Development and Evaluation of Global Korean Aviation Turbulence Forecast Systems Based on an Operational Numerical Weather Prediction Model and In Situ Flight Turbulence Observation Data

Dan Bi Lee, Hye Yeong Chun, Soo Hyun Kim, Robert D. Sharman, Jung Hoon Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A global Korean deterministic aviation turbulence guidance (G-KTG) system and a global Korean probabilistic turbulence forecast (G-KPT) system are developed using outputs from the operational Global Data Assimilation and Prediction System of the Korea Meteorological Administration, and the performance skill of the systems are evaluated against in situ flight eddy dissipation rates (EDRs) recorded for one year (September 2018–August 2019). G-KTG and G-KPT consider clear-air turbulence (CAT) and mountain wave turbulence diagnostics, while G-KTG additionally consid-ers near-cloud turbulence (NCT) diagnostics. In the G-KTG system, the various combinations of deterministic EDR forecasts are tested by different ensemble means of individual turbulence diagnostics. In the G-KPT system, the probabilistic forecast is established by counting the number of diagnostics that exceed a certain threshold for strong intensity turbulence on the given model grid. The evaluation results of the G-KTG system based on the area under the relative operating char-acteristic curve (AUC) reveal that G-KTG, which consists of CAT and NCT diagnostics, shows the highest AUC value among the various G-KTG combinations; in addition, the summertime performance is significantly improved when NCT diagnostics are included. In the evaluation results of the G-KTG system over the globe, U.S., and East Asia regions, the recent graphical turbulence guidance system–based G-KTG shows better performance than the regional KTG–based G-KTG for all three regions. For all altitude bands, the G-KPTs with 40% probability as the minimal threshold for alerting forecasters of strong turbulence show higher values of true skill statistic than the G-KTGs.

Original languageEnglish
Pages (from-to)371-392
Number of pages22
JournalWeather and Forecasting
Volume37
Issue number3
DOIs
Publication statusPublished - 2022 Mar

Bibliographical note

Funding Information:
Acknowledgments. The GDAPS data and in situ flight EDR and AMDAR observations for research purposes were provided by the KMA and NCAR, respectively. This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2018-07810.

Publisher Copyright:
© 2022, American Meteorological Society. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Fingerprint

Dive into the research topics of 'Development and Evaluation of Global Korean Aviation Turbulence Forecast Systems Based on an Operational Numerical Weather Prediction Model and In Situ Flight Turbulence Observation Data'. Together they form a unique fingerprint.

Cite this