Lee Waves Associated with a Commercial Jetliner Accident at Denver International Airport

Teddie L. Keller National Center for Atmospheric Research,* Boulder, Colorado

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Stanley B. Trier National Center for Atmospheric Research,* Boulder, Colorado

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William D. Hall National Center for Atmospheric Research,* Boulder, Colorado

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Robert D. Sharman National Center for Atmospheric Research,* Boulder, Colorado

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Mei Xu National Center for Atmospheric Research,* Boulder, Colorado

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Yubao Liu National Center for Atmospheric Research,* Boulder, Colorado

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Abstract

At 1818 mountain standard time 20 December 2008, a Boeing 737 jetliner encountered significant crosswinds while accelerating for takeoff at the Denver International Airport (DIA), ran off the side of the runway, and burst into flames. Passengers and crew were able to evacuate quickly, and, although there were injuries, there were no fatalities. Winds around the time of the accident were predominantly from the west, with substantial spatial and temporal speed variability across the airport property. Embedded in this mostly westerly flow were intermittent gusts that created strong crosswinds for the north–south runways. According to the report from the National Transportation Safety Board, it was one of these strong gusts that initiated the events that led to the runway excursion and subsequent crash of the aircraft. Numerous aircraft reported significant mountain-wave activity and turbulence over Colorado on the day of the accident. To determine whether wave activity may have contributed to the strong, intermittent gustiness at DIA, a high-resolution multinested numerical simulation was performed using the Clark–Hall model, with a horizontal grid spacing of 250 m in the inner domain. Results from this simulation suggest that the surface gustiness at DIA was associated with undulations in a train of lee waves in a midtropospheric stable layer above the airport, creating regions of higher-velocity air descending toward the surface. In contrast, a simulation with horizontal grid spacing that was similar to that of a state-of-the-art operational forecast model (3 km) did not predict strong winds at DIA.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Teddie L. Keller, National Center for Atmospheric Research, Research Applications Laboratory, P.O. Box 3000, Boulder, CO 80307. E-mail: tkeller@ucar.edu

Abstract

At 1818 mountain standard time 20 December 2008, a Boeing 737 jetliner encountered significant crosswinds while accelerating for takeoff at the Denver International Airport (DIA), ran off the side of the runway, and burst into flames. Passengers and crew were able to evacuate quickly, and, although there were injuries, there were no fatalities. Winds around the time of the accident were predominantly from the west, with substantial spatial and temporal speed variability across the airport property. Embedded in this mostly westerly flow were intermittent gusts that created strong crosswinds for the north–south runways. According to the report from the National Transportation Safety Board, it was one of these strong gusts that initiated the events that led to the runway excursion and subsequent crash of the aircraft. Numerous aircraft reported significant mountain-wave activity and turbulence over Colorado on the day of the accident. To determine whether wave activity may have contributed to the strong, intermittent gustiness at DIA, a high-resolution multinested numerical simulation was performed using the Clark–Hall model, with a horizontal grid spacing of 250 m in the inner domain. Results from this simulation suggest that the surface gustiness at DIA was associated with undulations in a train of lee waves in a midtropospheric stable layer above the airport, creating regions of higher-velocity air descending toward the surface. In contrast, a simulation with horizontal grid spacing that was similar to that of a state-of-the-art operational forecast model (3 km) did not predict strong winds at DIA.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Teddie L. Keller, National Center for Atmospheric Research, Research Applications Laboratory, P.O. Box 3000, Boulder, CO 80307. E-mail: tkeller@ucar.edu

1. Introduction

At 1818 mountain standard time (MST) on 20 December 2008 (0118 UTC 21 December) Continental Airlines flight 1404 was accelerating for takeoff to the north on runway 34R at Denver (Colorado) International Airport (DIA) when it was hit by a strong westerly crosswind gust. The captain reported it felt as though “someone put their hand on the tail of the airplane and weathervaned it to the left” [from the National Transportation Safety Board (NTSB) report; NTSB 2010]. The aircraft ran off the left side of the runway, bumped across uneven terrain, briefly became airborne, and then came to rest just north of fire station 4 at DIA (Fig. 1). Although the aircraft sustained substantial damage and became engulfed in flames, the passengers and crew escaped quickly and there were no fatalities.

Fig. 1.
Fig. 1.

Photographs of Continental Airlines flight 1404 at DIA taken after the accident that occurred at 0118 UTC 21 Dec 2008. (a) Aerial view showing the aircraft track departing runway 34R. The aircraft is circled in red. Part of the runway is visible in the lower right, and the building on the left side of the picture is fire station 4. (b) Close-up of the burned-out wreckage of the fuselage.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Winds at the airport around the time of the accident were extremely variable. Prior to the airplane pushing back from the gate, the automatic Airport Terminal Information Service reported winds of 11 kt (5.7 m s−1) at 270° magnetic. By the time the aircraft was positioned on the runway ready for takeoff, the local controller reported a wind speed of 27 kt (14 m s−1); although stronger, these winds were still within the airline’s published guideline for a maximum crosswind [33 kt (17 m s−1)] during takeoff (NTSB 2010). The stronger winds were also noted visually by the captain, who remarked “looks like…some wind out there,” and then “oh yeah, look at those clouds moving” while the plane was positioned on the runway and awaiting takeoff (NTSB 2010).

The NTSB report cited pilot error as contributing to the aircraft deviating off the side of the runway, but the initiating event was the strong and unexpected crosswind gust. Early in the investigation, the NTSB requested assistance from the National Center for Atmospheric Research (NCAR) in evaluating the meteorological conditions that contributed to the gustiness on the day of the accident. To this end, a high-resolution numerical simulation was performed, and the results suggested that lee-wave activity likely played a role in generating the wind gusts (NTSB 2009; discussed in section 4).

