• Atmosphere
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• v.24 no.2
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• pp.253-263
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• 2014

The Korea Meteorological Administration has recently focused on the promotion of the meteorological industry in the private sector. Broadcast meteorology has provided the main source of income to the Meteorological industry in the United States with The Weather Channel (TWC) being the most prominent enterprise. TWC has 31 years of history and has become an icon of innovation in the U.S. meteorological industry. TWC's success story was reviewed for the possible adaptation of Korea's meteorological media industry. Expected roles for public, academic, and private sectors were suggested for boosting industrial meteorology for the media at present and in the future.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 2023

Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

• Journal of Integrative Natural Science
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• v.10 no.4
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• pp.216-224
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• 2017

In the terrain of the Korean peninsula, mountainous and flat lands are complexly distributed in small areas. Therefore, local severe weather develops and disappears in a short time due to the influence of the terrain. Particularly in the case of local severe weather with heavy wind that has the greatest influence on aviation meteorology, the scale is very small, and it occurs and disappears in a short time, so it is impossible to predict with fragmentary data alone. So, we use weather radar to detect and predict local severe weather. However, due to the development of wireless communication services and the rapid increase of wireless devices, radio wave jamming and interference problems occur. In this research, we confirmed through the cases that when the radio interference echo which is one of the non-precipitation echoes that occur during the operation of the weather radar is displayed in the image, its form and shape are shown in a long bar shape, and have a strong dBZ. We also found the cause of the interference through the radio tracking process, and solved through the frequency channel negotiation and AP output minimizing. The more wireless devices increase as information communication technology develops in the future, the more emphasized the problem of radio wave interference will be, and we must make the radio interference eliminated through the development of the radio interference cancellation algorithm.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1025-1032
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• 2020

In this paper, we propose a method to classify road weather conditions into rain, fog, and sun using a SVM (Support Vector Machine) classifier after extracting weather features from images acquired in real time using an optical sensor installed on a roadside post. A multi-dimensional weather feature vector consisting of factors such as image sharpeness, image entropy, Michelson contrast, MSCN (Mean Subtraction and Contrast Normalization), dark channel prior, image colorfulness, and local binary pattern as global features of weather-related images was extracted from road images, and then a road weather classifier was created by performing machine learning on 700 sun images, 2,000 rain images, and 1,000 fog images. Finally, the classification performance was tested for 140 sun images, 510 rain images, and 240 fog images. Overall classification performance is assessed to be applicable in real road services and can be enhanced further with optimization along with year-round data collection and training.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3567-3582
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• 2020

Human activities are often affected by weather conditions. Automatic weather recognition is meaningful to traffic alerting, driving assistance, and intelligent traffic. With the boost of deep learning and AI, deep convolutional neural networks (CNN) are utilized to identify weather situations. In this paper, a three-channel convolutional neural network (3C-CNN) model is proposed on the basis of ResNet50.The model extracts global weather features from the whole image through the ResNet50 branch, and extracts the sky and ground features from the top and bottom regions by two CNN5 branches. Then the global features and the local features are merged by the Concat function. Finally, the weather image is classified by Softmax classifier and the identification result is output. In addition, a medium-scale dataset containing 6,185 outdoor weather images named WeatherDataset-6 is established. 3C-CNN is used to train and test both on the Two-class Weather Images and WeatherDataset-6. The experimental results show that 3C-CNN achieves best on both datasets, with the average recognition accuracy up to 94.35% and 95.81% respectively, which is superior to other classic convolutional neural networks such as AlexNet, VGG16, and ResNet50. It is prospected that our method can also work well for images taken at night with further improvement.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.437-443
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• 2015

In this paper, we analyze the performance of the all-optical multihop radio over a free space optical (RoFSO) communication system with amplify-and-forward (AF) relays under varying weather conditions. The proposed channel model considers the propagation loss, attenuation and atmospheric fading modeled by the Gamma-Gamma (GG) distribution. Both the amplified spontaneous emission (ASE) noise in the all-optical relays and the background noise projected onto receiver apertures have been considered in the analysis. The lower bound analytical expressions for the end-to-end bit error rate (BER) and outage probability are derived for the multihop system employing the all-optical relays with the full channel state information (CSI). Meanwhile, the exact results for BER and outage probability are obtained via Monte Carlo simulation. Results indicate the performance of the proposed system will be improved by the multihop transmission technology. For a fixed number of relays, the BER and outage probability will be increased with the deterioration of the weather conditions.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.201-208
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• 2011

The aim of this paper is to develop a framework of weather information services which is for processing contents and providing proper contents to new-media such as outdoor electronic display, DID (digital information display), and terrestrial multi-channel broadcasting, etc. By introducing the analysis of media use and perception science of human intelligence, the contents producing method to improve recognizing rate for weather information is provide and the layered framework of weather information services for new-media is designed. It integrates many different services to the framework. It can prevent duplicate investment for services and serve a major momentum to technical progress.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.409-414
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• 2009

I have not seen each of the existing technology, RFID/USN technology combined with the wireless communication channel for the state of nuclear safety in real-time remote monitoring and operation system technology CARE existing radioactive accident information collected by the nuclear power and nuclear power status, 10-20 second intervals to monitor the safety network (SIDS), and nuclear power plants located on the site within 40 ㎞ radius around the 13~15 of the wind speed from the automatic weather network weather information such as rainfall and temperature every 10 minutes to collect as automatic weather network (REMDAS), Evaluation of atmospheric radiation and radiation of the bomb radiation impact assessment system to calculate the goodness (FADAS) and thicken the radiation-related information consists of real-time web technology to collect, the last robot on behalf of the human will to manage the nuclear power plant accident of the technology to prevent the concrete from the following narrative about to have.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.645-648
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• 2005

The COMS(Communication, Ocean and Meteorological Satellite), a multi-mission geo-stationary satellite, is being developed by KARl. The first mission of the COMS is the meteorological image and data gathering for weather forecast by using a five channel meteorological imager. The second mission is the oceanographic image and data gathering for marine environment monitoring around Korean Peninsula by using an eight channel Geostationary Ocean Color Imager(GOCI). The third mission is newly developed Ka-Band communication payload certification test in space by providing communication service in Korean Peninsula and Manjurian area. There were many low Earth orbit satellites for ocean monitoring. However, there has never been any geostationary satellite for ocean monitoring. The COMS is going to be the first satellite for ocean monitoring mission on the geo-stationary orbit. The meteorological image and data obtained by the COMS will be distributed to end users in Asia-Pacific area and it will contribute to the improved weather forecast.

• Korean Journal of Computational Design and Engineering
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• v.17 no.5
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• pp.333-341
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• 2012

Modeling and simulation is important for military training. People can feel perspective when stereoscope images are created using multi-channel visualizations. A submarine oscillates when the submarine is just below the surface of the sea, so that the reconnaissance becomes difficult. Also, the operator should read the information of the target within 6 seconds using the periscope. The operator must have experience. To solve these problems, stereoscopic multi-channel visualization has been tested. The iCAVE system of KAIST provides a large-scale screen, 7 PCs, and 14 projectors to create the stereoscope images. To simulate the motion of a submarine just below the ocean surface, a 4-DOF motion platform is used. The motion data is transmitted to the visual system and the motion platform through the UDP protocol. Variety of weather conditions are created using the Vega Prime software. The stereoscopic multi-channel visualization and the motion platform system created a realistic simulation system.