D. Atmospheric Turbulence 

[Background]
[Analysis of a Significant Aircraft Encounter with Convectively Induced Turbulence]
[Turbulence climatological studies] [Turbulence forecasting]
[Juneau Terrain-Induced Turbulence Project]
[Remote Sensing of Turbulence]
[In-situ measurement and reporting system]
[Turbulence Characterization]

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1. Background

RAP has been involved in a number of research and development areas over the past several years aimed at minimizing the number and severity of aircraft encounters with turbulence.  The work areas are divided into two complementary directions: 1) improve and implement methods for better measurements of turbulence, either in-situ based or using remote sensing devices such as radar and lidar; and 2) develop, implement, and verify automated forecasts of upper level turbulence.  In support of both areas, research is being conducted to improve our understanding of the nature or character of aircraft scale turbulence, based primarily on field measurement campaigns and high resolution numerical simulations to recreate and study in detail actual turbulence encounters.   This work is being sponsored by the FAA Aviation Weather Research Program (AWRP) and the NASA Aviation Safety Program (AvSP).

2. Analysis of a Significant Aircraft Encounter with Convectively Induced Turbulence

From commercial airline pilot experiences, convectively-induced turbulence (CIT) , i.e., clear-air turbulence near to but outside of thunderstorms is a major aviation hazard. In an attempt to better understand out-of-cloud turbulence generating mechanisms, RAP scientists Todd Lane/ASP, Bob Sharman, Hsiao-Ming Hsu and MMM scientist Terry Clark, performed a series of very high resolution numerical simulations of an actual CIT encounter. The encounter chosen occurred on 10 July 1997 and involved a commercial passenger aircraft encountering severe turbulence at 37,000 ft near Dickinson, ND, en-route from Seattle to New York. The aircraft was negotiating a number of scattered thunderstorms, yet passed directly over a developing deep convective cloud. While passing over this cloud, the aircraft suffered accelerations of approximately two g's, in a period of about 10 seconds. Subsequently, twenty passengers and two flight attendants suffered minor injuries.

The use of high resolution simulations to study turbulence events has just now become viable with increased computing capability and three-dimensional plus time visualization software. Analysis of the evolution of the turbulence events in the simulations allows connections to be established between the turbulence scale and the larger scales which may be resolvable with current or next generation numerical weather prediction models. In the Dickinson simulation, both the convection and the turbulence-causing instabilities in the vicinity of the cloud are explicitly resolved. In particular, gravity waves are seen to break near the cloud top, causing vertical mixing and turbulence. In addition to this gravity wave breakdown, smaller-scale Kelvin-Helmholtz-like waves form on the cloud interface. The simulation demonstrates for the first time that CIT encounters can be explained by gravity waves propagation and breakdown from a cloud.

The animation below results from a high resolution two-dimensional simulation of a severe turbulence encounter above a rapidly growing thunderstorm on 10 July 1997. In the animation, blue represents the in-cloud air, red represents regions of small-scale turbulence, and the white lines are contours of potential temperature. The cloud can be seen to rise rapidly towards the stable air in the lower portions of the stratosphere. The cloud top then splits, inducing strong vorticity and turbulence in the vicinity of the cloud top. Vertically propagating gravity waves are also evident above the cloud, with some breaking as high as 1-2 km above the cloud top. It is unknown how high above the cloud the aircraft encountered the turbulence, so it is difficult to know whether the turbulence encounter was caused by the cloud splitting near the cloud top or by the breaking gravity waves above it. Click on the link below to view the animation.

Updraft movie (20MB)

3.  Turbulence climatological studies

For the past 3 years NCAR has been performing statistical studies of our turbulence pilot report (PIREP) database in an attempt to get a better understanding of the regional and seasonal/temporal distributions of turbulence encounters.  The NCAR PIREP database encompasses almost 10 complete years worth of data, going back to February 1992.  Previous years’ work had concentrated on obtaining statistics of the regional and seasonal distribution of PIREPs above 20,000 ft msl (FL200), without regard to the source of the turbulence.  This year, work undertaken by B. Sharman, T. Fowler, J. Wolff, and B. Brown was aimed at validating and extending previous work in the following areas:

a)      Assess PIREP accuracy. Comparisons of neighboring PIREPs indicated the reports were overall consistent among themselves.

