• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.173-185
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• 1999

The purpose of this study is to develope a forecasting model to implement short-term Congestion Management Program (CMP) based on TDM strategies in Seoul. The CMP is composed of three elements: 1) setting a goal of short-term traffic management. 2) developing a model to forecast the impacts of TDM alternatives, and 3) finding TDM measures to achieve the goal To Predict the impacts of TDM alternatives, a model called SECOMM (SEoul COngestion Management Model) is developed. The model assumes that trip generation and distribution are not changing in a short term, and that only mode split and traffic assignment are affected by TDM. The model includes the parameter values calibrated by a discrete mode choice model, and roadway and transit networks with 1,020 zones. As a TDM measure implement, it affects mode choice behavior first and then the speeds of roadway network. The chanced speed again affects the mode choice behavior and the roadway speeds. These steps continue until the network is equilibrated. The study recommends that CMP be introduced in Seoul, and that road way conditions be monitored regularly to secure the prediction accuracy of SECOMM. Also, TDM should be the major Policy tools in removing short-term congestion problems in a big city.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.2
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• pp.65-73
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• 2016

We estimated the averaged maximum incidences of bacterial canker at suitable sites for kiwifruit cultivation in 2020s and 2050s using D-PSA-K model with RCP4.5 and RCP8.5 climate change scenarios. Though there was a little difference between the estimation using RCP4.5 and that using RCP8.5, the estimated maximum disease incidences were more than 75% at all the suitable sites in Korea except for some southern coastal areas and Jeju island under the assumption that there are a plenty of infections to cause the symptoms. We also analyzed the intermediate and final outputs of D-PSA-K model to find out the trends on the change in disease incidence affected by climate change. Whereas increase of damage to kiwifruit canes in a non-frozen environment caused by bacterial canker was estimated at almost all the suitable sites in both the climate change scenarios, rate of necrosis increase caused by the bacterial canker pathogen in a frozen environment during the last overwintering season was predicted to be reduced at almost all the suitable sites in both the climate change scenarios. Directions of change in estimated maximum incidence varied with sites and scenarios. Whereas the maximum disease incidence at 3.14% of suitable sites for kiwifruit cultivation in 2020s under RCP4.5 scenario was estimated to increase by 10% or more in 2050s, the maximum disease incidence at 25.41% of the suitable sites under RCP8.5 scenario was estimated so.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.11-19
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• 2014

This study is analyze future climate and land cover change affects behaviors for amount of streamflow and sediment discharge within basin. We used the climate forecast data in RCP 4.5 and 8.5 (2011-2100) which is opposite view for each other among RCP scenarios that are discussed for 5th report for IPCC. Land cover map built based on a social economic storyline in RCP 4.5/8.5 using Logistic Regression model. In this study we set three scenarios: one scenario for climate change only, one for land cover change only, one for Last both climate change and land cover change. It simulated amount of streamflow and sediment discharge and the result showed a very definite change in the seasonal variation both of them. For climate change, spring and winter increased the amount of streamflow while summer and fall decreased them. Sediment showed the same pattern of change steamflow. Land cover change increases the amount of streamflow while it decreases the amount of sediment discharge, which is believed to be caused by increase of impervious Surface due to urbanization. Although land cover change less affects the amount of streamflow than climate change, it may maximize problems related to the amount of streamflow caused by climate change. Therefore, it's required to address potential influence from climate change for effective water resource management and prepare suitable measurement for water resource.

• Atmosphere
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• v.26 no.2
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• pp.347-356
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• 2016

Radiosonde is an observation equipment that measures pressure (geopotential height), temperature, relative humidity and wind by being launched up from the ground. Radiosonde data which serves as an important element of weather forecast and research often causes a bias in a model output due to accuracy and sensitivity between the different manufacturers. Although Korean Meteorological Administration (KMA) and several institutes have conducted routine and intensive radiosonde observations, very few studies have been done before on the characteristics of radiosonde performance. Analyzing radiosonde observation data without proper understanding of the unique nature of those sensors may lead to a significant bias in the analysis of results. To evaluate performance and reliability of radiosonde, we analyzed the differences between two sensors made by the different manufacturers, which have been used in the campaign of Experiment on Snow Storm At Yeongdong (ESSAY). We improved a couple of methods to launch the balloon being attached with the sensors. Further we examined cloud-layer impacts on temperature and humidity differences for the analysis of both sensors' performance among various weather conditions, and also compared daytime and nighttime profiles to understand temporal dependence of meteorological sensors. The overall results showed that there are small but consistent biases in both temperature and humidity between different manufactured sensors, which could eventually secure reliable precisions of both sensors, irrespective of accuracy. This study would contribute to an improved sounding of atmospheric vertical states through development and improvement of the meteorological sensors.

