• Title/Summary/Keyword: Synoptic key

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Note on the New Korean Common Names of Marasmioid Fungi -1. The Genus Marasmius (한국산 낙엽버섯류의 새로운 한국어 일반명 -1. 낙엽버섯속)

  • Ryoo, Rhim;Antonin, Vladimir;Ka, Kang-Hyeon;Shin, Hyeon-Dong
    • The Korean Journal of Mycology
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    • v.41 no.4
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    • pp.280-286
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    • 2013
  • 47 species was reported in the genus Marasmius in Republic of Korea up to now. 26 of total 47 species previously recorded from Korea were made up a list. Korean common names of 10 new species and 11 species newly recorded in Korea were introduced in study with synoptic key. These names were followed by the Romanization rule to express Korean common name.

Non-stationary and non-Gaussian characteristics of wind speeds

  • Hui, Yi;Li, Bo;Kawai, Hiromasa;Yang, Qingshan
    • Wind and Structures
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    • v.24 no.1
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    • pp.59-78
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    • 2017
  • Non-stationarity and non-Gaussian property are two of the most important characteristics of wind. These two features are studied in this study based on wind speed records measured at different heights from a 325 m high meteorological tower during the synoptic wind storms. By using the time-frequency analysis tools, it is found that after removing the low frequency trend of the longitudinal wind, the retained fluctuating wind speeds remain to be asymmetrically non-Gaussian distributed. Results show that such non-Gaussianity is due to the weak-stationarity of the detrended fluctuating wind speed. The low frequency components of the fluctuating wind speeds mainly contribute to the non-zero skewness, while distribution of the high frequency component is found to have high kurtosis values. By further studying the decomposed wind speed, the mechanisms of the non-Gaussian distribution are examined from the phase, turbulence energy point of view.

Effects of the Subgrid-Scale Orography Parameterization and High-Resolution Surface Data on the Simulated Wind Fields in the WRF Model under the Different Synoptic-Scale Environment (종관 환경 변화에 따른 아격자 산악모수화와 고해상도 지면 자료가 WRF 모델의 바람장 모의에 미치는 영향)

  • Lee, Hyeon-Ji;Kim, Ki-Byung;Lee, Junhong;Shin, Hyeyum Hailey;Chang, Eun-Chul;Lim, Jong-Myoung;Lim, Kyo-Sun Sunny
    • Atmosphere
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    • v.32 no.2
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    • pp.103-118
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    • 2022
  • This study evaluates the simulated meteorological fields with a particular focus on the low-level wind, which plays an important role in air pollutants dispersion, under the varying synoptic environment. Additionally, the effects of subgrid-scale orography parameterization and improved topography/land-use data on the simulated low-level wind is investigated. The WRF model version 4.1.3 is utilized to simulate two cases that were affected by different synoptic environments. One case from 2 to 6 April 2012 presents the substantial low-level wind speed over the Korean peninsula where the synoptic environment is characterized by the baroclinic instability. The other case from 14 to 18 April 2012 presents the relatively weak low-level wind speed and distinct diurnal cycle of low-level meteorological fields. The control simulations of both cases represent the systematic overestimation of the low-level wind speed. The positive bias for the case under the baroclinic instability is considerably alleviated by applying the subgrid-scale orography parameterization. However, the improvement of wind speed for the other case showing relatively weak low-level wind speed is not significant. Applying the high-resolution topography and land-use data also improves the simulated wind speed by reducing the positive bias. Our analysis shows that the increased roughness length in the high-resolution topography and land-use data is the key contributor that reduces the simulated wind speed. The simulated wind direction is also improved with the high-resolution data for both cases. Overall, our study indicates that wind forecasts can be improved through the application of the subgrid-scale orography parameterization and high-resolution topography/land-use data.

A data-driven method for the reliability analysis of a transmission line under wind loads

  • Xing Fu;Wen-Long Du;Gang Li;Zhi-Qian Dong;Hong-Nan Li
    • Steel and Composite Structures
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    • v.52 no.4
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    • pp.461-473
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    • 2024
  • This study focuses on the reliability of a transmission line under wind excitation and evaluates the failure probability using explicit data resources. The data-driven framework for calculating the failure probability of a transmission line subjected to wind loading is presented, and a probabilistic method for estimating the yearly extreme wind speeds in each wind direction is provided to compensate for the incompleteness of meteorological data. Meteorological data from the Xuwen National Weather Station are used to analyze the distribution characteristics of wind speed and wind direction, fitted with the generalized extreme value distribution. Then, the most vulnerable tower is identified to obtain the fragility curves in all wind directions based on uncertainty analysis. Finally, the failure probabilities are calculated based on the presented method. The simulation results reveal that the failure probability of the employed tower increases over time and that the joint probability distribution of the wind speed and wind direction must be considered to avoid overestimating the failure probability. Additionally, the mixed wind climates (synoptic wind and typhoon) have great influence on the estimation of structural failure probability and should be considered.

Local Enhancement Mechanism of Cold Surges over the Korean Peninsula (한반도 한파의 지역적 강화 메커니즘)

  • Lee, Hye-Young;Kim, Joowan;Park, In-Gyu;Kang, Hyungyu;Ryu, Hosun
    • Atmosphere
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    • v.28 no.4
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    • pp.383-392
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    • 2018
  • This study investigates synoptic characteristics of cold surges over South Korea during winter season (December-February). A total of 63 cold events are selected by quantile regression analysis using daily mean temperature observations from 11 KMA stations for 38 years (1979/80-2016/17). Large-scale pressure pattern during the cold surges is well characterized by high over Siberia and low over Aleutian regions, which elucidates cold advection over the Korean peninsula. However, the large-scale pattern cannot successfully explain the observed sudden decrease of temperature during the cold surges. Composite analyses reveal that a synoptic-scale cyclone developing over the northern Japan is a key feature that significantly contribute to the enhancement of cold advection by increasing pressure gradient over the Korean peninsula. Enhanced sensible and latent heat fluxes are observed over the southern ocean of Korea and Japan during the cold surges due to temperature and humidity differences between the near surface and the lower atmosphere over the ocean. The evaporated water vapor transported toward the center of the surface cyclone and condenses in the lower-to-middle troposphere. The released energy likely promotes the development of the surface cyclone by inducing positive PV near the surface of the heating region.

