본 연구는 머신러닝 기법을 토대로 15개 환경 변수를 활용하여 소나무재선충병의 위험지역 분포를 예측하였다. 연구는 최대 엔트로피 모델을 머신러닝 기법으로 활용하였고, 연구 지역은 경주이며 연구 기간은 2018∼2020년이다. 모델의 평가에는 AUC(area under the curve)를 이용하였다. 연구 지역에서 소나무재선충병의 감염목 핵심 분포 지역은 2018년 대비 2019년과 2020년에 각각 2.5배와 4.7배 확대되었다. 소나무재선충병의 감염목 분포 추정 모델의 AUC는 모든 해에 최소 0.86 이상이었다. 모델에서 가장 중요한 변수는 직전 해의 감염목 근접도 이었다. 지형과 도로와의 인접성, 목조건물 인접성, 5월 평균 기온도 중요한 변수이었다. 인간 활동과 매개충의 생장 환경이 소나무재선충병의 공간적 분포에 중요한 역할을 한다는 것을 의미한다. 나아가 연구의 결과는 감염목 분포 정보의 지속적인 구축과 공유가 소나무재선충병 예방을 위한 정책과 연구에 중요하다는 것을 시사한다.

Corporate philanthropic activities, such as charitable donations, have become one of the main business practices worldwide. However, academicians have paid relatively scant attention to verifying the effectiveness of corporate philanthropy (CP) in terms of a firm’s performance. Therefore, this study aims to reveal the influence of CP on consumer loyalty that leads to a firm’s ultimate financial success. In addition, this study aims to investigate mechanisms through which CP influences consumer loyalty, as yet largely unexplored field. Results reveal that CP has an impact on consumer loyalty that is sequentially mediated by gratitude, trust, and finally commitment. This research contributes to expanding the scope of CP research verifying the effectiveness of CP on consumer loyalty.

한국의 환경부에서 제작하여 배포한 국가 토지피복도(2000, 2009년)는 수문, 생태, 자연재해 취약성 평가 등 다양한 연구의 기초정보로 활용되고 있다. 하지만 2000년 국가 토지피복도의 정확도가 부족하기 때문에 국가토지피복도를 활용하여 토지피복 변화를 분석하는데 어려움이 있다. 이에 본 연구는 통계연보의 지목 자료와 환경부의 2009년 토지피복도를 활용하여 2000년 토지피복별 면적 추정 방법을 연구하였다. 이 연구는 본 연구에서 설계한 방법의 타당성을 평가하기 위해 그 방법을 덕유산 인근에 위치한 6개 읍·면의 2000년 토지피복별 면적을 추정하는데 적용하였다. 연구 결과 본 연구에서 추정한 2000년 토지피복별 면적은 통계연보와 전반적으로 6.12km2의 차이를 보였다. 이에 비해 토지피복도를 활용하여 산정한 토지피복별 면적은 통계연보와 전반적으로 13.10km2의 차이를 보였다. 토지피복도만을 이용하여 분석한 2000～2009년 토지피복별 면적 변화 경향은 통계연보와 54.2% 일치하였다. 반면에 본 연구에서 추정한 변화 경향은 통계연보와 95.8% 일치하였다. 이와 같은 결과는 본 연구에서 제안하는 방법이 토지피복도만을 활용했을 때에 비해 2000년 토지피복별 면적을 추정하는데 유용할 수 있다는 것을 보여주었다.

The basic building block of solar filaments/prominences is thin threads of cool plasma. We have studied the spectral properties of velocity threads, clusters of thinner density threads moving together, by analyzing a sequence of Hα images of a quiescent filament. The images were taken at Big Bear Solar Observatory with the Lyot filter being successively tuned to wavelengths of -0.6, -0.3, 0.0, +0.3, and +0.6 Åfrom the centerline. The spectra of contrast constructed from the image data at each spatial point were analyzed using cloud models with a single velocity component, or three velocity components. As a result, we have identified a couple of velocity threads that are characterized by a narrow Doppler width (ΔλDÅ=0.27), a moderate value of optical thickness at the Hα absorption peak(T0=0.3) and a spatial width(FWHM) of about 1". It has also been inferred that there exist 4-6 velocity threads along the line of sight at each spatial resolution element inside the filament. In about half of the threads, matter moves fast with a line-of-sight speed of 15±3 km s-1, but in the other half it is either at rest or slowly moving with a line-of-sight velocity of 0±3 km s-1. It is found that a statistical balance approximately holds between the numbers of blue-shifted threads and red-shifted threads, and any imbalance between the two numbers is responsible for the non-zero line-of-sight velocity determined using a single-component model fit. Our results support the existence not only of high speed counter-streaming flows, but also of a significant amount of cool matter either being at rest or moving slowly inside the filament.

