Earticle

We investigated the change in land-use alteration in a 45 km × 45 km area around the Upo wetlands in 1920s(before the Japanese occupation period), 1950s(immediately Korean independence) and the period 1970s to 2000s. These data can guide in understanding surface environmental changes in the lower Nakdong River from the early 20^th century to the present. The influence of the long-term decreasing trend of the wetland area at the Upo Swamp was evaluated using a high-resolution local circulation model. The cooling effect of the wetlands on surface air during the daytime in summer(e.g, early August) was approximately 2℃ greater in the 1920s than in the 2000s, which is attributed to wider water areas in the 1920s. Additionally, long-term changes in land use have caused changes in the convergence zone of local circulation wind.

본 연구에서는 2016년부터 2020년까지 내륙 관측소 중 안개 최다발 지역인 안동을 대상으로 XGBoost-DART 머신러닝 알고리즘을 이용하여 1 시간 후 안개 유무를 예측하였다. 기상자료, 농업관측자료, 추가 파생자료와 각 자료를 오버 샘플링한 확장자료, 총 6개의 데이터 세트를 사용하였다. 목측으로 획득한 기상현상번호와 시정계 관측으로 측정된 시정거리 자료를 각각 안개 유[1]무[0]로 이진 범주화하였다. 총 12개의 머신러닝 모델링 실험을 설계하였고, 안개가 사회와 지역사회에 미치는 유해성을 고려하여 모델의 성능은 재현율과 AUC-ROC를 중심으로 평가하였다. 전체적으로, 오버샘플링한 기상자료와 기상현상번호 기반의 예측 목표를 조합한 실험이 최고 성능을 보였다. 이 연구 결과는 머신러닝 알고리즘을 활용한 안개 예측에 있어서, 목측으로 획득한 기상현상번호의 중요성을 암시한다.

In this study, we predicted the presence of fog with a one-hour delay using the XGBoost DART machine learning algorithm for Andong, which had the highest occurrence of fog among inland stations from 2016 to 2020. We used six datasets: meteorological data, agricultural observation data, additional derived data, and their expanded data. The weather phenomenon numbers obtained through naked-eye observations and the visibility distances measured by visibility meters were classified as fog [1] or no-fog [0]. We set up twelve machine learning modeling experiments and used data from 2021 for model validation. We mainly evaluated model performance using recall and AUC-ROC, considering the harmful effects of fog on society and local communities. The combination of oversampled meteorological data features and the target induced by weather phenomenon numbers showed the best performance. This result highlights the importance of naked-eye observations in predicting fog using machine learning algorithms.

This study analyzed the impact of recirculation on high-concentration PM_2.5 in the coastal area. Through the analysis of observational data, it was observed that the development of sea breeze led to an increase in PM_2.5 and SO₄^2- concentrations. Hysplit backward trajectory analysis confirmed the occurrence of air mass recirculation. Results from WRF and CMAQ numerical simulations indicated that pollutants transported from land to sea during the night were re-transported to the land by daytime sea breeze, leading to high-concentration PM_2.5 in Busan. To quantitatively investigate the recirculation a recirculation factor (RF) was calculated, showing an increase in RF values during high-concentration PM_2.5 episodes. However, the RF values varied slightly depending on the time resolution of meteorological data used for the calculations. This variation was attributed to the terrain characteristics at observation sites. Additionally, during long-range transported days leading to nationwide high-concentration PM_2.5 events, synoptic-scale circulation dominated, resulting in weaker correlation between PM_2.5 concentration and RF values. This study enhances the understanding of the influence of recirculation on air pollution. However, it is important to consider the impact of temporal resolution and terrain characteristics when using RF for evaluating recirculation during episodes of air pollution.

To investigate the occurrence characteristics and types of fog on the Korean Peninsula over the past three years (2020 to 2022), data from 96 synoptic meteorological observatories and 21 ocean buoys were collected and analyzed. We included precipitation fog, which occurs after precipitation events, and cloud-base lowering fog, which is caused by the development of lower-level clouds, with a total six subtypes of fog. In the case of cloud-base lowering fog, the occurrence frequency at 2.6% was not high at 2.6%, but the duration of low visibility below 200 m was very long at 6.9 hours. The seasonal frequency of fog is low in spring and winter, high in summer over islands and coastal areas, and high in autumn over inland areas. The frequency of inland fog, which is characterized by high radiation fog and dense fog, requires attention in terms of transportation safety, with an occurrence time of 0500 LST to 1000 LST. Therefore, systematic analysis of precipitation fog and cloud-base lowering, as well as radiation and advection fog, is required in the analysis of recognizing fog as a disaster and causing transportation disorders.

