Assessment of the Graphical Turbulence Guidance, Nowcast (GTGN)

Details

• Personal Author:
  Wandishin, Matthew Scott, 1972- ; Paulik, Laura A. ; Hart, Joan (Joan E.) ; Etherton, Brian J. ; Petty, Melissa A.
• Corporate Authors:
  Earth System Research Laboratory (U.S.), Global Systems Division,
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; GSL (Global Systems Laboratory)
• Description:
  "The QA PDT was tasked to assess the quality of the Graphical Turbulence Guidance, Nowcast, (GTGN) algorithm developed by the National Center for Atmospheric Research. This product is designed to provide near-real-time situational awareness to support operational aviation turbulence decisions. GTGN uses a short-term (1- or 2-h lead) forecast from the Graphical Turbulence Guidance, Version 3 (GTG3) product as a first guess field which is then augmented with direct observations--both pilot reports (PIREPs) and EDR measurements--and remotely sensed data from the NEXRAD Turbulence Detection Algorithm (NTDA). Updates are supplied every 15 minutes, with output provided on the same Rapid Refresh (RAP)-based, 13-km grid used by GTG3. GTGN is intended as a nowcast product to be used for tactical decisions. GTG3 provides forecasts out to 18h to support strategic decision-making. In other words, these two products are meant to provide complementary information. There is, currently, no gridded product providing real-time situational awareness for atmospheric turbulence; the best available product is a short-term GTG3 forecast. Therefore, they are compared here as competing products. The assessment compares GTGN with the 2-h GTG3 forecast used in its first-guess field and incorporates output from the operational GTG3 algorithm, GTGN, as well as PIREPs and EDR values derived from in situ measurements. The forecasts were analyzed using output generated from 1 July - 30 September 2013 and 1 January - 31 March 2014 over the CONUS. Primary findings include: " When assessed in the context of near-real-time situational awareness, GTGN outperforms GTG3 " GTGN has more strong turbulence and more smooth turbulence than GTG3 " In winter, GTGN has fewer misses and fewer false alarms than GTG3 " GTGN recovers much of the decline in skill from winter to summer seen with GTG3 (by capturing events missed by GTG3), but a lower forecast threshold is required to achieve that skill " Results vary somewhat by region and by altitude layer: " Improvement is greatest in the Southeast region " In winter, improvement is greatest in 0-10 kft layer " In summer, improvement is greatest in 10-20 kft layer " Fall off in skill for GTGN is slow--45 min old GTGN still much better than the corresponding GTG3"--Executive summary.
• Content Notes:
  Matthew S. Wandishin, Laura Paulik, Joan Hart, Brian Etherton, Melissa A. Petty. ; "March 2016." ; Includes bibliographical references (page 25).
• Series:
  NOAA technical memorandum OAR GSD ; 54
• DOI:
  http://doi.org/10.7289/V5/TM-OAR-GSD-54
• Document Type:
  Technical Memorandum
• Place as Subject:
  United States
• License:
  https://creativecommons.org/publicdomain/zero/1.0/
• Rights Information:
  CC0 Public Domain
• Compliance:
  Library
• Download URL:
  https://repository.library.noaa.gov/view/noaa/16877/noaa_16877_DS1.pdf
• File Type:
  [PDF - 2.53 MB]
• Collection(s):
  Office of Oceanic and Atmospheric Research (OAR)
• Main Document Checksum:
  urn:sha256:9e6afc03824fc63aef9a5cdc1931555f9449c4b539f1c884c4b26730a3eca0df