b)      Validate procedures to remove air traffic biases. A traffic independent metric of turbulence encounters was proposed last year, and that metric was verified using two years of air traffic density data.

c)      Update database. On the order of one hundred thousand turbulence PIREPs are received and archived every year.

d)      Investigate altitude dependencies on the turbulence encounter patterns. Plotting encounter densities as a function of flight altitude indicates, contrary to intuitive beliefs, the number of encounters is not substantially greater near the tropopause or jet stream levels. See Figure D1.

e)      Compare turbulence climatology to NTSB turbulence related incidents. Derived climatologies based on PIREPs were shown to be consistent with NTSB turbulence incident reports.

f)        Preliminary assessments of upper-level turbulence causes. Maximum encounters occur over mountainous areas, indicating likely mountain wave induced turbulence. Maxima in the southeast point to convectively related causes.  Maxima in the northeast are probably related to jet streams and winter cyclogenesis.

 

 

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4. Turbulence forecasting

Over the past several years NCAR has been developing and testing an automated algorithm for forecasting upper level turbulence locations and intensities.  The product, dubbed ITFA, for Integrated Turbulence Forecasting Algorithm, is intended to provide end users, e.g., aviation forecasters, airline dispatchers, and pilots, with easy to understand, yet accurate, nowcasts and forecasts.  Forecast images of likely turbulence regions are produced automatically based on RUC2 NWP model output which updates every 3 hours.  From the NWP output various turbulence indices, empirically or theoretically derived, are computed and combined using fuzzy logic to give the best agreement with available PIREPS.  The resulting images are provided on two web sites, the NCAR site (http://www.rap.ucar.edu/projects/itfa) and the NWS aviation digital data service (http://adds.awc-kc.noaa.gov).  A sample image is shown in Figure D2, along with available PIREPs.  The derivation and testing of new diagnostics and optimum strategies for combining the various diagnostics are areas of continued research.  This year, B. Sharman, J. Wolff, and G. Wiener, concentrated on making the algorithm more robust and added an empirically based mountain wave turbulence algorithm.  Performance metrics for the algorithm are derived by the methods outlined in the next section.

5. Juneau Terrain-Induced Turbulence Project

In FY01, there was a lull in the scientific aspects of this project. In FY02, however, there will be a great deal of scientific activities. Regardless, in FY01, three journal papers describing certain aspects of the scientific activity were published, or accepted for publication. These papers dealt with the use of Doppler wind profilers in the measurement of wind and turbulence. RAP scientists L. Cornman, K. Goodrich, and C. Morse directed these efforts.

Cohn, S.A., R.K. Goodrich, C.S. Morse, E. Karplus, L.B. Cornman, and R.A. Weekley, 2001: Radial velocity and wind measurements with NIMA: comparisons with human estimation and aircraft measurements, Journal of Applied Meteorology, 40, 704-719.

Goodrich, R.K., C.S. Morse, L.B. Cornman, and S.A. Cohn, 2002: A horizontal wind and wind confidence algorithm for Doppler wind profilers,  Journal of Atmospheric and Oceanic Technology, accepted for publication.

Morse, C.S., R.K. Goodrich and L.B. Cornman, 2002: The NIMA method for improved moment estimation from Doppler spectra, Journal of Atmospheric and Oceanic Technology, accepted for publication.

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6. Remote Sensing of Turbulence

In FY01, research related to the detection of atmospheric turbulence by remote sensing devices has continued. Specifically, this research has been focused on two tasks: the development of an improved turbulence detection algorithm for airborne Doppler radars and the WSR-88D radar network, as well as an investigation of turbulence detection algorithms for Doppler lidars.  This work continues to be directed by RAP scientist L. Cornman, in collaboration with R. Frehlich, S. Dalton, G. Meymaris, and J. Williams.

The airborne radar turbulence detection activity is sponsored by NASA’s Aviation Safety program. A research team comprised of NASA, NCAR, radar manufacturers and others, is developing methods for using existing airborne Doppler radars to detect convective turbulence. The research and development activities have included cloud-scale modeling of convective turbulence encounters, radar and aircraft simulations using analytical-turbulence and model fields, detection algorithm development, as well as flight tests of the radar on the NASA 757 research aircraft. Promising results have been forthcoming from the flight test data analysis (see Figure D3).

