Search Results

You are looking at 1 - 10 of 21 items for

  • Author or Editor: Jung-Hoon Kim x
  • Refine by Access: All Content x
Clear All Modify Search
Jung-Hoon Kim and Hye-Yeong Chun

Abstract

On 2 April 2007, nine cases of moderate-or-greater-level clear-air turbulence (CAT) were observed from pilot reports over South Korea during the 6.5 h from 0200 to 0830 UTC. Those CAT events occurred in three different regions of South Korea: the west coast, Jeju Island, and the eastern mountain areas. The characteristics and possible mechanisms of the CAT events in the different regions are investigated using the Weather Research and Forecasting model. The simulation consists of six nested domains focused on the Korean Peninsula, with the finest horizontal grid spacing of 0.37 km. The simulated wind and temperature fields in a 30-km coarse domain are in good agreement with those of the Regional Data Assimilation and Prediction System (RDAPS) analysis data of the Korean Meteorological Administration and observed soundings of operational radiosondes over South Korea. In synoptic features, an upper-level front associated with strong meridional temperature gradients is intensified, and the jet stream passing through the central part of the Korean Peninsula exceeds 70 m s−1. Location and timing of the observed CAT events are reproduced in the finest domains of the simulated results in three different regions. Generation mechanisms of the CAT events revealed in the model results are somewhat different in the three regions. In the west coast area, the tropopause is deeply folded down to about z = 4 km because of the strengthening of an upper-level front, and the maximized vertical wind shear below the jet core produces localized turbulence. In the Jeju Island area, localized mixing and turbulence are generated on the anticyclonic shear side of the enhanced jet, where inertial instability and ageostrophic flow are intensified in the lee side of the convective system. In the eastern mountain area, large-amplitude gravity waves induced by complex terrain propagate vertically and subsequently break down over the lee side of topography, causing localized turbulence. For most of the CAT processes considered, except for the mountain-wave breaking, standard NWP resolutions of tens of kilometers are adequate to capture the CAT events.

Full access
Jung-Hoon Kim and Hye-Yeong Chun

Abstract

At 1034 UTC 2 September 2007, a commercial aircraft flying from Jeju, South Korea, to Osaka, Japan, at an altitude of approximately 11.2 km encountered severe turbulence above deep convection. To investigate the characteristics and generation mechanism of this event, the real atmosphere is simulated using the Weather Research and Forecasting model with six nested domains, the finest of which is a horizontal grid spacing of 120 m. The model reproduces well the observed large-scale flows and the location and timing of the turbulence along the evolving deep convection. Three hours before the incident, isolated deep convection with two overshooting tops develops in a warm area ahead of the cold front in the southwestern region of the turbulence. As the deep convection moves with the dominant southwesterly flow toward the incident region, its thickness shrinks significantly because of weakening of upward motions inside the convection. Twenty minutes before the incident, the dissipating convection disturbs the southwesterly flow at the incident altitude, enhancing local vertical wind shear above the dissipating convection. The leading edge of the cloud stretches toward the lee side because of shear-induced y vorticity, finally overturning. This activates turbulence and vertical mixing at the cloud boundary through convective instability in the entrainment process. While the dissipating convection, its thickness still shrinking, continues to move toward the observed turbulence region, the turbulence generated at the cloud interface is advected by the dominant southwesterly flow, emerging about 1–2 km above the dissipating convection and intersecting the aircraft’s flight route at the incident time.

Full access
Jung-Hoon Kim and Hye-Yeong Chun

Abstract

The characteristics of aviation turbulence over South Korea during the recent five years (2003–08, excluding 2005) are investigated using pilot reports (PIREPs) accumulated by the Korea Aviation Meteorological Agency (KAMA). Among the total of 8449 PIREPs, 4607 (54.53%), 1646 (19.48%), 248 (2.94%), 7 (0.08%), and 1941 (22.97%) correspond to the turbulence categories of null, light, moderate, severe, and missing, respectively. In terms of temporal variations, the annual total number of turbulence events increased from 2003 to 2008, and the seasonal frequency is the highest in the spring. With regard to spatial distributions, reported turbulence encounters are dominant along the prevailing flight routes, but are locally higher over the west coast, Jeju Island, and the Sobaek and Taebaek mountains. The turbulence events in these regions vary by season. To examine the regional differences and possible sources of the observed turbulence, lightning flash data, Regional Data Assimilation and Prediction System (RDAPS) analysis data with a 30-km horizontal grid spacing provided by the Korean Meteorological Administration (KMA), and a digital elevation model (DEM) dataset with a 30-s resolution, are additionally used. Convectively induced turbulence (CIT) and clear-air turbulence (CAT) events comprised 11% and 89% of the total 255 moderate or greater (MOG)-level turbulence events, respectively. CAT events are classified as tropopause/jet stream–induced CAT (TJCAT) and mountain-wave-induced CAT (MWCAT) events. The MOG-level TJCAT and MWCAT events are responsible for 41.2% and 19.6% of the total MOG-level turbulence events, respectively. The CIT events in summer and the TRCAT and MWCAT events in spring occur most frequently over the previously mentioned regions of South Korea, associated with specific generation mechanisms.

