• Journal of Korean Society of Rural Planning
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• v.24 no.4
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• pp.99-119
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• 2018

Unit load factor, which is used for the quantification of non-point pollution in watersheds, has the limitation that it does not reflect spatial characteristics of soil, topography and temporal change due to the interannual or seasonal variability of precipitation. Therefore, we developed the method to estimate a watershed-scale non-point pollutant load using seasonal forecast data that forecast changes of precipitation up to 6 months from present time for watershed-scale water quality management. To establish a preemptive countermeasure against non-point pollution sources, it is possible to consider the unstructured management plan which is possible over several months timescale. Notably, it is possible to apply various management methods such as control of sowing and irrigation timing, control of irrigation through water management, and control of fertilizer through fertilization management. In this study, APEX-Paddy model, which can consider the farming method in field scale, was applied to evaluate the applicability of seasonal forecast data. It was confirmed that the rainfall amount during the growing season is an essential factor in the non-point pollution pollutant load. The APEX-Paddy model for quantifying non-point pollution according to various farming methods in paddy fields simulated similarly the annual variation tendency of TN and TP pollutant loads in rice paddies but showed a tendency to underestimate load quantitatively.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.305-310
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• 1998

This research conducted concerning measures for the influence reduction to an investigation in the structure of offshore breakwater maintenance, an evaluation, a reexamination of the forecast, and a peripheral sediment transport environment. Furthermore, it aimed at the establishment of the beach transformation forecast method based on a hydraulic model study and a numeric simulation. A good result was obtained from a hydraulic model experiment and a numeric simulation as part of the basic research. And a qualitative evaluation of the flow field around the structure became possible since a numeric simulation examined flow field characteristics.

• Korean Journal of Organic Agriculture
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• v.30 no.2
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• pp.231-239
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• 2022

The purpose of this study is to provide meaningful information for various stakeholders' decision-making process through forecasting of domestic beef demand. Three different exponential smoothing models were evaluated, and a double exponential smoothing model was used to forecast domestic beef demand based on time-series data, As a result of the forecast, domestic beef consumption is expected to increase by 37,000 to 40,000 tons per year from 2020 to 2025.

• Ocean and Polar Research
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• v.40 no.3
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• pp.99-114
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• 2018

In the present study, we assess the GloSea5 (Global Seasonal Forecasting System version 5) near-surface ocean current forecasts using globally observed surface drifter dataset. Annual mean surface current fields at 0-day forecast lead time are quite consistent with drifter-derived velocity fields, and low values of root mean square (RMS) errors distributes in global oceans, except for regions of high variability, such as the Antarctic Circumpolar Current, Kuroshio, and Gulf Stream. Moreover a comparison with the global high-resolution forecasting system, HYCOM (Hybrid Coordinate Ocean Model), signifies that GloSea5 performs well in terms of short-range surface-current forecasts. Predictions from 0-day to 4-week lead time are also validated for the global ocean and regions covering the main ocean basins. In general, the Indian Ocean and tropical regions yield relatively high RMS errors against all forecast lead times, whilst the Pacific and Atlantic Oceans show low values. RMS errors against forecast lead time ranging from 0-day to 4-week reveal the largest increase rate between 0-day and 1-week lead time in all regions. Correlation against forecast lead time also reveals similar results. In addition, a strong westward bias of about $0.2m\;s^{-1}$ is found along the Equator in the western Pacific on the initial forecast day, and it extends toward the Equator of the eastern Pacific as the lead time increases.

• Atmosphere
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• v.34 no.1
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• pp.23-34
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• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.967-974
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• 2011

Based on daily time series from RDAPS numerical weather forecast, Streamflow prediction was simulated and the result of ESP analysis was implemented considering quantitative mid- and long-term forecast to compare the results and review applicability. The result of ESP, ESP considering quantitative weather forecast, and flow forecast from RDAPS numerical weather forecast were compared and analyzed with average observed streamflow in Guem River Basin. Through this process, the improvement effect per method was estimated. The result of ESP considering weather information was satisfactory relatively based on long-term flow forecast simulation result. Discrepancy ratio analysis for estimating accuracy of probability forecast had similar result. It is expected to simulate more accurate flow forecast for RDAPS numerical weather forecast with improved daily scenario including time resolution, which is able to accumulate 3 hours rainfall or continuous simulation estimation.

• Atmosphere
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• v.24 no.2
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• pp.207-223
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• 2014

The bogussing method was further developed by incorporating the asymmetric component into the symmetric bogus tropical cyclone of the Structure Adjustable Balanced Vortex (SABV). The asymmetric component is separated from the disturbance field associated with the tropical cyclone by establishing local polar coordinates whose center is the location of the tropical cyclone. The relative importance of wave components in azimuthal direction was evaluated, and only two or three wave components with large amplitude are added to the symmetric components. Using the Weather Research and Forecast model (WRF), initialized with the asymmetric bogus vortex, the track and central pressure of tropical cyclones were predicted. Nine tropical cyclones, which passed over Korean peninsula during 2010~2012 were selected to assess the effect of asymmetric components. Compared to the symmetric bogus tropical cyclone, the track forecast error was reduced by about 18.9% and 17.4% for 48 hours and 72 hours forecast, while the central pressure error was not improved significantly. The results suggest that the inclusion of asymmetric component is necessary to improve the track forecast of tropical cyclones.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.631-641
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• 2012

In this study, satellite data (MTSAT-1R), a numerical weather prediction model, RDAPS (Regional Data Assimilation and Prediction System) output, ground weather station data, and artificial neural networks were used to improve the accuracy of summer rainfall forecasts. The developed model was applied to the Seoul station to forecast the rainfall at 3, 6, 9, and 12-hour lead times. Also to reflect the different weather conditions during the summer season which is related to the frontal precipitation and the cyclonic precipitation such as Jangma and Typhoon, the neural network models were formed for two different periods of June-July and August-September respectively. The rainfall forecast model was trained during the summer season of 2006 and 2008 and was verified for that of 2009 based on the data availability. The results demonstrated that the model allows us to get the improved rainfall forecasts until lead time of 6 hour, but there is still a large room to improve the rainfall forecast skill.

• Journal of the military operations research society of Korea
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• v.29 no.2
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• pp.26-44
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• 2003

This study Is to forecast the damage of smallpox as a biological weapon and to measure the effect of potential responses (quarantine, vaccination and cure) to the spread of smallpox infection when a smallpox bioterrorism attack occurs. We designed the smallpox spreading simulation model through the literature study on a basis of some existing infectious disease models such as SIR, SEIR model by using Vensim program. In order to evaluate the performance of responses to smallpox, we measure the total infection population, infection sustaining duration, average infection rate and the infection spreading behavior of the smallpox. This study can help those who are related to the bioterrorism forecast the present and possible demage, and take more effective actions for minimizing the damage by smallpox bioterrorism.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.329-330
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• 2015

From the results of previous my paper [10] in 2015 year of economic and electrical power storage research conference in Naju, this paper describes an application of autoregressive and moving average (ARMA) model to forecast hourly average wind speed (HAWS) in Jeju island. The models are used to build up short-term forecast of hourly average wind speed by the weighted sum of previous wind speed values.