• Atmosphere
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• v.16 no.3
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• pp.247-257
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• 2006

The Yeong-dong heavy snowfall forecast supporting system has been developed during the last several years. In order to construct the conceptual model, we have examined the characteristics of heavy snowfalls in the Yeong-dong region classified into three precipitation patterns. This system is divided into two parts: forecast and observation. The main purpose of the forecast part is to produce value-added data and to display the geography based features reprocessing the numerical model results associated with a heavy snowfall. The forecast part consists of four submenus: synoptic fields, regional fields, precipitation and snowfall, and verification. Each offers guidance tips and data related with the prediction of heavy snowfalls, which helps weather forecasters understand better their meteorological conditions. The observation portion shows data of wind profiler and snow monitoring for application to nowcasting. The heavy snowfall forecast supporting system was applied and tested to the heavy snowfall event on 28 February 2006. In the beginning stage, this event showed the characteristics of warm precipitation pattern in the wind and surface pressure fields. However, we expected later on the weak warm precipitation pattern because the center of low pressure passing through the Straits of Korea was becoming weak. It was appeared that Gangwon Short Range Prediction System simulated a small amount of precipitation in the Yeong-dong region and this result generally agrees with the observations.

• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.337-348
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• 2011

Urban environmental problem became one of major issues during its urbanization processes. Environmental impacts are assessed during recent urban planning and development. Though the environmental impact assessment considers meteorological impact as a minor component, changes in wind environment during development can largely affect the distribution pattern of air temperature, humidity, and pollutants. Impact assessment of local wind is, therefore, a major element for impact assessment prior to any other meteorological impact assessment. Computational Fluid Dynamics (CFD) models are utilized in various fields such as in wind field assessment during a construction of a new building and in post analysis of a fire event over a mountain. CFD models require specially formatted input data and produce specific output files, which can be analyzed using special programs. CFD's huge requirement in computing power is another hurdle in practical use. In this study, a CFD model and related software processors were automated and integrated as a microscale wind environmental impact assessment system. A supercomputer system was used to reduce the running hours of the model. Input data processor ingests development plans in CAD or GIS formatted files and produces input data files for the CFD model. Output data processor produces various analytical graphs upon user requests. The system was used in assessing the impacts of a new building near an observatory on wind fields and showed the changes by the construction visually and quantitatively. The microscale wind assessment system will evolve, of course, incorporating new improvement of the models and processors. Nevertheless the framework suggested here can be utilized as a basic system for the assessment.

• Atmosphere
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• v.31 no.5
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• pp.563-576
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• 2021

The performance of East Asian summer monsoon is assessed for GC2 and GC3.1, which are climate change models of the current and next climate prediction system in the Korea Meteorological Administration (KMA), GloSea5 and GloSea6. The most pronounced characteristics of GC models are strong monsoon trough and the weakening of the Western North Pacific Subtropical High (WNPSH). These are related to the weakening of the southwesterly wind and resulting weak monsoon band toward the Korean Peninsula. The GC3.1 is known to have improved the model configuration version compared to GC2, such as cloud physics and ocean parameters. We can confirm that the overall improvements of GC3.1 against GC2, especially in pressure, 850 hPa wind fields, and vertical wind shear. Also, the precipitation band stagnant in the south of 30°N in late spring is improved, therefore the biases of rainy onset and withdrawal on the Korean Peninsula are reduced by 2~4 pentad. We also investigate the impact of initialization in comparison with GloSea5 hindcast. Compared with GCs, hindcast results show better simulation within 1 month lead time, especially in pressure and 850 hPa wind fields, which can be expected to the improvement of WNPSH. Therefore, it is expected that the simulation performance of WNPSH will be improved in the result of applying the initialization of GloSea6.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.6
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• pp.600-618
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• 2014

The metadata for urban meteorological observation is standardized through comparison with those established at the World Meteorological Organization and the Korea Meteorological Administration to understand the surrounding environment around the sites exactly and maintain the networks and sites efficiently. It categorizes into metadata for an observational network and observational sites. The latter is again divided into the metadata for station general information, local scale information, micro scale information, and visual information in order to explain urban environment in detail. The metadata also contains the static information such as urban structure, surface cover, metabolism, communication, building density, roof type, moisture/heat sources, and traffic as well as the update information on the environment change, maintenance, replacement, and/or calibration of sensors. The standardized metadata for urban meteorological observation is applied to the Weather Information Service Engine (WISE) integrated meteorological sensor network and sites installed at Incheon area. It will be very useful for site manager as well as researchers in fields of urban meteorology, radiation, surface energy balance, anthropogenic heat, turbulence, heat storage, and boundary layer processes.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.47-59
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• 2011

