Turbulence

Background

Turbulence encounters by general and commercial aviation continue to pose significant safety and flight efficiency concerns. Almost anyone who has flown commercially has had an unpleasant experience with turbulence and has a tale to tell about it. According to some estimates, turbulence encounters account for well over 75% of all weather-related injuries on commercial aircraft and amount to at least $200M annually in costs due passenger and crew injuries and aircraft damage. Consequently, there is an urgent need to provide better turbulence information to pilots and route planners so that the number of encounters can be minimized, or adequate warnings provided so that passengers and crew can better prepare for an expected encounter.

For more than 25 years, a group of scientists and engineers at the National Center for Atmospheric Research’s Research Application Laboratory (NCAR/RAL) has led efforts to address these needs. Working under the sponsorship of the Federal Aviation Administration (FAA), the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the Taiwan Civil Aeronautics Administration (CAA) and in collaboration with several universities and private companies, the team has conducted research aimed at improving fundamental understandings of the nature and causes of turbulence and developing new techniques for better observing and forecasting turbulence.

Efforts have been focused in four areas: (1) Development, implementation, and monitoring of new techniques for obtaining automated in situ reports of turbulence encounters from commercial aircraft; (2) development of an automated system for detecting in-cloud turbulence using Doppler weather radar data; (3) development and implementation of an automated turbulence nowcasting and forecasting system called Graphical Turbulence Guidance or GTG; and (4) high-resolution simulation studies of observed turbulence events to better characterize the nature and genesis of free atmosphere turbulence. The products developed at RAL have reached a level of maturity that allows them to be used operationally by pilots and route planners in tactical and strategic planning for avoiding turbulence or mitigating the effects of encounters. One important aspect of all products is that they provide an aircraft-independent measure of atmospheric turbulence known as the energy (or eddy) dissipation rate or EDR (m 2⁄3/s).

Automated In situ EDR Measurements

Despite the continued reporting of the frequency and severity of turbulence encounters, our understanding of the nature and genesis of aviation-scale atmospheric turbulence remains limited.  Research to better understand the nature and causes of free atmosphere aviation-scale turbulence has been hampered in part by a lack of reliable observational data. Until recently, verbal pilot reports (PIREPs) have typically been the only source of information about the location and severity of turbulence. These reports are, unfortunately, incomplete (since reporting is voluntary), and highly subjective (what one pilot views as “moderate” might be perceived as “light” or “severe” by another). Further, recent investigations into the accuracy of PIREPs have indicated an average position error of about 50 km, or several grid points, given current operational numerical weather prediction (NWP) model grid spacings. While NWP models are very useful in forecasting other atmospheric hazards, they are of limited value for turbulence given that turbulence exists for short periods of time and in small geographical areas. In order to improve the detection and forecasting of turbulence, it is clearly essential to upgrade the turbulence observation and reporting system and to create automated systems for obtaining more abundant, reliable data. In pursuit of this goal, NCAR is in the process of augmenting, and eventually replacing, the PIREPs with in situ observations from commercial aircraft. These observations and dissemination of them are completely automated, and provide a measure of atmospheric turbulence intensity levels (EDR), instead of aircraft-specific estimates of turbulence severity. The in situ EDR system developed by NCAR scientists and engineers consists of a simple software upgrade to the aircraft’s ACMS (Aircraft Condition and Monitoring System), and no hardware changes are required.

Figure 1. In situ EDR observations of turbulence automatically reported by UAL 757, DAL737, DAL767, and SWA737 aircraft for the 24hr period on 19 October 2017.

Figure 1. In situ EDR observations of turbulence automatically reported by UAL 757, DAL737, DAL767, and SWA737 aircraft for the 24hr period on 19 October 2017.  

FY2017 Accomplishments

Currently the in situ EDR software package is implemented on Delta Air Lines (DAL) B737, B767, and 777, United Airlines B777, and Southwest Airlines (SWA) B737 aircraft, providing roughly 22,000 reports per month. An example of the coverage by these aircraft is shown in Fig. 1. This algorithm is expected to be implemented on other aircraft in the coming years; the highest priority is implementation on international aircraft to enhance global coverage.  Commercial vendors are also beginning to provide automated in situ EDR estimates, and one work area this year was to develop EDR estimation standards to insure that all EDR estimation methods provide similar results, at least within the operational needs.

FY2018 Plans

Discussions will be conducted with AirBus, Lufthansa, SWISS, Air France, British Airways, Lufthansa, Korean Airlines, Qantas, Xiamen Airlines, and DAL to implement the in situ EDR algorithm on all or parts of their fleets. Some of these implementations will be on laptops in the cockpit for downlink by wifi.

Remote Sensing Measurements

In order to give pilots better information about potentially hazardous regions of turbulence in thunderstorms before they encounter them, RAL scientists developed the NEXRAD Turbulence Detection Algorithm (NTDA) which uses ground-based Doppler radar data to remotely detect turbulence within clouds. The algorithm runs on data from each radar, processing each “tilt” or “sweep” independently to obtain estimates of EDR within cloud. The results are merged (or “mosaicked”) with measurements from other NEXRADs and mapped to chosen flight altitudes. The initial version of the NTDA was adopted by the National Weather Service and implemented on all of its radar systems in 2007 and 2008. Since then, a number of advancements have been made to the NTDA to increase its coverage, accuracy, speed and maintainability, and to accommodate NEXRAD changes like the adoption of dual-pol and the implementation of a new spectrum width estimator (also developed by RAL staff). The NTDA has been modified to run on radars in Taiwan, as well.

