• Journal of the Korean earth science society
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• v.31 no.5
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• pp.465-474
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• 2010

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and $12-{\mu}m$ channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.

• Korean Management Science Review
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• v.34 no.1
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• pp.1-13
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• 2017

The percentage of 3PL (Third-party Logistics), which uses third party businesses to outsource elements of the company's distribution and fulfillment services, is increasing steadily. To provide 3PL service to the customers, it is needed to estimate the total transportation cost and propose the unit cost to the customers. In this paper, we develop a decision support system for estimation of transportation cost of 3PL provider considering various transportation services, such as direct transportation, multi point visiting transportation, and cross docking. The system supports route planning of vehicles by using algorithms based on tabu search and dynamic programming.

• Journal of Environmental Science International
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• v.21 no.6
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• pp.749-755
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• 2012

The effect of elevation and meteorological elements is analyzed in Jeju Island for analysis of evapotranspiration with two different height observation station during 3 years data. The slope of temperature gradient recorded $1.30^{\circ}C$/100 m from the analysis of temperature data. There is much difference evapotranspiration between low elevation and high elevation station because of decrease solar radiation and wind speed with height increase. The evapotranspiration is observed by mini lysimeter at Hankukgonghang. The result of observation is presented 34.2% of global solar radiation changed into evapotranspiration during 4 clear days.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.123-129
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• 2006

The measurement method of natural wind to understand the characteristics of the natural wind along the railway lines in Korea has been investigated to be used in the assessment of the risk of train overturn. The weather information service provided by Korea Meteorological Administration has been employed to outline the broad characteristic of natural wind in Korea. Anemometers using CDMA telecommunication for data transfer have been installed near the railway lines to measure velocities and directions of natural wind and the data processing method has been studied using the measured data.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.91-101
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• 2018

This study has analyzed applicable characteristics on big data of the meteorology and climate depending on press releases in the media. As a result, more than half of them were conducted by governmental departments and institutions (26.9%) and meteorological administration (25.0%). Most articles were written by journalists, especially the highest portion stems from straight articles focusing on delivering simple information. For each field, the number of cases had listed in order of rank to be exposed to the media; information service, business management, farming, livestock, and fishing industries, and disaster management, but others did rank far behind; insurance, construction, hydrology and energy. Application of big data about meteorology and climate differed depending on the seasonal change, it was directly related to temperature information during spring, to weather phenomenon such as monsoon and heat wave during summer, to meteorology and climate information during fall, and to weather phenomenon such as cold wave and heavy snow during winter.

• Atmosphere
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• v.33 no.2
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• pp.73-104
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• 2023

Over the past 60 years, Korean numerical weather prediction (NWP) has advanced rapidly with the collaborative effort between the science community and the operational modelling center. With an improved scientific understanding and the growth of information technology infrastructure, Korea is able to provide reliable and seamless weather forecast service, which can predict beyond a 10 days period. The application of NWP has expanded to support decision making in weather-sensitive sectors of society, exploiting both storm-scale high-impact weather forecasts in a very short range, and sub-seasonal climate predictions in an extended range. This article gives an approximate chronological account of the NWP over three periods separated by breakpoints in 1990 and 2005, in terms of dynamical core, physics, data assimilation, operational system, and forecast application. Challenges for future development of NWP are briefly discussed.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1125-1139
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• 2006

