• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.47-54
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• 2003

Climate of Mongolia is a driven force on natural conditions as well as socio-economic development of the country. Due to the precariousness of climate conditions and traditional economic structure, natural disasters, specially disasters of meteorological and hydrological origin, have substantial effect upon the natural resources and socio-economic sectors of Mongolia. Mongolia's climate is characterized by high variability of weather parameters, and high frequency and magnitude of extreme climate and weather events. During the last few decades, climate of the country is changing significantly under the global warning. The annual mean air temperature for the whole territory of the country has increased by $1.56^{\circ}C$ during the last 60 years,. The winter temperature has increased by $1.56^{\circ}C$. These changes in temperature are spatially variable: winter warming is more pronounced in the high mountains and wide valleys between the mountains, and less so in the steppe and Gobi regions. There is a slight trend of increased precipitation during the last 60 years. The average precipitation rate is increased during 1940-1998 by 6%. This trend is not seasonally consistent: while summer precipitation increased by 11 %, spring precipitation decreased by 17. The climate change studies in Mongolia show that climate change will have a significant impact on natural resources such as water resources, natural rangeland, land use, snow cover, permafrost as well as major economic activities of arable farming, livestock, and society (i.e. human health, living standards, etc.) of Mongolia. Therefore, in new century, sustainable development of the country is defined by mitigating and adaptation policies of climate change. The objective of the presentation is to contribute one's idea in the how to reflect the changes in climate system and weather extreme events in the country's sustainable development concept.

• Wind and Structures
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• v.26 no.3
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• Journal of Ecology and Environment
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• v.47 no.2
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• pp.35-41
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• 2023

Background: Several species of amphibians in agricultural areas are often infected with ranaviruses; however, the biological or ecological factors that cause this infection are not well understood. In this study, we investigated whether local tadpole density, Gosner developmental stage, and weather conditions affected ranavirus infection in Dryophytes japonicus tadpoles in rice paddies over three months. Results: During the study, eight samplings were undertaken between June 6 and August 21, 2022. No die-off of tadpoles occurred, but 20 of 110 tadpoles (18.8%) were found to be infected with ranavirus. The tadpole density at the sampling site and Gosner stage of the sampled tadpoles were not related to the daily ranavirus infection rate. The mean daily highest temperature during the two weeks prior to the sampling date and the mean daily lowest and highest temperatures during the week prior to the sampling date were negatively related to the daily infection rate. Conclusions: Our results suggest that low and extreme temperatures caused by flooding and draining of paddy fields or climate change in summer could be a significant risk factor for ranavirus infection in summer-breeding frogs in agricultural areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.513-521
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• 2008

The objective of this study is the evaluation of the impact on the construction condition due to historical observation data and IPCC SRES A2 climate change scenario. For this purpose, daily precipitation and daily mean temperature data which have been observed over the past 30 years by Korea Meteorological Administration are collected and applied. Also, A2 scenarios during 2011~2040 and 2051~2080 are used for this analysis. According to the results of trend analyses on annual precipitation and annual mean temperature, they are on the increase mostly. The available working day and the day occurred an extreme event are used as correlation indices between climate factor and construction condition. For the past observation data, linear regression and Mann-Kendall test are used to analyze the trend on the correlation index. As a result, both working day and extreme event occurrence day are increased. Likewise, for the future, variation analysis showed the similar result to that of the past and the occurrence frequency of extreme events is increased obviously. Therefore, we can project to increase flood damage potential on the construction site by climate change.

• Proceedings of the Korean Quaternary Association Conference
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• 2004.06a
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• pp.29-29
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• 2004

Long term observational analysis by climatologists has confirmedthat the global warming is no longer a topic of debate among scientists andpolicy makers. According to the report of IPCC-2001 (Intergovernmental Panelon Climate Change), the global mean surface air temperature is increasinggradually. The reported increase of mean temperature is by 0.6 degree in the end of twentieth century. This could represent severe threat for propertylosses especially due to increase in the number of extreme weather arising out of global warming. period of model integration from 2001 to 2100 using output of ECHAM4/HOPE-G of Max Planet Institute of Meteorology (MPI) for IPCC SRES (Special Report on Emission Scenarios). The main results of this study indicate increase of surface air temperature by 6.20C and precipitation by 2.6% over Korea in the end of 21st century. Simulation results also show that there is increase in daily maximum and minimum temperatures while decrease in diurnal temperature range (DTR). DTR changes are diminished mainly due to relatively rapid increase of daily minimum temperature than that of daily maximumtemperature. It has been observed that increase in precipitation amount anddecrease in the number of rainy days lead to increase of pre precipitationintensity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.69-74
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• 2015

