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dc.date.accessioned2022-05-09T00:50:01Z
dc.date.available2022-05-09T00:50:01Z
dc.date.copyright25 Mar 2022
dc.date.issued2022
dc.identifier.otherWAF-D-21-0095.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285604
dc.description.abstractA 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 considers 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 characteristic 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.
dc.titleDevelopment and Evaluation of Global Korean Aviation Turbulence Forecast Systems Based on an Operational Numerical Weather Prediction Model and In Situ Flight Turbulence Observation Data
dc.typeJournal Paper
dc.journal.volume37
dc.journal.issue3
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-21-0095.1
dc.page371–392
dc.treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 003
dc.contenttypeFulltext


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