Gravity-wave activity was widespread over Colorado on that day, as confirmed by numerous pilots who reported both turbulence and wave motion and by wave patterns in satellite imagery. It is well known that large-amplitude mountain gravity waves may be manifested at the surface as strong downslope flow with gusty surface winds. A classic example is the 11 January 1972 windstorm in Boulder, Colorado, during which instrumented aircraft documented a very large amplitude wave, as well as significant turbulence, throughout the depth of the troposphere over the eastern foothills of the Rocky Mountains (Lilly and Zipser 1972). The wave trough extended downward near Boulder, and wind speeds in Boulder varied in conjunction with the temporal oscillation in the position of the main trough (Lilly 1978). Since then extensive research has been devoted to understanding large-amplitude quasi-hydrostatic mountain-wave dynamics, wave breaking and turbulence, and the link with strong downslope winds in Boulder and other locations in the lee of mountainous terrain (e.g., Klemp and Lilly 1975, 1978; Peltier and Clark 1979; Smith 1979, 1985; Durran 1986, 1990; Neiman et al. 1988; Clark et al. 1994, 2000; Wurtele et al. 1996; Ralph et al. 1997b; Doyle et al. 2000; among many others). Boulder is located much closer to the base of the Rocky Mountains than DIA, however, and strong surface winds associated with classic Boulder windstorm conditions are often confined to regions closer to the foothills (e.g., Brinkmann 1974). In fact, on the day of the accident at DIA Boulder did not experience a severe windstorm, and from 0000 to 0300 UTC the maximum wind gust measured at NCAR, located in Boulder, was less than 25 m s−1 (J. Brown 2009, personal communication).

Recent studies have found that amplifying nonhydrostatic lee waves extending downstream of mountainous terrain may generate gusty surface winds. For instance, unsteadiness and high spatial variability in wind speeds over flat terrain downwind of topography associated with lee waves aloft have been observed during field experiments in northern England (Sheridan et al. 2007) and near an airfield in the Falkland Islands (Mobbs et al. 2005). In the idealized simulations of Vosper (2004), lee waves amplifying in an inversion layer atop a neutral boundary layer created regions of acceleration (deceleration) beneath the lee-wave troughs (crests). Doppler lidar observations of significant velocity perturbations with flow reversal beneath lee waves in a stable layer have been well documented (Ralph et al. 1997a). Many other studies have demonstrated a connection between surface wind variability, including the formation of low-level rotors, with lee waves aloft (e.g., Doyle and Durran 2002; Hertenstein and Kuettner 2005; Darby and Poulos 2006; Grubišić and Billings 2007; Grubišić et al. 2008; Vosper et al. 2006, 2013).

In this paper, we address the atmospheric conditions that contribute to the gustiness at DIA on the day of the accident. Observations are presented in section 2. The synoptic-scale meteorological conditions are discerned using an operational-model analysis in section 3. A high-resolution nonhydrostatic numerical simulation, with 250-m horizontal grid spacing in the innermost domain, shows that the intermittent gustiness at the surface was likely caused by undulating lee waves in a midtropospheric stable layer above DIA (section 4). Section 5 addresses whether a state-of-the-art high-resolution operational forecast model, the NOAA High-Resolution Rapid Refresh (HRRR) model (http://rapidrefresh.noaa.gov/hrrr/), is able to reproduce the strong winds at DIA and provide forecast guidance for these types of events. Conclusions are presented in section 6.

2. Meteorological observations

Meteorological observations around the time of the accident, including wind sensors at DIA, satellite imagery, and pilot reports of waves and turbulence, are discussed in this section.

a. Surface wind sensors at DIA

Denver International Airport is equipped with a Low Level Windshear Alert System (LLWAS; http://www.ral.ucar.edu/projects/llwas/), consisting of 32 surface wind sensors that are located near the runways (represented by the pink circles in Fig. 2). These sensors report a running 2-min-average wind speed and direction every 10 s. Also located at DIA are two surface stations, indicated by the green triangles in Fig. 2, that are part of NCAR’s Weather Support to Deicing Decision Making (WSDDM) program and provide temperature and relative humidity in addition to wind information (Rasmussen et al. 2001; http://www.ral.ucar.edu/projects/wsddm/). The WSDDM sensors sample every 10 s and report a 1-min-average and maximum wind speed that are based on sampling over the previous minute.

Fig. 2.
Fig. 2.

Schematic of the DIA property. Black lines represent the runways, and the corresponding runway numbers are indicated in the blue boxes. Runways are numbered according to their approximate magnet heading (divided by 10). Thus runways 34L and 34R, which are oriented approximately north–south (351.5° magnetic), refer to the southern end of the two parallel runways (left and right) marked 16R-34L and 16L-34R. Pink circles indicate the locations of the 32 LLWAS wind sensors. WSSDM surface stations are marked by the green triangles. The approximate location at which the aircraft departed runway 34R is indicated by the arrow.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

LLWAS wind vectors for 0118 UTC 21 December are plotted in Fig. 3. At this time the winds were predominantly from the west, creating a direct crosswind for the north–south runways, with the strongest wind speeds occurring in a swath across the middle of the airport property. To the south of the runways, winds were light and variable. The three LLWAS stations closest to runway 34R are circled. Station 3, located at the northern end of 34R, is used to advise aircraft departing this runway. Station 2, closest to the initial rollout for planes departing to the north, is used to report wind conditions to incoming aircraft about to land on 34R. Station 29 is to the west of the middle of the runway, that is, upwind on this day.

Fig. 3.
Fig. 3.

Wind speed and direction (red vectors) from the 32 LLWAS wind sensors at 0118:02 UTC 21 Dec 2008. LLWAS wind direction has been converted from magnetic to true north. Stations 2, 3, and 29, the three LLWAS stations closest to the location where the aircraft departed runway 34R (marked by the X), are circled in blue. At this time a maximum wind speed of 19 m s−1 (37 kt) was recorded at station 2.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

These three LLWAS stations recorded substantial temporal and spatial wind variability near runway 34R around the time of the accident (Fig. 4). Two minutes prior to the accident, station 3, located near the northern end of 34R, reported a wind speed of 11.8 m s−1 (23 kt) while station 2, located at the southern end of the runway and closer to the beginning of the takeoff roll, recorded a maximum wind speed of 20.6 m s−1 (40 kt). This higher wind speed was not conveyed to the pilots of flight 1404, however, since LLWAS station 3 is the official station used to report winds to aircraft departing runway 34R (NTSB 2010). Wind speeds at station 29, upwind of the middle of the runway, were also extremely variable during this time.

