• International Journal of Highway Engineering
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• v.14 no.4
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• pp.141-148
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• 2012

PURPOSES : This study demonstrates the need for the collection of road weather information in order to perform efficient snow removal works during the winter season. Snow removal operations are usually dependent upon weather information obtained from the Automatic Weather Station provided by the Korea Meteorological Administration. However, there are some difference between road weather and weather forecasts in their scope. This is because general weather forecasts are focused on macroscopic standpoints rather than microscopic perspectives. METHODS : In this study, the relationship between snow removal works and historical weather forecasts are properly analyzed to prove the importance of road weather information. We collected both weather data and snow removal works during winter season at "A" regional offices in Gangwon areas. RESULTS : Results showed that the validation of weather forecasts for snow removal works were depended on the height difference between AWS location and its neighboring roadway. CONCLUSIONS : Namely, it appears that road weather information should be collected where AWS location and its neighboring roadway have relatively big difference in their heights.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.735-743
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• 2017

With growing concerns about ever-increasing anthropogenic greenhouse gas emissions, it is crucial to enhance preparedness for unprecedented extreme weathers that can bring catastrophic consequences. In this study, we proposed a stochastic framework that considers uncertainty in weather forecasts for flood analyses. First, we calibrated a simple rainfall-runoff model against observed hourly hydrographs. Then, using probability density functions of rainfall depths conditioned by 6-hourly weather forecasts, we generated many stochastic rainfall depths for upcoming 48 hours. We disaggregated the stochastic 6-hour rainfalls into an hourly scale, and input them into the runoff model to quantify a probabilistic range of runoff during upcoming 48 hours. Under this framework, we assessed two rainfall events occurred in Bocheong River Basin, South Korea in 2017. It is indicated actual flood events could be greater than expectations from weather forecasts in some cases; however, the probabilistic runoff range could be intuitive information for managing flood risks before events. This study suggests combining deterministic and stochastic methods for forecast-based flood analyses to consider uncertainty in weather forecasts.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.6
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• pp.25-32
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• 1999

The purpose of this study is to analyse the accuracy of weather forecasts of temperature, precipitation probability , and sky condition and to evaluate the applicability of weather forecasts for the estimation of potential evapotranspiration for irrigation scheduling. Five weather station s were selected to compare forecasted and measured climatcal data. The error between forecasted and measured temperature was calculated and discussed. The accuracy of temperature forecast using relative frequency of the error was calculated . The temperature forecasting showed considerably high accuracy. Average sunshine hours for forecasted sky conditions were calculated and showed reasonable quality. From the reliability graphs, the forecasting precipation probabililty was reliable. Potential evapotranspirations were calculated and compared using forecast and measured temperatures. The weather forecast is considered usable for irrigation scheculing.

• Korean Management Science Review
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• v.27 no.1
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• pp.33-43
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• 2010

This paper presents a method for the estimation and analysis of the economic value of weather forecasts for CRM decision-making problems in the leisure industry. Value is calculated in terms of the customer's satisfaction returned from the user's decision under the specific payoff structure, which is itself represented by a customer's satisfaction ratio model. The decision is assessed by a modified cost-loss model to consider the customer's satisfaction instead of the loss or cost. Site-specific probability and deterministic forecasts, each of which is provided in Korea and China, are applied to generate and analyze the optimal decisions. The application results demonstrate that probability forecasts have greater value than deterministic forecasts, provided that the users can locate the optimal decision threshold. This paper also presents the optimal decision strategy for specific customers with a variety of satisfaction patterns.

