PURPOSES : The aim of this study is to develop a road fog information system based on the geostationary meteorological satellite (GK2A) for road weather services on highways. METHODS : Three threshold values sensitive to fog intensity in the GK2A fog algorithm were optimized using multi-class receiver operating characteristic analysis to produce road fog information depending on day and night. The developed a GK2A road fog algorithm that can detect three levels of road fog based on the visibility distance criteria (1km, 500m, and 200m). Furthermore, the GK2A road fog product was not only substituted with visibility objective analysis data in unknown and cloud-covered areas of satellite data, but also integrated with visibility distance data obtained from visibility gauges and CCTV image analysis to improve the accuracy of road fog information. RESULTS : The developed road fog algorithm based on meteorological satellite data provides real-time road fog information categorized into three levels (attention, caution, and danger) based on the visibility distance, with a spatial resolution of 1km × 1km and temporal resolution of 5 minutes. The road fog algorithm successfully detected road fog in five out of seven fog-related traffic accidents reported by Korean media outlets from 2020 to 2022, resulting in a detection success rate of 71.4%. The Korea Meteorological Administration is currently in the process of installing additional visibility gauges on 26 highways until 2025, and the next high-resolution meteorological satellite (GK5) is planned to be launched in 2031. We look forward to significantly improving the accuracy of the road fog hazard information service in the near future. CONCLUSIONS : The road fog information test service was initiated on the middle inner highway on July 27, 2023, and this service is accessible to all T-map and Kakao-map users through car navigation systems free of charge. After 2025, all drivers on the 26 Korean highways will have access to real-time road fog information services through their navigation systems.

Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people’s life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing ‘heavy snow’ in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.

본 연구에서는 풍환경에 따른 열손실을 분석하는데 있어 필요한 풍속 기초자료를 제공하기 위하여 주요 11개 해안지역 중 온실밀집지역을 선정하여 기상환경 및 온실 방위를 조사 분석하였다. 대상지역은 난방온실 재배면적과 풍환경 기준으로 선정하였고 온실밀집지역은 50,000m2 이상인 지역을 대상으로 하였다. 11곳의 기상자료 중 기온,풍속, 풍향을 대상으로 30년간 자료를 수집하여 분석하였고 기온은 최저, 평균, 최고 기온을 나누고 풍속 및 풍향 기준은 기상청 분석 기준을 적용하였다. 온실의 배치방향은 형태가 대칭인 점을 감안하여 0~180o 범위로 자료를 수집하였다. 또한, 각 지역마다 풍향이 있으며 온실길이방향을 기준으로 하였을 때 적용되는 풍향은 달라질 수 있으며 이를 상대풍향으로 지칭하고 중복되는 점을 고려하여 0~90o 범위로 자료를 수집하였다. 11개 지역의 기온은 중부지방에 있는 보령, 영광 지역과 남부지방에 있는 9개 지역의 기온차이가 구분되었다. 중부해안 대상지역은 1월 최저기온은 약 3~4oC 정도 온 도가 높은 것을 확인할 수 있었고 평균기온은 약 3oC 정도 높았으며 월별 기온 중 최저기온을 선정할 때에 1 월 기온을 고려해야 되는 것으로 판단된다. 대상지역의 주풍향에 대한 월별 차이는 크게 발생하지 않았으며 풍향 분포에 따라 지역별로 서해안측, 서해 및 남해 경계 해안측, 남해안측으로 구분되어졌다. 풍속은 영광을 제외 한 10개 지역은 월간 풍속 포차이가 크게 발생하지 않는 것으로 판단된다. 대상지역의 온실의 방향은 길이방향 기준으로 분석하였으며 보령과 영광, 남해 지역은 60%이상 집중되어 있는 방향이 존재하였고 해남, 통영 지역은 약 90% 집중되어있는 방향이 존재하였으며 이는 경지정리로 인하여 방향이 편향되어있는 지역이 존재하는 것으로 판단된다.

Solar energy has been known as a successful alternative energy source, however it requires a large area to build power generation facilities compared to other energy sources such as nuclear power. Weather factors such as rainy weather or night time impact on solar power generation because of lack of insolation and sunshine. In addition, solar power generation is vulnerable to external elements such as changes in temperature and fine dust. There are four seasons in the Republic of Korea hereby variations of temperature, insolation and sunshine are broad. Currently factors that cause find dust are continuously flowing in to Korea from abroad. In order to build a solar power plant, a large area is required for a limited domestic land hereby selecting the optimal location for the plant that maximizes the efficiency of power generation is necessary. Therefore, this research analyze the optimal site for solar power generation plant by implementing analytic hierarchy process based on weather factors such as fine dust. In order to extract weather factors that impact on solar power generation, this work conducts a case study which includes a correlation analysis between weather information and power generation.

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22nd December, 2020 and 29th January, and 25th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

Heat watch warning systems are operating in Korea and several other countries (China, the United Kingdom, France, the United States, Germany, Australia, and Japan). The heat wave indices used in this system are the heat index, perceived temperature, the wet bulb globe temperature, and the daily maximum temperature. To improve the heat wave advisory and warning system, some suggestions have been made. The meteorological-health index (i.e., indirect index), has especially been proposed in previous studies. This information should be provided not only to vulnerable groups (seniors, infants, and children), but also to outdoor workers who may be particularly exposed to heat waves. In addition, to have sufficient preemptive response times, the need for an extension of the heat watch warning period was suggested. Finally, the subdivision of administrative units and risk stages was proposed.

