ADDS Turbulence Help

Tutorial on GTG

The GTG algorithm uses forecast fields from the RAP forecast model distributed by the National Weather Service's NCEP. With each release of a new RAP forecast time, several turbulence diagnostics are automatically computed from the RAP forecast output and combined to provide the final GTG3 product. An explanation of the algorithms and the GTG formulation can be found in Sharman et al. (2006). Basically, the algorithm combines the results of several turbulence diagnostics (listed below) and weights the diagnostics based on comparisons to observations (i.e. Pilot Reports (PIREPs) or in situ EDR data). The final turbulence forecast is in EDR units and are interpolated to flight levels (FLs) from the native RAP grid for display.

The actual GTG algorithm uses different sets of diagnostics and weights for low-levels (below 10,000 ft MSL), mid-levels (10,000 feet MSL and FL200) and upper levels (above FL200). The three separate regions are blended at the boundaries between the altitude bands. GTG outputs grids on 36 flight levels separated by 1000 feet intervals, regardless of the altitude. A flight level is a constant pressure surface referenced to a world-wide sea level pressure datum (1013.25 hPa). Thus the flight level is referenced to a standard atmosphere; and the actual altitude and flight level will not generally be the same, although typically the difference is small. Flight levels are a convenient way to ensure adequate vertical spacing at altitudes above all terrain. At lower altitudes, terrain avoidance is of primary concern and flight altitudes are typically defined as MSL altitude. In the US and Canada the transition altitude (to the flight level regime) was set at 18,000 feet, while in Europe and other parts of the world it is implemented based on terrain height surrounding the airport or on the runway elevation. The GTG3 reports all forecasts on flight levels both above and below the transition altitude of 18,000 MSL with the understanding that the difference between flight level and actual MSL altitude is small.

At upper-levels, the following 7 turbulence diagnostics are used within the GTG-3.0 combination (see Sharman (2006) for an explanation of each index):

  1. Frontogenesis function (isentropic coordinates) /Ri (Richardson Number)
  2. |Deformation|2/Ri
  3. Structure function derived eddy dissipation rate
  4. Wind speed X horizontal deformation/Ri
  5. Ri with shear computed from thermal wind relation
  6. |vertical velocity|/Ri
  7. Frontogenesis function (z coordinates)/ Ri

At mid-levels, the following 5 indices are used:

  1. Ri with shear computed from thermal wind relation
  2. Wind speed X horizontal deformation
  3. iawind/Ri
  4. Structure function derived eddy dissipation rate, EDR
  5. Frontogenesis function (z coordinates)/Ri

And at low-levels, the following 5 indices are used:

  1. Ri
  2. Wind speed X horizontal deformation
  3. Lighthill-Ford-Knox spontaneous gw predictor/Ri
  4. Vertical velocity
  5. Structure function derived vertical velocity variance/Ri

Graphical Turbulence Guidance (GTG) History

The Graphical Turbulence Guidance (GTG) system product is a fully automated system providing turbulence analyses and forecasts for the aviation community over the contiguous U.S., parts of Mexico and Canada, and the western Atlantic Ocean and eastern Pacific Ocean. Funding for the product has been through the FAA’s Aviation Weather Research Program (AWRP) since about 2001. Its basic algorithmic structure is described in detail in Sharman et al. (2006). Briefly, the system automatically pulls full resolution native numerical weather prediction (NWP) model forecast grids as they become available, then computes an ensemble of turbulence diagnostics on a grid point by grid point basis, combines them, and finally interpolates the combination onto flight levels. GTG output was first made available on NOAA’s Aviation Digital Data Service (ADDS) website in March 2003.

Since then the GTG product has gone through a continuous cycle of upgrades, and each major upgrade is independently evaluated before being made available on the ADDS web site. The capabilities of the various releases are as follows:

  • GTG1: The initial product released in March 2003 provides forecasts of mainly clear-turbulence (CAT) sources in the altitude range of flight levels (FL) 200-450. The product is based on analyses and forecasts from the Rapid Update Cycle (RUC) Numerical Weather Prediction (NWP) model (Benjamin et al. 2004). Output is provided on a 0-1 scale on a 3D grid at 1,000 ft altitude increments with a horizontal grid spacing of 20 km extending vertically from FL200-FL450. The 0-1 scale corresponds roughly to traditional verbal pilot reports (PIREPs) with 0 corresponding to “smooth” reports, 0.5 to “moderate” reports, and 1.0 to “extreme” reports.
  • GTG2: After continued development, testing, independent verification analyses and safety impact assessments, the first upgrade (GTG2) was released for viewing to the ADDS website in February 2010. Like the GTG1 product the underlying NWP model was the RUC, but the output range was extended to include middle levels (10,000 ft MSL-FL200). The mid-level and upper-level forecasts (FL200-FL450) are computed separately, and the results merged at the FL200 boundary. The suite of diagnostics used is different for the mid-level and upper-level GTG combinations. The final output is provided on a 0-1 scale at 1,000 ft altitude increments on a 20 km horizontal grid extending vertically from 10,000 ft MSL to FL450. It includes all sources of turbulence that may be resolved by the underlying NWP model resolution, including CAT, mountain wave turbulence (MWT), and convectively-induced turbulence (CIT) from large scale clouds (either convective or stratiform). This is the version described in Sharman et al. (2006).
  • GTG2.5: In October 2011 the RUC NWP model was replaced by a newer more sophisticated NWP model called the Weather Research and Forecasting Rapid Refresh (WRF-RAP) model. Descriptions of this model can be found at http://rapidrefresh.noaa.gov/; see also Benjamin et al. (2006). This model is based on the Advanced Research WRF (ARWRF) dynamic core (Skamarock et al. 2008), which is substantially different than the RUC model in several ways. The WRF-RAP domain covered by the model is much larger and includes most of North America, however, cutout grids were made available that covers approximately the same domain as the previous RUC model, and these are used to drive the newer versions of GTG. Although the functionality of GTG2.5 is similar to GTG2, and the methodology for computing the turbulence diagnostics and combining them are unchanged from previous versions, the underlying diagnostic computations and the GTG output are somewhat different:
    • The suite of diagnostics had to be retuned for maximum performance at both upper and mid-levels
    • Some of the diagnostics had to be reformulated in the WRF-RAP vertical coordinate system
    • To take advantage of the in situ edr measurements (Cornman et al. 1995, Sharman et al., 2014) now available from some UAL and DAL aircraft, and for consistency with the NextGen requirements, the final GTG2.5 combination is scaled to EDR (=ε 1/3, where ε is the energy dissipation rate in units of m2/s3) instead of the previous 0-1 scale. It turns out that for representative values of EDR, the output is also on a 0-1 scale so there is no difference in appearance of the ADDS graphics.
    • GTG2.5 output is at the native WRF-RAP 13km horizontal resolution as opposed to the 20km horizontal grids in previous versions.

    As with previous versions, GTG2.5 underwent rigorous independent statistical performance evaluations, which were completed in Aug 2011. GTG2.5 then became viewable on the ADDS website in May 2012.

  • GTG3: As with GTG2.5, the algorithms are driven by the WRF-RAP 13km cutout grids. Several new features include:
    • Extension of GTG output to include low-levels (surface-10,000 ft MSL),
    • Explicit inclusion of mountain-wave turbulence (MWT) forecasts,
    • Extension of maximum forecast lead time from 12 hrs to 18 hrs, updated hourly,
    • Inclusion of a nowcast product, providing updates at 15 min intervals, which is especially important for convective turbulence,
    • Recalibration of the GTG output to better match the distributions of DAL in situ EDR data,
    • Updates to the displays to include contour levels of EDR, and MWT forecasts separately
  • GTG4: Work has already begun on the next version of GTG, GTG4, which concentrates on developing better forecasts of convectively-induced turbulence. To do this, a higher resolution, convective resolving NWP model, viz., NOAA’s High-resolution Rapid Refresh (HRRR) model, with a horizontal grid spacing of 3 km will be used to drive the GTG product.

References:

Benjamin, S.G., D. Devenyi, T. Smirnova, S. Weygandt, J.M. Brown, S. Peckham, K. Brundage, T.L. Smith, G. Grell, and T. Schlatter, 2006: From the 13-km RUC to the Rapid Refresh. 12th Conf. on Aviation, Range, and Aerospace Meteorology (ARAM), Atlanta, GA, Amer. Meteor. Soc. CD-ROM, 9.1

Cornman, L. B., C. S. Morse, and G. Cunning, 1995: Real-time estimation of atmospheric turbulence severity from in-situ aircraft measurements. J. Aircraft, 32, 171-177.

Sharman, R., C. Tebaldi, G. Wiener, and J. Wolff, 2006: An integrated approach to mid- and upper-level turbulence forecasting. Wea. Forecasting, 21, 268-287.

Sharman, R. D., L. B. Cornman, G. Meymaris, J. Pearson, and T. Farrar, 2014: Description and derived climatologies of automated in situ eddy dissipation rate reports of atmospheric turbulence. J. Appl. Meteor. Climatol., 53, 1416-1432, doi:10.1175/JAMC-D-13-0329.1

Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A description of the Advanced Research WRF version 3. NCAR/TN-475+STR, 113 pp. [Available at http://www.mmm.ucar.edu/wrf/users/docs/ arw_v3.pdf.]



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