• Atmosphere
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• v.27 no.2
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• pp.119-131
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• 2017

We present and discuss the Tropopause Folding Turbulence Detection (TFTD) algorithm for the Korean Communication, Ocean, Meteorological Satellite (COMS) which is originally developed for the Tropopause Folding Turbulence Product (TFTP) from the Geostationary Operational Environmental Satellite (GOES)-R. The TFTD algorithm assumes that the tropopause folding is linked to the Clear Air Turbulence (CAT), and thereby the tropopause folding areas are detected from the rapid spatial gradients of the upper tropospheric specific humidity. The Layer Averaged Specific Humidity (LASH) is used to represent the upper tropospheric specific humidity calculated using COMS $6.7{\mu}m$ water vapor channel and ERA-interim reanalysis temperature at 300, 400, and 500 hPa. The comparison of LASH with the numerical model specific humidity shows a strong negative correlation of 80% or more. We apply the single threshold, which is determined from sensitivity analysis, for cloud-clearing to overcome strong gradient of LASH at the edge of clouds. The tropopause break lines are detected from the location of strong LASH-gradient using the Canny edge detection based on the image processing technique. The tropopause folding area is defined by expanding the break lines by 2-degree positive gradient direction. The validations of COMS TFTD is performed with Pilot Reports (PIREPs) filtered out Convective Induced Turbulence (CIT) from Dec 2013 to Nov 2014 over the South Korea. The score test shows 0.49 PODy (Probability of Detection 'Yes') and 0.64 PODn (Probability of Detection 'No'). Low POD results from various kinds of CAT reported from PIREPs and the characteristics of high sensitivity in edge detection algorithm.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.1-11
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• 2020

In order to diagnose low-level turbulence in Korea, diagnostic indices of low-level turbulence were calculated from Aug 2016 to Jul 2019 using a Korea Meteorological Administration Post Precessing (KMAPP) developed by the National Institute Meteorological Sciences (NIMS), and the indices were evaluated using Aircaft Meteorological Data Relay (AMDAR). In the mean horizontal distribution of diagnostic indices calculated, severe turbulence was simulated along major domestic mountains, including near the Taebaek Mountains, the Sobaek Mountains and Hallasan Mountain on Jeju Island due to geographical factors. Later, detection performance was evaluated by calculating the KMAPP Low-Level Turbulencd index (KLT) on combined index, using AUC value of Individual diagnostic indices as a weight. The result showed that the AUC value of KLT was 0.73, and the detection performance was improved (0.02-0.13) when the index was combined. Also, when looking for the AMDAR data is divided into years, seasons, and altitudes, up to 0.94 AUC values were found in winter (DJF) and the surface (surface-1,000ft). By using high-resolution numerical data reflecting detailed terrain data, local turbulence distribution was well demonstrated and high detection performance was shown at low-level.

• Atmosphere
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• v.25 no.2
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• pp.367-374
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• 2015

Korean Peninsula has high potential for occurrence of aviation turbulence. A Korean aviation Turbulence Guidance (KTG) system focused on the Korean Peninsula, named Korean-Peninsula KTG (KP-KTG) system, is developed using the high resolution (horizontal grid spacing of 1.5 km) Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration (KMA). The KP-KTG system is constructed first by selection of 15 best diagnostics of aviation turbulence using the method of probability of detection (POD) with pilot reports (PIREPs) and the LDAPS analysis data. The 15 best diagnostics are combined into an ensemble KTG predictor, named KP-KTG, with their weighting scores computed by the values of area under curve (AUC) of each diagnostics. The performance of the KP-KTG, represented by AUC, is larger than 0.84 in the recent two years (June 2012~May 2014), which is very good considering relatively small number of PIREPs. The KP-KTG can provide localized turbulence forecasting in Korean Peninsula, and its skill score is as good as that of the operational-KTG conducting in East Asia.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.2
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• pp.33-38
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• 2006

