “winter break,” which presents an opportunity to travel; this period also coincides with several holidays, including Christmas and New Year’s Day. The number of long-distance trips [defined as a destination at least 80 km (~50 mi) away] during this period increases by 23% compared to the average number of long-distance trips during the remainder of the year (BTS 2017). According to the BTS (2017), in 2015 there were 679 million enplaned domestic passengers. Although only 5% to 6% of holiday trips are by air, the frequency and strength of winter storms can seriously disrupt travel for passengers, airports, and airlines. This means that hundreds—and sometimes thousands—of flights are canceled or delayed because of winter weather. In fact, in preparation for powerful winter storms, some airlines canceled flights before the actual storm arrived at the airport, as an airline’s flight network operation may be severely disrupted. This has helped not only the airline, but also the airport itself, as it aided in the management process once the storm ended and regular operations resumed (Mouawad 2011).

In the Northern Hemisphere, meteorological winter extends from December through February. However, fluctuations in atmospheric patterns and geography may induce winterlike conditions as early as October or as late as April in some places. As temperatures turn colder, frozen precipitation becomes more common, leading to potential disruptions in daily life activities, including airport operations. For instance, Chin et al. (1997) interviewed different levels of air traffic control (ATC) staff and pilots, who indicated that taxiing slows significantly when ground visibility is less than 0.8 km (0.5 mi) or when there is snow or ice on the surface. But during these times, there tends to be considerably less traffic because of precautionary flight cancellations by airlines. Several weather elements can impact airport operations during the winter and are the main reasons why a flight is delayed or canceled because of weather in the cold season (Table 1).

Table 1.

Main factors affecting airport operations during winter.

Table 1.

Aside from snowfall produced by storm systems, some areas in the United States receive large amounts of frozen precipitation from the meteorological phenomenon known as lake-effect snow. It particularly affects the downwind areas of the North American Great Lakes during late fall and early winter (Wright et al. 2013), producing large amounts of snow during short periods of time in relatively small areas. In fact, for some locales near the Great Lakes, lake-effect snowfall accounts for almost half of their total winter precipitation (Scott and Huff 1996). Snowfall rates as high as 30 cm (~12 in.) h−1 and 75 cm (~30 in.) day−1 have been observed, as has lightning in some of the most intense cases (Markowski and Richardson 2010). The states of Indiana, Michigan, New York, Pennsylvania, and Ohio are the main areas in the United States that are affected by this phenomenon.

The impact of winter weather on flight operations in American airports has been studied in the past, with focus on the Northeast and the south. For instance, Schmidlin (1993) analyzed the impacts that several snowstorms had on civil activities, including airports, during December 1989 in the Lake Erie Snowbelt: the areas of Ohio, Pennsylvania, and New York that border Lake Erie and are prone to lake-effect snow. Data were gathered through surveys sent to key civil services, which included public school districts, universities, hospitals, electric utilities, and local airports. The region’s largest airport, Erie International Airport in Erie, Pennsylvania, received 70 cm (27.56 in.) of snow, which was a monthly record. This airport closed several times during the month due to snow, but none of the closings lasted longer than 6 h. Cerruti and Decker (2011) studied the 9–11 February 2010 snowstorm that affected the northeastern corridor. For instance, at the Newark Liberty International Airport in Newark, New Jersey, the storm started as a mix of rain and snow but quickly changed to heavy snow and resulted in the closing of the airport for several hours. Their results showed that when the variables of snow density and the timing and duration of the strongest winds and heaviest precipitation were combined with diverse degrees of societal susceptibility, it led to disparate impacts in several locations.

Robinson (1989) conducted a study on weather-related delays and cancellations at the Atlanta Hartsfield International Airport using a 3-yr record, which featured various weather events that prompted flight cancellations, including snowfall, which occurs from time to time, leading to major disruptions in the city’s airspace. Three major snowstorms were studied: 1) 31 January 1977, 2) 20–21 January 1983, and 3) 24 March 1983. In 1, 15% of the flights for the day were canceled, with the most between 0500 and 0900 local time. During 2, the storm started as snow but changed over to freezing rain, which prompted 65% of flights to be canceled. Meanwhile, for 3, 47% of flights were canceled, with the storm’s precipitation all falling as snow.

