• Journal of Environmental Science International
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• v.10 no.6
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• pp.437-444
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• 2001

The characteristic features of surface ozone concentration and the forecasting procedure of high ozone days have been studied. The ozone concentration was continuously measured during 3 years (1997~1999) at air quality monitoring stations in five major cities in Korea. The diurnal variation of surface ozone concentration on high ozone days is characterized by low ozone concentration at night. The ozone concentration Increases continuously after sunrise, In reach a peak at 1500~1600 LST. Thereafter it decreases steadily to a low concentration at sunset. The diurnal and annual maximum of the surface ozone concentration at Seoul were observed in May and June, respectively. The favorable synoptic condition for the high ozone day is divided into 4 different synoptic weather patterns: a high-pressure system from the Sea of Okhotsk, the Pacific subtropical high extending westward, a moving high-pressure system covering the Korean peninsula. and a synoptic system In front of a typhoon. Most of high ozone days occur under the high pressure system in Korea.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.10 no.S_4
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• pp.197-206
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• 2001

The long-range transport mechanisms of Asian dust were analyzed based on the synoptic weather system and numerical simulation by using NCEP/NCAR reanalysis and TOMS data during the periods of 1996-2001. We classified the whole weather types of eastern Asia during spring and created the representative weather types during the yellow sand events using cluster analysis and weather charts for the last 6 years(1996~2001). These long-range transport mechanisms were related to various pressure patterns including high and low, trough and ridge, and upper-level fronts. Case studies of the yellow sand events have performed by the simulation of MM5 with meteorological elements such as the horizontal wind of u and v component, potential temperature, potential vorticity, and vertical circulation during the episodic days(2~8 March 2001). In addition, the origin of the long-range transport was examined with the estimation of backward trajectory using HYSPLIT4 Model. In this paper, we concluded that three weather types at 1000 hPa, 850 hPa, 500 hPa, and 300 hPa levels were classified respectively. The dominant features were the extending continental outflow from China to Korea at 1000 hPa and 850 hPa levels, the deep trough passage and cold advection at 500 hPa and 300 hPa levels during the yellow sand events. And also, we confirmed the existence of pola $r_tropical jets in the upper-level, the behavior of potential vorticity over Korea, the estimation of potential vorticity through vertical cross section, and the transport of yellow sand through backward trajectories.es.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.1
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• pp.57-74
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• 2009

In order to clarify the vertical ozone distribution in planetary boundary layer of coastal area with complex terrain, an observation campaign was carried out around Gwangyang Bay with dense pollutant emission sources during two days from June, 4 2007. For this observation are Radiosonde, SODAR(SOnic Detection And Ranging) and Tethered ozone sonde were employed. The surface meteorological and photochemical observation data provided by AWS (Automatic Weather System) and AQMS (Air Quality Monitoring System) were also applied for analysis. Synoptic condition is strongly associated with lower level ozone distribution in complex terrain coastal area. Since mesoscale circulation induced by difference of characteristics of land and sea and orographic forcing is predominant under calm synoptic condition, vertical distribution of ozone is complicate and vertical ozone concentration greatly fluctuated. However in second day when synoptic influence become strong, ozone concentration in lower levels is vertically uniform regardless of observation level. This results in vertical observation indicates that vertical ozone distribution is often determined by synoptic condition and also affects surface ozone concentration.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.74-85
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• 2014

This study is a part of "Early Warning Service for Weather Risk Management in Climate-smart Agriculture", describes the delivery techniques from 840 catchment scale weather warning information using 150 counties unit special weather report(alarm, warning) released from KMA(Korea Meteorological Administration) and chronic weather warning information based on daily weather data from 76 synoptic stations. Catchment weather hazard warning service express a sequential risk index map generated by countries report occurs and report grade(alarm, warning) convert to catchment scale using zonal summarizing method. Additional services were chronic weather warning service at crop growth and accumulated more than 4 weeks, based on an unsuitable weather conditions, representing a relative risk compared to its catchment climatological normal conditions (normal distribution ) in addition to special weather report. Service provided by a real-time catchment scale map overlaid with VWORLD open platform operated by Ministry of Land, Infrastructure and Transport. Also provide a foundation for weather risk information to inform individual farmers to farm located within the catchment zone warning occur.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.319-326
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• 2015

Rainfall data is necessary component for water resources design and flood warning system. Most analysis are used long-term hourly data of surface synoptic stations from the Meteorological Administration, Ministry of land, Infrastructure and Transport and others. However, It will be used minutely data of more high density automatic weather stations than surface synoptic stations expecting to increase the frequency of heavy precipitation. But minutely data has a problem about quality of rainfall data by auto observation. This study analyzed about quality control method using automatic weather station's minutely rainfall data of meteorological administration. It was performed assessment of the quality control that was classified quality control of miss Data, outlier data and rainfall interpolation. This method will be utilized when hydrological analysis uses minute rainfall data.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.853-864
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• 2016

Meteo-tsunamis are tsunamis that are typically caused by strong atmospheric instability (e.g., pressure jumps) in low pressure systems, but some meteo-tsunamis in winter can be caused by local atmospheric instability in high pressure systems (e.g., the Siberian High). In this study, we investigated a meteo-tsunami event related to a high pressure system that occurred during winter on the Yellow Sea in 2005. Sea level data from tidal stations were analyed with a high-pass filter, and we also performed synoptic weather analyses by using various synoptic weather data (e.g., surface weather charts) collected during the winter season(DJF) of 2005. A numerical weather model (WRF) was used to analyze the atmospheric instability on the day of the selected event (21 Dec. 2005). On the basis of the results, we suggest that the meteo-tsunami triggered by the high pressure system occurred because of dynamic atmospheric instability induced by the expansion and contraction of the Siberian High.

• Journal of the Korean Geographical Society
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• v.45 no.3
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• pp.319-341
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• 2010

The purposes of this study are to classify heavy snowfall types in the Republic of Korea based on fresh snowfall data and atmospheric circulation data during the last 36(1973/74-2008/09) snow seasons and to identify typical surface synoptic climate patterns that characterize each heavy snowfall type. Four synoptic climate categories and seventeen regional heavy snowfall types are classified based on sea level pressure/surface wind vector patterns in East Asia and frequent spatial clustering patterns of heavy snowfall in the Republic of Korea, respectively. Composite analyses of multiple surface synoptic weather charts demonstrate that the locations and intensity of pressure/wind vector mean and anomaly cores in East Asia differentiate each regional heavy snowfall type in Korea. These differences in synoptic climatic fields are primarily associated with the surge of the Siberian high pressure system and the appearance of low pressure systems over the Korean Peninsula. In terms of hemispheric atmospheric circulation, synoptic climatic patterns in the negative mode of winter Arctic Oscillation (AO) are also associated with frequent heavy snowfall in the Republic of Korea at seasonal scales. These results from long-term synoptic climatic data could contribute to improvement of short-range or seasonal prediction of regional heavy snowfall.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1071-1081
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• 2021

In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.

• Journal of Environmental Impact Assessment
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• v.16 no.1
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• pp.89-98
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• 2007

In order to conduct the environmental assessment of long range transboundary air pollutants over East Asia, the moving pathways of air pollutants are of great importance, which are depending upon the meteorological weather patterns. Therefore regional scale modeling study requires the identified geopotential height distribution patterns to deal with behaviors of long range transport air pollutants for the effective long term atmospheric environmental assessment. In this study the synoptic meteorological classification using cluster analysis technique over Northeast Asia, and its previous applications of the regional scale air pollutant modeling studies were reviewed and summarized in detail. Other synoptic meteorological characteristics over Korean peninsula are also discussed.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.