Turbulence characterization

Overview

Fundamental research aimed at characterizing different sources of aviation–scale turbulence continues to be a focus of RAL research. Funding from the FAA and NASA has supported a number of high–resolution numerical simulations of cases involving encounters with turbulence induced by jet streams, mountain waves, island wakes, and convection. The use of high resolution (few km to 100s m) mesoscale simulations can provide a robust ability to reproduce observed turbulence events. The simulations use a multi–nested approach with the outer domains initialized with standard NWP model output (such as RUC or GFS) to provide a realistic representation of the large scales, with the smaller inner domains at high enough resolution to resolve turbulence scales that are relevant to aircraft motions. In most case studies, turbulence information is provided from either aircraft flight data recorders or in situ EDR data. This allows verification of the simulation and provides a method to analyze the linkage between the large scale environment and small scale turbulence.

Example 1 – Characterization of turbulence above thunderstorm clouds

Simulation of above-cloud convectively-induced turbulence (CIT) associated with rapidly-growing convectively cloud as it penterates the stratosphere.  Blue regions are cloud, white lines are isentropes, red are regions of overturning and turbulence.  Courtesy Prof. Todd Lane, U. of Melbourne.
White lines are isentropes at 2K intervals, blue area is cloud water + ice concentrations > 0.05 g/kg red area are areas of enhanced turbulence with a diffusion coefficient > 0.1 m^2/s

On 10 July 1997, a commercial passenger jet encountered severe turbulence over Dickinson, North Dakota. The aircraft was negotiating a path through a number of scattered thunderstorms, and at the time of the encounter was passing directly over a developing deep convective cloud. 22 passengers sustained minor injuries, and the aircraft sustained enough damage to cause it to make an unscheduled stop at Denver, CO. The NTSB report concluded that the probable cause was "unforecast convection induced turbulence (CIT)." This type of turbulence is common enough that the CIT acronym is well known within the aviation community; it is used to describe turbulence in the clear air either above the thunderstorm top, under the anvil, or near the lateral visible boundaries. Every major U.S. air carrier has documentation of many such CIT encounters. Because of the turbulence hazard in the clear air above and surrounding thunderstorms, the FAA suggests pilots "avoid by at least 20 miles any thunderstorm identified as severe or giving an intense radar echo," and "known or suspected severe thunderstorm." (See the FAA Aeronautical Information Manual (AIM) Chapter 7, "Safety of Flight" at http://www.faa.gov/ATpubs/AIM/).

RAL scientists investigated the causes of the turbulence associated with the Dickinson encounter using high resolution two–and three–dimensional numerical simulations and compared the output to observations from ground–based radar and the aircraft flight data recorder. The simulations showed that the turbulence above the (rapidly growing) thunderstorm cloud was related to breaking gravity waves above the storm (see animation). The waves were shown to propagate into the clear air above the cloud, become unstable and break due to nonlinear interactions with its critical level. Comparisons to ground–based radar echoes showed good agreement to the simulated clouds, and the flight data recorder vertical velocity trace was well–reproduced by the simulated gravity wave induced velocity fields above the cloud. Further, it was shown that the vertical extent of the turbulence was related to the strength of the wind shear above the cloud top, not the wind speed as suggested by the FAA guidelines, and importantly, that in this case, the FAA guidelines were inadequate to avoid this turbulence encounter.

Example 2–Characterization of turbulence near an MCS anvil

Combining automated EDR–based turbulence measurements with radar and satellite imagery has confirmed the large frequency of CIT encounters outside of active thunderstorm regions. On 17 June 2005 long–lasting and widespread turbulence occurred along the outer cirrus anvil of a mesoscale convective system (MCS) in the southern Great Plains of the United States (see figure below), which was several hundred kilometers north of the MCS thunderstorm region (Trier and Sharman 2009).

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Turbulence measurements along the tracks of three edr(ε 1/3 )–equipped commercial aircraft taken near the time of the satellite image. Each dot is a color code of the peak edr during a one–minute interval of flight time, where green represents edr values <0.1, yellow 0.1–0.2, orange 0.2–0.3, and red 0.3–0.4 m 2/3 s –¹, nominally categorized as smooth, light, moderate, and moderate–severe respectively)

The mesoscale environment of the 17 June 2005 turbulence encounter was investigated using a convection–permitting model simulation with horizontal grid spacing of 3 km (Trier and Sharman 2009). While this horizontal resolution is significantly higher than most current operational models, the turbulence is still not well resolved and turbulence kinetic energy (TKE) needs to be parameterized (i.e., objectively estimated) based on resolved–scale flow properties such as vertical shear and static stability. Simulated TKE in this case is most widespread within the MCS outflow several hundred kilometers north of the heavy rainfall region (figure below), consistent with observations.

