• Journal of the Korean earth science society
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• v.42 no.5
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• pp.504-513
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• 2021

Different physical processes, according to the atmospheric boundary layer types, were used in the Local Data Assimilation and Prediction System (LDAPS) of the Unified Model (UM) used by the Korea Meteorological Administration (KMA). Therefore, it is important to verify the atmospheric boundary layer types in the numerical model to improve the accuracy of the models performance. In this study, the atmospheric boundary layer types were verified using observational data. To classify the atmospheric boundary layer types, summer intensive observation data from radiosonde, flux observation instruments, Doppler wind Light Detection and Ranging(LIDAR) and ceilometer were used. A total number of 201 observation data points were analyzed over the course 61 days from June 18 to August 17, 2019. The most frequent types of differences between LDAPS and observed data were type 1 in LDAPS and type 2 in observed(each 53 times). And type 3 difference was observed in LDAPS and type 5 and 6 were observed 24 and 15 times, respectively. It was because of the simulation performance of the Cloud Physics such as that associated with the simulation of decoupled stratocumulus and cumulus cloud. Therefore, to improve the numerical model, cloud physics aspects should be considered in the atmospheric boundary layer type classification.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.119-134
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• 2019

In order to analyze the observational environment of solar radiation stations operated by the Korea Meteorological Administration (KMA), we used the digital elevation model (DEM) and the solar radiation model to calculate a topographical shading, sky view factor (SVF) and solar radiation by surrounding terrain. The sky line and SVF were calculated using high resolution DEM around 25 km of the solar stations. We analyzed the topographic effect by analyzing overlapped solar map with sky line. Particularly, Incheon station has low SVF whereas Cheongsong and Chupungryong station have high SVF. In order to validation the contribution of topographic effect, the solar radiation calculated using GWNU solar radiation model according to the sky line and SVF under the same meteorological conditions. As a result, direct, diffuse and global solar radiation were decreased by 12.0, 5.6, and 4.7% compared to plane surface on Cheongsong station. The 6 stations were decreased amount of mean daily solar radiation to the annual solar radiation. Among 42 stations, eight stations were analyzed as the urgent transfer stations or moving equipment quickly and more than half of stations (24) were required to review the observational environment. Since the DEM data do not include artifacts and vegetation around the station, the stations need a detail survey of observational environment.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.451-461
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• 2019

The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.15-26
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• 2019

The stability of the gravity quay wall against earthquakes is evaluated on the basis of the allowable displacement of the wall. To estimate the displacement caused by external forces, empirical equations based on the Newmark sliding block method or numerical analysis are widely used. In numerical analysis, it is possible to analyze precisely a complicated site and structure, but difficult to set the appropriate parameters and environments; there are limitations in obtaining reliable results, depending on one's level of expertise. The Newmark method, with only seismic motions, is widely used because it is simpler than numerical simulations when estimating permanent displacement. However, the empirical equations do not have any parameters for the response characteristics and sliding block of the structure, and sliding blocks being assumed as rigid bodies does not consider the nonlinear behavior of the soil and interaction with the structure. Therefore, in order to evaluate the seismic stability of the gravity quay wall, a newly-developed empirical equation is needed to overcome the above-mentioned limitations. In this study, numerical simulations are performed to analyze the response characteristics of the backfill of the structure, and to propose an optimal method of calculating the active area. For this purpose, finite element analyses were performed to analyze the response characteristics, and stress-strain relationships for various seismic motions. As a result, the response characteristics, sliding block, and failure surface of the backfill vary depending on the input seismic motions.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.39-50
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• 2012

KMA(Korea Meteorological Administration) projected that annual mean temperatures of South Korea will rise $3.8^{\circ}C$ and the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea. Thus the risk of landslide by heavy rain is expected to increase. After the landslide of Mt. Umyeon occurred in July 2011, disaster of forest sector is highlighted. Therefore vulnerability assessment of landslide is urgent. However, vulnerability assessment based on local governments was not done yet. In this study, we assess vulnerability of landslide by heavy rain for local governments. We used several scenarios to consider uncertainty of climate change. Through this study, local governments can use the results to establish adaptation plans. Also, the results could be used to decrease vulnerability of landslide.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.402-413
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• 2022

Objectives: In this study, the scale of exceeding the extreme heat exposure standard at the construction site was estimated using the nationally approved statistical data and wet bulb globe temperature modeling method. By comparing and analyzing the modeling results with the existing work environment monitoring results, the risk of heat exposure at outdoor construction sites was considered. Methods: Using the coordinates of second level administrative districts and meteorological observatories as the key, the automated synoptic observing system data and building permit data for 2021 were matched. The wet-bulb temperature was obtained using Stull's formula, and the globe temperature was obtained using the Tg_KMA2006 model. WBGT was calculated using these. Excess rates were obtained compared to exposure limits for heavy work-continuous work and moderate work-25% rest. It was compared with the results of the work environment monitoring in 2020. Results: As a result, 1,827,536 cases were estimated for 11,052 workplaces in one year. This is much higher than the 5,116 cases of 3818 workplaces of the existing work environment monitoring results. It is confirmed that the exposure limit was exceeded in 10.6~24.0% of the entire period and 70.2~84.1% of the peak period of the heat wave. It is very high compared to 0.9% of the existing work environment monitoring result. Conclusions: It is necessary to improve the system of monitoring and statistics related to extreme heat. Additional considerations are needed regarding WBGT estimation methods, meteorological data, and evaluation time. Various follow-up risk assessment studies for other industries and time series need to be continued.

• Journal of Animal Science and Technology
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• v.64 no.4
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• pp.770-781
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• 2022

Meteorological disasters caused by climate change like heat, cold waves, and unusually long rainy seasons affect the milk productivity of cows. Studies have been conducted on how milk productivity and milk compositions change due to heat stress (HS). However, the estimation of losses in milk production due to HS and hereby environmental impacts of greenhouse gas (GHG) emissions are yet to be evaluated in Korean dairy farms. Dairy milk production and milk compositions data from March to October 2018, provided by the Korea Dairy Committee (KDC), were used to compare regional milk production with the temperature-humidity index (THI). Raw data for the daily temperature and relative humidity in 2018 were obtained from the Korea Meteorological Administration (KMA). This data was used to calculate the THI and the difference between the maximum and minimum temperature changing rate, as the average daily temperature range, to show the extent to which the temperature gap can affect milk productivity. The amount of milk was calculated based on the price of 926 won/kg from KDC. The results showed that the average milk production rate was the highest within the THI range 60-73 in three regions in May: Chulwon (northern region), Hwasung (central region), and Gunwi (southern region). The average milk production decreased by 4.96 ± 1.48% in northern region, 7.12 ± 2.36% in central region, and 7.94 ± 2.57% in southern region from June to August, which had a THI range of 73 or more, when compared to May. Based on the results, the level of THI should be maintained like May. If so, the farmers can earn a profit of 9,128,730 won/farm in northern region, 9,967,880 won/farm in central region, and 12,245,300 won/farm in southern region. Additionally, the average number of cows raised can be reduced by 2.41 ± 0.35 heads/farm, thereby reducing GHG emissions by 29.61 ± 4.36 kg CO₂eq/day on average. Overall, the conclusion suggests that maintaining environmental conditions in the summer that are similar to those in May is necessary. This knowledge can be used for basic research to persuade farmers to change farm facilities to increase the economic benefits and improve animal welfare.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1119-1130
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• 2021

Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.