Unlike other weather-related airport delays and cancellations, those related to winter weather not only create problems in rescheduling both aircraft and passengers, but also in the scheduling of crew (Wyckoff and Maister 1977; Robinson 1989). Robinson (1989) concluded that the amount of delays and cancellations depends greatly on the time of storm arrival, as an arrival early in the day when few aircraft are operational allows for cancellations, whereas a late arrival prompts delays since operations at the airport are well under way. Following a more aviation-oriented approach, Weber et al. (1991) were able to construct an Aviation Weather Delay Model (AWDM) to estimate flight delays caused by weather conditions in 20 of the major U.S. airports based on previous data. One key difference between this study and that of Robinson was the number of airports studied and the fact that Weber et al. conducted their study for all four seasons instead of just winter. Only three weather categories were used: thunderstorms, heavy fog, and reduced visibility. Their results presented reduced visibility (52%) as the primary year-round cause for flight delays, while thunderstorms and heavy fog were observed with similar frequencies, 25% and 23%, respectively.

Given that New York City, with an estimated population of 8.5 million in 2015 (U.S. Census 2017), is the country’s most populated city and that major cities like Boston, Philadelphia, and Washington, D.C., lie along the northeastern region of the United States, past studies focused on flight delays and cancellations in airports located within this area; the majority classified the impacts of winter storms at large airports and in the cities themselves. However, most of these studies focused solely on the impacts of a single storm on the Northeast’s aviation system, and little research has been done outside of this geographical region. Likewise, there has been a lack of research into the meteorological factors that prompt disruptions in airport operations; flight delays and cancellations are impacts of a winter storm and are used to measure how disruptive the storm is, but little is known about the specific weather conditions that caused the delays and cancellations.

The purpose of this study is to identify the meteorological factors that prompt flight delays and cancellations during the winter season in the Midwest region of the United States. As previous research only considers airports on the eastern coast of the United States, this study will consider another region that is also severely affected by winter storms and thus will try to cover a geographical area that has not yet been studied. These results present some differences from research performed in the 1980s and 1990s; while Robinson (1989) used snow as his sole cause for delay, this study classifies delays according to its most likely weather-related cause, which may or not be snow. Cancellations were classified according to the magnitude of the storm affecting the region. Another key difference between this study and previous studies is that those studies used few categories to subdivide weather events; in the case of Weber et al. (1991), only three were used.

To achieve this, flight delay and cancellation data, along with meteorological data for several of the Midwest’s largest airports, were retrieved and analyzed. After assessing the weather conditions around the scheduled departure time, the meteorological factor(s) that prompted each flight’s delay were determined; only departures were considered since weather affecting Midwest airports that would delay arrivals would likely already be identified in departures. In the case of cancellations, broad synoptic-scale analyses were made to determine the type of system that prompted them. It must be noted that flights operate within an airline’s network of flights and not individually. As such, each airline must maintain its network integrity in terms of airport operations, crew, and aircraft. As this study focuses on the effect that weather alone has on flights, it does not take into account network effects of airline operations and therefore this study is limited to a flight-by-flight analysis.

2. Data and methods

a. Study area

Much of the study of winter weather impacts in aviation has been made using major airports in the Northeast and southern United States, but no significant study has focused on other regions of the country; the area selected for this study is the Midwest, which is defined by the U.S. Census Bureau as the area comprising the states of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin, putting this region roughly between latitudes 36° and 43°N and longitudes 80° and 104°W. The region’s total population as of the 2010 Census was 66 972 390, accounting for 21.6% of the entire U.S. population. For this study, the Midwest was more narrowly defined as the area comprising the states of Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, and Wisconsin, as they represent 90.7% of the region’s population and are most likely to host the area’s main airports.

The Midwest was also chosen because of the wide range of winter weather events experienced there, as it is in one of the main paths that strong low-pressure systems take during winter. Its relatively high latitudinal location makes it prone to experience longer durations of cold weather, as cold air from the Arctic descends southward into the United States, effectively making the region one that receives all types of winter precipitation, prompting disruptions in all modes of travel. In fact, winter storms are the second most frequent weather-related catastrophe in the region (Winkler et al. 2014).

Average winter temperatures from 1981 to 2010 for the Midwest range from −13°C (~9°F) in the far northern areas of Minnesota to around 2°C (~35°F) in the southern sections near the Ohio River. The same trend is observed regarding snowfall, averaging less than 50 cm (~20 in.) yr−1 in the southern tip of Missouri to more than 350 cm (~138 in.) yr−1 in the exposed northern parts of Michigan (Fig. 1). The areas with the highest annual average snowfall are located on the leeward shores of the Great Lakes because of the lake-effect snow events (Kunkel et al. 2013).

Fig. 1.
Fig. 1.