The WSR-88D activities have been mainly addressed at quality control problems with the spectrum width data as well as the analysis of data from a WSR-88D radar. The spectrum width data is a primary source of data for the improved turbulence detection algorithm and hence the quality of the algorithm will be directly related to the quality of these data. These issues have come to the forefront this year as a data set from a WSR-88D with co-located in situ aircraft data has been obtained. Radar data from the Goodland, Kansas WSR-88D was collected during the STEPS-2000 field experiment. During this field experiment, the SDSM&T T-28 aircraft was used to penetrate thunderstorms, and the vertical acceleration data from the T-28 data was used to compare against turbulence estimates from the radar data (Figures D4 and D5).

 

In the lidar area, new algorithms to correctly estimate the estimation error of Doppler lidar velocity measurements have been developed. These algorithms have been applied to the measurement of spatial structure functions. Simulations were performed for isotropic wind fields with a Von-Karman spatial spectrum to determine the accuracy of various algorithms to extract the two turbulence parameters of the Von-Karman model: energy dissipation rate and intergal length scale. The statistical performance of these algorithms is determined by computer simulation. A journal paper, describing this work, “Estimating Spatial Velocity Statistics with Coherent Doppler Lidar,” by R. Frehlich and L. Cornman, has been accepted by the Journal of Atmospheric and Oceanic Technology and is in press.

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7. In-situ measurement and reporting system

The only method currently available to obtain observations of aircraft scale turbulence is the manual pilot reporting system.  Typically each report contains time, position and intensity information.  But there are some problems inherent in this system.  First, because a specific action is required by the pilot to initiate the report, typically only a few observations, sometimes none at all, are reported per flight leg.  Second, not all the reports actually are entered into the automated systems (e.g., at the Flight Service Stations (FSSs) or Air Route Traffic Control Centers (ARTCCs).  Consequently, even over an hour’s time, there are very few PIREPs in the automated system, making it difficult to obtain a complete mapping of the turbulence.  Besides, this underreporting problem, the PIREPs that do actually make it into the automated system are subject to human error.   In order to correct this problem, NCAR RAP has developed an automated turbulence reporting system that takes in-situ measures of aircraft acceleration, attitude, mass, etc., and backs out an aircraft independent measure of atmospheric turbulence.  This metric, currently established as an eddy dissipation rate, is recorded (both the maximum and mean) every minute of cruise flight, and automatically downloaded every four minutes.  The system is actually a software package that is easily loaded onto ACARS-equipped aircraft.  The result is many, perhaps several hundred, turbulence measurements per flight accompanied by precise position and time information. 

This year, RAP scientists L. Cornman, C. Morse, and G. Meymaris have concentrated on tuning and verifying the algorithm.  The results of one sample verification exercise are shown in Figure D6. 

8.  Turbulence Characterization

Better understandings of the causes and life cycles of turbulence and its relation to the larger scale flow is needed to obtain better forecasts.  One particularly difficult problem is the generation of out-of-cloud turbulence by thunderstorm or convective clouds.  To better understand what causes the out-of-cloud turbulence, a high resolution numerical simulation of an actual encounter was undertaken this last year by RAP scientists R. Sharman and T. Lane, in collaboration with T. Clark (MMM).   The event occurred on 10 July 1997, when an American Airlines B737-223 passenger jet en route from Seattle, WA to New York City, NY encountered severe turbulence over North Dakota. Twenty-two passengers sustained minor injuries, and the aircraft sustained some damage to the passenger service units, forcing the passenger liner to make an unscheduled stop at Denver, CO.  An NTSB report cited the probable cause as “unforecast convection induced turbulence (CIT).”   Flight data recorder information indicated the event was due to two isolated spikes of vertical velocity as the aircraft flew over the top of the thunderstorm. 

Both two-dimensional and three-dimensional simulations of the event, with grid resolutions down to 25 m, indicate the probable cause was gravity waves generated by the thunderstorm that broke at levels above the storm (see Figure D7).  This is the first hard evidence of breaking gravity waves being responsible for CIT encounter.