• Journal of Climate Change Research
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• v.9 no.3
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• pp.283-291
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• 2018

The purpose of this study is to analyze the effects of useof weather and climate information on farmer income. To accomplish the objective of the study a farm survey was conducted, whose target respondents were local correspondents and reporters of the Korea Rural Economic Institute. The ordered logit model was employed for empirical analysis on determining whether use of weather and climate information affects farmer income. The analysis results show that the greater is farmer use of short-range weather forecasts, the higher is the income. The results also show higher farmers income with use of short-range special weather forecasts. Based upon the empirical results, the dissemination of more precise weather and climate information is suggested to increase farmer income.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.55-60
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• 2015

Agro-Meteorological Information Service (AMIS) network has been established since 2001 by Rural Development Administration (RDA) in Korea, and has provided access to current and historical weather data with useful information for agricultural activities. AMIS network includes 158 automated weather stations located mostly in farm region, with planning to increase by 200 stations until 2017. Agrometeorological information is disseminated via the web site (http://weather.rda.go.kr) to growers, researchers, and extension service officials. Our services will give enhanced information from observation data (temperature, precipitation, etc.) to application information, such as drought index, agro-climatic map, and early warning service. AMIS network of RDA will help the implementation of an early warning service for weather risk management.

• Atmosphere
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• v.15 no.2
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• pp.119-127
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• 2005

It is challenging work to predict weather and climate conditions of the future in advance. Since ENIAC was developed, weather and climate research areas have been taking advantage of the improvements in computer hardware. High performance computers allows researchers to build high quality models that allow them to make good predictions of what might happen in the future. Statistics on the high performance computers are one of the major interest to not only manufacturers but also the users such as weather and climate researchers. For this reason, the Top500 Supercomputer Sites Report has been being released twice a year since 1993 to provide a reliable basis for tracking and detecting trends in high performance computing. Using the Top500 Report, a short review on the supercomputer trends in weather and climate research areas is provided in this article.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Atmosphere
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• v.16 no.2
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• pp.141-157
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• 2006

A revolution in weather and climate forecasting is in progress. This has been made possible as a result of theoretical advances in our understanding of the predictability of weather and climate, and by the extraordinary developments in supercomputer technology. New problem areas have been discovered and different solutions have been found by the recent high performance computers whose performance has been increased rapidly. Such advances in the computational performance may change the strategy of development of numerical models and prediction methods. This paper discusses a brief history and current status of the supercomputers in institutions for research and forecast of weather/climate. The main purpose of this study is to provide the preliminary information about supercomputers such as architecture of system and processor. Such information would be useful for meteorologists to understand the features and the preference of supercomputers in each institution.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.1-12
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• 2018

There is an emphasis on the importance of adaptation against to climate change and related natural disasters. As a result, various climate information with different time-scale can be used for science-based climate change adaptation policy. From the aspects of Global Framework for Climate Services (GFCS), various time-scaled climate information in Korea is mainly produced by Korea Meteorological Administration (KMA) However, application of weather and climate information in different application sectors has been done individually in the fields of agriculture and water resources mostly based-on weather information. Furthermore, utilization of climate information including seasonal forecast and climate change projections are insufficient. Therefore, establishment of the Cooperation Center for Application of Weather and Climate Information is necessary as an institutional platform for the UIP (User Interface Platform) focusing on multi-model ensemble (MME) based climate service, seamless climate service, and climate service based on multidisciplinary approach. In addition, APCC Integrated Modeling Solution (AIMS) was developed as a technical platform for UIP focusing on user-centered downscaling of various time-scaled climate information, application of downscaled data into impact assessment modeling in various sectors, and finally producing information can be used in decision making procedures. AIMS is expected to be helpful for the increase of adaptation capacity against climate change in developing countries and Korea through the voluntary participation of producer and user groups within in the institutional and technical platform suggested.

• Atmosphere
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• v.20 no.2
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• pp.101-109
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• 2010

The service of health information was provided through internal and external weather agency web sites. The purpose of this study was to analyze current status of the weather agency web sites dealing with health information in the internet, and to evaluate their contents and technical aspects. The evaluation tool consisted of five area (appropriateness, accessibility, supportiveness, feedback, and continuance) with nineteen items. For the public confidence, web sites were limited to national meteorological administration and representative weather agencies. The evaluating web sites were fourteen from eight countries. The evaluation scores of fourteen web sites were 37.8 out of 53.0 in total. Each subcategory score were 5-12 out of 12 in appropriate, 4-12 out of 12 in accessibility, 4-10 out of 11 in supportiveness, 2-8 out of 9 in feedback, and 2-8 out of 9 in continuance. The score of feedback was the lowest. Survey results indicated that Korean Meteorological Administration homepage was middle status compared with the others in side of depth of health information and feedback from expert. Climate change affect human health, so it will be possible to prevent some disease at first through climate information. It should be developed to provide high quality health information and system related climate on KMA homepage.

• 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.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.33-44
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• 2005

Recently, the weather has been influenced by the environmental pollution and the oil price has been risen because of the lack of resources. So, the weather and energy are influencing on not only enterprises or nations, but also individual daily life and economic activities very much. Because of these reasons, there are so many researches about management of solar radiation needed to develope solar energy as alternative energy. And many researchers are also interested in identifying the area according to changing characteristics of climate data. However, the researches have not developed how to apply the cluster analysis, retrieval and analytical results according to the characteristics of the area through data mining. In this paper, we design a data model of the data for storing and managing the climate data tested in twenty cities in the domestic area. And we provide the information according to the characteristics of the area after clustering the domestic climate data, using k-means clustering algorithm. And we suggest the way how to apply the department store and amusement park as an applied weather marketing. The proposed system is useful for constructing the database about the weather marketing and for providing the elements and analysis information.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.164-168
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• 2023

Accurate and reliable weather forecasts for temperature, relative humidity, and precipitation using advanced transformer models and IoT are essential in various fields related to global climate change. We propose a novel weather prediction device that integrates state-of-the-art transformer models and IoT techniques to improve prediction accuracy and real-time processing. The proposed system demonstrated high reliability and performance, offering valuable insights for industries and sectors that rely on accurate weather information, including agriculture, transportation, and emergency response planning. The integration of transformer models with the IoT signifies a substantial advancement in weather and climate modeling.