국민의 안전과 편의성에 직결되는 도로 인프라인 PSC거더교의 바닥판 손상 및 노후화로 인한 교체공사를 대비하여 매립형 분리식 전단연결재가 개발되었다. 분리식 전단연결재는 바닥판 철거 공정에서 파쇄를 최소화하고 교체공사를 위한 전단연결재 재시공이 용이하여 시공성 향상으로 인한 공사기간 감소로 도로이용자의 불편과 손실을 최소화할 수 있다. 공법별 공사기간과 공사기간 중 교통차단으로 인해 발생하는 도로이용자비용을 산출하여 비교하는 방법으로 기존 공법 대비 매립형 분리식 전단연결재를 적용한 PSC거더교의 경제성을 도로이용자(국민) 입장에서 분석하였다. 매립형 분리식 전단연결재가 적용된 교량 바닥판 교체공사 시 도로이용자비용은 34일 1,404,687,725원으로 기존 ∩형태 전단철근 노출 전단연결재가 적용된 경우(54일, 1,924,740,367원) 대비 공사기간 20일, 도로이용자비용 27.02 %를 절감할 수 있는 것으로 분석되었다.

The embedded demountable shear connector was developed in preparation for replacement works due to deterioration and damage to the bridge panel of the PSC girder bridge which is a road infrastructure directly related to the safety and convenience of the people. The demountable shear connector minimizes crushing works in the demolition process of the panel, and it is easy to re-construct the shear connector for replacement work. The economic feasibility of the PSC girder bridge using the embedded demountable shear connector compared to the existing construction method was analyzed from the perspective of road users (people) by calculating and comparing the cost of road users caused by traffic blocking during each construction method.

To investigate the reason for the spatial difference in PM_2.5 (Particulate Matter, < 2.5 ㎛) concentration despite a similar synoptic pattern, a synoptic analysis was performed. The data used for this study were the daily average PM_2.5 concentration and meteorological data observed from 2016 to 2020 in Busan and Seoul metropolitan areas. Synoptic pressure patterns associated with high PM_2.5 concentration episodes (greater than 35 ㎍/m³) were analyzed using K-means cluster analysis, based on the 900 hPa geopotential height of NCEP (National Centers for Environmental Prediction) FNL (Final analysis) data. The analysis identified three sub-groups related to high concentrations occurring only in Busan and Seoul metropolitan areas. Although the synoptic patterns of high PM_2.5 concentration episodes that occur independently in Busan and Seoul metropolitan areas were similar, there was a difference in the intensity of pressure gradient and its direction, which tends to be an important factor determining the movement time of pollutants. The spatial difference in PM_2.5 concentration in the Korean Peninsula is due to the difference and direction of the atmospheric pressure gradient that develops from southwest to northeast direction.

Fog can have severe impacts on human life (e.g., accidents in transportation systems) because it causes low visibility. Areas prone to fog near the sea or a river require accurate fog forecasts. In this study, we analyzed the characteristics of fog occurrence around Gumi Reservoir, a part of the inland Nakdong River. We also simulated and predicted visibility using the Weather Research and Forecasting (WRF) model. Visibility was estimated using several point measurements and several different methods: Stoelinga and Warner (SW99), Rapid Update Cycle (RUC), the Forecast System Laboratory (FSL), Decision Tree (DT), revised visibility (RVIS) and Gultepe_06 methods. The DT method showed a pattern similar to the observed fog occurrences. In this study, the Gulteppe_06 method produced the best performance under the lowest visibility situation, although there is some discrepancy in microphysics' simulated results, followed by DT and RUC.

