• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.21-28
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• 2016

Numeric weather prediction is important to prevent meteorological disasters such as heavy rain, heat wave, and cold wave. The Korea meteorological administration provides a realtime special weather report and the rural development administration demonstrates information about 2-day warning of agricultural disasters for farms in a few regions. To improve the early warning systems for meteorological hazards, a nation-wide high-resolution dataset for weather prediction should be combined with web-based GIS. This study aims to develop a web service prototype for early warning of meteorological hazards, which integrates web GIS technologies with a weather prediction database in a temporal resolution of 1 hour and a spatial resolution of 1 km. The spatially and temporally high-resolution dataset for meteorological hazards produced by downscaling of GME was serviced via a web GIS. In addition to the information about current status of meteorological hazards, the proposed system provides the hourly dong-level forecasting of meteorologic hazards for upcoming seven days, such as heavy rain, heat wave, and cold wave. This system can be utilized as an operational information service for municipal governments in Korea by achieving the future work to improve the accuracy of numeric weather predictions and the preprocessing time for raster and vector dataset.

• Journal of Environmental Science International
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• v.28 no.11
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• pp.1047-1059
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• 2019

To address the increase of weather hazards and the emergence of new types of such hazards, an optimization technique for three-dimensional (3D) representation of meteorological facts and atmospheric information was examined in this study as a novel method for weather analysis. The proposed system is termed as "meteorological and air quality information visualization engine" (MAIVE), and it can support several file formats and can implement high-resolution 3D terrain by employing a 30 m resolution digital elevation model. In this study, latest 3D representation techniques such as wind vector fields, contour maps, stream vector, stream line flow along the wind field and 3D volume rendering were applied. Implementation of the examples demonstrates that the results of numerical modeling are well reflected, and new representation techniques can facilitate the observation of meteorological factors and atmospheric information from different perspectives.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2016.09a
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• pp.44-48
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• 2016

Extreme temperature impacts on field crop are of key concern and increasingly assessed, however the studies have seldom taken into account the automatic adaptations such as shifts in planting dates, phenological dynamics and cultivars. In this present study, trial data on rice phenology, agro-meteorological hazards and yields during 1981-2009 at 120 national agro-meteorological experiment stations were used. The detailed data provide us a unique opportunity to quantify extreme temperature impacts on rice yield more precisely and in a setting with automatic adaptations.

• Journal of Environmental Science International
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• v.29 no.10
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• pp.981-988
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• 2020

This study presents meteorological data integrity to improve environmental quality assessment in Yongdam catchment. The study examines both extreme ranges of meteorological data measurements and data reliability which include maximum and minimum temperature, relative humidity, dew point temperature, radiation, heat flux. There were some outliers and missing data from the measurements. In addition, the latent heat flux and sensible heat flux data were not reasonable and evapotranspiration data did not match at some points. The accuracy and consistency of data stored in a database for the study were secured from the data integrity. Users need to take caution when using meteorological data from the Yongdam catchment in the preparation of water resources planning, environmental impact assessment, and natural hazards analysis.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.711-726
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• 2021

This paper presents a multiple parameters-based recursive methodology for the reliability quantification of civil structures subjected to meteorological disasters. Recognizing the challenge associated with characterizing at a single stroke all the meteorological disasters that may hit a structure during its service life, the proposed methodology by contrast features a multiparameter recursive mechanism to describe the meteorological demand of the structure. The benefit of the arrangements is that the essentially inevitable deviation of the practically observed meteorological data from those in the existing model can be mitigated in an adaptive manner. In particular, the implications of potential climate change to the relevant reliability of civil structures are allowed for. The application of the formulated methodology of recursive reliability quantification is illustrated by first considering the reliability quantification of a linear shear frame against simulated strong wind loads. A parametric study is engaged in this application to examine the effect of some hyperparameters in the configured hierarchical model. Further, the application is extended to a nonlinear hysteretic shear frame involving some field-observed cyclone data, and the incompleteness of the relevant structural diagnosis data that may arise in reality is taken into account. Also investigated is another application scenario where the reliability of a building envelope is assessed under hailstone impacts, and the emphasis is to demonstrate the recursive incorporation of newly obtained meteorological data.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.1-11
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• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.487-491
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• 2007

Recently, rainfall induced hazard has been increased gradually, for example, typhoon Rusa in 2002 and Maemi in 2003. In addition, localized heavy rainfall has been also caused tremendous damage to railroad systems. Measured data from the Meteorological Adminstration sometimes, However, are not in accordance with those of rain gauges in local area, because of its good distance. This study develop automatic alarming software to estimate and prevent these kind of rainfall induced hazards in railroad system with online transportation.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• The Journal of the Petrological Society of Korea
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• v.23 no.4
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• pp.405-418
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• 2014

Ontake Volcano, Japan, began to erupt without any precursors on September 27, 2014, at 11:52 AM, and it caused many losses of life. Although Japan's preparation manual and prevention for volcanic eruptions and volcanic hazards has been well established, it could not prevent damage due to the sudden eruption of the volcano. Soon after the eruption, however, Japan Meteorological Agency (JMA) led many organizations and institutions, including JMA's Volcanic Eruption Prediction Liaison Council, Meteorological Research Institute (MRI) and National Agriculture and Food Research Organization and they understood the eruption situation quickly and shared the information based on their close cooperation and contact systems. Through these efforts, JMA published the unified result to the public, informing the public of the situation around the volcano and about the eruption and of how the residents and climbers around the volcano should react to the volcanic hazards caused by the eruption. The Korean Government can learn how to respond to a future eruption of a volcano, such as Mt. Baekdu which has the potential to erupt in the foreseeable future.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.