Fig. 4.
Fig. 4.

Time-series plot of wind speed for the three LLWAS stations closest to runway 34R (see Figs. 2 and 3) from 0030 to 0200 UTC 21 Dec 2008, approximately 45 min before and after the accident. The vertical dashed line indicates the time of the accident. Station 2 (red) is closest to the southern (rollout) end of the runway. Station 3 (green) is used to advise aircraft departing 34R of the wind conditions. Station 29 (blue) is to the west (upwind on this day) of the middle of runway 34R.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Temperature, average wind speed, and maximum gusts from the two WSDDM surface stations are plotted in Fig. 5 for the same time period. Prior to 0035 UTC, temperatures slowly decreased (sunset occurred at 2339 UTC 20 December); after ~0050 UTC, both temperature and wind speed began to increase (Fig. 5). During the 10-min interval surrounding the time of the accident, from approximately 0113 to 0123 UTC, there was a rapid jump in both wind speed and gustiness, with maximum gusts of 16.3 m s−1 (31.7 kt) and 18.9 m s−1 (36.7 kt) at WSDDM stations 1 and 2 (identified as A and B, respectively, in Fig. 2). Rising temperatures accompanied the wind speed increases at both stations. Distinct temporal undulations in the wind speed trace are clearly evident in Fig. 5b from 0115 to 0135 UTC. The wind direction was approximately constant throughout this period, and relative humidity (not shown) decreased when wind speeds, gustiness, and temperature increased. These features are consistent with descending motion in the vicinity of DIA.

Fig. 5.
Fig. 5.

Time series of temperature (solid line), wind speed (dotted line), and maximum wind gust (dashed line) for the two WSSDM stations (a) DIA1 and (b) DIA2 from 0030 to 0200 UTC 21 Dec 2008, approximately 45 min before and after the accident. Locations of WSSDM sensors DIA1 and DIA2 are marked by the green triangles labeled A and B, respectively, in Fig. 2. The vertical dashed line indicates the time of the accident.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

b. Soundings

Both the Denver and Grand Junction, Colorado, soundings at 0000 UTC 21 December exhibit a deep, almost neutral, boundary layer extending up to about 600 hPa, topped by a midtropospheric stable layer (Fig. 6). Within the 150–200-hPa-deep stable layer, the westerly/northwesterly winds increase rapidly with height.

Fig. 6.
Fig. 6.

Plots of the National Weather Service 0000 UTC 21 Dec 2008 radiosonde data for (a) Denver and (b) Grand Junction, whose locations are depicted in Fig. 7. The images were obtained from the University of Wyoming Department of Atmospheric Science (http://www.weather.uwyo.edu/upperair/sounding.html).

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

A stable layer above mountaintop in the background flow is a feature often identified with mountain-induced large-amplitude mountain waves and downslope windstorms (e.g., Brinkmann 1974; Klemp and Lilly 1975). Variations in the inversion height can have a significant effect on the developing mountain wave and resulting windstorm (e.g., Smith and Skyllingstad 2011). Lee-wave events within elevated stable layers have also been identified (e.g., Ralph et al. 1997a; Doyle and Durran 2002), and a stable layer topping a neutral boundary layer was a key feature of idealized simulations linking lee waves to highly perturbed surface winds (Vosper 2004). Rapidly increasing winds with height can also contribute to trapping, or partial trapping, of lee waves (e.g., Wurtele et al. 1987; Keller 1994). Two-dimensional linear theory predicts nonhydrostatic waves will be trapped when the Scorer parameter
eq1
where N is the Brunt–Väisälä frequency and U is the east–west wind component, decreases sufficiently rapidly with height Z (Scorer 1949). In this case the upstream wind was more or less westerly, and calculation of l2 from the Grand Junction sounding (not shown) indicates that trapping conditions existed in the upstream flow impinging on the Rocky Mountains on this day. In addition, increasing winds through a low-level inversion layer have been shown to favor rotor development beneath lee waves in the stable layer (Hertenstein and Kuettner 2005). Thus the atmospheric conditions on this day were consistent with lee waves forming in the midtropospheric stable layer with the potential for variable surface winds.

c. Satellite

Both infrared (Fig. 7) and visible (Fig. 8) satellite imagery show a sharp north–south-oriented clearing zone in the cloud layer along the eastern edge of the Rocky Mountains over north-central Colorado that persisted for hours before the accident. This relatively fixed boundary between the cloudy air over the mountains and clear air over the eastern foothills and adjacent plains is consistent with descending air in a stationary mountain wave, similar to the cloud-free gap noted in Jiang and Doyle (2004). Also evident in the visible imagery are distinct wave patterns downstream of the Rockies between 106° and 100°W longitude (Fig. 8), indicating that wind and stability conditions are conducive to the formation of lee waves over Colorado.

Fig. 7.
Fig. 7.

IR satellite image for 2015 UTC 20 Dec 2008 over the United States. Colorado is outlined in red. The sharp boundary in the clouds along the eastern edge of the Rocky Mountains is indicated by the arrow. GJT (DEN) marks the location for the Grand Junction (Denver) sounding shown in Fig. 6.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Fig. 8.
Fig. 8.

Visible satellite images for (a) 2215 and (b) 2245 UTC 20 Dec 2008 over eastern Colorado. Note the wave pattern in the clouds (indicated by circles).

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

d. Pilot reports

Many pilots reported experiencing both turbulence and wave motion over Colorado and northern New Mexico throughout the day of the accident. A plot of the pilot reports (PIREPs) of turbulence with a reported intensity of light or greater from 1800 UTC 20 December to 0600 UTC 21 December 2008 is shown in Fig. 9. These PIREPs are color coded in the following way. PIREPs with a reported turbulence intensity of moderate-to-severe (MOD–SEV) or greater are red, those in which the pilot specifically mentioned experiencing wave motions are blue, and PIREPs that have both a reported intensity of MOD–SEV or greater and indicated experiencing wave motion are green.

