Background
Figure 1. Experimental ADDS Web-based display showing in situ turbulence reports overlaid on contours of the Graphical Turbulence Guidance (GTG) turbulence forecast product. (click on image to enlarge).
Turbulence research and development efforts at RAL in FY2005 have been focused on applications to aviation safety and applications to transport and diffusion within the urban boundary layer.
Encounters with turbulence for commercial and general aviation aircraft pose significant safety, efficiency and workload issues. The number of pilot-reported encounters with turbulence is substantial, with moderate-or-greater turbulence pilot reports averaging about 65,000/year and severe-or-greater reports averaging about 5,500/year. More often than not, pilots will try to avoid or exit turbulent air, so turbulence significantly impacts national airspace (NAS) efficiency and air traffic controller workload. Fortunately, not every significant encounter with turbulence results in an injury; nevertheless, according to NTSB numbers, each year turbulence accounts for approximately 71% of all weather-related accidents and incidents. The cost to U.S. 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. In order to help reduce the number and severity of turbulence encounters and the impact of turbulence on the NAS, RAL scientists are working on improving the detection and forecasting of turbulence and providing operationally useful products directly to users.
Turbulence within urban boundary layers dramatically affects the transport and diffusion (T&D) of chemical and biological releases, intentional or inadvertent. Better monitoring and, to the extent possible, prediction of turbulence within urban areas can be used to obtain improved forecasts of plume dispersal and allow first responders to institute timely evacuations and emergency treatments as necessary. Better techniques for profiling urban boundary layers using Doppler lidar are also being developed, and building-resolving simulations are being performed to improve understanding of the effects of varying meteorological conditions on T&D in urban areas.
Current Activities
Aviation turbulence R&D at RAL is funded primarily through theFAA’s Aviation Weather Research Program Turbulence Product Development Team (TPDT), and is augmented by NASA’s Advanced Satellite Aviation-weather Products (ASAP) program. The TPDT has been focusing on three work areas:
- Providing automated, quantitative, and aircraft-independent in situ reports of turbulence from commercial aircraft. Currently 200 aircraft from United Airlines have the in situ turbulence software deployed, with approximately 1.3 million reports being generated every month—compared to the approximately 55,000 conventional reports per month. Work is ongoing with Southwest Airlines to equip its fleet of Boeing 737 aircraft with the in situ turbulence software. This work is led by L. Cornman.
- Over the last several years NCAR has developed a turbulence diagnosis and forecast system for the continental U.S. This system, dubbed Graphical Turbulence Guidance (GTG), has been part of the National Centers for Environmental Prediction Aviation Digital Data Service (ADDS) operational suite since March 2003. GTG producesa 4-D grid of turbulence potential for clear-air turbulence above 20,000 ft MSL using RUC model forecast grids. Work is currently underway to provide an improved GTG that will also extend the forecasts down to 10,000 ft MSL. This product should become operational in late 2006. This work is led by R. Sharman, with support from J. Wolff, C. Tebaldi, R. Frehlich, and J. Abernethy. In addition, WRF model simulations of turbulence encounters by B. Hall have provided insight into the genesis of turbulence events that may lead to better forecasting algorithms.
- A new turbulence detection algorithm designed for use on WSR-88D (NEXRAD) radars has been developed. The detection product generated by this algorithm will provide an important supplement to radar reflectivity as an indication of in-cloud aviation hazards, including convectively-induced turbulence (CIT). In collaboration with the Advanced Weather Radar Techniques PDT, the detection algorithm has been implemented and tested in the Open Radar Products Generator (ORPG), and the process of obtaining approval for its installation on all WSR-88Ds has been initiated. This work is led by J. Williams and L. Cornman, with support from J. Yee and S. Carson.
Results
Turbulence R&D at RAL has:
- Provided an unprecedented number of quantitative turbulence measurements. These in situ turbulence reports have been essential in verifying and tuning the WSR-88D turbulence detection algorithm as well as the GTG forecasts. United Airlines meteorologists and dispatchers also find these data very useful in their daily activities.
- Developed and tested several new turbulence diagnostics and improved methods for combining the diagnostics for incorporation into the next operational version of GTG, GTG2. Methods for incorporating in situ data into GTG2 were also developed. GTG2 will extend down to 10,000 ft MSL from the current operational GTG1 lower limit of 20,000 ft MSL.
- Verified and tuned the WSR-88D turbulence detection algorithm. A technique to merge and mosaic the data from multiple radars has been developed and implemented. Case studies based on field program and NTSB data and broader statistical analysis using in situ turbulence reports show that the algorithm has good skill in detecting in-cloud turbulence.
- Demonstrated the feasibility of detecting convectively-induced gravity waves in satellite spectroradiometer (MODIS) water vapor imagery. This capability may be used for early detection of out-of-cloud convectively-induced turbulence.
Figure 2. Left: Web-based Java display of mosaicked in-cloud turbulence detected by the WSR-88D algorithm operating on data from 16 radars in the upper Midwest with overlaid aircraft tracks depicting in situ turbulence reports. Right: A sample text-based graphic generated for the cockpit uplink demonstration. (click on image to enlarge).
Recent Accomplishments
In FY2005, the TPDT has produced the following:
- An automated quality control algorithm for the in situ reports has been developed and implemented. These reports are now displayed on an Experimental ADDS website, and are used by meteorologists and dispatchers at United Airlines (see Figure 1).
- GTG2 was approved as an experimental product by the Aviation Weather Technology Transfer (AWTT) Board in November 2004, and displays are available on the Experimental ADDS web site (www.weather.aero).
- A real-time demonstration of the WSR-88D turbulence detection algorithm was performed during the summer of 2005 using data from 16 WSR-88Ds in the upper Midwest. A 4-D graphical product was made available to United Airlines meteorologists and dispatchers via a web-based Java display, and a text-based graphic of in-cloud turbulence ahead was uplinked to select United Airlines aircraft (see Figure 2).
Figure 3. Comparison of high-rate Tethered Lifting System (TLS) measurements (solid line), lidar derived measurements (bullets), and sodar (open circles) in an urban area at night versus normalized height z/H where H is the mixing height defined by the maximum gradient in the profile of energy dissipation rate (e). Shown are wind speed (WS) and direction, potential temperature (Q), velocity turbulence e, and thermal turbulence CT2. The vertical distribution of Q indicates stable stratification. Note the good agreement between the lidar-derived wind and turbulence information compared to the TLS measurements. (click on image to enlarge).
In the transport and dispersion work area, studies by R. Frehlich of the structure of the urban boundary layer have been accomplished using Doppler lidar to profile the wind and turbulence structures at night. Good agreement to high-rate tethered kite data has been obtained (see Figure 3).
Contact Information
Bob Sharman — ph: 303.497.8457 | fx: x8401 | sharman@ucar.edu