Full access
Chanil Park, Seok-Woo Son, and Jung-Hoon Kim

Abstract

The nature of the vertical motion responsible for the summertime heavy rainfall events (HREs) in South Korea is quantitatively examined. By compositing 318 HREs from June to September in 1979–2018, it is found that the synoptic conditions of the HREs are typically characterized by a developing surface cyclone with a southwesterly low-level jet on its southeastern flank and an upper-level trough to the west of the HREs. This baroclinic environment allows for well-organized vertical motion over South Korea at the equatorward side of the upper-level jet entrance. The relative importance of dynamic and diabatic forcings in driving the vertical motion is further quantified by solving the quasigeostrophic omega equation. It turns out that the dynamic forcing, defined as Q-vector convergence, is comparable to the diabatic forcing in the developing stage of the HREs. The diabatic forcing, however, becomes more important in the mature stage as latent heating rapidly increases. The decomposition of the Q vector into the transverse (cross-isentropic) and shearwise (along-isentropic) components reveals that the dynamic uplift is largely caused by the shearwise Q-vector convergence, which is closely related to the developing trough in the upper to middle troposphere on the west of the HREs. This result indicates that the HREs in South Korea are organized by the baroclinic trough coupled to moist processes, with a minor contribution of the thermally direct secondary circulation at the entrance region of the upper-level jet.

Restricted access
Sang-Hun Park, Joseph B. Klemp, and Jung-Hoon Kim

Abstract

Although a terrain-following vertical coordinate is well suited for the application of surface boundary conditions, it is well known that the influences of the terrain on the coordinate surfaces can contribute to increase numerical errors, particularly over steep topography. To reduce these errors, a hybrid sigma–pressure coordinate is formulated in the Weather Research and Forecasting (WRF) Model, and its effects are illustrated for both an idealized test case and a real-data forecast for upper-level turbulence. The idealized test case confirms that with the basic sigma coordinate, significant upper-level disturbances can be produced due to numerical errors that arise as the advection of strong horizontal flow is computed along coordinate surfaces that are perturbed by smaller-scale terrain influences. With the hybrid coordinate, this artificial noise is largely eliminated as the mid- and upper-level coordinate surfaces correspond much more closely to constant pressure surfaces. In real-data simulations for upper-level turbulence forecasting, the WRF Model using the basic sigma coordinate tends to overpredict the strength of upper-air turbulence over mountainous regions because of numerical errors arising as a strong upper-level jet is advected along irregular coordinate surfaces. With the hybrid coordinate, these errors are reduced, resulting in an improved forecast of upper-level turbulence. Analysis of kinetic energy spectra for these simulations confirms that artificial amplitudes in the smaller scales at upper levels that arise with the basic sigma coordinate are effectively removed when the hybrid coordinate is used.

Open access
Dan-Bi Lee, Hye-Yeong Chun, and Jung-Hoon Kim

Abstract

To test more consistent and reliable upper-level turbulence forecasts, seven global numerical weather prediction (NWP) model outputs are used to construct the multimodel-based ensemble forecasts for clear-air turbulence (CAT). We used the updated version of the well-known Ellrod index, the Ellrod–Knox index (EKI), which is currently an operational CAT diagnostic for the significant weather chart at one of the World Area Forecast Centers. In this study, we tested two types of ensemble forecasts. First is an ensemble mean of all EKI forecasts from the NWP models. Second is a probabilistic forecast that is computed by counting how many individual EKI values from the seven NWP models exceed a certain EKI threshold at each grid point. Here, to calibrate the best EKI thresholds for the moderate-or-greater CAT intensity, the individual EKI thresholds, which vary depending on the resolutions and configurations of the NWP models, are selected using the 95th, 98th, and 98th percentiles of the probability density functions for the EKIs derived from the seven NWP models for a 6-month period. Finally, performance skills of both the ensemble mean and probabilistic forecasts are evaluated against the observations of in situ aircraft eddy dissipation rate and pilot reports. As a result, the ensemble mean forecast shows a better performance skill than the individual EKI forecasts. The reliability diagram for the probabilistic forecast gives a better reliability when using high-percentile EKI values as the threshold although it still suffers overestimation of CAT events likely due to the lack of observation and ensemble spreads.

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

Abstract

Aglobal 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, United States, 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.

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

Abstract

Based on a convective gravity wave drag parameterization scheme in a numerical weather prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from the operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, 11 widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for one whole year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root-mean-square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel.

Restricted access
Jung-Hoon Kim, Hye-Yeong Chun, Robert D. Sharman, and Teddie L. Keller
Full access
Jung-Hoon Kim, Hye-Yeong Chun, Robert D. Sharman, and Teddie L. Keller

Abstract

The forecast skill of upper-level turbulence diagnostics is evaluated using available turbulence observations [viz., pilot reports (PIREPs)] over East Asia. The six years (2003–08) of PIREPs used in this study include null, light, and moderate-or-greater intensity categories. The turbulence diagnostics used are a subset of indices in the Graphical Turbulence Guidance (GTG) system. To investigate the optimal performance of the component GTG diagnostics and GTG combinations over East Asia, various statistical evaluations and sensitivity tests are performed. To examine the dependency of the GTG system on the operational numerical weather prediction (NWP) model, the GTG system is applied to both the Regional Data Assimilation and Prediction System (RDAPS) analysis data and Global Forecasting System (GFS) analysis and forecast data with 30-km and 0.3125° (T382) horizontal grid spacings. The dependency of the temporal variation in the PIREP and GFS data and the forecast lead time of the GFS-based GTG combination are also investigated. It is found that the forecasting performance of the GTG system varies with year and season according to the annual and seasonal variations in the large-scale atmospheric conditions over the East Asia region. The wintertime GTG skill is the highest, because most GTG component diagnostics are related to jet streams and upper-level fronts. The GTG skill improves as the number of PIREP samples and the vertical resolution of the underlying NWP analysis data increase, and the GTG performance decreases as the forecast lead time increases from 0 to 12 h.

Full access