Fig. 9.
Fig. 9.

Pilot reports of light (lgt) or greater turbulence for the 12-h period from 1800 UTC 20 Dec to 0600 UTC 21 Dec 2008 over Colorado and northern New Mexico. Reports with an intensity of moderate to severe (MOD–SEV) or greater are colored red, those in which the pilot specifically mentioned experiencing wave motion are plotted in blue, and reports that both have an intensity of MOD–SEV or greater and the pilot mentioned wave motion are plotted in green. The correspondence between symbol shape and turbulence intensity is listed below the plot.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

The large cluster of turbulence and wave reports over Colorado includes reports of a strong mountain wave at 8000 ft (2.4 km) near DIA, numerous wave reports between 37 000 and 47 000 ft (11.3–14 km), and severe–extreme turbulence from 17 000 to 19 000 ft (5–5.8 km) north of DIA at 0118 UTC 21 December.

Thus long-lasting mountain-wave activity throughout a deep region of the atmosphere over Colorado on the day of the accident is confirmed by both pilot reports and satellite imagery. In addition, the stable layer above mountaintop evident in both the Denver and Grand Junction soundings is a feature that is commonly associated with large-amplitude mountain waves and downslope windstorms, as well as with nonhydrostatic lee-wave events. In the next section the meteorological conditions are further explored using analyses (0-h forecasts) from the Rapid Update Cycle (RUC) data assimilation and modeling system (Benjamin et al. 2004).

3. Synoptic conditions inferred from the RUC analysis

RUC model analyses with a horizontal grid spacing of 13 km indicated eastward progression of a midtropospheric trough axis through Colorado as an arctic cold front moved into the Great Plains 12–18 h prior to the aircraft accident. This pattern resulted in strong westerly-to-northwesterly midtropospheric flow (40–55 m s−1) over the Rocky Mountains at 0100 UTC, 18 min prior to the accident (Fig. 10). Synoptic-scale geopotential heights and horizontal winds over the western United States at 500 hPa at this time are shown in Fig. 10a. Enlargement of the region over Colorado (Fig. 10b) indicates 35–50 m s−1 flow with a large terrain-normal component upstream of DIA, which is indicated by the black dot.

Fig. 10.
Fig. 10.

RUC 500-hPa analysis (0-h forecast) for 0100 UTC 21 Dec 2008. (a) Synoptic-scale geopotential heights (black lines; 60-m contour interval) and horizontal winds (barbs) over part of the United States, centered near Colorado. Wind barbs have the standard meteorological meaning, with half barb = 2.5 m s−1, full barb = 5 m s−1, and pennant = 25 m s−1. (b) Enlargement of the region over Colorado, showing wind barbs at 500 hPa along with topography starting at 2 km MSL (terrain contour interval 250 m). The W–E black transect indicates the location of the vertical cross sections shown in Fig. 11. The location of DIA is marked by the black dot.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

A vertical cross section through DIA at 0100 UTC 21 December (Fig. 11) shows westerly downslope flow in the lee of the Rockies, a local minimum of lower-tropospheric relative humidity, and downward bending isentropes, which together are consistent with mesoscale subsidence extending ~100 km east of the mountains. The western edge of the shallow cold arctic air mass was situated just east of DIA at this time. The RUC model-analysis data assimilation includes numerous observations (http://ruc.noaa.gov), such as data from commercial aircraft, rawinsondes, and profiler data from the Platteville, Colorado, profiler (about 50 km north of DIA), resulting in a picture from the RUC analysis that is consistent with the lesser cloudiness observed in the satellite imagery (Figs. 7 and 8) and the deep dry-adiabatic layer seen in the Denver sounding (Fig. 6a).

Fig. 11.
Fig. 11.

Cross sections from the RUC analysis along the W–E black line in Fig. 10 for 0100 UTC 21 Dec 2008, about 20 min before the accident. (a) Relative humidity (color) and winds parallel to the cross section (contour lines in 5 m s−1 intervals). The gray dashed line indicates the axis of maximum enhanced cross-mountain flow that is associated with the quasi-stationary hydrostatic mountain wave. (b) Relative humidity (color), potential temperature (black lines; 2-K contour interval), and wind barbs. The shading at the bottom indicates the terrain profile. The location of DIA is marked by the plus symbol.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

At and slightly above mountaintop level lies a layer of nearly neutral stratification that extends for a significant distance upstream (Fig. 11b). On top of this neutral boundary layer is a stable layer (∂θ/∂z ≫ 0) above 4 km MSL, which also extends far upstream. Within this midtropospheric stable layer, the strong westerly/northwesterly flow increases rapidly with height.

Embedded within the general westerly current is a quasi-stationary hydrostatic mountain wave with a westward-tilting zone of enhanced flow in the immediate lee of the mountains, as indicated by the dashed gray line in Fig. 11a. The subsiding region of this wave likely contributes to the low relative humidity in this area. A second area of slightly enhanced westerlies is evident extending downward to just a few hundred meters above the surface near DIA and just west of the leading edge of the colder arctic air mass (Fig. 11b). Similar cross sections at 0000 and 0200 UTC (not shown) indicate that this mountain-wave feature and the associated subsidence were persistent.

In summary, the RUC analyses show strong and persistent midlevel westerly/northwesterly flow combined with a stable layer above mountaintop that extended far upstream of DIA for the time period surrounding the accident. Although strong cross-mountain winds combined with a stable layer aloft are features known to be associated with large-amplitude gravity waves and downslope windstorms (e.g., Brinkmann 1974), several attributes of the large-scale environment differ from the “classic” conditions for mountain-wave-induced strong downslope Boulder windstorms. For example, surface high pressure located to the north and east of Colorado (not shown) is not typical (e.g., Mercer et al. 2008; Neiman et al. 1988). Also, on this day a cold air mass was located just to the east of DIA. In the idealized numerical simulations presented in Lee et al. (1989) a cold pool downstream of a mountain could inhibit development of widespread strong downslope winds.

