Aviation Turbulence

Encounters of commercial and GA aircraft with turbulence pose significant safety, efficiency and workload issues. The number of pilot–reported encounters with turbulence is substantial: moderate–or–greater pilot reports (PIREPs) averaging about 65,000/year, and severe–or–greater PIREPs averaging about 5,500/year. More often than not, pilots will try to avoid or exit turbulent air, so turbulence significantly impacts NAS efficiency and controller workload. Fortunately, not every significant encounter with turbulence results in an injury, nevertheless, according to NTSB numbers, each year turbulence accounts for approximately 75%* of all weather–related accidents and incidents. The cost to US airlines due to injuries (medical attention and liability suits), cabin and aircraft damage, flight delays, and time lost to inspection and maintenance is substantial, with estimates in the $150–$500 million/year range. For GA aircraft turbulence encounters account for about 40 fatalities/year.

RAL has been involved in a number of research and development areas over the past several years aimed at better understanding turbulence as it relates to aviation safety and producing decision support systems to address operational needs, including NextGen. RAL turbulence research areas have traditionally aimed at improving and implementing methods for:

• Quantitative, precise in situ measurements of aviation–scale turbulence
• Using remote sensing devices such as radar and lidar (either ground–based or airborne) and satellite inferences to diagnose turbulence hazardous areas to aviation
• Nowcasting and forecasting aviation scale turbulence using observations combined with automated turbulence diagnostics computed from NWP model output, in the U. S. airspace and globally.

To support these activities research is also being conducted to better characterize turbulence from field measurement campaigns and high resolution numerical simulations. RAL turbulence research is currently sponsored by the FAA Aviation Weather Research Program (AWRP) and the NASA Advanced Satellite Aviation Weather Products Program (ASAP).

This DC–8 cargo aircraft encountered extreme clear–air turbulence over the Colorado Rocky Mountains on 9 Dec 1992, resulting in the loss of the right outboard engine and part of the right wing.

In Situ Turbulence

For both research and operational purposes, there are currently an insufficient number of reliable, accurate, and timely measurements of atmospheric turbulence locations and intensities. Turbulence "measurements" in the form of pilot reports (PIREPs), although useful, do not comprise a satisfactory turbulence detection system. NCAR, under FAA sponsorship, has developed state–of–the–art in situ algorithms for measuring and reporting turbulence encountered by commercial transport aircraft. The algorithms compute an eddy dissipation rate, or EDR (m ^2/3 s ^-1), from available on–board flight parameters. EDR is truly a "state–of–the–atmosphere" turbulence metric, and it is widely used in the research community as a measure of turbulence intensity, and in fact has been adopted as the ICAO standard for aviation turbulence. 200 aircraft from United Airlines are presently equipped with software which downlinks EDR reports at one–minute intervals (in cruise), although due to communication costs, only 100 or so report at any given time. In order to reduce communication costs, an improved algorithm has been developed that downlinks turbulence encounter information immediately if the EDR is above a certain threshold, and still provides routine reporting but at less frequent intervals. This improved algorithm has been recently implemented on about 70 Delta Airlines 737–800s. We are also working with Southwest Airlines to equip their entire fleet (about 280 aircraft) with the improved algorithm. As the airline industry becomes more aware of the benefits of this program, we anticipate the expansion of these observation systems to ultimately include the majority of commercial aircraft flying both continental U.S. (CONUS) and oceanic routes. Although for forecasting purposes, EDR is the preferred prediction metric, some users may also require the aircraft loads associated with an atmospheric EDR measurement. This is easily provided by an aircraft/configuration dependent linear mapping factor.

Coverage provided in a 24 hour period of in situ EDR measurements (colored code in units of m ^2/3 s ^-1) from UAL mostly 757–200 aircraft (top panel), with one–minute routine reporting and DAL 737–800 aircraft (bottom panel) with event–based EDR reporting plus 15–minute routine reporting.

Remote sensing

Detecting atmospheric turbulence using information provided by airborne and ground–based Doppler radars continues to be a major RAL work area. RAL scientists have developed and tested the NCAR Turbulence Detection Algorithm (NTDA), designed for use on the nation's NEXRAD and TDWR radars. The NTDA utilizes NEXRAD Level II data–the reflectivity, radial velocity, and spectrum width–to perform data quality control and produce turbulence intensity (eddy dissipation rate, EDR) estimates on the same polar grid as is used for the raw radar measurements. The expert system combines multiple modules for quality control and turbulence estimation using a "fuzzy logic" methodology to produce a final EDR and associated quality control index, or confidence. By providing direct detection of turbulence, the EDRs produced by the NTDA provide an important supplement to radar reflectivity as an indication of in–cloud aviation hazards. The first version of NTDA, NTDA–1 software was deployed on all NEXRADs in 2008 as part of ORPG Build 10. The next version, NTDA–2, is targeted as a Build 12 update (2010). In anticipation of this upgrade, a prototype version is running in real–time at NCAR on Level II data from 133 NEXRADs around the country, producing a mosaic of in–cloud EDR updated every 5 min. In addition to direct use by airline dispatchers and air traffic control meteorologists, it is anticipated that the NTDA EDRs will be incorporated into a new Aviation Digital Data Service (ADDS) Graphical Turbulence Guidance (GTG) product for providing convectively–induced turbulence nowcasts to the aviation community. Given the highly transient and spatially variable nature of in–cloud turbulence, maximum benefit of the NTDA product can be achieved if pilots can receive this information in the cockpit in nearly real time. A demonstration of this capability is ongoing in collaboration with United Airlines. Character graphics depictions of NTDA–derived EDR 100 miles ahead and 40 miles to either side of the planned route are uplinked to selected United Airlines flights via ACARS. Pilots have provided very positive feedback on the usefulness of these graphics for making tactical decisions for routing around storms, suggesting that this product could improve airline safety while reducing delays due to unneeded deviations.

