• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.331-337
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• 2016

Water vapor is main absorption factor of outgoing longwave radiation. So, it is essential to monitoring the changes in the amount of water vapor and to understanding the causes of such changes. In this study, we monitor temporal variability of Total Precipitable Water (TPW) which observed by satellite. Among climate variables, precipitation play an important part to analyze temporal variability of water vapor because it is produced by water vapor. And El $Ni{\tilde{n}}o$ is one of climate variables which appear regularly in comparison with the others. Through them, we analyze relationship between temporal variability of TPW and climate variable. In this study, we analyzed long-term change of TPW from Moderate-Resolution Imaging Spectroadiometer (MODIS) data and change of precipitation in middle area of Korea peninsula quantitatively. After these analysis, we compared relation of TPW and precipitation with El $Ni{\tilde{n}}o$. The aim of study is to research El $Ni{\tilde{n}}o$ has an impact on TPW and precipitation change in middle area of Korea peninsula. First of all, we calculated TPW and precipitation from time series analysis quantitatively, and anomaly analysis is performed to analyze their correlation. As a result, TPW and precipitation has correlation mostly but the part had inverse correlation was found. This was compared with El $Ni{\tilde{n}}o$ of anomaly results. As a result, TPW and precipitation had inverse correlation after El $Ni{\tilde{n}}o$ occurred. It was found that El $Ni{\tilde{n}}o$ have a decisive effect on change of TPW and precipitation.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.606-612
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• 2019

In this study, to estimate the occurrence of frost that has a negative effect on th growth of crops, we constructed to the statistical model. We factored such various meteorological elements as the minimum temperature, temperature at 18:00, temperature at 21:00, temperature at 24:00, average wind speed, wind speed at 18:00, wind speed at 21:00, amount of cloud, amount of precipitation within 5 days, amount of precipitation within 3 days, relative humidity, dew point temperature, minimum grass temperature and ground temperature. Among the diverse variables, the several weather factors were selected for frost occurrence estimation model using statistical methods: T-test, Variable importance plot of Random Forest, Multicollinearity test, Akaike Informaiton Criteria, and Wilk's Lambda values. As a result, the selected meteorological factors were the amount of cloud, temperature at 24:00, dew point temperature, wind speed at 21:00. The accuracy of the frost occurrence estimation model using Random Forest was 70.6%. When it applied to the main production areas of vegetables, a estimation accuracy of the model was 65.2 and 78.6%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.312-319
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• 2013

Our understanding of the sensitivities of crop responses to changes in carbon dioxide, temperature, and water is limited, which makes it difficult to fully utilize crop models in assessing the impact of climate change on future agricultural production. Genetic coefficients of CERES-Barley model for major domestic cultivars in South Korea (Olbori at Suwon, Albori at Milyang, Saessalbori at Iksan, and Samdobori at Jinju) were estimated from the observed data for daily weather and field trials for more than 10 years by using GenCalc in DSSAT. Data from 1997-2002 annual crop status report (Rural Development Administration, RDA) were used to validate the crop coefficients. The sitecalibrated CERES-Barley model was used to perform crop growth simulation with the 99 treatments of step change combinations in temperature, precipitation and carbon dioxide concentration with respect to the baseline climate (1981-2010) at four sites. The upper boundary corresponds to the 2071-2100 climate outlook from the RCP 8.5 scenario. The response surface of grain yield showed a distinct pattern of model behavior under the combined change in environmental variables. The simulated grain yield was most sensitive to $CO_2$ concentration, least sensitive to precipitation, and showing a variable response to temperature depending on cultivar. The emulated impacts of response surfaces are expected to facilitate assessment of projected climate impacts on a given cultivar in South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.298-306
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• 2016

Planting date shift is one of the means of adapting to climate change in Kimchi Cabbage growers in major production areas in Korea. This study suggests a method to estimate the potential yield of Kimchi Cabbage based on daily temperature accumulation during the growth period from planting to maturity which is determined by a plant phenology model tuned to Kimchi Cabbage. The phenology model converts any changes in the thermal condition caused by the planting date shift into the heat unit accumulation during the growth period, which can be calculated from daily temperatures. The physiological maturity is estimated by applying this model to a variable development rate function depending either on growth or heading stage. The cabbage yield prediction model (Ahn et al., 2014) calculates the potential yield of summer cabbage by accumulating daily heat units for the growth period. We combined these two models and applied to the 1km resolution climate scenario (2000-2100) based on RCP8.5 for South Korea. Potential yields in the current normal year (2001-2010) and the future normal year (2011-2040, 2041-2070, and 2071-2100) were estimated for each grid cell with the planting dates of July 1, August 1, September 1, and October 1. Based on the results, we divided the whole South Korea into 810 watersheds, and devised a three - dimensional evaluation chart of the time - space - yield that enables the user to easily find the optimal planting date for a given watershed. This method is expected to be useful not only for exploring future new cultivation sites but also for developing cropping systems capable of adaptation to climate change without changing varieties in existing production areas.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1342-1344
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• 2002