본 연구에서는 K-means 군집 분석을 통하여 최근 5년간(2014-2018) 한반도 남동 지역의 고농도 미세먼지 발생에 영향을 미치는 주요 종관 기상 패턴을 분류하였다. 또한 고농도 미세먼지 사례일의 발생과 관련된 지역적 차이를 살펴보기 위하여 NCEP (National Centers for Environmental Prediction)/FNL (Final Operational Global Analysis) 재해석 기상자료를 이용하여 부산, 울산, 경남 지역의 미세먼지 발생 특성과 관련된 종관 규모 기상의 특성에 대한 비교 연구도 수행하였다. 한반도 남동 지역의 고농도 미세먼지 사례일과 관련된 종관 기상 패턴은 총 5개(C1-C5)로 분류된다. 각 군집의 발생빈도는 24.8% (C1), 21.3% (C2), 20.4% (C3), 17.3% (C4), 16.2% (C5)이다. 기상 패턴 분석을 통하여 제시된 남동 지역의 고농도 미세먼지를 유발하는 요인에는 지역 외부에서 장·단거리 수송(C1, C3, C5)에 의한 영향과 지역내 배출(C2, C4)에 의한 것임을 알 수 있었다. 또한 고농도 미세먼지 발생일에 대해 부산, 울산, 경남 세 지역의 기상장을 분석하였을 때, 500 hPa 지위 고도 및 풍속 등의 기상학적 특성이 지역별로 다르게 나타났다. 그리고 고기압의 작은 위치 변화가 각 지역의 미세먼지 발원과 장거리 이동 경향성에 영향을 미치고 있었다.

This study presents the K-means clustering analysis-based classification of the meteorological patterns affecting the occurrence of high PM₁₀ concentration in the southeastern region of the Korean peninsula for the last five years (2014-2018). Regional differences in Busan, Ulsan, and Gyeongnam related to high PM₁₀ episodes, were clarified through the statistical comparison study using synoptic scale meteorological elements using NCEP (National Centers for Environmental Prediction/FNL (Final Operational Global Analysis) re-analysis meteorological data. Meteorological patterns were classified into a total of five categories (C1-C5). The incidence of each cluster was 24.8% (C1), 21.3% (C2), 20.4% (C3), 17.3% (C4), and 16.2% (C5), respectively. The high PM₁₀ concentration in the southeastern region resulted from long and short range transports (C1, C3, C5) from outside of the region, and the emissions (C2, C4) inside the region. In the high PM₁₀ episodes in Busan, Ulsan, and Gyeongnam regions, meteorological characteristics such as different geopotential height and wind speed at 500 hPa in each cluster and the change in the location of high pressure over Korean Peninsula is strongly associated with the dispersion of PM₁₀ around inventories in the region and the tendency of long-range transportation of PM₁₀ emitted from outside of region.

Recently, a heavy rainfall with high spatial variation occurred frequently in the Korean Peninsula. The meteorological event that occurred in Busan on 3 May 2016 is characterized by heavy rain in a limited area. In order to clarify the reason of large spatial variation associated with mountain height and location of low level jet, several numerical experiments were carried out using the dynamic meteorological Weather Research and Forecasting (WRF) model. In this case study, the raised topography of Mount Geumjeong increased a barrier effect and air uplifting due to topographic forcing on the windward side. As a result, wind speed reduced and precipitation increased. In contrast, on the downwind side, the wind speed was slightly faster and since the total amount of water vapor is limited, the precipitation on the downwind side reduced. Numerical experiments on shifting the location of the lower jet demonstrated that if the lower jet is close to the mountain, its core becomes higher due to the effect of friction. Additionally, the water vapor convergence around the mountain increased and eventually the precipitation also increased in the area near the mountain. Hence, the location information of the lower jet is an important factor for accurately predicting precipitation.

In order to protect the lives and property of citizens, the central and local governments are responding by enacting municipal ordinances and regulations as the frequency of extreme weather conditions due to climate change increases and intensity increases gradually. Accordingly, the basic contents and strategies of domestic and foreign policies to cope with cold and heat waves were reviewed, referring to measures suitable for application to the Daegu metropolitan area. In addition, it is intended to provide a policy alternative to Daegu metropolitan area to minimize damage from extreme weather by identifying the current status, characteristics, and future prospects of extreme weather in Daegu metropolitan area. Since the damage caused by the cold wave in Daegu area is not as great as that of other regions, it is urgent to come up with cold wave measures for the health and transportation sectors, and to come up with measures against the heat wave as the damage caused by the heat wave is the most serious in the country. Also we will identify spatial characteristics so that the districts and counties with high vulnerability to extreme weather can be identified and implemented first, and present civic life-oriented facilities and civic action guidelines to overcome cold and heat waves.