Even though the environmental conditions may not have been ideal for a “classical” severe downslope windstorm (of the Boulder variety), the RUC analysis, pilot reports, and satellite imagery all suggest that there was widespread gravity-wave activity on this day. The deep dry-adiabatic layer evident in both the RUC analysis and the Denver sounding ~1 h prior to the accident suggests the potential for strong vertical mixing while the stable layer aloft creates an environment conducive to lee waves (e.g., Vosper 2004). Both the amplitude and wavelength of lee waves are sensitive to the height and depth of the stable layer, which acts as a waveguide (e.g., Ralph et al. 1997a; Smith and Skyllingstad 2011). Undulations in mountain lee waves have been associated with localized regions of strong surface winds some distance downstream of mountainous topography in both field experiments and numerical simulations (e.g., Doyle and Durran 2002; Hertenstein and Kuettner 2005; Vosper et al. 2006; Sheridan et al. 2007; among others), and could explain the surface gustiness at the time of the accident. The RUC analyses, which have a relatively coarse horizontal grid spacing of 13 km, are unable to resolve both shorter-wavelength lee waves and the observed localized strong surface winds, however.

To resolve the shorter-wavelength lee waves that may be present and to determine the relationship of the larger-scale atmospheric structure to the surface gustiness observed at DIA, a simulation with a much-higher-resolution, nonhydrostatic model is required.

4. High-resolution Clark–Hall numerical simulations

The multinested parallelized version of the Clark–Hall anelastic terrain-following mesoscale model was used to simulate the three-dimensional flow conditions affecting DIA at the time of the accident. The Clark–Hall (C–H) model, described in Clark (1977) and Clark and Hall (1991, 1996), has demonstrated success in research simulations of mountain waves and downslope windstorms (e.g., Clark and Peltier 1977; Peltier and Clark 1979). In addition, results from the C–H model have compared favorably to observations of mountain-wave events (e.g., Clark and Gall 1982) and aircraft turbulence encounters (Clark et al. 2000). This model has also been used to investigate the mechanisms involved in gustiness associated with downslope windstorms (Clark and Farley 1984; Clark et al. 1994). Thus this model is well suited for simulating conditions associated with this accident.

a. Model configuration

Model equations, boundary conditions, and the turbulent-mixing scheme are as given in Clark et al. (1997). Note that this model runs in a large-eddy-simulation mode with a Smagorinsky-type closure and does not use a planetary boundary layer parameterization scheme. In the current study, the C–H model utilized five progressively higher resolution two-way nested domains, allowing for increasing resolution both horizontally and vertically in the area of interest. The location of the model domains and the topography of the innermost domain, which has a horizontal grid spacing of 250 m, are shown in Fig. 12. Table 1 lists the grid size, horizontal spacing, and starting time for each domain. Grid spacing was stretched in the vertical direction, increasing smoothly in the inner domain from 10 m near the ground to about 280 m at 10 km. The outermost domain extended up to 29 km and included an upper-level absorbing region beginning at 17.6 km to damp upward-propagating waves. The model used terrain data from the U.S. Geological Survey global 30-arc-s elevation dataset (GTOPO30; http://rda.ucar.edu/datasets/ds758.0).

Fig. 12.
Fig. 12.

Location of the five nested domains for the C–H model simulation. Topography for the innermost domain, with 250-m horizontal resolution (inset), is shown in grayscale (terrain contour interval is 500 m). The location of DIA is indicated by the X, and the black box within the inset represents the 25-km-per-side square region around the airport that is displayed in Fig. 16.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Table 1.

Domain number; horizontal resolution; number of grid points in X, Y, and Z; and the time at which each domain was started for the C–H simulation discussed in section 4.

Table 1.

The model was initialized using output from the RUC model analysis at 2200 UTC (1500 MST) 20 December 2008, and hourly RUC analyses provided lateral boundary conditions for the outer domain. Thus information from observations assimilated by the RUC model was included in the C–H model run.

b. Simulation results

Significant wave activity developed over both the Rocky Mountains and the adjacent eastern Colorado plains near the time of the accident in the C–H simulation. A horizontal plot of vertical velocity over the plains at 5.3 km MSL (3.6 AGL) shows extensive lee-wave activity downwind of the Rocky Mountains at 0120 UTC (Fig. 13). Here vertical velocity is plotted in color, the upstream mountain topography higher than 2 km MSL is shaded in gray, and the blue wind vectors represent horizontal winds over the mountains at approximately 5.3 km MSL. The wave pattern over the plains includes a region approximately between 39.5° and 40°N latitude where lee waves with vertical velocity cells that are primarily oriented north–south extend eastward beyond DIA (marked by the X). To the north of this region, the bands of vertical velocity are oriented at an angle, primarily from southwest to northeast. The wave pattern in different regions is influenced by the three-dimensional complexity of the mountainous terrain upwind.

Fig. 13.
Fig. 13.

Horizontal plot of vertical velocity (color contours; contour interval is 1.5 m s−1) over the plains at a height of 5.3 km MSL from the inner domain (Fig. 12, inset) of the C–H model simulation. Mountain topography higher than 2 km MSL upstream of the waves is shaded in gray with a contour interval of 250 m. The blue arrows represent horizontal winds at 5.3 km MSL over the mountains. The location of DIA is indicated by the X. The two dashed lines indicate the locations of cross-sectional plots from Fig. 14, corresponding to latitudes 39.87° (transect A–B) and 39.81°N (transect C–D).