• The Plant Pathology Journal
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• v.21 no.2
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• pp.111-118
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• 2005

Weather data for disease forecasts are usually derived from automated weather stations (AWS) that may be dispersed across a region in an irregular pattern. We have developed an alternative method to simulate local scale, high-resolution weather and plant disease in a grid pattern. The system incorporates a simplified mesoscale boundary layer model, LAWSS, for estimating local conditions such as air temperature and relative humidity. It also integrates special models for estimating of surface wetness duration and disease forecasts, such as the grapevine downy mildew forecast model, DMCast. The system can recreate weather forecasts utilizing the NCEP/NCAR reanalysis database, which contains over 57 years of archived and corrected global upper air conditions. The highest horizontal resolution of 0.150 km was achieved by running 5-step nested child grids inside coarse mother grids. Over the Finger Lakes and Chautauqua Lake regions of New York State, the system simulated three growing seasons for estimating the risk of grape downy mildew with 1 km resolution. Outputs were represented as regional maps or as site-specific graphs. The highest resolutions were achieved over North America, but the system is functional for any global location. The system is expected to be a powerful tool for site selection and reanalysis of historical plant disease epidemics.

• Atmosphere
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• v.14 no.3
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• pp.41-54
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• 2004

In this study, a brief overview on a WMO/WWRP program - The Observing System Research and Predictability Experiment (THORPEX) and discussions on perspectives and potential benefits of Asian countries are provided. THORPEX is aimed at accelerating improvements in the accuracy of 1 to 14-day high-impact weather forecasts with research objectives of: 1) predictability and dynamical processes; 2) observing systems; 3) data assimilation and observing strategies; and 4) societal and economic applications. Direct benefits of Asian countries from THORPEX include improvement of: 1) forecast skills in global models, which exerts positive impact on mesoscale forecasts; 2) typhoon forecasts through dropwindsonde observations; and 3) forecast skills for high-impact weather systems via increased observations in neighboring countries. Various indirect benefits for scientific researches are also discussed. Extensive adaptive observation studies are recommended for all high-impact weather systems coming into the Korean peninsula, and enhancement of observations in the highly sensitive regions for the forecast error growth is required to improve forecast skills in the peninsula, possibly through international collaborations with neighboring countries.

• 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 the Korean Society for Aviation and Aeronautics
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• v.28 no.1
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• pp.45-58
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• 2020

According to the Ministry of Land, Infrastructure and Transport press release ('18.12.21.) The amendment of the Aviation Business Act will reduce the capital requirements for aviation leisure operators and make it easier to enter aviation leisure businesses by improving regulations on small air transportation business. In addition, as the scale of the UAV(Unmanned Aerial Vehicle) sector is expected to increase globally, the dramatic increase in low altitude operating aircraft, including this, must be taken into account. The low altitude aircraft category is divided into small airplanes, helicopters, light aircrafts and ultra-light aircrafts, and instructors include school instructor pilots and student pilots, military and national helicopter pilots, and aviation leisure operators. In case of low altitude aircraft, there are cases of canceling operations due to low visibility and low clouds, and aircraft accidents due to excessive operation and sudden weather phenomenon. Therefore, in order to prevent low-altitude aircraft accidents, a safe flight plan based on weather conditions and weather forecasts and more accurate and local weather forecasts and weather forecast data are needed to prepare for the rapidly changing weather conditions.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.563-577
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• 2017

As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.51-56
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• 2006

Biases embedded in numerical weather precipitation forecasts by the RDAPS model was determined, quantified and corrected. The ultimate objective is to eventually enhance the reliability of reservoir operation by Korean Water Resources Corporation (KOWACO), which is based on precipitation-driven forecasts of stream flow. Statistical post-processing, so called MOS (Model Output Statistics) was applied to RDAPS to improve their performance. The Artificial Neural Nwetwork (ANN) model was applied for 4 cases of 'Probability of Precipitation (PoP) for wet and dry season' and 'Quantitative Precipitation Forecasts (QPF) for wet and dry season'. The reduction on the large systematic bias was especially remarkable. The performance of both networks may be improved by retraining, probably every month. In addition, it is expected that performance of the networks will improve once atmospheric profile data are incorporated in the analysis. The key to the optimal performance of ANN is to have a large data set relevant to the predictand variable. The more complex the process to be modeled by the ANN, the larger the data set needs to be.