Meteorological factors and air pollutants are associated with respiratory diseases, and appropriate use of weather and air quality information is helpful in the management of patients with such diseases. This study was performed to investigate both the utilization of weather and air quality information by, and the needs of, patients with respiratory diseases. Questionnaires were administered to 112 patients with respiratory diseases, 60.7% of whom were female. The rates of bronchial asthma and chronic obstructive pulmonary disease among patients were 67.0% and 10.7%, respectively. The majority of subjects (90%) responded that prevention was important for respiratory disease management and indicated that they used weather and air quality information either every day or occasionally. However, respondents underestimated the importance of weather and air quality information for disease management and were unaware of some types of weather information. The subjects agreed that respiratory diseases were sensitive to weather and air quality. The most important weather-related factors were diurnal temperature range, minimum temperature, relative humidity, and wind, while those for air quality were particulate matter and Asian dust. Information was gleaned mainly from television programs in patients aged 60 years and older and from smartphone applications for those below 60 years of age. The subjects desired additional information on the management and prevention of respiratory diseases. This study identified problems regarding the utility of weather and air quality information currently available for patients with respiratory diseases, who indicated that they desired disease-related information, including information in the form of action plans, rather than simple health- and air quality-related information. This study highlights the necessity for notification services that can be used to easily obtain information, specifically regarding disease management.

Provider-oriented weather information has been rapidly changing to become more customer-oriented and personalized. Given the increasing interest in wellness and health topics, the demand for health weather information, and biometeorology, also increased. However, research on changes in the human body according to weather conditions is still insufficient due to various constraints, and interdisciplinary research is also lacking. As part of an effort to change that, this study surveyed medical practitioners at an actual treatment site, using questionnaires, to investigate what kind of weather information they could utilize. Although there was a limit to the empirical awareness that medical staff had about weather information, most respondents noted that there is a correlation between disease and weather, with cardiovascular diseases (coronary artery disease (98.5%) and hypertension (95.9% ), skin diseases (atopic dermatitis (100%), sunburn (93.8%)) being the most common weather-sensitive ailments. Although there are subject-specific differences, most weather-sensitive diseases tend to be affected by temperature and humidity in general. Respiratory and skin diseases are affected by wind and solar radiation, respectively.

As a result of broadcasters' websites, there were more reports during the typhoon Bolaven/Tembin in 2012 than in 2002 and 2003. Checking related press releases of each broadcaster on NAVER, YTN reports are 3 times more than KBS. Considering great technology progress in the Internet and smart phone user environment compared to the past, it is thought to be rather regretful in that KBS has been the supervising broadcaster over Korean disaster. As a result of daily reports, the year 2002 typhoon Rusa was reported from the date of its arrival on Korean Peninsular to 3 days, but the information required to be provided for disaster prevention before its arrival was too scarce. 2003 typhoon Maemi was reported as many times as the 2002 typhoon, but its information was provided before its arrival. This is meaningful because the information provision was intended for disaster prevention unlike the past. In 2012, the number of weather forecast broadcast on the typhoon Bolaven/Tembin increased greatly compared to 2002 and 2003. This was also determined to be due to abundant information provided by broadcasters and the Internet portal sites as a result of great progress in Korea internet industry.

In this paper, sensors and equipments for monitoring the weather in test-bed of Honam high-speed railroad are introduced, and integrated monitoring system linked to weather information and its management plan are suggested.

재해영향예보는 기존의 기상요소 중심의 예보에서 벗어나 기상상황에 따른 잠재적 사회경제적 위험도 정보를 함께 제공하는 것을 의미한다. 재해영향예보의 제공시 가장 핵심적 사항은 기상상황에 따라 발생가능한 재해를 예측하고 이에 대한 위험도 정보를 적절히 제공하는 것이다. 하지만 단순히 기상정보와 재해정보를 통합하여 제공하는 재해영향 예보는 기상예보가 확률적 성격을 가지고 있으므로 예보의 내용이 실현된 기상상황과 괴리가 보일 때 재해영향예보 소비자에게 혼동을 줄 수 있다. 따라서 효과적인 재해영향예보는 소비자가 비교적 쉽게 예보의 확률적 성격을 이해할 수 있으며 재해기상상황에 대한 위험도 정보를 미리 숙지할 수 있는 것이어야 한다. 그리고 예보에 기반하여 기상재해에 대한 소비자의 합리적 대응이 가능하도록 하는 것이어야 한다. 본 연구에서는 재해영향예보시 재해기상에 대한 예보정보를 과거재해를 발생시킨 재해기상 및 확률기상 정보와 비교하여 제공하여 기상정보의 소비지가 기상현상이 가져오는 위험도를 보다 직관적으로 이해할 수 있도록 하는 방안을 제시하였다.

본 논문에서는 현재 건설 중인 목포대교와 선박 사이의 충돌 위험도 평가에 필요한 선박 정보와 기상 정보 수집 장치(Data Acquisition System, DAS) 개발에 관하여 기술하였다. 본 연구에서는 DAS를 통항 선박과 기상 현황 데이터를 수집하기 위한 신호 수신 및 처리 유닛과, 데이터 전송과 분배를 위한 네트워킹 유닛, 데이터 관리를 위한 유닛 등으로 구성하였다. 목포항 여객터미널과 신안군 안좌도를 왕복하는 카페리 선상에서의 현장 실험을 통해, 충돌 위기 평가에 적합한 정보를 DAS가 제공할 수 있음을 알았다. 또한 5차 버터워스 디지털 필터를 이용하여 기상 데이터에 포함된 잡음성 데이터를 충분히 억제할 수 있었다.