• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.74-85
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• 2014

This study is a part of "Early Warning Service for Weather Risk Management in Climate-smart Agriculture", describes the delivery techniques from 840 catchment scale weather warning information using 150 counties unit special weather report(alarm, warning) released from KMA(Korea Meteorological Administration) and chronic weather warning information based on daily weather data from 76 synoptic stations. Catchment weather hazard warning service express a sequential risk index map generated by countries report occurs and report grade(alarm, warning) convert to catchment scale using zonal summarizing method. Additional services were chronic weather warning service at crop growth and accumulated more than 4 weeks, based on an unsuitable weather conditions, representing a relative risk compared to its catchment climatological normal conditions (normal distribution ) in addition to special weather report. Service provided by a real-time catchment scale map overlaid with VWORLD open platform operated by Ministry of Land, Infrastructure and Transport. Also provide a foundation for weather risk information to inform individual farmers to farm located within the catchment zone warning occur.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.365-374
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• 2012

Weather derivatives designed to manage casual changes of weather, as opposed to catastrophic risks of weather, are relatively a new class of financial instruments. There are still many theoretical and practical challenges to the effective use of these instruments. The objective of this paper is to develop a pricing approach for valuing weather derivatives and presents a case study that is practical enough to be used by the risk managers of electrical utility firms. Utilizing daily average temperature data of Guangzhou, China from $1^{st}$ January 1978 to $31^{st}$ December 2010, this paper adopted a univariate time series model to describe weather behavior dynamics and calculates equilibrium prices for weather futures and options for an electrical utility firm in the region. The results imply that the risk premium is an important part of derivatives prices and the market price of risk affects option values much more than forward prices. It also demonstrates that weather innovation as well as weather risk management significantly affect the utility's financial outcomes.

• Korean Journal of Organic Agriculture
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• v.28 no.4
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• pp.459-475
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• 2020

This study analyzes weather derivatives as an alternative risk management tool to stabilize farm revenue to complement the existing crop insurance program which suffers from asymmetric information problems such as adverse selection, moral hazard, and verifiability. We estimated apple yield functions to observe the relationship between yields and weather indices such as temperature and precipitation. Based on the estimated yield functions we designed weather futures and options products underlying temperature and precipitation, and calculated the prices of futures and options by two different approaches, historical distribution and Monte Carlo simulation. We found that weather futures and options stabilize farm revenue based on the estimated four risk indicators: Coefficient of Variation, Value at Risk, Certainty Equivalence, and Risk Premium. As a result, weather derivatives could be considered as a potential farm risk management tool through studying more in legal and institutional strategies and developing various derivatives products.

• Fire Science and Engineering
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• v.29 no.5
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• pp.88-95
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• 2015

We propose a weather-related service for fire risk assessment in order to increase fire safety awareness in everyday life. The proposed service offers a fire risk assessment level according to weather forecasts and a degree of fire risk according to fire factors under certain weather conditions. In order to estimate the fire risk, we produced a risk matrix through data mining with a decision tree using investigation data and weather data. Through the proposed service, residents can calculate the degree of fire risk under certain weather conditions using the fire factors around them. In addition, they can choose from various solutions to reduce fire risk. In order to demonstrate the feasibility of the proposed services, we developed a system that offers the services. Whenever weather forecasting is carried out by the Korea Meteorological Administration, the system produces the fire risk assessment levels for seven major cities and nine provinces of South Korea in an online process, as well as the fire risk according to fire factors for the weather conditions in each region.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.171-175
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• 2017

The purpose of the farmstead-specific early warning service system for weather risk management is to develop custom-made risk management recommendations for individual farms threatened by climate change and its variability. This system quantifies weather conditions into a "weather risk index" that is customized to crop and its growth stage. When the risk reaches the stage where it can cause any damage to the crops, the system is activated and the corresponding warning messages are delivered to the farmer's mobile phone. The messages are sent with proper recommendations that farmers can utilize to protect their crops against potential damage. Currently, the technology necessary to make the warning system more practical has been developed, including technology for forecasting real-time weather conditions, scaling down of weather data to the individual farm level and risk assessments of specific crops. Furthermore, the scientific know-how has already been integrated into a web-based warning system (http://new.agmet.kr). The system is provided to volunteer farmers with direct, one-on-one weather data and disaster warnings along with relevant recommendations. In 2016, an operational system was established in a rural catchment ($1,500km^2$) in the Seomjin river basin.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.9
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• pp.487-493
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• 2004

The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RTS. The system performance index for power flow presents the power system stability. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into the case of normal and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking required for security under the deregulated electricity market.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.319-353
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• 2006

This paper shows how weather derivatives can be used to hedge against the price risk and volume risk of purchasing relatively large amounts of electricity. Our specific approach to designing new contracts for electricity is to focus on the return over a summer season rather than on the daily levels of demand and price. It is shown that correct market signals can be preserved in a contract and the associated financial risk can be offset by weather options. The advantage of combining a forward contract with a weather derivative is that the high prices on hot days or when the temperature is high reflect the underlying high cost of producing power when the load is high and that the combined contract with a weather derivative substantially reduces the volatility of the return.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.69-75
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• 2023

Purpose: The risk of disaster from extreme weather events is increasing due to the increase in occurrence and the strength of heavy rains and storms from continued climate change. To reduce these risks, emergency weather information customized for the characteristics of the information users and related circumstances should be provided. Method: A first-stage emergency weather information delivery system has been developed to provide weather information to the disaster-risk area residents and the disaster response personnel. Novel methods to apply artificial intelligence to identify emergencies have been studied. The relationship between special weather reports from meteorological administration and disaster-related news articles has been analyzed to identify the significance of a pilot study using text analytic artificial intelligence. Result: The basis to identify the significance of the relations between disaster-related articles and special weather reports has been established and the possibility of the development of a real-world applicable system based on a broader analysis of data has been suggested. Conclusion: Through direct alert delivery of weather emergency alerts, a weather emergency alert system is expected to reduce the risk of damage from extreme weather situations.

• 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.