• Atmosphere
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• v.26 no.1
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• pp.19-33
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• 2016

Water vapor in the atmosphere is an important element that generates various meteorological phenomena and modifies a hydrological cycle. In general, the Yeongdong region has a lot of snow compared to the other regions in winter due to the complex topography and an adjacent East Sea. However, the phase change from water vapor to ice cloud and further snowfall has little been examined in detail. Therefore, in this study, we investigated phase change of liquid water in terms of a quantitative budget as well as time lag of water vapor conversion to snowfall in the ESSAY (Experiment on Snow Storms At Yeongdong) campaign that had been carried out from 2012 to 2015. First, we classified 3 distinctive synoptic patterns such as Low Crossing, Low Passing, and Stagnation. In general, the amount of water vapor of Low Crossing is highest, and Low Passing, Stagnation in order. The snowfall intensity of Stagnation is highest, whereas that of Low Crossing is the lowest, when a sharp increase in water vapor and accordingly a following increase in precipitation are shown with the remarkable time lag. Interestingly, the conversion rate of water vapor to snowfall seems to be higher (about 10%) in case of the Stagnation type in comparison with the other types at Bukgangneung, which appears to be attributable to significant cooling caused by cold surge in the lower atmosphere. Although the snowfall is generally preceded by an increase in water vapor, its amount converted into the snowfall is also controlled by the atmosphere condition such as temperature, super-saturation, etc. These results would be a fundamental resource for an improvement of snowfall forecast in the Yeongdong region and the successful experiment of weather modification in the near future.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.47-54
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• 2004

Recently, a large reduction in domestic aviation demand had roughly shown in the range between 34% and 75% in east central and western corridor of Korea. The reasons for the drop in air traffic demand were the provisioning of several new highway serveces and the national economic difficulties. Since April 2004, moreover, the Korea Train Express(KTX) was operated between Seoul and Daegu in the first phrase of 293Km in KTX operational distance and 258Km in air route distance. The operation of KTX significantly impacted air traffic volume, particularly on the overlapped air routes with KTX routes. This study analyzed the effects on air traffic demand in accordance with the opening of KTX by applying the Stated Preference (SP) survey method, the survey conducted prior to 8 months of the KTX initiative. Also, the comparison of the decreased demand forecast by SP analysis and actual revealed traffic volume during two months service after inauguration of KTX was conducted. The Seoul-Daegu route was analysed using the 3 variables considered access and egress time, fare rate, operational frequency. The result obtained from the analysis showed that air users would be preferred only 14%. Comparatively, however, the actual revealed air passengers after the opening KTX were remained 28%, The less "decreased demand" was caused by the instability of the KTX's operation in the initial stage. Therefore, small numbers of passenger were preferable to airservices rather than high speed railroad service.

• Journal of Climate Change Research
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• v.6 no.3
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• pp.233-241
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• 2015

In 2014, the United Nations Framework Convention on Climate Change (UNFCCC) agreed to submit the Intended Nationality Determined Contributions (INDCs) at the conference of parties held in Lima, Peru. Then, the South Korean government submitted the INDCs including GHGs reduction target and reduction potential on July, 2015. The goal of this study is to predict GHGs emission and to analyze reduction potential in agricultural sector of Korea. Activity data to estimate GHGs emission was forecast by Korea Agricultural Simulation Model (KASMO) of Korea Rural Economic Institute and estimate methodology was taken by the IPCC and guideline for MRV (Measurement, Reporting and Verification) of national greenhouse gases statistics of Korea. The predicted GHGs emission of agricultural sectors from 2021 to 2030 tended to decrease due to decline in crop production and its gap was less after 2025. Increasing livestock numbers such as sheep, horses, swine, and ducks did not show signigicant impact the total GHGs emission. On a analysis of the reduction potential, GHGs emission was expected to reduce $253Gg\;CO_{2-eq}$. by 2030 with increase of mid-season water drainage area up to 95% of total rice cultivation area. The GHGs reduction potential with intermittent drainage technology applied to 10% of the tatal paddy field area, mid-drainage and no organic matter would be $92Gg\;CO_{2-eq}$. by 2030.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1101-1117
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• 2018

The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.1-16
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• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.85-91
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• 2021

In contrast to standard train tracks, tramlines are often set along public roads, with trams running among pedestrians and other vehicles. In some cities and towns, trams and buses share the same routes and stations. Under the current investment appraisal system, trams are classified into light rail when predicting traffic demand and calculating benefits, but in the case of non-capital areas, it is notable that the origin-destination and transit lines of buses are not provided in the Korea Transport Database distribution data. Due to this problem, it is difficult to reflect proper mode changing behaviors between route buses and trams. This study examines the impact on tramlines of bus routes that are not currently considered in non-capital areas. Following an analysis of the effect of tram projects according to whether bus routes are considered or not, an improvement in methodology is proposed. Through this study, it is expected that the investment appraisal system for the planning of new tramlines will be improved in the future.