Average snowfall in the Midwest (December–March). Major cities of the region are shown.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

To select the airports to be studied, the FAA’s list of largest airports by passenger boardings in the United States for the 2014 calendar year was utilized. The list, which includes 550 airports, was narrowed down to the top 50 airports, and from those, the nine largest ones located in the Midwest were selected. As seen in Fig. 2, every state included in the region’s geographical definition, except for Iowa, has at least one major airport; a comprehensive list of these airports is shown in Table 2.

Fig. 2.
Fig. 2.

Study area along with the location of major airports in the Midwest region of the United States. Each airport is identified by its International Air Transport Association (IATA) airport code.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

Table 2.

Largest airports in the Midwest region of the United States by passenger boardings in 2014.

Table 2.

Chicago (the region’s most populated city), unsurprisingly, has the largest airport of the region, located 17 mi northwest of the city’s downtown. To relieve O’Hare International Airport (ORD) from being the sole airport in the city, the Midway International Airport, located about 10 mi west of downtown, serves as Chicago’s secondary airport, handling around a third of the passengers of O’Hare. However, being in the same city, Midway also experiences its fair share of disruptions during extreme winter weather. Although Midway ranked as the twenty-fourth busiest airport in the United States, with 10 311 996 passenger boardings in 2014 (which would rank fourth in Table 2), its data were excluded from this study. The rationale behind this is the fact that O’Hare and Midway lie 15 mi away from each other, a small distance given the area’s geography, landscape, and climate. If a weather system were affecting the Chicago area, both airports would likely be observing similar or nearly identical conditions, and by analyzing both airports, data overlapping could occur; therefore, only data from O’Hare were used.

b. Data collection

To study the level of disruption that these airports experience because of winter weather, data on the amount of flights that were canceled or delayed during 11 winter seasons (2005–06 through 2015–16) were collected from the BTS database. This database contains records pertaining to every kind of travel (air, land, and sea) within the United States, including territories. Information that can be gathered from this database includes national transportation statistics, border crossing/entry data, airspace operations, and the National Household Travel Survey, among others. Data for this study were extracted from the national transportation statistics section of the database, specifically from the subject area of “airlines and airports.” Since this study is focused on delays and cancellations, data were extracted from the “on-time performance” section, which contains records of delayed and canceled flights per month from all commercial airports that are regulated by the FAA. Flights are classified by airline-submitted information on their cause of delay, which follows the five categories that the Air Carrier On-Time Reporting Advisory Committee created in their 2002 assessment to the BTS: air carrier, extreme weather, national aviation system, late-arriving aircraft, and security. As the goal of this study is to see which meteorological factors affect aviation during the winter season, flight data were taken from the extreme weather category. A set of new categories were created for this study, as BTS only classifies the cause of delay or cancellation as “weather” and does not specify what kind of weather prompted the disruption.

Although meteorological winter extends from 1 December to 28/29 February, winter conditions in areas of the Midwest can be experienced beginning around the middle of November and can continue well into the month of March; therefore, data were gathered from 15 November to 15 March for each year. As mentioned previously, the location of the region within the North American continent makes it prone to early and late-season cold episodes that sometimes are accompanied by high winter precipitation amounts. For this reason, the second half of November and the first half of March were included in the data analysis.

The National Weather Service (NWS) is the agency within the United States in charge of issuing watches and warnings in accordance with a specific set of criteria whenever a weather system has the potential to cause any level of disruption. NWS meteorologists use several tools such as satellite images, radars, and both upper-air and surface observations, among others, to forecast the potential impacts that any storm may produce in a specific area. One of those tools, surface observations, is taken by the Automated Surface Observing System (ASOS), which are weather stations that, for the most part, are located on the grounds of airports throughout the nation (NWS 2012) and are the primary source of real-time weather data in the aviation industry. Both traffic controllers and pilots rely on ASOS data to make airplane–airport operation-related decisions such as takeoffs, landings, taxiing, and, in extreme cases if weather conditions warrant, delaying or cancelling departing flights.

Climatological data in the form of the monthly climate summary and the daily hourly weather observations from each airport’s ASOS station were obtained from NCEI’s local climatological records database. The monthly climate summary for a location contains weather statistics for each day of the month, including maximum and minimum temperature, maximum wind speed and gusts, and any significant weather that occurred during a single day. The daily hourly weather observations contain the standard hourly observations for every day of every month that was studied, along with special observations that the weather station reported outside of the standard observations. Special attention was given to the following parameters: surface temperature, surface dewpoint, surface winds (speed and direction), precipitation, cloud ceiling, and visibility. If for any reason any of these parameters was not available, the Iowa Environmental Mesonet archive of the aviation routine weather reports (METARs) was used. METARs are usually issued hourly and serve as a description of the meteorological elements observed at an airport at a specific time.