Heat transfer coefficients and static pressure distributions on a gas turbine vane endwall were experimentally investigated in a 5 bladed linear cascade. The Reynolds number based on an axial chord length and the cascade exit velocity was 500,000. Both heat transfer and pressure measurements on the vane endwall were made at the two different turbulence intensity levels of 6.8% and 10.8%. Detailed heat transfer coefficient distributions on the vane endwall region were measured using a hue detection based transient liquid crystals technique. Results show various regions of high and low heat transfer coefficients on the vane endwall surface due to several types of secondary flows and vortices. Heat transfer coefficient and endwall static pressure distributions showed similar trends for both turbulence intensity, however, the averaged heat transfer coefficients for higher turbulence intensity case was higher than the lower turbulence intensity case by 15%.

• Atmosphere
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• v.24 no.2
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• pp.235-243
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• 2014

Sources of aviation turbulence vary through the seasons, especially in the East Asia including Korean peninsula, associated primarily with the changes in the jet/front system and convective activities. For this reason, a seasonal Korean aviation Turbulence Guidance (KTG) system (seasonal-KTG) is developed in the present study by using pilot reports (PIREPs) and analysis data of the operational Unified Model (UM) of the Korea Meteorological Administration (KMA) for two years between June 2011 and May 2013. Twenty best diagnostics of aviation turbulence in each season are selected by the method of probability of detection (POD) using the PIREPs and UM data. After calculating a weighting value of each selected diagnostics using their area under curve (AUC), the 20 best diagnostics are combined with the weighting scores into a single ensemble-averaged index by season. Compared with the current operational-KTG system that is based on the diagnostics applying all seasons, the performances of the seasonal-KTG system are better in all seasons, except in fall.

• New & Renewable Energy
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• v.18 no.1
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• pp.1-16
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• 2022

Climatic characteristics were described using the LiDAR (Light Detection and Ranging) and the met-mast on Dongbok·Bukchon region. The influences of meteorological conditions on the power performance of wind turbines were presented using the data of Supervisory Control And Data Acquisition (SCADA) and met-mast of the Dongbok·Bukchon Wind Farm (DBWF) located in Jeju Island. The stability was categorized into three parameters (Richardson number, Turbulence intensity, and Wind shear exponent). DBWF was dominant in unstable atmospheric conditions. At wind speeds of 14 m/s or more, the proportion of slightly unstable conditions accounted for more than 50%. A clear difference in the power output of the wind turbine was exhibited in the category of atmospheric stability and turbulence intensity (TI). Particularly, a more sensitive difference in power performance was showed in the rated wind speeds of the wind turbine and wind regime with high TI. When the flow had a high turbulence at low wind speeds and a low turbulence at rated wind speeds, a higher wind energy potential was produced than that in other conditions. Finally, the high-efficiency of the wind farm was confirmed in the slightly unstable atmospheric stability. However, when the unstable state become stronger, the wind farm efficiency was lower than that in the stable state.

• Atmosphere
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• v.19 no.3
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• pp.269-287
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• 2009

CAT (clear-air turbulence) forecasting algorithm, the Graphical Turbulence Guidance (GTG) system developed at NCAR (national center for atmospheric research), is evaluated with available observations (e.g., pilot reports; PIREPs) reported in South Korea during the recent 5 years (2003-2008, excluding 2005). The GTG system includes several steps. First, 44 CAT indices are calculated in the domain of the Regional Data Assimilation and Prediction System (RDAPS) analysis data with 30 km horizontal grid spacing provided by KMA (Korean Meteorological Administration). Second, 10 indices that performed ten best forecasting scores are selected. Finally, 10 indices are combined by measuring the score based on the probability of detection, which is calculated using PIREPs exclusively of moderate-or-greater intensity. In order to investigate the best performance of the GTG system in Korea, various statistical examinations and sensitivity tests of the GTG system are performed by yearly and seasonally classified PIREPs. Performances of the GTG system based on yearly distributed PIREPs have annual variations because the compositions of indices are different from each year. Seasonal forecasting is generally better than yearly forecasting, because selected CAT indices in each season represent meteorological condition much more properly than applying the selected CAT indices to all seasons. Wintertime forecasting is the best among the four seasonal forecastings. This is likely due to that the GTG system consists of many CAT indices related to the jet stream, and turbulence associated with the jet stream can be activated mostly in wintertime under strong jet magnitude. On the other hand, summertime forecasting skill is much less than other seasons. Compared with current operational CAT prediction system (KITFA; Korean Integrated Turbulence Forecasting System), overall performance of the GTG system is better when CAT indices are selected seasonally.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.25-37
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• 2017