FY2017 Accomplishments

NTDA data were used to analyze the development of turbulence inside thunderstorms and relate turbulence intensity and volume to the occurrence of lightning. The correlation between these quantities may be used in conjunction with future geostationary satellite lightning mapping data to help diagnose likely regions of turbulence in regions not served by Doppler radar.  Transfer of the NTDA system to the National Weather Service was begun.

FY2018 Plans

RAL scientists plan to investigate the possibility of using the newly-available NEXRAD dual-polarization data to further improve the NTDA’s data quality.  NTDA will continue to run as a real-time prototype over the CONUS, Alaska, Hawaii and Puerto Rico, providing data used for the development of turbulence nowcast products and scientific investigations of the development of convective storms. It will be adapted as needed to accommodate changes to the NEXRAD radars.  Implementation at NCEP will be completed.

Nowcasting/Forecasting Turbulence

RAL has been developing and testing aviation-scale turbulence forecast algorithms that provide forecasts out to 18 hours, updated hourly. The forecast system is known as the GTG (Graphical Turbulence Guidance product). It relies on the WRF RAP NWP model (http://rapidrefresh.noaa.gov/) output and provides what amounts to an ensemble weighted mean of various turbulence diagnostics output as EDR (m2/3 s-1) on designated flight levels. The output is available to interested users on NOAA’s ADDS web site (http://www.aviationweather.gov/adds/).   

Figure 2. Example GTG3 output as it appears on NOAA’s ADDS website for a 0-hr forecast at flight level (FL) 370, i.e., about 37,000 ft.  PIREPs are overlaid for comparison.

Figure 2. Example GTG3 output as it appears on NOAA’s ADDS website for a 0-hr forecast at flight level (FL) 370, i.e., about 37,000 ft.  PIREPs are overlaid for comparison.

In addition to the GTG forecast system (forecasts out to 18-hrs lead time, updated hourly), RAL is currently developing a nowcast system, GTG-N, which provides rapid (every 15 min) updates and make heavy use of the latest available turbulence observations from the in situ EDR estimates, PIREPs, NTDA, and other sources (e.g., METARs gust information) on a GTG background. This product is intended to provide enhanced pilot situational awareness, especially for turbulence associated with thunderstorms (convectively-induced turbulence or CIT).

FY2017 Accomplishments

Work continued on the development of a global GTG (dubbed G-GTG), using the GFS, UKMet Office and ECMWF global NWP models.  A prototype version was delivered to NCEP for integration into its Unified Post Processing System (UPP) and to the UKMet Office for use with its Unified Model (UM).

New low-level turbulence (LLT) prediction algorithms were developed to better represent turbulence in both the stable and unstable boundary layers.  This is particularly important for Unmanned Aerial Systems (UAS) operations which typically fly in the atmospheric boundary layer (ABL).

FY2018 Plans

An update to the GTG forecast component will include a nowcast component (GTG-N), which uses observations merged with short-term forecasts to provide EDR maps updated at 15 min intervals.  Testing and evaluation of the G-GTG will continue, with an expected delivery to the World Aviation Forecast System (WAFS) in 2018-9. Research on developing algorithms for forecasting convectively-induced turbulence (CIT) will also continue.  These CIT forecast algorithms will become part of the next version of GTG, GTG4, which will use the 3-km HRRR model as input; GTG4 will incorporate the new LLT algorithms researched and developed in FY2017.

Characterization efforts

Substantial effort has been invested in developing a better physical understanding of the mechanisms responsible for convectively induced turbulence (CIT) and clear-air turbulence (CAT) with the long-term goal of providing better operational turbulence forecasts. These studies make use of high-resolution nested (WRF) numerical simulations that have outer computational domains large enough to capture the relevant large-scale forcing processes and inner domains fine enough to capture the turbulence generating mechanisms. An example turbulence case related to banded structures in anvil cirrus associated with a wintertime storm over the North Atlantic is shown in Fig. 3.  In this case, there were many reports of turbulence in the vicinity of the bands.

 

Figure 3. Example (16 UTC 15 Nov 2011) of turbulence associated with banded structures in a North Atlantic storm.

FY2017 Accomplishments

By careful examination of observations (PIREPs and in situ EDR reports) compared to satellite imagery, RAL scientists have isolated several cases in which banded structures in the anvil cirrus of convective storms seem to be highly correlated to regions of elevated turbulence.  The relation of the bands to the turbulence has been investigated for summertime storms revealing that the bands seem to have the character of planetary boundary layer rolls.  Other cases involving banded structures in winter-time storms was investigated (see Fig. 3), and the results published in the Monthly Weather Review.  Such cases are extremely complex, with convection playing a major role in the production of turbulence, even when the turbulence occurs outside the storm boundaries.  Case studies such as these are ongoing.  

FY2018 Plans

Efforts to isolate cases and resolve turbulence sources will continue. This will lead to a better understanding of turbulence in the free atmosphere, which in turn should suggest improved forecasting strategies. Since this work is unique and original, we anticipate several publications to be forthcoming on these investigations.