The purpose of this paper is to simulate the high ozone concentration in Shiwha Banwol indusrial complex. High pollution episodes (ozone alert) of this area are the results of geographical location and its air pollutants emission. This research has used meteorological model (RAMS) and photochemical air pollution Model (CIT model). As first step of the evaluate of this combined model system simulations are done in terms of meteorological characteristics like wind fields, PBL-height, etc.. Numerical simulations are carried out with real meteorological synoptic data on June. 24-25, 2010. In comparison with real measurement and another research the model reflects well local meteorological phenomena and shows the possibility to be utilized to analyse the pollutant dispersion over irregular terrain region. The high ozone concentration is deeply correlated to the ambient air temperature, wind speed and solar radiation. Local meteorological phenomena like sea-land breeze impact on horizontal dispersion of ozone. This analysis of meteorological characteristics can, in turn, help to predict their influences on air quality and to manage the high ozone episodes.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.554-569
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• 2017

Sensitivity analysis on $PM_{10}$ forecasting simulations was carried out by using two different initial and boundary conditions of meteorological fields: NCEP/FNL (National Centers for Environmental Prediction/Final Analysis) reanlaysis data and NCEP/GFS (National Centers for Environmental Prediction/Global Forecast System) forecasting data, and the comparisons were made between two different simulations. The two results both yielded lower $PM_{10}$ concentrations than observations, with relatively lower biased results by NCEP/FNL than NCEP/GFS. We explored the detailed individual meteorological variables to associate with $PM_{10}$ prediction performance. With the results of NCEP/FNL outperforming GFS, our conclusion is that no particular significant bias was found in temperature fields between NCEP/FNL and NCEP/GFS data, while the overestimated wind speed by NCEP/GFS data influenced on the lower $PM_{10}$ concentrations simulation than NCEP/FNL, by decreasing the duration time of high-$PM_{10}$ loaded air mass over both coastal and metropolitan areas. These comparative characteristics of FNL against GFS data such as maximum 3~4 m/s weaker wind speed, $PM_{10}$ concentration control with the highest possible factor of 1.3~1.6, and one or two hour difference of peak time for each case in this study, were also reflected into the results of statistical analysis. It is implying that improving the surface wind speed fluctuation is an important controlling factor for the better prediction of $PM_{10}$ over Korean Peninsula.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1225-1235
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• 2011

This paper suggests a method for tuning a numerically simulated wind speed data, provided by NIMR(National Institute of Meteorological Research) and generated from a numerical meteorological model to improve a wind resource map with a $1Km{\times}1Km$ resolution. To this end, "tuning factor method" is developed that consists of two procedures. First, estimate monthly wind fields based on a suitably designed statistical wind field model that covers 345,682 regions obtained by $1Km{\times}1Km$ lattice sites in South Korea. The second procedure computes the tuning factor and then tunes the generated wind speeds of each month as well as each lattice site. The second procedure is based on the wind fields estimated by the first procedure. The performance of the suggested tuning method is demonstrated by using two wind data(both TMY and numerically simulated wind speed data) of 75 weather station areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

• Ocean and Polar Research
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• v.40 no.3
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• pp.99-114
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• 2018

In the present study, we assess the GloSea5 (Global Seasonal Forecasting System version 5) near-surface ocean current forecasts using globally observed surface drifter dataset. Annual mean surface current fields at 0-day forecast lead time are quite consistent with drifter-derived velocity fields, and low values of root mean square (RMS) errors distributes in global oceans, except for regions of high variability, such as the Antarctic Circumpolar Current, Kuroshio, and Gulf Stream. Moreover a comparison with the global high-resolution forecasting system, HYCOM (Hybrid Coordinate Ocean Model), signifies that GloSea5 performs well in terms of short-range surface-current forecasts. Predictions from 0-day to 4-week lead time are also validated for the global ocean and regions covering the main ocean basins. In general, the Indian Ocean and tropical regions yield relatively high RMS errors against all forecast lead times, whilst the Pacific and Atlantic Oceans show low values. RMS errors against forecast lead time ranging from 0-day to 4-week reveal the largest increase rate between 0-day and 1-week lead time in all regions. Correlation against forecast lead time also reveals similar results. In addition, a strong westward bias of about $0.2m\;s^{-1}$ is found along the Equator in the western Pacific on the initial forecast day, and it extends toward the Equator of the eastern Pacific as the lead time increases.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.523-537
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• 2004

In order to raise the accuracy of meteorological data, several numerical experiments about the usefulness of data assimilation to prediction of air pollution was carried out. Used data for data assimilation are surface meteorological components observed by Automatical Weather System with high spatial density. The usage of surface data assimilation gives changes of temperature and wind fields and the change caused by the influence of land-use on meterological simulation is more sensitive at night than noon. The data quality in assimilation it also one of the important factors to predict the meteorological field precisely and through the static IOA (Index of Agreement), simulated meteorological components with selected limited surface data assimilation are agree well with observations.