Wind is a significant and valuable renewable energy resource. It is safe and abundant and can make an important contribution to future clean, sustainable and diversified electricity supplies. Unlike other sources of energy, wind does not pollute the atmosphere nor create any hazardous waste. In some countries wind energy is already competitive with fossil and nuclear power even without accounting for the environmental benefits of wind power. The cost of electricity from conventional power stations does not usually take full account of its environmental impact (acid rain, oil slick clean up, the effects of climate change, etc). In this paper, a transient phenomenon simulation method for Wind Power Generation System(WPGS) under real weather conditions has been proposed. The simulation method is expected to be able to analyze easily under various conditions with considering the sort of wind turbine, the capacity of system and the converter system. Wind turbine connected to the synchronous generator and power converter was simulated.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.425-433
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• 2009

Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.

• The Journal of Fisheries Business Administration
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• v.44 no.3
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• pp.77-84
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• 2013

While some steps in laver aquaculture production can be controlled artificially to a certain extent, the culturing process is largely affected by natural factors, such as the characteristics of seawater, climatic and oceanographic conditions, etc. This study aims to find a direct relationship between climatic and oceanographic factors (water temperature, air temperature, salinity, rainfall, sunshine duration and wind speed) and laver aquaculture production in Wando region, the biggest aquaculture production area of laver, located in the southwest coast of Korea using a multiple regression analysis. Despite the small sample size of a dependent variable, the goodness of model fit appeared acceptable. In addition, the R-squared value was 0.951, which means that the variables were very explanatory. Model results indicated that duration of sunshine, temperature, and rainfall during the farming period from the end of September to the end of April would be important factors affecting significantly to the laver aquaculture production.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.700-707
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• 2009

The application of renewable energy in electric power systems is growing rapidly in order to make provision for the inequality of the climate, the dwindling supplies of coal, oil and natural gas and a further rise in oil prices. Solar cell generators(SCG) is one of the fastest growing renewable energy. This paper presents a methodology on probabilistic production cost simulation of a power system including SCGs. The generated power by SCGs is variable due to the random variation of solar radiation. In order to solve this problem, the SCGs is modeled as multi-state operational model in this paper. Probabilistic production cost of a power system can be calculated by proposed method considering SCGs with multi-state. The results show that the impacts of SCGs added to a power system can be analyzed in view point of production cost using the proposed method.

• Journal of Korean Society of Rural Planning
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• v.17 no.3
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• pp.1-13
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• 2011

This study aims to analyse the landscape ecological characteristics of 39 rural villages in Korea and classify them according to their characteristics. After producing a land-use map of rural villages, this study quantified the landscape ecological characteristics of the subject sites as 18 landscape indexes using Fragstats. By applying the landscape index as a variable, selecting 4 factor through principal component analysis and conducting a cluster analysis, it classified them into 3 groups. Rural villages of Korea have their unique types of land-use due to the influence of physical environment such as geography, climate and ecology as well as the social and cultural influence, and the characteristics of land-use can be analysed and classified using the landscape index, the quantified landscape ecological characteristics.

• Journal of Ecology and Environment
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• v.29 no.2
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• pp.171-173
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• 2006

A species of moss (Musci) is observed on the Matanuska Glacier of Alaska in the middle of summer. The life cycle of the moss is perfectly observed. This is very rare and special because the environment is completely glacial and barren of plants. Matanuska is a gigantic glacier formed about 18,000 years ago in the Palmer region near Anchorage. It has a dimension of 27 miles in length and 4 miles in width. The glacier is located in the region between Anchorage and Mount McKinley. This huge glacier carved the Matanuska valley thousands of years ago. The mighty glacier also forms the Matanuska River. The summer weather is very changeable throughout the day: warm, cold, sunshiny, windy, cloudy, rainy, snowy, foggy, etc. The Arctic clouds move very quickly and create variable climates. So there are four seasons even in one day during the summer period of this region.