c. Analysis methods

Data were filtered by selecting the flights that reported weather as their cause of delay and sorted in descending order of the number of minutes each flight was delayed. Considering the FAA’s definition of a delayed flight, delays of at least 15 min were selected first. However, since delays of this small magnitude are not likely to cause major disruptions, minimum connection times were looked at to further narrow the final sample for delayed flights into the most extreme cases. It was found that minimum connecting times for domestic flights in large airports in the United States can be as low as 30 min in extreme cases but usually less than 60 min (Perkins 2015), thus providing little room to afford any delays. By taking an average of this range, and considering the domino effect that a delayed connection may have on the national airspace, only flights with delay durations of at least 45 min were ultimately considered for inclusion. Given the great disparity in passenger boardings between the top three airports included in this study and the remaining six airports [Table 2; a difference of nearly 10 million passengers existed between Detroit Metropolitan Wayne County Airport (DTW) and Kansas City International Airport (MCI)], two different approaches were taken to obtain a representative sample of data from each airport; they were divided in two categories: large airports and small airports. For large airports, the 35 days with the most delays were taken from each airport, while for small airports, the top 10% of days with delayed flights were used. This sampling process provided an adequate distribution of flights per airport and avoided focusing too much on the three largest airports in the study region at the expense of the others.

After each delayed flight was sorted in descending order by the scheduled time of departure, NCEI’s hourly weather observations from each airport were assessed by looking at the weather parameters 1 h before the scheduled departure time of each delayed flight to determine which meteorological factor(s) had the most influence in the decision to delay the flight. This determination was made using a classification scheme based on the FAA’s factors for delaying flights (Table 3; FAA 2008). The classification scheme for this study consists of 11 categories (factors), with criteria definitions that were derived from NWS, FAA, and International Civil Aviation Organization (ICAO) guidelines and adapted accordingly.

Table 3.

The classification scheme used to determine the cause of flight delays or cancellations.

Table 3.

If the cause of a delay could not be determined from the available weather data, it was classified as “unknown.” Examples of situations in this category include clear skies, light winds, and no obstructions to visibility. In some cases, fair weather was occurring at the departing airport, but inclement weather was occurring at other airports that may affect the departure of planes headed to the departing airport; these cases are known as upstream delays and also fell under the unknown category. An example of this may be that clear conditions were reported at Indianapolis International Airport (IND), but a scheduled flight from IND to Los Angeles International Airport (LAX) was delayed because of weather. The plane covering this route flew from New York, having John F. Kennedy International Airport (JFK)–IND as its first leg, but because there was inclement weather in New York, the plane was not able to depart on time. The flight dataset used in this study did not specify the origin airport (in the example, JFK), so limitations existed in knowing from which airport the plane covering the main route (IND–LAX) came. Nevertheless, it was a delay in one of the airports studied and would be counted as such despite its cause remaining unknown. In addition, propagated delays were also not included in this study. Once each flight was classified in one of these categories, a final tally was performed to determine which meteorological factor was most prevalent in influencing delays of flights during the winter season in nine of the major airports in the Midwest.

The selection process for the sample of canceled flights was slightly different than for delays, since canceled flights do not have any duration associated with them. Instead, flights were filtered by the number canceled per day. It was found that the nine airports had a combined 1138 days with fewer than 75 canceled flights per day, accounting for 85.1% of flights. Choosing to focus on the days when weather was most disruptive to air travel, only days with at least 300 combined cancellations between the airports were examined. Cancellations were also sorted by scheduled departure time and categorized by the type of storm that broadly affected airport operations (Table 4) using the monthly climate summary for each airport from each month of the sample. The determination of what type of storm affected each airport was done according to the overall weather conditions during the storm’s duration.

Table 4.

Types of storms that can cause flight cancellations. Definitions adapted from the NWS glossary.

Table 4.

3. Results and discussion

An analysis of the data was performed on nine airports in the Midwest over 11 winter seasons spanning from 2005–06 through 2015–16, where both flight delays and flight cancellations were assessed. However, these flight disruptions were approached in different ways, as specific weather factors leading up to delays could be extracted from an airport’s climatological data, whereas cancellations were mostly produced by large, complex weather systems that affected entire regions, not only specific airports.