Development of Multi-Ensemble GCMs Based Spatio-Temporal Downscaling Scheme for Short-term Prediction (여름강수량의 단기예측을 위한 Multi-Ensemble GCMs 기반 시공간적 Downscaling 기법 개발)

  • Kwon, Hyun-Han;Min, Young-Mi;Hameed, Saji N.
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1142-1146
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    • 2009
  • A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

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Application of machine learning for merging multiple satellite precipitation products

  • Van, Giang Nguyen;Jung, Sungho;Lee, Giha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.134-134
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    • 2021
  • Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

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Deriving vertical velocity in tornadic wind field from radar-measured data and improving tornado simulation by including vertical velocity at velocity inlet

  • Yi Zhao;Guirong Yan;Ruoqiang Feng;Zhongdong Duan;Houjun Kang
    • Wind and Structures
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    • v.38 no.4
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    • pp.245-259
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    • 2024
  • In a tornadic wind field, the vertical velocity component in certain regions of tornadoes can be significant, forming one of the major differences between tornadic wind fields and synoptic straight-line wind fields. To better understand the wind characteristics of tornadoes and properly estimate the action of tornadoes on civil structures, it is important to ensure that all the attributes of tornadoes are captured. Although Doppler radars have been used to measure tornadic wind fields, they can only directly provide information on quasi-horizontal velocity. Therefore, lots of numerical simulations and experimental tests in previous research ignored the vertical velocity at the boundary. However, the influence of vertical velocity in tornadic wind fields is not evaluated. To address this research gap, this study is to use an approach to derive the vertical velocity component based on the horizontal velocities extracted from the radar-measured data by mass continuity. This approach will be illustrated by using the radar-measured data of Spencer Tornado as an example. The vertical velocity component is included in the initial inflow condition in the CFD simulation to assess the influence of including vertical velocity in the initial inflow condition on the entire tornadic wind field.

Evaluation of horizontal-axis-three-blade wind turbines' behavior under different tornado wind fields

  • Mohamed AbuGazia;Ashraf El Damatty;Kaoshan Dai;Wensheng Lu;Nima Ezami
    • Wind and Structures
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    • v.37 no.6
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    • pp.413-423
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    • 2023
  • Wind turbines are usually steel hollow structures that can be vulnerable to dramatic failures due to high-intensity wind (HIW) events, which are classified as a category of localized windstorms that includes tornadoes and downbursts. Analyzing Wind Turbines (WT) under tornadoes is a challenging-to-achieve task because tornadoes are much more complicated wind fields compared with the synoptic boundary layer wind fields, considering that the tornado's 3-D velocity components vary largely in space. As a result, the supporting tower of the wind turbine and the blades will experience different velocities depending on the location of the event. Wind farms also extend over a large area so that the probability of a localized windstorm event impacting one or more towers is relatively high. Therefore, the built-in-house numerical code "HIW-WT" has been developed to predict the straining actions on the blades considering the variability of the tornado's location and the blades' pitch angle. The developed HIWWT numerical model incorporates different wind fields that were generated from developed CFD models. The developed numerical model was applied on an actual wind turbine under three different tornadoes that have different tornadic structure. It is found that F2 tornado wind fields present significant hazard for the wind turbine blades and have to be taken into account if the hazardous impact of this type of unexpected load is to be avoided.

The Features of Asian Dust Events Originated in Manchuria (만주에서 발원한 황사현상 (II) -2001년 이후 사례를 중심으로-)

  • Kim, Sumin;Chun, Youngsin;Kim, Seung-Bum
    • Atmosphere
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    • v.20 no.3
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    • pp.273-286
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    • 2010
  • The northeast part of China(hereafter Manchuria) is one of Asian dust source regions along with Gobi, Inner Mongolia and Loess Plateau. In this study, a geographical survey over the area was carried out to determine its soil characteristics in June 2009. It revealed that some parts of the area, especially near Keerchin desert, consist of alkali clay soil mixed up with sand. Manchuria, where is a vast cornfield, can be a potential source region of Asian dust from fall to following spring after harvesting. The frequency of Asian dust over the region from 1996 to 2009 was examined using 3-hourly GTS SYNOP data and it showed that the occurrence of Asian dust over the region is high in the springtime. It was also revealed that snow cover is the key parameter affecting on the frequency through the analysis of NCEP reanalysis data. To scrutinize the path and structure of Asian dust from Manchuria, the event on 3~4 April 2008 and 25 January 2010 were intensively investigated with regard to features of synoptic weather patterns, satellite imagery, airstream, naked eye-observations, concentrations of PM10, 2.5 and 1.0. For this case, the Asian dust from the area reached to Korea less than a day. However, the duration time of the dust in Korea was short (< 7 hours). The average of hourly PM10 reached up to $340{\mu}g/m^{3}$ at Baengnyeondo during the period. The high PM2.5 and PM1.0 concentrations were also observed at several sites in Korea, indicating that air pollutants could be transported along with the dust.