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Plots of potential temperature and the east–west horizontal wind speed U, which represents a crosswind for the north–south runways, at 0120 UTC along two west–east vertical cross sections intersecting the DIA property are shown in Fig. 14. There is a well-defined large-amplitude wave over the mountains, with the wave trough and higher wind speeds extending downward along the foothills west of DIA (Fig. 14). A region of reversed flow (easterlies) under the wave crest close to the base of the foothills in Fig. 14b is indicated by the pink colors. It is noteworthy that for several hours before the accident the wind direction measured at the NCAR Mesa Laboratory, located near the base of the foothills in Boulder, varied between westerly and easterly (not shown). The midtropospheric stable layer noted in the Denver and Grand Junction soundings, as well as in the RUC analysis, is clearly evident in both cross sections. Lee waves in this elevated stable layer extend downstream of the mountains over DIA (Fig. 14). Associated with the lee-wave troughs are regions of higher-velocity air penetrating downward, resulting in wind speeds underneath the stable layer that vary with undulations in the lee wave aloft. Simulated wind speeds of greater than 20 m s−1 (green colors) can be seen extending down near the surface in the vicinity of DIA. Similar observations of wind variability associated with lee waves aloft have been noted in both field experiments and numerical simulations (e.g., Sheridan et al. 2007; Vosper 2004).

Fig. 14.
Fig. 14.

Vertical cross sections of the east–west (U) component of the wind (color) and potential temperature (black lines) at two different latitudes within the DIA property (indicated by the dashed lines in Fig. 13) from the inner (250-m horizontal resolution) domain of the C–H model simulation at 0120 UTC. The U wind speed contour interval is 5 m s−1, and the potential temperature contour interval is 2 K. The latitudes of the cross sections are (a) 39.87°N (transect A–B in Fig. 13), which intersects runway 34R near the location where the aircraft departed the runway, and (b) 39.81°N (transect C–D in Fig. 13), which is south of the runways. The location of DIA is indicated by the red X.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

The temporal variability of the lee-wave pattern for the same cross section shown in Fig. 14a is illustrated by the vertical variation of three isentropes (286, 292, and 302 K) over the 32 min surrounding the time of the accident (Fig. 15). Here lines are plotted every 8 min from 0102 to 0134 UTC, with color denoting time. A comparison of the green lines, which correspond to 0102 and 0110 UTC, with the purple and red lines (0126 and 0134 UTC) reveals an amplification of the wave near the foothills, as well as a lowering of the 286-K isentrope over DIA, during this time. Note that nonsteady lee-wave patterns may be generated by mechanisms such as nonlinearities or unsteadiness in the background flow (e.g., Nance and Durran 1997, 1998; Ralph et al. 1997a).

Fig. 15.
Fig. 15.

Vertical cross section showing temporal variability of the lee wave over the 32-min period surrounding the accident along the same latitude (39.87°N) as Fig. 14a. Plotted are three isentropes (K)—286: lower solid lines, 292: middle dashed lines, and 302: upper solid lines—at every 8 min from 0102 to 0134 UTC. The different colors denote time, with time–color correspondence indicated along the top of the figure.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

The spatiotemporal variability of both the LLWAS and model-simulated winds near the surface in a 25 km × 25 km square area immediately surrounding DIA for the time period 0110–0135 UTC is shown in Fig. 16. Black (red) vectors represent model (LLWAS) winds, and color contours are the modeled U wind component. Overall, both the model winds and LLWAS winds depict stronger westerly flow over the northern and central part of the airport property near the time of the accident, with large regions of relatively light winds to the south. A patch of simulated easterly near-surface flow to the south of the airport is designated by the pink colors.

Fig. 16.
Fig. 16.

Color contours of the east–west wind speed U, which represents a crosswind for runway 34R, along a horizontal slice at 35.2 m (115 ft) AGL for a 25 km × 25 km square area surrounding DIA. The contour interval is 2.5 m s−1. Pink-shaded areas are negative (easterly flow). Runways are indicated by the black lines (see Fig. 2 for runway numbers), and the accident site is marked by the black X. The black arrows represent model winds, red arrows represent LLWAS winds, and white arrows point out several simulated wind gusts. Times shown are (a) 0110, (b) 0120, (c) 0130, and (d) 0135 UTC 21 Dec 2008.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Embedded in the mostly westerly flow are strong gusts with speeds greater than 20 m s−1, which is greater than the airline’s published crosswind tolerance of 33 kt (17 m s−1), as indicated by the bright yellow and red colors. Although the model does not (and cannot be expected to) reproduce gusts in the exact location and time of the LLWAS observed gusts, the strength and spatial variability of the wind vectors agree fairly well. A particularly strong simulated gust, U > 30 m s−1, at 0110 UTC occurs just south of the west–east-oriented runway 07–25 (the southernmost east–west runway in Figs. 2 and 3), near 39.83°N (the red patch identified by the long white arrow in Fig. 16a). It is interesting to note that several LLWAS horizontal wind shear alerts were generated for runway 07–25, indicating that a headwind gain of greater than 20 kt (10.3 m s−1) for aircraft approaching runway 25 and departing runway 07 occurred within minutes of the accident.

Several other simulated gusts with U wind speeds exceeding 20 m s−1 move across DIA during this time period. For example, at 0110 UTC there is another gust upwind of the north–south runways 34L and 34R (Fig. 16a). At 0120 UTC (Fig. 16b) the white arrow indicates a gust just east of the southern end of the north–south runway 35R. Two more strong gusts are evident at 0130 UTC west of the runways 34L and 34R (white arrows Fig. 16c), which have moved closer to the runways by 0135 UTC (Fig. 16d).

A time-series plot that compares observed wind speeds from LLWAS station 2 and the WSSDM stations DIA1 and DIA2 with the C–H model winds from a location close to LLWAS station 2 is shown in Fig. 17. Since the exact time and location of wind gusts cannot be expected to be accurately simulated, the model winds have been time shifted to show correspondence in overall trend (model winds are 15 min later than the LLWAS and WSSDM winds). Note the prominent temporal variability in both the observed and model winds. The modeled winds have a slightly larger amplitude variation than the observed winds in some parts of the time series. Contributing to this may be the fact that in the model the downscale cascade of turbulent energy is not properly represented for turbulent eddies that are too small to be fully resolved, possibly leading to slightly larger perturbations in the model-resolved scales.

Fig. 17.
Fig. 17.