a. Delays

There was a total of 8399 delayed flights among all nine airports, and from those, 4771 flights (53.2%) had a weather-related delay of at least 45 min. The absolute number of delayed flights was used instead of percentages to observe a wider range of delays within the selected airports. As expected, Chicago’s O’Hare International Airport had the largest share of delays from this subset, with 2956 (61.9%), as seen in Table 5. Each airport experienced at least one factor listed in Table 3, although the only one in which every factor alone contributed to delays was Detroit. Low visibility caused by snow was the leading cause of flight delays, being the meteorological factor responsible for the delay of 1041 flights (Fig. 3), accounting for approximately 21.8% of all delays. Following that, 688 flights (14.4%) were affected by ceilings that were severely reduced to the point that the sky was completely obscured and only vertical visibility was reported. The third most frequent reason for delays, ice, which required planes to undergo deicing measures, was responsible for the delay of 608 flights (12.7%). For its part, wind alone was the factor that contributed the least to the number of weather-related delays, with only 25 flights (0.52%) delayed. However, wind was one of the factors that affected 91 of the 598 flights that were delayed because of a combination of factors, which was the fourth most common cause of delays.

Table 5.

Number of delayed flights per factor in each studied airport.

Table 5.
Fig. 3.
Fig. 3.

Number of delayed flights per meteorological factor in the studied airports. Blue denotes large airports, while light green denotes small airports.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

Winter storm systems have a “warm side,” which leads to precipitation falling as rain and can even produce severe weather events in more southern locales; therefore, a category for thunderstorms was included in the classification scheme. In all, 57 flights (1.1%) appeared to be delayed because of this factor, with almost three-quarters of them occurring in Detroit and Milwaukee. By looking at the temporal distribution of these thunderstorm-related delays, it was found that Detroit’s occurred in mid-March, which is expected, as this month marks the transition between winter and spring. On the other hand, Milwaukee’s delays were rather surprising, as they occurred in mid-January, an unlikely time of year for this type of event, as the combination of less humid air and colder surface temperatures may prevent the formation of strong updrafts [National Severe Storms Laboratory (NSSL) 2017].

Flight delays were further analyzed by the number of days on which each factor was identified; if multiple factors caused delays at an airport on a certain day, it was counted as one day for each factor. In total, there were 408 days with delayed flights among all airports. As seen in Fig. 4, low visibility caused by snow was again the factor that affected the most flights, with 79 of the 408 days (19.3%) having at least one delay because of it. Following that, low ceilings accounted for 70 days (17.1%), and with 12.9% of days, a combination of factors was the third most frequent.

Fig. 4.
Fig. 4.

Number of days per meteorological factor in the studied airports. Blue denotes large airports, while light green denotes small airports.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

1) Common factors

Based on the results described above, many delays were caused by two main factors: reductions in visibility caused by snow and low ceiling heights from either low clouds or obscured skies. Although visibility, low ceilings, and ice were expanded to two or more categories in the analysis presented above to provide more specific information about the causes of delays, it is instructive to examine these factors as a whole to identify overarching trends in flight delays. For the following analysis, the three subcategories relating to reduced visibility—fog, snow, and blowing snow—were consolidated into a single visibility category, low ceilings because of clouds and obscured skies were combined into a low ceilings category, and icy precipitation and deicing into the ice category.

It is seen in Fig. 5a that these three consolidated factors account for more than 75% of delayed flights. Moreover, 58% of flights were delayed by either visibility or low ceilings, leaving these two factors as the primary causes for flight delays in midwestern airports during the winter, with visibility (32%) delaying flights slightly more frequently than low ceilings (25%). The number of days with visibility and low ceilings were very close (Fig. 5b), differing by only 1%. When airports were again grouped by size, similar frequencies were observed, with visibility and low ceilings resulting in the most delays. As shown in Figs. 6a and 6b, large airports followed the overall proportion seen in all airports, while small airports (Figs. 6c,d) experienced more visibility-related delays.

Fig. 5.
Fig. 5.

Combined factors for (a) number of flights per factor and (b) number of days per factor.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

Fig. 6.
Fig. 6.

Combined number of flights and number of days per factor by airport size. Flight statistics for large airports is presented in (a), daily data for large airports is in (b), flight statistics for small airports is in (c), and daily data for small airports is in (d).

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

It was shown that visibility and low ceilings were the main factors that affected airport operations in the Midwest during the winter season. As Roebber et al. (1998) found in their study, November through March had the highest percentage of hours per month with overcast conditions in comparison to the summer months in the city of Milwaukee, Wisconsin, based on climate averages calculated from 1961 to 1990. Therefore, it can be said that given the high frequency of winter storms, the generally cold temperature pattern, and the relative low sun angle, winter is the season with the cloudiest days in the region, which affects both ceilings and visibility. Furthermore, according to Martin (2017), the frequency of the instrument meteorological conditions in areas of the Midwest, including Illinois, Indiana, and Ohio, exceeds 50% during the winter, which indicates that low ceilings and visibility are often present in these areas. This finding by Martin is supported by the results of this study.