With global warming and the rapid increase in urbanization accompanied by a concentration of population, the urban heat island effects (UHI) have become an important environmental issue. In this study, rooftop greening and permeable asphalt pavement were selected as measures to reduce urban heat island and applied to a simple virtual urban environment to simulate temperature change using ENVI-met. A total of five measures were tested by dividing the partial and whole area application of each measure. The results showed that the temperature range of the base experiment is 33.11-37.11 ℃, with the UTCI comfort level described as strong heat and very strong heat stress. A case applied permeable asphalt has a greater temperature difference than a rooftop greening case, the larger the area where each condition was applied, the greater the temperature change was.

Solar hot water system produces hot water using solar energy. If it is not used effectively, overheating occurs during the summer. Therefore, a lot of research is being done to solve this. This study develops thermoelectric power module applicable to solar hot water system. A thermoelectric material can directly convert thermal energy into electrical energy without additional power generation devices. If there is a temperature difference between high and low temperature, it generate power by Seebeck effect. The thermoelectric module generates electricity using temperature differences through the heat exchange of hot and cold water. The water used for cooling is heated and stored as hot water as it passes through the module. It can prevent overheating of Solar hot water system while producing power. The thermoelectric module consists of one absorption and two radiation part. There path is designed in the form of a water jacket. As a result, a temperature of the absorption part was $134.2^{\circ}C$ and the radiation part was $48.6^{\circ}C$. The temperature difference between the absorption and radiation was $85.6^{\circ}C$. Also, The Thermoelectric module produced about 122 W of irradiation at $708W/m^2$. At this time, power generation efficiency was 2.62% and hot water conversion efficiency was 62.46%.

To establish initial response scenarios for nuclear accidents around the Kori nuclear power plants, the potential for radionuclide diffusion was estimated using numerical experiments and statistical techniques. This study used the numerical model WRF (Weather Research and Forecasting) and FLEXPART (Flexible Particle dispersion model) to calculate the three-dimensional wind field and radionuclide dispersion, respectively. The wind patterns observed at Gijang, near the plants, and at meteorological sites in Busan, were reproduced and applied to estimates of seasonally averaged wind fields. The distribution of emitted radionuclides are strongly associated with characteristics of topography and synoptic wind patterns over nuclear power plants. Since the terrain around the power plants is complex, estimates of radionuclide distribution often produce unexpected results when wind data from different sites are used in statistical calculations. It is highly probable that in the summer and autumn, radionuclides move south-west, towards the downtown metropolitan area. This study has clear limitations in that it uses the seasonal wind field rather than the daily wind field.

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

풍력 자원의 단기 예측 가능성은 풍력 발전 단지의 경제적 타당성을 평가하는 중요한 요소이다. 본 연구에서는 풍력 자원의 단기 예측 가능성을 향상시키는 방법의 하나로 베이지안 칼만 필터를 후처리 과정으로 적용하였다. 이때 추정된 모델과 관측 데이터의 상관관계를 평가하기 위하여 일정 시간 동안 베이지안 칼만 훈련 기간이 요구된다. 본 연구는 여러 훈련 기간에 따라 예측 특성을 정량적으로 분석하였다. 태백 지역에서는 3일 단기 베이지안 칼만 훈련으로 기온과 풍속을 예측하는 것이 다른 훈련 기간을 적용할 때보다 우수한 예측 성능을 보였다. 반면 이어도는 6일 이상의 베이지안 칼만 필터의 훈련 기간을 적용한 경우 가장 좋은 예측 성능을 나타낸다. WRF 예측 성능이 떨어지는 사례에서 베이지안 칼만 필터의 예측 성능향상이 뚜렷하게 나타나며, 반대로 WRF 예측이 정확한 지점에서는 필터적용에 따른 성능향상 정도가 약한 경향을 가진다.

The short term predictability of wind resources is an important factor in evaluating the economic feasibility of a wind power plant. As a method of improving the predictability, a Bayesian Kalman filter is applied as the model data postprocessing. At this time, a statistical training period is needed to evaluate the correlation between estimated model and observation data for several Kalman training periods. This study was quantitatively analyzes for the prediction characteristics according to different training periods. The prediction of the temperature and wind speed with 3-day short term Bayesian Kalman training at Taebaek area is more reasonable than that in applying the other training periods. In contrast, it may produce a good prediction result in Ieodo when applying the training period for more than six days. The prediction performance of a Bayesian Kalman filter is clearly improved in the case in which the Weather Research Forecast (WRF) model prediction performance is poor. On the other hand, the performance improvement of the WRF prediction is weak at the accurate point.