Time-series plot comparing simulated C–H model (red line) and WRF-HRRR model (gray line) wind speeds with observed winds from LLWAS station 2 (black line) and 1-min wind speed maximum from WSSDM DIA1 (blue line) and DIA2 (green line). Height of the wind speed from the C–H model is 35.2 m (115 ft) AGL, and that from the WRF-HRRR model is 28 m (92 ft). The sensor height of LLWAS station 2 is 110 ft AGL, and the height of the WSSDM sensor is 2 m (6.5 ft). C–H model winds have been time shifted by 15 min (C–H model times were 15 min later than WRF, LLWAS, and WSSDM times).

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

In summary, the C–H model shows extensive mountain-wave activity over much of Colorado at the time of the accident. Lee waves in the midtropospheric stable layer extended downstream of the Rocky Mountains over DIA. Associated with these lee waves are regions of high-velocity air penetrating downward and intermittent strong surface winds.

Although the C–H simulation for this event reproduced surface gustiness at DIA, this is a research model run at a much higher resolution than the operational forecast models can currently accommodate. This fact raises the following question: Would the operational forecast model in its current configuration adequately resolve this event, possibly providing forecast guidance to airport operations by identifying these situations in the future? This question is addressed in the next section.

5. Simulation with an operational forecast model

The high-resolution Clark–Hall simulation of this event, described in section 4, produced lee waves in a midtropospheric stable layer that were associated with strong surface gustiness at DIA, similar to the winds observed at the time of the accident. However, the horizontal grid spacing (250 m) of the innermost fifth domain is much finer than the 3-km horizontal grid spacing in the latest-generation limited-area nonhydrostatic operational numerical model, NOAA’s HRRR (Smith et al. 2008; http://rapidrefresh.noaa.gov/hrrr/). Therefore, we performed a simulation using the Advanced Research version of the Weather Research and Forecasting (WRF) Model (ARW; Skamarock and Klemp 2008), version 3.2, with HRRR updates. The intent here is to determine whether the highest-resolution operational model in its current configuration would be useful in explicitly predicting similar situations at DIA.

The WRF simulation was configured similarly to the HRRR with a 3-km horizontal grid spacing over a single domain covering the continental United States and 50 vertical levels. Subgrid physical parameterization schemes included the Mellor–Yamada–Janjić (MYJ) planetary boundary layer (PBL) scheme (Janjić 2001), the RUC land surface model (Benjamin et al. 2004), Thompson microphysics (Thompson et al. 2008), and RRTM longwave (Mlawer et al. 1997) and Dudhia (Dudhia 1989) shortwave radiation schemes. This simulation was initialized at 2200 UTC 20 December 2008, which was the same time as the C–H model initialization (section 4), 3 h plus 18 min prior to the accident at DIA.

A horizontal cross section of vertical velocity at 5.3 km MSL from the WRF simulation shows that this model also generated lee waves downstream of the Rockies (Fig. 18). Similarities in the wave pattern with the C–H simulation (Fig. 13) include wave crests that are oriented primarily north–south in the region directly downstream of the mountains and south of 40° latitude, with waves to the north of this oriented southwest–northeast. However, the pattern of the waves is much smoother, the amplitude of the vertical velocity pattern in the WRF Model is much smaller, and the location of the upward and downward motions varies between the simulations.

Fig. 18.
Fig. 18.

Horizontal plot of vertical velocity contours (color scale) at 5.3 km MSL over the plains from the WRF simulation at 0120 UTC 21 Dec 2008. Upstream mountain topography higher than 2 km is contoured in grayscale (contour interval 250 m). The black A–B transect line indicates the location of the cross section in Fig. 19, and X marks the location of DIA.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

A vertical cross section from the WRF simulation through DIA shows a large-amplitude wave associated with strong surface winds over the mountains (Fig. 19), similar to the C–H simulation (Fig. 14). The wave trough is located much farther west in the mountains than in the C–H simulation, however. In the WRF simulation, there is a very small amplitude lee wave extending a short distance downstream of the large-amplitude wave trough, which is accompanied by undulations in wind speed in the lower troposphere (Fig. 19). As in the C–H simulation, the wave amplitude varies with time. However, in the WRF simulation the lee wave does not extend as far downstream and higher-velocity air does not penetrate to the ground near DIA. Near the time of the accident there is an extensive but shallow region of weak easterly surface flow along the mountain slope in the foothills, and surface wind speeds near DIA are relatively weak when strong surface westerlies were actually present (Fig. 17).

Fig. 19.
Fig. 19.

Vertical cross section of westerly horizontal wind component (color scale) and potential temperature (2-K contour interval) from the WRF Model simulation at 0120 UTC along the A–B transect line in Fig. 18. Horizontal model resolution is 3 km, and physical parameterization schemes are similar to those of the HRRR model. The X symbol indicates the location of DIA.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

Note that the upper boundary of the stable layer, indicated by the change in the vertical gradient of potential temperature above about 7 km, is much less well defined in the WRF Model (Fig. 19) than in the C–H simulation (Fig. 14), the RUC analysis (Fig. 11b), and the soundings (Fig. 6). Both lee-wave amplitude and wavelength are sensitive to the structure of the stable layer (e.g., Ralph et al. 1997a), and this would affect the character of the lee waves in the WRF simulation.

Therefore, the 3-km WRF Model in this configuration, while simulating some aspects of the wave activity, does not capture the penetration to the surface of the higher-velocity air beneath the lee wave that was observed in the C–H simulation. Both the model resolution and the less-well-defined upper boundary of the midtropospheric stable layer likely contribute to a less-well-developed lee wave. Note that Shutts (1992) found that the Met Office mesoscale model with 3-km horizontal grid spacing had sufficient resolution to simulate a partially trapped lee-wave event observed over Wales; in other situations with shorter-wavelength lee waves, however, this grid spacing may be inadequate. In addition, other model factors, such as parameterization schemes or initialization times, could alter the results.

