• Journal of Environmental Science International
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• v.22 no.10
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• International Journal of Contents
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• v.18 no.1
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• pp.17-26
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• 2022

With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.

• Atmosphere
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• v.23 no.4
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• pp.443-452
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• 2013

The original Fog Stability Index (FSI) is formulated as FSI=$2(T-T_d)+2(T-T_{850})+WS_{850}$, where $T-T_d$ is dew point deficit (temperature-dew point temperature), $T-T_{850}$ is atmospheric stability measure (temperature-temperature at 850 hPa altitude) and $WS_{850}$ is wind speed at 850 hPa altitude. As a way to improve fog prediction at Incheon International Airport (IIA), we develop the modified FSI for IIA, using the meteorological data at IIA for two years from June 2011 to May 2013, the first one year for development and the second one year for validation. The relative contribution of the three parameters of the modified FSI is 9: 1: 0, indicating that $WS_{850}$ is found to be a non-contributing factor for fog formation at IIA. The critical success index (CSI) of the modified FSI is 0.68. Further development is made to consider the fact that fogs at IIA are highly influenced by advection of moisture from the Yellow Sea. One added parameter after statistical evaluation of the several candidate parameters is the dew point deficit at a buoy over the Yellow Sea. The relative contribution of the four parameters (including the new one) of the newly developed FSI is 10: 2: 0.5: 6.4. The CSI of the new FSI is 0.50. Since the developmental period of one year is too short, the FSI should be refined more as the data are accumulated more.

• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Atmosphere
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• v.18 no.4
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• pp.299-316
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• 2008

The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.59-70
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• 2023

In order to predict low-level wind shear at Incheon International Airport (RKSI), a Low-Level Wind Shear prediction system (KMAP-LLWS) along the runway take-off and landing route at RKSI was established using Korea Meteorological Administration Post-Processing (KMAP). For the performance evaluation, the case of low-level wind shear cases calculated from Aircraft Meteorological Data Relay (AMDAR) from July 2021 to June 2022 was used. As a result of verification using the performance evaluation index, POD, FAR, CSI, and TSS were 0.5, 0.85, 0.13, and 0.34, respectively, and the prediction performance was improved by POD, CSI, and TSS compared to the Low-Level Wind Shear prediction system (LDPS-LLWS) calculated using the Korea Meteorological Administration's Local Data Assimilation and Prediction System (LDAPS). This means that the use of high-resolution numerical models improves the predictability of wind changes. In addition, to improve the high FAR of KMAP-LLWS, the threshold for low-level wind shear strength was adjusted. As a result, the most effective low-level wind shear threshold at 8.5 knot/100 ft was derived. This study suggests that it is possible to predict and respond to low-level wind shear at RKSI. In addition, it will be possible to predict low-level wind shear at other airports without wind shear observation equipment by applying the KMAP-LLWS.

• Journal of Plant Biology
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• v.26 no.2
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• pp.101-117
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• 1983

The phenological phenomena in terms of year day index (YDI) in South Korea were studied. The YDI was proposed here, because the remainer index such as Nuttonson's index is unadequate for the interpretation on the phenological phenomena of early spring season in sourthern coastal area. The YDI was calculated by summing daily mean temperature of the year days (YD) above physical zero degree in centigrade, based on the data of the Monthly Weather Reports from 1967 to 1980 by the Central Meteorological Office. The pattern of YDI increase with the increase of YD was similar to that of the remainder index such as the Nuttonson's index. The some YDI distribution maps were made by Yim and Kira (1975), dividing into 30'$\times$40' meshes, in latitude and longtude, on the topographical map(1 : 500,000) of the Korea Peninsula. According to the year day of different localities flowering dates of Prunus yedoensis and other phenological phenomena in various species delayed about 3.5 day as the increase of 1 degree of latitude, which coincides with the Hopkins bioclimatic law. It was found that the YDI is useful to interprete the phenology of plant and animal species and to select the optimum range of cultivars in South Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.457-467
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• 2022

Drought has strong local characteristics, an objective definition or standard that can define the progress or severity of drought is needed and to date, many drought-related studies are being conducted around the world. In this study, Standardized Precipitation Index (SPI), which is a representative meteorological drought index, was calculated, and the drought risk index (DRI) that can consider actual drought was applied to the target area, Uiryeong-gun, by applying the drought vulnerability index (DVI) and the drought hazard index (DHI). A method for practical drought evaluation that can establish a water supply system is presented in this study.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.1-11
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• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• Journal of Environmental Science International
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• v.23 no.11
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• pp.1929-1941
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• 2014

Now a days, frequency of abnormally high temperatures like heat wave by global warming and climate change is increasing constantly and the number of patient with heat related illness are jumping rapidly. In this study, we chose the case day for the heat wave in Busan area(Busan and Yangsan), 2013 which it was the most hottest year during 21th century. And then, we analysed the weather condition using automatic synoptic observing system(ASOS) data. Also, four indices, heat index(HI), wet bulb globe temperature(WBGT), Man-ENvironment heat EXchange model(MENEX)'s results like Physiological subjective temperature(PST), Physiological strain(PhS), were calculated to evaluate the thermal comfort and stress quantitatively. However, thermal comfort was different as the each station and thermal comfort index during same time. Busan's thermal indices (HI: hot, WBGT: sweltering, PST: very hot, PhS: very hot) indicated relatively higher than Yansan's (HI: very hot, WBGT: sweltering, PST: very hot, PhS: sweltering). It shows that Busan near coast is relatively more comfortable than Yangsan located in inland.