To analyze quantitatively environmental characteristics of cultivation area of citrus, Satsuma mandarin (Citrus unshiu Marc.), we made digital maps of environmental elements such as topography and climate. Elevation, degree of slope, and slope aspect were selected as elements of topological environment, and the annual mean air temperature, annual total precipitation, mean air temperature on January, extreme value of daily minimum air temperature, and the number of days below $-5^{\circ}C$ were selected as elements of climatic environments. The grid values of 8 environmental elements were extracted by shape of citrus farm area and analyzed distribution patterns. We can determine 3 agroclimatic criteria for growing Satsuma mandarin as over $14.5^{\circ}C$ of annual mean air temperature, over $-10.0^{\circ}C$ of extreme value of daily minimum air temperature, and less 5 days of below $-5^{\circ}C$ of daily minimum air temperature.

• Atmosphere
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• v.34 no.2
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• pp.123-138
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• 2024

Using 18 multi-model-based a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) climate change scenarios, future changes in temperature and warmth index on the Korean Peninsula in the 21st century (2011~2100) were analyzed. In the analysis of the current climate (1981~2010), the ensemble averaged model results were found to reproduce the observed average values and spatial patterns of temperature and warmth index similarly well. In the future climate projections, temperature and warmth index are expected to rise in the 21st century compared to the current climate. They go further into the future and the higher carbon scenario (SSP5-8.5), the larger the increase. In the 21st century, in the low-carbon scenario (SSP1-2.6), temperature and warmth index are expected to rise by about 2.5℃ and 24.6%, respectively, compared to the present, while in the high-carbon scenario, they are expected to rise by about 6.2℃ and 63.9%, respectively. It was analyzed that reducing carbon emissions could contribute to reducing the increase in temperature and warmth index. The increase in the warmth index due to climate change can be positively analyzed to indicate that the effective heat required for plant growth on the Korean Peninsula will be stably secured. However, it is necessary to comprehensively consider negative aspects such as changes in growth conditions during the plant growth period, increase in extreme weather such as abnormally high temperatures, and decrease in plant diversity. This study can be used as basic scientific information for adapting to climate change and preparing response measures.

• Fisheries and Aquatic Sciences
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• v.26 no.11
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• pp.639-648
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• 2023

The sea surface temperature (SST) and ocean heat content in the Korea Waters are gradually increased. Especially the increasing trend of annual mean SST in the Korea Water is higher about 2.6 times than the global mean during past 55 years (1968-2022). Before 2010s, the increasing trend of SST was led by winter season in the Korea Waters. However, this pattern was clearly changed after 2010s. The increasing trend of SST during summer is higher about 3.9 times than during winter after 2010s. We examine the long-term variations of several ocean and climate factors to understand the reasons for the long-term pattern changes of SST between summer and winter in recent. Tsushima warm current was significantly strengthened in summer compare to winter during past 33 years (1986-2018). The long-term patterns of Siberian High and East Asian Winter Monsoon were definitely changed before and after early- or mid-2000s. The intensities of those two climate factors was changed to the increasing trend or weakened decreasing trend from the distinctive decreasing trend. In addition, the extreme weather condition like the heatwave days and cold spell days in the Korea significantly increased since mid- or late-2000s. From these results, we can consider that the occurrences of frequent and intensified marine heatwaves during summer and marine cold spells during winter in the Korea Waters might be related with the long-term pattern change of SST, which should be caused by the long-term change of climate factors and advection heat, in a few decade.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.585-596
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• 2013

The objective of this study is to evaluate the hybrid downscaling method combined Step-Wise Scaling (SWS) method with Regional Climate Model (RCM) simulation data for climate change impact study on hydrology area. The SWS method is divided by 3 categories (extreme event, dry event and the others). The extreme events, wet-dry days and the others are corrected by using regression method, quantile mapping method, mean & variance scaling method. The application and evaluation of SWS method with 3 existing and popular statistical techniques (linear scaling method, quantile mapping method and weather generator method) were performed at the 61 weather stations. At the results, the accuracy of corrected simulation data by using SWS are higher than existing 3 statistical techniques. It is expected that the usability of SWS method will grow up on climate change study when the use of RCM simulation data are increasing.