One way to assess the extent of disruptions caused by a single factor, and to address the disparity between airport size, was to separate airports into two categories: large airports [DTW, Minneapolis–Saint Paul International Airport (MSP), and ORD] and small airports [Cleveland Hopkins International Airport (CLE), John Glenn Columbus International Airport (CMH), IND, MCI, General Mitchell International Airport (MKE), and St. Louis Lambert International Airport (STL)]. An in-depth analysis of both categories, along with the most common factors for delays, is presented in the following subsections.

2) Large airports

Because of their size and status as hubs for major U.S. carriers, these large airports contributed most of the delayed flights with a total of 4174, which accounted for 87.4% of all delays in this study; the leading factor was low visibility caused by snow with 912 flights (Fig. 3) or 21.8%. Chicago had the most flights delayed because of low visibility from snow (712), with Minneapolis and Detroit having 99 and 101, respectively. Among these flights, reductions in visibility ranged from 0.125 (~0.19 km) to 3 mi (~4.8 km), with a median of 1.56 mi. The next most frequent factor leading to delayed flights, with 618 (14.8%), were situations in which only vertical visibility was reported because of an obscured sky. Following that was plane deicing with 14.0% (586) of flights delayed. The factor that produced the least number of delays at these airports was wind, with only 19 flights (0.45%) meeting this classification. Low visibility caused by snow and low ceilings were the two leading factors when considering the amount of days that had delays, with 18.6% and 17.3% of all days, respectively; these three airports had a combined 289 delay days (Fig. 4).

(i) O’Hare International Airport (Chicago, Illinois)

Located in the Midwest’s population epicenter, O’Hare International Airport is the largest airport of this group, and, as such, it experienced the majority of delays. From the nearly 3000 disrupted flights reported at O’Hare, 24.0% were delayed because of poor visibility caused by snow falling on airport grounds, and falling precipitation or low clouds obscuring the sky was the second most common factor, with 15.1% of delayed flights (Fig. 7a). Unique to this airport in this study, delays at O’Hare presented major disruptions in the entire U.S. airspace, resulting from its position as a major hub for many airlines in the country. These data reflect that status, revealing that departing flights to 153 domestic airports—including warm-weather destinations such as Miami, Honolulu, and San Juan—were delayed: the most for any airport in the study.

Fig. 7.
Fig. 7.

Delays per factor in each of the large airports in the study. Flight statistics for (a) Chicago O’Hare, (b) Minneapolis, and (c) Detroit.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

(ii) Minneapolis–St. Paul International Airport (Minnesota)

As the northernmost and, on average, snowiest of the nine airports studied, it is not surprising that reduced visibility caused by snowfall was the leading meteorological factor at the Minneapolis–St. Paul International Airport, with 20.2% of delayed flights attributed to this factor (Fig. 7b). Low ceilings because of obscured skies was the second most common factor affecting airplane departure, accounting for 16.1% of these data. A combination of factors was the third most frequent cause of delays with 14.7%.

(iii) Detroit Metropolitan Wayne County Airport (Michigan)

Michigan’s primary airport was the only one in this study that experienced flight delays caused by every factor (Table 2). All factors were nearly evenly distributed; however, as seen in Fig. 7c, 17.2% of flights were delayed because of low clouds, making it the leading cause of disruptions. There were at least five instances during each month in which half of the delayed flights encountered ceiling heights of 500 ft or less. A combination of factors and low visibility caused by snow were the second and third most frequent, accounting for 15.1% and 13.8% of flights, respectively. Detroit was also one of the airports that had delayed flights because of thunderstorm events near the airport, with 3.9% of its data categorized as such.

3) Small airports

The other six airports accounted for the remaining 597 flights (12.6%) in the dataset, and despite having a significantly lower number of flights and passengers, these smaller airports also reflected the overall distribution of flight delays by factor, with low visibility caused by snowfall as the main factor leading to delays (22.6%; Fig. 3). Cleveland, Milwaukee, and St. Louis had 35, 37, and 31 flights delayed, respectively, in this category, the most among these six airports. Differing from the overall distribution, and the distribution associated with the three large airports, the next most frequent factor was a combination of individual factors that led to the delay of 113 flights (18.9%). All factors were represented in these combinations, with the most frequent including low visibility caused by blowing snow (in several instances visibility was as low as zero miles), fog, strong winds, and icy precipitation. The two main factors at these airports, when looking at the number of days with delays in Fig. 4, was low visibility caused by snow (21.0%) and low ceiling (16.8%), of the 119 total days with delays.

