• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.27-32
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• 2003

Atmospheric and oceanic numerical models are usually initial-value and/or boundary-value problems. Change in either initial or boundary conditions leads to a variation of model solutions. Much of the predictability research has been done on the response of model behavior to an initial value perturbation. Less effort has been made on the response of model behavior to a boundary value perturbation. In this study, we use the latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) to study the model uncertainty to tiny SST errors. The results show the urgency to investigate the second kind predictability problem for the climate models.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.270-271
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• 2019

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.31-32
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• 2020

Concrete changes its internal moisture distribution depending on the external environment, and changes in the condition of the material's interior over time affect the performance of the concrete. These effects are closely related to the long-term behavior and durability of concrete, and the degree of deterioration varies from climate to climate in each region. In this study, we use actual climate data from each region with distinct climates. A multi-physical analysis based on the method was conducted to predict the difference and degree of deterioration rate by climate.

• Atmosphere
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• v.33 no.2
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• pp.73-104
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• 2023

Over the past 60 years, Korean numerical weather prediction (NWP) has advanced rapidly with the collaborative effort between the science community and the operational modelling center. With an improved scientific understanding and the growth of information technology infrastructure, Korea is able to provide reliable and seamless weather forecast service, which can predict beyond a 10 days period. The application of NWP has expanded to support decision making in weather-sensitive sectors of society, exploiting both storm-scale high-impact weather forecasts in a very short range, and sub-seasonal climate predictions in an extended range. This article gives an approximate chronological account of the NWP over three periods separated by breakpoints in 1990 and 2005, in terms of dynamical core, physics, data assimilation, operational system, and forecast application. Challenges for future development of NWP are briefly discussed.

• Ocean and Polar Research
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• v.35 no.2
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• pp.123-125
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• 2013

According to the Intergovernmental Panel on Climate Change (IPCC), ocean warming and acidification are accelerating as a result of the continuous increase in atmospheric $CO_2$. This may affect the function and structure of marine ecosystems. Recently, changes in marine environments/ecosystems have been observed (increase in SST, decrease in the pH of seawater, northward expansion of subtropical species, etc.) in Korean waters. However, we still don't understand well how climate change affects these changes and what can be expected in the future. In order to answer these questions with regard to Korean waters, the project named 'Assessment of the impact of climate change on marine ecosystems in the South Sea of Korea' has been supported for 5 years by the Ministry of Oceans and Fisheries and is scheduled to end in 2013. This project should provide valuable information on the current status of marine environments/ecosystems in the South Sea of Korea and help establish the methodology and observation/prediction systems to better understand and predict the impact of climate/marine environment changes on the structure and function of marine ecosystems. This special issue contains 5 research and a review articles that highlight the studies carried out during 2012-2013 through this project.

• Ocean and Polar Research
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• v.40 no.1
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• pp.37-48
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• 2018

The purpose of this study is to assess the climate change vulnerability of coastal and offshore fisheries in the South Sea of Korea using the RCP scenarios. Based on the vulnerability defined by IPCC, the indicator-based method was applied. Exposure indicator was calculated through weighted sum of the sea temperature and salinity forecasted by National Institute of Fisheries Science, and the weights were obtained from the time-space distribution of each fisheries. Sensitivity indicator was determined by applying the catch proportion of fisheries to the sensitivity of fish species. The adaptive capacity was measured by survey of fisheries which represent the ability of the fishermen well. As a result of summarizing the above indicators, vulnerability of coastal fisheries is higher than offshore fisheries. This shows that measures against coastal fisheries are needed. In addition, the results of each scenario are somewhat different, so it is considered that accurate prediction of climate change is important for adaptation measures.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.287-295
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• 2017

This paper provides a mathematical approach for estimating flood risks due to the effects of climate change by developing a one dimensional (1D) hydraulic model for the mountainous river reaches located close to the Yeongwol thermal power plant. Input data for the model, including topographical data and river discharges measured every 10 minutes from July $1^{st}$ to September $30^{th}$, 2013, were imported to a 1D hydraulic model. Climate change scenarios were estimated by referencing the climate change adaptation strategies of the government and historical information about the extreme flood event in 2006. The down stream boundary was determined as the friction slope, which is 0.001. The roughness coefficient of the main channels was determined to be 0.036. The results show the effectiveness of the riverbed widening strategy through the six flooding scenarios to reduce flood depth and flow velocity that impact on the power plant. In addition, the impact of upper Namhan River flow is more significant than Dong River.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.38-38
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• 2023

Pleikrong reservoir with a concrete gravity dam that impound more than 1 billion cubic meter storage volume is one of the largest reservoir in Central Highland of Vietnam. Sedimentation is a major problem in this area and it becomes more severe due to the effect of climate change. Over time, it gradually reduces the reservoir storage capacity affecting to the reliability of water and power supply. This study aims to integrate the soil and water assessment tool (SWAT) model with 14 bias-corrected GCM/RCM models under two emissions scenarios, representative concentration pathway (RCP) 4.5 and 8.5 to estimate sediment inflow to Pleikrong reservoir in the long term period. The result indicated that the simulated total amount of sediment deposited in the reservoir from 2010 to 2018 was approximately 39 mil m³ which is a 17% underestimate compared with the observed value of 47 mil m³. The results also show the reduction in reservoir storage capacity due to sedimentation ranges from 25% to 62% by 2050, depending on the different climate change models. The reservoir reduced storage volume's rate in considering the impact of climate change is much faster than in the case of no climate change. The outcomes of this study will be helpful for a sustainable and climate-resilient plan of sediment management for the Pleikrongreservoir.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.709-719
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• 2022

Recently, as the importance of environmental protection has emerged, interest in new and renewable energy is also increasing worldwide. In particular, the solar energy sector accounts for the highest production rate among new and renewable energy in Korea due to its infinite resources, easy installation and maintenance, and eco-friendly characteristics such as low noise emission levels and less pollutants during power generation. However, although climate prediction is essential since solar power is affected by weather and climate change, solar radiation, which is closely related to solar power, is not currently forecasted by the Korea Meteorological Administration. Solar radiation prediction can be the basis for establishing a reasonable new and renewable energy operation plan, and it is very important because it can be used not only in solar power but also in other fields such as power consumption prediction. Therefore, this study was conducted for the purpose of improving the accuracy of solar radiation. Solar radiation was predicted by a total of three weather variables, temperature, humidity, and cloudiness, and solar radiation outside the atmosphere, and the results were compared using various models. The CatBoost model was best obtained by fitting and comparing the Boosting series (XGB, CatBoost) and RNN series (Simple RNN, LSTM, GRU) models. In addition, the results were further improved through Time series cross-validation.