Research collaborations for better predictions of aviation weather hazards

Hye Yeong Chun, Jung Hoon Kim, Dan Bi Lee, Soo Hyun Kim, Matt Strahan, Brian Pettegrew, Philip Gill, Paul D. Williams, Ulrich Schumann, Joel Tenenbaum, Young Gon Lee, Hee Wook Choi, In Sul Song, Ye Ji Park, Robert D. Sharman

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


More than 50 participants consisting of research scientists, federal agencies, and operational forecasters from South Korea, the United States, the United Kingdom, and Germany met in Jeju Island, Korea, during 2-4 November 2016 at the Fifth Workshop on Aviation Meteorology to share their research results and forecasting experiences for improving the prediction of aviation weather hazards. Hye-Yeong Chun from YSU presented the current status of the Korean Aviation Turbulence Guidance (KTG) product, which forecasts aviation turbulence over East Asia, and outlined future plans to extend it as a global forecasting system, Global-KTG (G-KTG), to be based on the Global Data Assimilation and Prediction System (GDAPS) developed by the Korean Meteorological Administration (KMA). Philip Gill from the Met Office in the United Kingdom (WAFC) presented their efforts on ensemble-based global aviation hazard forecasts. Current global forecasts from the two WAFCs are produced from deterministic model output. Matt Strahan from the National Oceanic and Atmospheric Administration/Aviation Weather Center (NOAA/AWC) introduced the missions and roles of the NOAA/AWC for the WAFS upgrades. Jung-Hoon Kim from NOAA/AWC also presented joint efforts with the National Center for Atmospheric Research (NCAR) for the development of the Global Graphical Turbulence Guidance (G-GTG) for WAFS upgrades. Young-Gon Lee from KMA/National Institute of Meteorological Sciences (NIMS) developed a 300-m weather prediction model that is downscaled from 17-km GDAPS to the Incheon International Airport (IIA). Joel Tenenbaum from the State University of New York (SUNY) discussed the Global Aircraft Dataset (GADS) experiment, which was initiated by contributions from multiple international airlines for verification of winter jets.

Original languageEnglish
Pages (from-to)ES103-ES107
JournalBulletin of the American Meteorological Society
Issue number5
Publication statusPublished - 2017 May

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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