• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.19-28
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• 2016

The objective of this study is the generation of the gridded flash flood index using the gridded hydrologic components of TOPLATS land surface model and statistic flash flood index model. The accuracy of this method is also examined in this study. The study area is the national capital region of Korea, and 38 flash flood damages had occurred from 2009 to 2012. The spatio-temporal resolutions of land surface model are 1 h and 1 km, respectively. The gridded meteorological data are generated using the inverse distance weight method with automatic weather stations (AWSs) of Korea Meteorological Administration (KMA). The hydrological components (e.g., surface runoff, soil water contents, and water table depth) of cells corresponding to the positions of 38 flood damages reasonably respond to the cell based hourly rainfalls. Under the total rainfall condition, the gridded flash flood index shows 71% to 87% from 4 h to 6 h in the lead time based on the rescue request time and 42% to 52% of accuracy at 0 h which means that the time period of the lead time is in a limited rescue request time. From these results, it is known that the gridded flash flood index using the cell based hydrological components from land surface model and the statistic flash flood index model have a capability to predict flash flood in the mountainous area.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.155-166
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• 2020

In this study, we applied the Radar-AWS Rainrates (RAR), weather radar-based quantitative precipitation estimations (QPEs), to the Yongdam study watershed in order to perform the flood runoff simulation and calculate the inflow of the dam during flood events using hydrologic model. Since the Yongdam study watershed is a representative area of the mountainous terrain in South Korea and has a relatively large number of monitoring stations (water level/flow) and data compared to other dam watershed, an accurate analysis of the time and space variability of radar rainfall in the mountainous dam watershed can be examined in the flood modeling. HEC-HMS, which is a relatively simple model for adopting spatially distributed rainfall, was applied to the hydrological simulations using HEC-GeoHMS and ModClark method with a total of eight independent flood events that occurred during the last five years (2014 to 2018). In addition, two NCL and Python script programs are developed to process the radar-based precipitation data for the use of hydrological modeling. The results demonstrate that the RAR QPEs shows rather underestimate trends in larger values for validation against gauged observations (R² 0.86), but is an adequate input to apply flood runoff simulation efficiently for a dam watershed, showing relatively good model performance (E_NS 0.86, R² 0.87, and PBIAS 7.49%) with less requirements for the calibration of transform and routing parameters than the spatially averaged model simulations in HEC-HMS.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.92-101
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• 2020

To prevent and mitigate damage to farms due to heavy snowfall, snow weight information should be provided in addition to snow depth. This study reviews four formulae regarding snow density and weight used in extant studies and applies them in Suwon area to estimate snow weight in Korea. We investigated the observed snow depth of 94 meteorological stations and automatic weather stations (AWS) data over the past 30 years (1988-2017). Based on the spatial distribution of snow depth by area in Korea, much of the fresh snow cover, due to heavy snowfall, occurred in Jeollabuk-do and Gangwon-do. Record snowfalls occurred in Gyeongsangbuk-do and Gangwon-do. However, the most recent heavy snowfall in winter occurred in Gyeonggi-do, Gyeongsangbuk-do, and Jeollanam-do. This implies that even if the snow depth is high, there is no significant damage unless the snow weight is high. The estimation of snow weight in Suwon area yielded different results based on the calculation method of snow density. In general, high snow depth is associated with heavy snow weight. However, maximum snow weight and maximum snow depth do not necessarily occur on the same day. The result of this study can be utilized to estimate the snow weight at other locations in Korea and to carry out snow weight prediction based on a numerical model. Snow weight information is expected to aid in establishing standards for greenhouse design and to reduce the economic losses incurred by farms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.65-77
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• 2012

This study examined changes in land cover for the past 25 years in Busan and subsequently evaluated heat island potential by using land surface temperature and observation temperature data. The results were as below. The urban area of Busan increased by more than 2.5 times for the past 25 years from 1975 to 2000. It was believed that an increase in the pavement area of city within such a short period of time was an unprecedented phenomenon unique to our country. It could be assumed that urban heat island would be worsened through this process. After analyzing the land temperature according to the land cover, it was shown that there were noticeable changes in the temperature of urban & built-up and mountain & forest areas. In particular, the temperature rose to $36{\sim}39^{\circ}C$ in industrial areas during the summer, whereas it went down to $22{\sim}24^{\circ}C$ in the urban areas at whose center there were mountains. It was found that heat island potential according to the level of land cover had various values depending on the conditions of land cover. Among the areas of urbanization, the industrial area's heat island potential is 6 to $8^{\circ}C$, and the residential and commercial area's is $0{\sim}5^{\circ}C$, so it has been found that there is high possibility to induce urban heat islands. Meanwhile, in the forest or agricultural area or the waterside, the heat island potential is $-6{\sim}-3^{\circ}C$. With this study result, it is possible to evaluate the effects of temperature increase according to the urban land use, and it can be used as foundational data to improve urban thermal environment and plan eco-friendly urban development.