The cluster analysis of diurnal precipitation patterns is performed by using daily precipitation of 59 stations in South Korea from 1973 to 1996 in four seasons of each year. Four seasons are shifted forward by 15 days compared to the general ones. Number of clusters are 15 in winter, 16 in spring and autumn, and 26 in summer, respectively. One of the classes is the totally dry day in each season, indicating that precipitation is never observed at any station. This is treated separately in this study. Distribution of the days among the clusters is rather uneven with rather low area-mean precipitation occurring most frequently. These 4 (seasons)$\times$2 (wet and dry days) classes represent more than the half (59 %) of all days of the year. On the other hand, even the smallest seasonal clusters show at least $5\sim9$ members in the 24 years (1973-1996) period of classification. The cluster analysis is directly performed for the major $5\sim8$ non-correlated coefficients of the diurnal precipitation patterns obtained by factor analysis In order to consider the spatial correlation. More specifically, hierarchical clustering based on Euclidean distance and Ward's method of agglomeration is applied. The relative variance explained by the clustering is as high as average (63%) with better capability in spring (66%) and winter (69 %), but lower than average in autumn (60%) and summer (59%). Through applying weighted relative variances, i.e. dividing the squared deviations by the cluster averages, we obtain even better values, i.e 78 % in average, compared to the same index without clustering. This means that the highest variance remains in the clusters with more precipitation. Besides all statistics necessary for the validation of the final classification, 4 cluster centers are mapped for each season to illustrate the range of typical extremities, paired according to their area mean precipitation or negative pattern correlation. Possible alternatives of the performed classification and reasons for their rejection are also discussed with inclusion of a wide spectrum of recommended applications.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.3
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• pp.256-271
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• 2016

The source and transport of the severe Asian dust event (ADE) recently observed in the Korean peninsula were analyzed based on observations (surface weather charts and satellite data) and modeling study (WRF-CMAQ modeling systems). The ADE occurred on 20-21 March 2010 in South Korea with very high $PM_{10}$ concentrations (up to approximately $3,000{\mu}g/m^3$ in Daegu and Jeju). The dominant meteorological conditions affecting the dust outbreak and transport processes were found to be associated with the two synoptic features: (1) strong airflows (i.e., westerlies) induced by a strong pressure gradient resulting from a dense isobar pattern (west-high and east-low) between Tuva Republic and Mongolia and (2) a rapid movement of the strong westerlies merged with airflows generated near Gobi Desert and Inner Mongolia. The merged strong westerlies with a low pressure played a pivotal role in the huge amount of AD and its transport height of 5-8 km. The time and location of dust emissions calculated in the source regions were similar to those observed in the weather charts and satellite image. The ADE simulation mostly showed agreement in the patterns and the concentration levels of modeled dust (including $PM_{10}$) with those of the observations.

• The Plant Pathology Journal
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• v.26 no.1
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• pp.37-48
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• 2010

This paper describes a web-based information system for plant disease forecast that was developed for crop growers in Gyeonggi-do, Korea. The system generates hourly or daily warnings at the spatial resolution of $240\;m{\times}240\;m$ based on weather data. The system consists of four components including weather data acquisition system, job process system, data storage system, and web service system. The spatial resolution of disease forecast is high enough to estimate daily or hourly infection risks of individual farms, so that farmers can use the forecast information practically in determining if and when fungicides are to be sprayed to control diseases. Currently, forecasting models for blast, sheath blight, and grain rot of rice, and scab and rust of pear are available for the system. As for the spatial interpolation of weather data, the interpolated temperature and relative humidity showed high accuracy as compared with the observed data at the same locations. However, the spatial interpolation of rainfall and leaf wetness events needs to be improved. For rice blast forecasting, 44.5% of infection warnings based on the observed weather data were correctly estimated when the disease forecast was made based on the interpolated weather data. The low accuracy in disease forecast based on the interpolated weather data was mainly due to the failure in estimating leaf wetness events.

• Journal of Advanced Navigation Technology
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• v.21 no.2
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• pp.206-211
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• 2017

Recently computing devices by connecting to a network, grid computing, the next generation of digital neural networks that provide maximum service will connect all of the computer such as a PC or server, PDA into one giant network makes the virtual machine. Therefore, we propose the grid computing implementation model to be applied to meteorological business field as follows. First, grid computing will be used for tasks such as the development of numerical models below the mid-scale or test operations, and the final backup of the weather supercomputer. Second, the resources that will constitute grid computing are limited to business PCs and Linux servers operated by the central government considering operational efficiency. Third, the network is restricted to the LAN section, which suggests the implementation of high performance computing.