(i) St. Louis Lambert International Airport (Missouri)

Although it is the southernmost airport in the study, St. Louis had 25% of its flights delayed because of snow, reducing visibility to 3 mi or less. Icy precipitation created problems for 16 flights (14.8%), while low ceilings alone accounted for 12 flights (11.1%) delayed. Combinations of low visibility, low clouds, high winds, or fog were the second most common cause for delays at this airport (Fig. 8a).

Fig. 8.
Fig. 8.

Delays per factor in each of the small airports in the study. Flight statistics for (a) St. Louis, (b) Kansas City, (c) Cleveland, (d) Indianapolis, (e) Milwaukee, and (f) Columbus.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

(ii) Kansas City International Airport (Missouri)

Kansas City was the second airport to have a large portion of its flights delayed because of a combination of factors; as can be seen in Fig. 8b, 38.7% of its flights dealt with this issue. The main factors that contributed to these combinations were low ceiling, poor visibility caused by snow, and freezing rain. There were six instances when flights were delayed because of thunderstorms, all of them on a single day: 27 December 2008 in the early morning hours. Temperatures were not especially warm, but the wind pattern in the area suggested a cold front was passing through, which likely initiated convection.

(iii) Cleveland Hopkins International Airport (Ohio)

Cleveland Hopkins International Airport is located 9 mi southwest of the central business district of Cleveland, Ohio, and because of its proximity to Lake Erie, the airport’s climate is greatly influenced. With respect to this study, lake-effect snow and strong winds were major factors that contributed to flight delays (Fig. 8c). This airport was one of two that had a combination of factors as the main cause of flight delays, although low visibility because of snow was also a significant contributor. Main factors contributing to the 37 delays in Cleveland were high winds, blowing snow, and freezing fog.

(iv) Indianapolis International Airport (Indiana)

Located in the southwestern corner of the city of Indianapolis, this airport had the lowest number of delays of all the airports studied, with just 45 during the 10-yr study period. About 42.2% of them were due to skies being obscured, impeding the horizontal view (Fig. 8d). In all of these instances heavy snowfall was observed, and although snow was the primary reason for the reduction in ceiling heights, an obscured sky was classified as a different factor since vertical visibility was treated as a ceiling measure rather than a visibility measure.

(v) General Mitchell International Airport (Milwaukee, Wisconsin)

Milwaukee’s airport had about 40.6% of departures delayed because of snow reducing visibilities, and 19.7% were because of instances where vertical visibility was an issue for planes, as seen in Fig. 8e. This airport, along with Kansas City, had flights delayed because of thunderstorms during a time of the year that is not typically expected based on climatology. While only 13 flights were delayed because of thunderstorms, it is notable since this occurred in early January. Temperatures were just above 60°F prior to thunderstorm development on the day they occurred, which could have been a contributing factor.

(vi) John Glenn Columbus International Airport (Ohio)

Because of its large distance from Lake Erie, this airport has a more continental climate compared to Cleveland, and it averages less annual snowfall. Therefore, is not surprising that icy precipitation in the form of freezing rain or ice pellets was the primary factor for delays at this airport, with 33 of the 95 flights having departed later than scheduled (Fig. 8f). Low visibility caused by snowfall was responsible for 20 delayed flights, making it the second most common factor at this airport.

b. Cancellations

During the study period, there were a total of 28 days with 300 or more cancellations for a total of 15 512 weather-related cancellations throughout the nine midwestern airports. As seen in Table 6, similar to delays, Chicago’s O’Hare International Airport had the largest number of cancellations with 9325, while Columbus International Airport had the fewest, with 437. Since O’Hare is clearly an outlier, the other eight airports were analyzed separately; cancellations average 773 per airport during the 28 days studied, and the average number of flights canceled per day was 220. Detroit stands out as the airport with the most cancellations, while Columbus had the least. Indianapolis, which had the least number of delays during the period, was second to Columbus in cancellations.

Table 6.

Number of canceled flights per airport during the study period.

Table 6.

When comparing cancellation frequencies by category, most were due to blizzards (55%; Fig. 9), while snowstorms accounted for a significant proportion (31%) as well. Of the 28 days that saw at least 300 canceled flights across all airports, 13 had blizzard conditions (Fig. 10), which relates to the high number of individual flights that were canceled. From an airport operation perspective, blizzard conditions are particularly dangerous for any flight, as they represent possible reductions to visibility, heavy snow, and strong winds, while crosswinds may also be present.

