• Journal of Korean Society for Atmospheric Environment
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• v.30 no.6
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• pp.600-618
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• 2014

The metadata for urban meteorological observation is standardized through comparison with those established at the World Meteorological Organization and the Korea Meteorological Administration to understand the surrounding environment around the sites exactly and maintain the networks and sites efficiently. It categorizes into metadata for an observational network and observational sites. The latter is again divided into the metadata for station general information, local scale information, micro scale information, and visual information in order to explain urban environment in detail. The metadata also contains the static information such as urban structure, surface cover, metabolism, communication, building density, roof type, moisture/heat sources, and traffic as well as the update information on the environment change, maintenance, replacement, and/or calibration of sensors. The standardized metadata for urban meteorological observation is applied to the Weather Information Service Engine (WISE) integrated meteorological sensor network and sites installed at Incheon area. It will be very useful for site manager as well as researchers in fields of urban meteorology, radiation, surface energy balance, anthropogenic heat, turbulence, heat storage, and boundary layer processes.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.117-129
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• 2018

This study examines the impact of severe weather on lean supply chains. First, this paper reviewed the literature on the disruptions and damages that severe weather events cause on supply chain. Then, several recent examples of lean supply chain disruptions due to severe weather were discussed. The results of the study indicated that the frequency of weather related disasters is increasing and extreme weather events will increase potential risks to supply chains. First, building organizational resilience will help firms look beyond efficiency and profits in managing lean supply chains. Second, the concept of sole sourcing may need rethinking to maintain a supply chain that is lean and resilient. Third, organizations must plan ahead for supply chains in unpredictable weather. Fifth, communication is a key for anticipating and avoiding the impact of severe weather. This study proposes of a set of strategies, both theoretical and practical, that business firms should develop to effectively prevent and respond to severe weather related disruptions in lean supply chains.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.101.2-101.2
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• 2011

We have developed solar and space weather monitoring system for space weather users since 2007 as a project named 'Construction of Korea Space Weather Prediction Center'. In this presentation we will introduce space weather monitoring system for Geostationary Satellites and Polar Routes. These were developed for satisfying demands of space weather user groups. 'Space Weather Monitoring System for Geostationary Satellites' displays integrated space weather information on geostationary orbit such as magnetopause location, nowcast and forecast of space weather, cosmic ray count rate, number of meteors and x-ray solar flux. This system is developed for space weather customers who are managing satellite systems or using satellite information. In addition, this system provides space weather warning by SMS in which short message is delivered to users' cell phones when space weather parameters reach a critical value. 'Space Weather Monitoring System for Polar Routes' was developed for the commercial airline companies operating polar routes. This provides D-region and polar cap absorption map, aurora and radiation particle distribution, nowcast and forecast of space weather, proton flux, Kp index and so on.

• IE interfaces
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• v.13 no.4
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• pp.646-657
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• 2000

We developed an efficient small sized weather condition forecasting system (WFS). A cheap NT-server was utilized for handling a large amount of data, while traditional WFS has conventionally relied on Unix based workstation server. The proposed WFS contains automatic weather observing system (AWS). AWS was designed for collecting weather conditions automatically, and it was linked to WFS in order to provide various weather condition information. The existing two phase scheme and chain code algorithm were used for transforming AWS's data into WFS's data. The WFS's data were mapped into geometric information system using various display techniques. Finally the transformed WFS's data was also converted into JPG (Joint Photographic Group) data type, and the final JPG data could be accessible by others though Internet. The developed system was implemented using WWW environment and has provided weather condition forecasting information. Real case is given to show the presented integrated WFS with detail information.

• Journal of Environmental Science International
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• v.26 no.5
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• pp.675-684
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• 2017

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.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1874-1885
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• 2018

The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1737-1743
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• 2008

A weather radar extracts the weather information from the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. The characteristics of Doppler weather signal and ground clutter should be analyzed to extract the accurate weather information. However, the conventional symmetric weather Doppler model is somewhat inappropriate in representing various weather situations. Therefore, the improved model is suggested to describe the skewness in the Doppler spectrum model. Using the suggested model, many various weather signals can be simulated efficiently in time and spectral domain according to weather situations, operation environment and system characteristics. This simulation method may be very helpful in verifying the accuracy of the weather information extraction algorithms and developing the new system for further performance improvement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1180-1187
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• 2022

As the likelihood of occurrence of the localized microbursts or severe flooding is increased due to the unusual weather changes, it is the very urgent problem to detect these weather hazards with a local weather radar. For a local weather radar of this purpose, it is essential to detect the low altitude and the fast varying weather conditions. Therefore, the very fast update of the weather information and the efficient clutter removal is very important. To achieve this goal, the appropriate method should be applied which does not need the mechanical elevation scanning and has the capability of the efficient clutter removal. Therefore, in this paper, the usefulness of the implementation of elevational filter banks with the spatial FFT algorithm was analyzed and investigated using a simple array antenna. It is shown that the suggested method can be used for both the minimization of the ground clutter and the fast update of weather information.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.917-929
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• 2010

This paper aims to find out the statistical characteristics of the weather related railroad accidents and incidents. Data from Korea Railroad Operation Information System(KROIS) and Korea Railroad Accidents reports during 1996-2008 were used to investigate the occurrence frequency of railroad accidents and operation obstacles and their association with weather phenomena. The results are as follows; The occurrence frequency of railroad accidents and operation obstacles decrease gradually, and most of railroad accidents is a railroad traffic accidents. The amount of damages by a railroad weather-related accidents is higher than those of the railroad accidents and operation obstacles. It was also found that weather events influencing the railroad weather-related accidents and incidents are rainfall, snowfall, lightning, winds. And they caused a railroad weather-related accidents and incidents, such as railway obstruction, signal failure, and power supply failure. Therefore we need research about threshold review and a quantitative and qualitative analysis of a railroad weather-related accidents and incidents according to climate change.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.