A study on factors influencing measurement error of Ground-based LiDAR(Light Detection And Ranging) system was conducted in Kimnyeong wind turbine test site on Jeju Island. Three properties of wind including inclined angle, turbulence intensity and power law exponent were taken into account as factors influencing the measurement error of Ground-based LiDAR. In order to calculate LiDAR measurements error, 2.5-month wind speed data collected from LiDAR (WindCube v2) were compared with concurrent data from the anemometer on a nearby 120m-high meteorological mast. In addition, data filtering was performed and its filtering criteria was based on the findings at previous researches. As a result, at 100m above ground level, absolute LiDAR error rate with absolute inclined angle showed 4.58~13.40% and 0.77 of the coefficients of determination, $R^2$. That with turbulence intensity showed 3.58~23.94% and 0.93 of $R^2$ while that with power law exponent showed 4.71~9.53% and 0.41 of $R^2$. Therefore, it was confirmed that the LiDAR measurement error was highly affected by inclined angle and turbulence intensity, while that did not much depend on power law exponent.

• Atmosphere
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• v.28 no.2
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• pp.223-232
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• 2018

The Global-Korean aviation Turbulence Guidance (G-KTG) system is developed using the operational Global Data Assimilation and Prediction System of Korea Meteorological Administration with 17-km horizontal grid spacing. The G-KTG system provides an integrated solution of various clear-air turbulence (CAT) diagnostics and mountain-wave induced turbulence (MWT) diagnostics for low [below 10 kft (3.05 km)], middle [10 kft (3.05 km) - 20 kft (6.10 km)], and upper [20 kft (6.10 km) - 50 kft (15.24 km)] levels. Individual CAT and MWT diagnostics in the G-KTG are converted to a 1/3 power of energy dissipation rate (EDR). 12-h forecast of the G-KTG is evaluated using 6-month period (2016.06~2016.11) of in-situ EDR observation data. The forecast skill is calculated by area under curve (AUC) where the curve is drawn by pairs of probabilities of detection of "yes" for moderate-or-greater-level turbulence events and "no" for null-level turbulence events. The AUCs of G-KTG for the upper, middle, and lower levels are 0.79, 0.69, and 0.63, respectively. Comparison of the upper-level G-KTG with the regional-KTG in East Asia reveals that the forecast skill of the G-KTG (AUC = 0.77) is similar to that of the regional-KTG (AUC = 0.79) using the Regional Data Assimilation and Prediction System with 12-km horizontal grid spacing.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.2
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• pp.145-151
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• 2011

In this paper, among the active islanding detection techniques, the modified active frequency drift method was analyzed, which is relatively easy to apply to the single-phase grid-connected PV PCS. The existing designs for turbulences in these applications were empirically conducted, and do not have sufficient reliability and performance. Therefore, three application forms of the modified active frequency drift technique were modeled, based on which the proper magnitude of turbulence, which is the frequency acceleration component, was calculated. Using the results, the magnitude of and injection method for turbulence for ensuring the islanding detection performance and improving the output power quality were proposed, and they were verified via simulations and experiment to prove that the reliable islanding detection technique can be developed merely by measuring the basic output power quality, without the need for expensive islanding simulation equipment.