Fig. 9.
Fig. 9.

Number of cancellations per storm type.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

Fig. 10.
Fig. 10.

Days of cancellation per storm type.

Citation: Weather, Climate, and Society 10, 2; 10.1175/WCAS-D-17-0054.1

4. Conclusions

The purpose of this study was to identify the meteorological factors that prompt flight delays and cancellations during the winter season in the Midwest region of the United States. Because of the high latitude of the area, winter conditions in the Midwest may extend from mid-November to mid-March, bringing high amounts of wintry precipitation, strong winds, and extended periods of cloudiness and cold temperatures. Aviation is one of the first areas affected by these hazards, prompting the delay or cancellation of flights. To discover the exact causes of flight delays and cancellations, data from 11 winter seasons (2005–06 to 2015–16) were analyzed to determine the meteorological factors that most affected airport operations in the Midwest. Since winter weather conditions may be experienced both very early and very late in the season, the period from 15 November to 15 March was selected to conduct the study. Data were collected from several sources such as the Bureau of Transportation Statistics, Federal Aviation Administration, National Centers for Environmental Information, and the Iowa Environmental Mesonet.

Airport selection was performed using a list of the largest airports by passenger boardings in the nation; nine airports in the region were selected. All states in the area, except for one, had at least one airport in the final sample. Because of the large disparity between their sizes, airports were further divided into two categories: large and small. For delays, large airports had a sample that consisted of the 35 days with the most delays from each airport, while for small airports the top 10% of delayed flights per day were used. Finally, to correctly assess meteorological data, delays and cancellations were analyzed differently.

Results revealed that visibility reductions of 3 mi or less caused by snowfall was the meteorological factor that caused the most delays among the nine airports studied. When joining all low visibility and low ceilings categories into one, low ceilings and visibility are the two main factors that affected airport operations in the Midwest during the winter season. Likewise, low visibility was the factor with most delay days. Although there was a marked difference between airport sizes, both large and small airports shared the overall distribution of flights delayed by factor, with low visibility caused by snowfall as the main factor for delays. Based on an examination of the snowfall climatology of the area, it is not surprising that this type of winter precipitation was the cause for lower visibilities in the region. Blizzards were the most common cause for cancellations, with more than half of all canceled flights the result of this type of weather event. Likewise, the most days with cancellations occurred during blizzard conditions. By being the most hazardous weather event in the cancellation categories, blizzards were the most likely to affect the most flights in the area.

These results present some differences with the previous research performed in the 1980s and 1990s. For instance, Robinson (1989) cited only “snow” as a cause for delays and cancellations in the Atlanta airport, whereas this study presents visibility caused by snow as the primary cause for delays. Although this study differed from Robinson’s, its results agree with those of Weber et al. (1991), as both present reduced visibility as the main cause for flight delays. In the case of Weber et al., their study examines the primary cause for flight delays by classifying them according to the most likely weather-related cause and cancellations according to the magnitude of the storm affecting the region. This study differs from theirs in that Weber et al. only used three categories to subdivide weather events: thunderstorms, heavy fog, and reduced visibility.

The choice of study period (15 November to 15 March) was effective in not only capturing the entirety of winter weather–related delays, and thus providing enough data to conduct the study, but also capturing a variety of disruptive weather events, including thunderstorms, which are not common during the colder months. Dividing airports by size proved to be very useful, as not all airports handle the same quantity of flights and passengers, and if left all grouped in one single group, results would have been biased toward the largest airport, in this case Chicago. If this were the case, this study would have neglected the region’s smaller airports, and the purpose of the study would not have been achieved.

This study could serve as a guideline for potential travelers, airlines, and airports, which may use it to better understand weather conditions surrounding winter in the Midwest and how to foresee possible delays because of low visibilities. Winter weather researchers could also benefit from this study as it may serve as a climatological record for the area and as proof of how strong winter storms can affect a society’s day-to-day activities. The study may be extended by focusing on those midwestern airports that rank 51–100 on the FAA’s list, which may provide a better insight into the operational impact winter weather has on smaller airports. Other future work may include focusing exclusively on specific holidays such as Thanksgiving and Christmas, which are dates when airports experience a significant rise in the number of travelers and also to compare the results from this study using arrivals that were delayed because of weather.

Acknowledgments

The authors thank Dr. Petra Zimmermann and Dr. David Call for their helpful comments and suggestions and Dr. Adam Berland for his guidance in creating the maps included in this study. The constructive comments and suggestions made by three anonymous reviewers helped to improve the manuscript.

REFERENCES

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