RAL is also collaborating with researchers at the University of Wisconsin Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the University of Alabama Huntsville (UAH) in developing diagnostics of turbulence likelihood based on inferences from satellite imagery. This is a particularly important piece of information for transcontinental flights where other sources of turbulence information are not available. This team is currently investigating the utility of using satellite information for inferring likely regions of turbulence associated with convection, mountain waves, and tropopause folds.

The feasibility of using other remote sensing techniques to detect turbulence for tactical avoidance is also being studied. These include airborne forward-looking Doppler radar, lidar, GPS scintillation, and forward-looking infrared interferometer methods.

166 FAA, NWS and DoD NEXRADs are currently in operation, providing Doppler wind and wind variability measurements as well as reflectivity. The NTDA is a software upgrade that uses these data to detect in–cloud turbulence before aircraft encounter it.

NCAR's demonstration system merges NTDA output from multiple radars to form a 3–D map of EDR, revealing regions of moderate and severe turbulence within clouds and thunderstorms.

Example of text–based graphic used in uplink demonstration.

Example of in situ EDR tracks related to rapidly–growing convection as observed from GOES–8 imagery. Purple and blue areas of the track indicate light, green and yellow indicate moderate and orange and red indicate severe.

Turbulence Forecasting and Nowcasting

Over the last several years the FAA has funded NCAR and others to develop a turbulence nowcast and forecast system for mid– upper level turbulence over the continental U. S. The forecast system, named GTG for "Graphical Turbulence Guidance," provides contours of turbulence potential based on RUC model forecasts out to 12 hours lead time. The original system, which since March 2003 has been part of the NCEP operational suite (available through the ADDS web site http://adds.aviationweather.gov), produces forecasts of clear–air turbulence above 20,000 ft MSL. An experimental upgrade (GTG2) to extend the forecasts down 10,000 ft MSL is currently available on the Experimental ADDS website (http://weather.aero/).

The GTG procedure uses numerical weather prediction model forecasts to compute a number of turbulence diagnostics which are then weighted and combined. The relative weights for the combination are dynamically optimized for best agreement with the most recent available turbulence observations (in situ EDR data and pilot reports). This procedure allows the algorithm to minimize forecast errors due to uncertainties in individual diagnostic performance and thresholds. Intense statistical verification exercises have been performed in which probabilities of yes and no detections were determined by comparing turbulence forecasts to PIREPs. These statistics have made it possible to compare performance of the individual diagnostics, as well as test various diagnostic thresholding and weighting strategies. The overall forecast performance using the weighted diagnostics provides superior skill to the use of individual diagnostics.

The GTG is a constantly evolving product, with specific mountain wave turbulence and convectively–induced turbulence diagnostics and probabilistic forecasts as well as a global forecast product currently under development.

Since it is a forecast product, the GTG is most useful for route planning, i.e., strategic avoidance of turbulence. However, given the rapidly evolving phenomenon character of turbulence, for tactical avoidance it is more useful to have a rapidly updated nowcast system. This system, called GTGN (N for nowcast), is currently under development at RAL and is primarily driven by the most recent available turbulence observations (in situ EDR measurements, turbulence pilot reports, NTDA output, satellite inferences) merged together with a GTG short–term forecast. The product updates every 15 min. It is scheduled for implementation on ADDS in the 2011–2012 time frame.

Example of GTG1 9-hour turbulence forecast as it appears on the Operational ADDS web site.

Example of GTG2 9-hour turbulence forecast as it appears on the Experimental ADDS web site.

Turbulence characterization

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 (∼100 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 aircraft flight data recorders. 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

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 "clear the top of a known or suspected thunderstorm by at least 1,000 feet altitude for each 10 knots of wind speed at the cloud top." (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 Mountain Wave Turbulence. Click on image to view full-size. (courtesy Todd Lane, Univ. of Melbourne)

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.

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.

Clark-Hall anelastic model of severe mountain wave. Click on image to view full-size.

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Primary Contacts

• CARMICHAEL, Bruce | AAP DIRECTOR | ph: 8406 | email: brucec
• BARRON, Bob: | AAP DEPUTY DIRECTOR | ph: 8410 | email: bob
• POLITOVICH, Marcia | AAP DEPUTY DIRECTOR | ph: 8449 | email: marcia