• Journal of Korea Water Resources Association
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• v.48 no.1
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• pp.57-67
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• 2015

One of main benefits of a dual polarization radar is improvement of quantitative rainfall estimation. In this paper, performance of two representative rainfall estimation methods for a dual polarization radar, JPOLE and CSU algorithms, have been compared by using data from a MOLIT S-band dual polarization radar. In addition, this paper presents evaluation of specific differential phase ($K_{dp}$) retrieval algorithm proposed by Lim et al. (2013). Current $K_{dp}$ retrieval methods are based on range filtering technique or regression analysis. However, these methods can result in underestimating peak $K_{dp}$ or negative values in convective regions, and fluctuated $K_{dp}$ in low rain rate regions. To resolve these problems, this study applied the $K_{dp}$ distribution method suggested by Lim et al. (2013) and evaluated by adopting new $K_{dp}$ to JPOLE and CSU algorithms. Data were obtained from the Mt. Biseul radar of MOLIT for two rainfall events in 2012. Results of evaluation showed improvement of the peak $K_{dp}$ and did not show fluctuation and negative $K_{dp}$ values. Also, in heavy rain (daily rainfall > 80 mm), accumulated daily rainfall using new $K_{dp}$ was closer to AWS observation data than that using legacy $K_{dp}$, but in light rain(daily rainfall < 80mm), improvement was insignificant, because $K_{dp}$ is used mostly in case of heavy rain rate of quantitative rainfall estimation algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.479-495
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• 2021

This study investigates the synoptic (patterns of southern highs, northern lows, and lows rapidly developed by tropopause folding), thermodynamic, and kinematic characteristics of a strong wind that occurred in the Yeongdong region of South Korea on March 18-20, 2020. To do so, we analyzed data from an automatic weather station (AWS), weather charts, the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis, rawinsonde, and windprofiler radars. The daily maximum instantaneous wind speed, exceeding 20 m s^-1, was observed at five weather stations during the analysis period. The strongest instantaneous wind speed (27.7 m s^-1) appeared in the Daegwallyeong area. According to the analysis of weather charts, along with the arrangement of the north-south low-pressure line, the isobars were moved to the Yeongdong area. It showed a sine wave shape, and a strong wind developed owing to the strong pressure gradient. On March 19, in the northern part of the Korean Peninsula, with a drop in atmospheric pressure of 19 hPa or more within one day, a continuous strong wind was developed by the synoptic structure of the developing polar low. In the adiabatic chart observed in Bukgangneung, the altitude of the inversion layer was located at an altitude of approximately 1-3 km above the mountaintop, along with the maximum wind speed. We confirmed that this is consistent with the results of the vertical wind field analysis of the rawinsonde and windprofiler data. In particular, based on the thermodynamic and kinematic vertical analyses, we suggest that strong winds due to the vertical gradient of potential temperature in the lower layer and the development of potential vorticity due to tropopause folding play a significant role in the occurrence of strong winds in the Yeongdong region.

• Journal of Welding and Joining
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• v.34 no.5
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• pp.33-40
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• 2016

The microstructures and the creep rupture properties of dissimilar welds between the Ni-based superalloy Inconel 740H and the non-stabilized austenitic stainless steel TP316H have been characterized. The welds were produced by shielded metal arc (SMA) welding process with the AWS A5.11 Class ENiCrFe-3 filler metal, commonly known as Inconel 182 superalloy. Postweld heat treatment at $760^{\circ}C$ for 4 hours was conducted to form ${\gamma}^{\prime}$ strengthener in Inconel 740H. The austenitic weld metal produced by Inconel 182 had a dendritic microstructure, and grew epitaxially from the both sides of Inconel 740H and TP316H base metals. Since both Inconel 740H and TP316H did not undergo any solid-state transformation during welding process, there were no heat-affected-zone (HAZ) sub-regions and the coarsoned grains near the weld interface were limited to a narrow region. The hardness of Inconel 182 weld metal was ~220 Hv. The gradual hardness decrease was detected at HAZ of TP316H, and the TP316H base metal displayed the lowest hardness value (~180 Hv) whilst the Inconel 740H showed the highest hardness value (~400 Hv). Fracture after creep occurred at the center of weld metal, regardless of creep condition. It was found that during creep the cracks initiated and propagated along interdendritic regions and grain boundaries at which Laves particles enriched in Nb, Si and Cr were present. The appropriate design of weld metal was discussed to suppress the creep-induced cracking of the present dissimilar weld.