Since the late 20th century, the urbanization in Korea has been rapidly increasing, especially in major cities like Seoul, as a result of industrialization. One of the aspects of urbanization is coating the surfaces with impervious concrete or asphalt that water cannot penetrate. In addition, various urban, such as urban heat islands, which also have a great impact on the urban environment, occur within the cities. Therefore, the urban environment is gradually becoming hot and dry, and the need for more urban parks to compensate for these negative impacts is growing. Thus, several numerical studies have been conducted to assess these problems using coupled Numerical Weather Prediction (NWP) and Computational Fluid Dynamics (CFD). In this study, an experiment was conducted to determine the accuracy of the area of the input field using Weather Research and Forecasting (WRF) model, and applying the more accurate input field to a numerical simulation using ENVI-met, in order to investigate the effect of urban parks on the thermal comfort. The results showed that an input field with a larger area is more accurate than that with a smaller area, because the surrounding terrain and cities are considered in details in the experiment with the larger area. Subsequently, the more accurate input field was used in ENVI-met, and the results of this simulation showed that the presence of the urban park increased the thermal comfort and improved the humidity conditions.

Freezing rain is a phenomenon when precipitation falls as a liquid rain drop, but freezes when it comes into contact with surfaces or objects. In this study, we investigated the predictability of freezing rain and its characteristics, which are strongly related with the occurrence of black ice using synoptic scale meteorological observation data. Two different cases occurred at 2012 were analyzed and in the presented cases, freezing rain often occurs in the low-level low pressure with the warm front. The warm front due to the lower cyclone make suitable environment in which snow falling from the upper layer can change into supercooled water. The $0^{\circ}C$ temperature line to generate supercooling water is located at an altitude of 850 hPa in the vertical temperature distribution. And the ground temperature remained below zero, as is commonly known as a condition for black ice formation. It is confirmed that the formation rate of freezing rain is higher when the thickness after 1000-850 hPa is 1290-1310 m and the thickness of 850-700 hPa layer is larger than 1540 m in both cases. It can also be used to predict and estimate the generation of freezing rain by detecting and analyzing bright bands in radar observation.

In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean $PM_{10}$ concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.

In order to investigate the $PM_{10}$ concentration trend and its characteristics over five different sub area in Busan from 2013 to 2015, data analysis with considering air flow distribution according to its topography was carried out using statistical methodology. The annual mean concentrations of $PM_{10}$ in Busan tend to decrease from $49.6{\mu}g/m^3$ in 2013 to $46.9{\mu}g/m^3$ in 2015. The monthly mean concentrations value of $PM_{10}$ were high during spring season, from March to May, and low during summer and fall due to frequent rain events. The concentration of $PM_{10}$ was the highest in five different sub-area in Busan. High concentration episodes over 90 percentile of daily $PM_{10}$ concentration were strongly associated with mean daily wind speed, and often occurred when the westerly wind or southwesterly wind were dominant. Regardless of wind direction, the highest correlation of $PM_{10}$ concentrations was observed between eastern and southern regions, which were geographically close to each other, and the lowest in the western and eastern regions blocked by mountains. Wind flow along the complex terrain in Busan is also one of the predominant factors to understand the temporal variation of $PM_{10}$ concentrations.

In this study, we investigated the effect of aerosol feedback on $PM_{10}$ simulation using a two-way coupled air quality model (WRF-CMAQ). $PM_{10}$ concentration over Korea in January 2014 was simulated, and the aerosol feedback effect on the simulated solar radiation was intensively examined. Two $PM_{10}$ simulations were conducted using the WRF-CMAQ model with (FB) and without(NFB) the aerosol feedback option. We find that the simulated solar radiation in the west part of Korea decreased by up to $-80MJ/m^2$ due to the aerosol feedback effect. The feedback effect was significant in the west part of Korea, showing high $PM_{10}$ estimates due to dense emissions and its long-range transport from China. The aerosol feedback effect contributed to the decreased rRMSE(relative Root Mean Square Error) for solar radiation (47.58% to 30.75%). Aerosol feedback effect on the simulated solar radiation was mainly affected by concentration of $PM_{10}$. Moreover, FB better matched the observed solar radiation and $PM_{10}$ concentration than NFB, implying that taking into account the aerosol direct effects resulted in the improved modeling performance. These results indicate that aerosol feedback effects can play an important role in the simulation of solar radiation over Korean Peninsula.