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Simulated column–maximum radar reflectivity (colored shading), 13–km MSL horizontal winds using the standard meteorological convention (half barb = 2.5 m s–¹, full barb = 5 m s–¹, pennant = 25 m s–¹), and 12–km MSL turbulence kinetic energy (thick brown contours, 1 m² s–² contour intervals starting at 1 m² s–²) at 0730 UTC 17 June 2005

As in many midlatitude cases the MCS outflow is asymmetric, which is related to how it superposes on the background flow and can impact where turbulence develops. The simulation showed that the gradient Richardson Number,gradient Richardson Number, where the numerator is the static stability and the denominator depends on vertical wind shear, had strong regional variations within the simulated MCS outflow. On the north side of the simulated MCS at point 'N' in the figure, at flight levels between 11.5 and 12 km MSL indicated susceptibility to turbulence, whereas on its south side near 'S', Ri was typically greater than 1 and less supportive of turbulence.

Recent simulations of the 17 June event at even smaller horizontal grid spacing, Δ = 600 m (Trier et al. 2010), resolve transverse cloud bands that also appear in the satellite data. Turbulence is commonly observed in the vicinity of such bands in MCS anvils and in other atmospheric phenomena, such as tropical cyclone outflows and cirrus near atmospheric jet streams.

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Simulated brightness temperature within a portion of a high resolution nested model domain with Δ = 600 m from a simulation of the 17 June 2005 MCS. The annotations indicate automated EDR–based turbulence reports of the southernmost flight track with 'L' indicating light turbulence, and 'M' indicating moderate turbulence.

Example 3–Characterization of wintertime CAT and CIT

CIT induced by deep convection is an important consideration during the midlatitude warm season (as demonstrated in Examples 1 and 2), but it can also occur in other seasons as well. For example, clusters of turbulence in clear air occurred over the U.S. Mississippi River Valley region on 9-10 March 2006; and simulations of this event illustrated multiple mechanisms commonly responsible for CIT occurring in different locations, and sometimes acting in tandem.

A key ingredient for this CIT event is the convectively-induced anticyclonic upper-level outflow similar to those in warm-season MCSs (see Figure below). The perturbation anticyclone deduced for this cold-season midlatitude case was associated with a large prefrontal squall line occurring ahead of a middle and upper tropospheric trough. The strong anticyclonic outflow enhanced the southerly flow ahead of the trough axis, resulting in exceptionally intense northerly vertical shear above the jet (Figure), which in turn led to local Kelvin-Helmoholtz instabilities (KHI).   Elsewhere, shallower moist convection occurred within the midtropospheric trough (Figure). This convection was shown to trigger vertically propagating gravity waves similar to Example 1 above when it impinged on the lowered tropopause within the trough.  These gravity waves amplify and break at some locations above the convection, leading directly to turbulence, while in other locations they aid turbulence development through excitation of KHI within layers of the strongest vertical shear above them.  This study demonstrates the complexity of mid-latitude clear-air turbulence generation processes in general, and in particular, emphasizes the role of clouds and convection in the generation of turbulence in clear air outside the cloud.  This has obvious implications for CAT forecasting .

Simulation

CAT episode related to the synoptic scale based on a 24-hr AR WRF forecast (Trier et al. 2012). (a) Model-derived radar reflectivity (colors), 5440-m geopotential height contour, and the convectively-induced outflow at 10.5-km MSL illustrated schematically by the dashed curve with arrowheads. The shaded region indicates the location of strongest vertical shear at flight levels. (b) A vertical cross section along transect SN of panel (a) showing the total cloud condensate (colors and shadings) and the south-to-north wind component. The red circles indicate approximately concurrent and collocated reports of observed moderate and severe turbulence. Adapted from Trier et al. [2012]. ©American Meteorological Society.

Example 4–Characterization of wintertime CAT and CIT

On March 15, 2006 a Boeing 757 commercial aircraft encountered severe turbulence at 39,000 feet in the lee side of the Rocky Mountains over northern Colorado. According to the pilot and the NTSB report the aircraft was in visual meteorological conditions when it encountered a severe mountain wave and was unable to maintain altitude. One flight attendant was injured and the flight was diverted to Omaha, NE.

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Simulation

A simulation of this event was conducted using a multi–nested version of the Clark–Hall anelastic model. An example output is shown in the animation. This is an east–west vertical cross section of east–west velocity U near the location of this incident at times surrounding the incident. Large parts of this region have wind speeds less than 10 m s–¹, including a few areas of stagnate flow (in white) and reversed flow (in blue). These features are in good agreement with the FDR measurements, and indicate the severe turbulence was probably due to the production of a gravity wave–induced critical level, which are known to be areas conducive to the formation of turbulence.