To investigate this possibility further, simulations were performed to test the sensitivity of the WRF Model results to both the initialization time and the boundary layer parameterization scheme. In particular, the boundary layer scheme was changed from MYJ to the Yonsei University (YSU) scheme (Hong et al. 2006), and the initialization time was changed from 2200 to 1800 UTC. Figure 20 compares the results of these sensitivity simulations with the control WRF-HRRR run at 0110, 0120, and 0130 UTC. Figure 20e corresponds to the previous Fig. 19. The character of the modeled lee waves varied slightly with these changes. For example, the lee-wave amplitude downstream of the mountain is somewhat larger for the simulation using the MYJ boundary layer scheme initialized at 1800 UTC (Figs. 20a–c) than the control simulation initialized at 2200 UTC (Figs. 20d–f). Use of the YSU scheme (Figs. 20g–i) resulted in lee-wave activity that extends slightly farther downstream at this latitude when compared with the control (Figs. 20d–f). Also, the extent of the surface easterlies in the lee of the Rockies varied somewhat between simulations. Despite these changes, winds at DIA were not substantially increased in any of the sensitivity simulations.

Fig. 20.
Fig. 20.

Vertical cross sections for (left) 0110, (center) 0120, and (right) 0130 UTC comparing potential temperature (black lines) and U wind speed (color) between (d)–(f) the WRF-HRRR control simulation (as in Fig. 19) and simulations (a)–(c) changing initialization time from 2200 to 1800 UTC and (g)–(i) changing the boundary layer scheme from MYJ to YSU. The location of DIA is indicated by the white X.

Citation: Journal of Applied Meteorology and Climatology 54, 7; 10.1175/JAMC-D-14-0270.1

6. Summary and discussion

A strong and unexpected crosswind gust was the initiating event that resulted in Continental flight 1404 deviating off the side of runway 34R and crashing at the Denver International Airport at 1818 MST 20 December 2008 (0118 UTC 21 December; NTSB 2010). Winds at the airport at the time were highly variable both temporally and spatially, as shown by the LLWAS and WSSDM wind sensors. Although the wind speed reported to the pilots had increased from 11 kt (5.7 m s−1) to 27 kt (14 m s−1) between the time the aircraft moved from the gate to the runway, they were unaware that within 2 min of the accident a wind speed of 40 kt (20.6 m s−1) from the west-northwest was recorded near the southern end of runway 34R. This recorded wind would create a crosswind for 34R of approximately 37 kt, which exceeds the airline’s published guideline (33 kt) for a crosswind component for takeoff on a dry runway (NTSB 2010).

The Clark–Hall nonhydrostatic model was used to simulate the meteorological conditions contributing to the gustiness on the day of the accident. Results from this high-resolution simulation, with a horizontal grid spacing of 250 m in the innermost domain, showed significant wave activity over the mountains and prominent lee waves in a midtropospheric stable layer downstream over DIA. The model produced realistic wind fields and intermittent gustiness at DIA, with gusts corresponding to crosswinds greater than 20 m s−1 for the north–south runways. Undulations in the lee waves aloft were associated with higher-velocity air penetrating downward, suggesting that the waves were the probable cause of the gustiness leading to the accident.

The model results are supported by evidence of widespread gravity-wave activity over Colorado on the day of the accident in satellite imagery, as well as numerous pilot reports of turbulence and wave motion. In addition, the phenomenon of lee waves inducing variable surface winds downstream of topography has been documented in both observational and numerical studies (e.g., Vosper 2004; Vosper et al. 2006, 2013; Doyle and Durran 2002; Sheridan et al. 2007).

To avoid similar accidents in the future it is clearly desirable to be able to forecast the conditions leading to strong, erratic crosswinds at DIA and other airports due to lee waves aloft, as well as to understand how often these conditions occur. It is not currently feasible to perform simulations operationally at the resolution of the C–H simulation, however.

Results from the WRF Model simulation with 3-km horizontal grid spacing and parameterization schemes similar to NOAA’s latest-generation operational forecast model (HRRR) showed that in this configuration the strong, variable surface winds at DIA were not explicitly forecast. This may well be a function of resolution, given that sensitivity studies varying boundary layer parameterization schemes and initialization times did not significantly change the result. Even if the WRF-HRRR model does not directly forecast the highly variable surface winds resulting from the penetration of strong winds to the surface in similar lee-wave events, it is quite possible that features in the larger-scale model output could be identified that would help to predict such an event, just as algorithms that are based on larger-scale flow patterns have aided in the prediction of aircraft turbulence at upper levels (Sharman et al. 2006) and downslope winds in Boulder (Mercer et al. 2008). In a similar way, parameterized wind gust algorithms such as developed by Brasseur (2001) and implemented in the HRRR postprocessing software (http://ruc.noaa.gov/rr/RAP_var_diagnosis.html) may be useful in identifying these types of situations. These types of gust algorithms are highly sensitive to the modeled PBL depth, however, and our experiments with this algorithm have shown large, unrealistic temporal discontinuities in the gust strength as based on the diagnosed boundary layer height—an effect that is not seen in the observations.

A climatological description, or “climatology,” of the surface winds at the airport—especially winter wind events—is needed before conclusions can be drawn regarding the frequency of occurrence of this type of event at DIA. The 32 operational LLWAS sensors at DIA would be ideal for this purpose. Winds from the LLWAS sensors are not currently archived, making it impossible at this time to establish a climatology of the variability of winds across the airport property.

If a climatology of wintertime gustiness at DIA could be established, other correlations might become apparent. For example, it might be possible to develop algorithms that are based on wind speeds from multiple LLWAS sensors, combined with sounding characteristics, to assess the potential for strong crosswind gusts during takeoff. Alternatively, algorithms already developed for summertime microburst wind shear alerts might be used in new ways to alert of wintertime crosswind gustiness on other runways.

Acknowledgments

The authors thank Donald Eick from the National Transportation Safety Board for many useful discussions about the accident. Discussions with John Brown from NOAA were also very enlightening in regard to the meteorological conditions on that day. Comments from the reviewers were very helpful in improving the manuscript. This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.

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