Observations have indicated that magnetic reconnect ion may occur frequently in the photosphere and chromosphere as well as in the solar corona. The observed features include cancelling magnetic features seen in photospheric magnetograms, and different kinds of small-scale activities such as UV explosive events and EUV jets. By integrating the observed parameters of these features with the Sweet-Parker reconnect ion theory, an attempt is made to clarify the nature of chromospheric magnetic reconnection. Our results suggest that magnetic reconnect ion may be occurring at many different levels of the photosphere and chromosphere without a preferred height and at a faster speed than is predicted by the Sweet-Parker reconnect ion model using the classical value of electric conductivity. Introducing an anomalous magnetic diffusivity 10-100 times the classical value is one of the possible ways of explaining the fast reconnect ion as inferred from observations.

Solar observations support that magnetic reconnect ion ubiquitously occurs in the chromosphere as well as in the corona. It is now widely accepted that coronal magnetic reconnect ion is fast reconnect ion of the Petschek type, and is the main driver of solar flares. On the other hand, it has been thought that the traditional Sweet-Parker model may describe chromospheric reconnect ion without difficulty, since the electric conductivity in the chromoshphere is much lower than that in the corona. However, recent observations of cancelling magnetic features have suggested that chromospheric reconnect ion might proceed at a faster rate than the Sweet-Parker model predicts. We have applied the Sweet-Parker model and Petschek model to a well-observed cancelling magnetic feature. As a result, we found that the inflow speed of the Sweet-Parker reconnect ion is too small to explain the observed converging speed of the feature. On the other hand, the inflow speeds and outflow speeds of the Petschek reconnect ion are well compatible with observations. Moreover, we found that the Sweet-Parker type current sheet is subject to the ion-acoustic instability in the chromosphere, implying the Petschek mechanism may operate there. Our results strongly suggest that chromospheric reconnect ion is of the Petschek type.

Climate change affects the occurrence of heat waves in Korea. Heat wave gives significant impacts not only to human health, but also adversely affects on traffic accidents both directly and indirectly. This study analyzed heat wave impacts on traffic accidents in summer time (JJA) from 2012 to 2017 timely. To consider some occupations work in earlier or later than regular working hour, 04~20h is set for this study. Generalized additive model is used to analyze the relation between the temperature and traffic accidents. The results showed that the traffic accidents in high temperature increases in 04~08h, 08~12h, and especially 18~20h. The percent difference for relative risk of traffic accidents is 2.34% (95% confidence interval: 1.140, 3.269) when the temperature increase by 1°C in 18~20h. The results of this study suggest some requirements for measures to prevent traffic accidents in the morning and evening hours with increasing temperatures.

This study estimated sunshine duration in South Korea using cloud detection images; the 2 class and 5 class images of Communication, Ocean and Meteorological Satellite (COMS). The images were preprocessed and then compared with the observed sunshine duration from the Automated Synoptic Observing System (ASOS). Based on the result of comparing yearly and monthly sunshine duration, the results of the 5 class were better than the results of the 2 class. In the case of comparing daily sunshine duration, the results of the 5 class also showed relatively better outcome than the 2 class images. The simulation performance of the sunshine duration observed by ASOS and the sunshine duration calculated by COMS were evaluated using Kling-Gupta Efficiency (KGE) technique. The 5 class data showed relatively high efficiency. RMSEs were relatively lower in the 5 class than the 2 class image in all years (2011-2014). Therefore, the 5 class data among the COMS satellite images could provide meaningful information at the points where there is no observation of sunshine duration.

We developed the Parameter-elevation Regressions on Independent Slopes Model(PRISM)-based Dynamical downscaling Error correction(PRIDE)-Wind speed(WS) model version 3.0 to produce highresolution( 1km) grid data at a monthly time scale by using observation and Regional Climate Model(RCM) wind speed data. We consequently produced monthly wind speed grid data during the observation period(2000~2014) and the future period(2021~2100) for Representative Concentration Pathway(RCP) 2 type scenarios by using the PRIDE-WS model. The PRIDE-WS model is constructed by combining the MK(Modified Korean)-PRISM-Wind, the RCM anomaly and Cumulative Density Function(CDF) fitting, basically based on Kim et al.(2016)’s algorithm applied for daily precipitation. The upper level wind(80m altitude) was estimated by Deacon equation using surface wind speed that was produced by the PRIDE-WS model. The results show that the wind speed at the upper level generally increased during the summer season while it decreased during the spring, autumn and winter seasons.

MK-PRISM developed for wind interpolation was applied to case studies and was verified in previous studies. Thus, some tests were necessary before the model used in order to produce wind speed maps for the whole area of South Korea. In this study, the MK-PRISM was applied to producing wind speed maps of South Korea. The result showed that sharp changes occur in wind speed distribution, despite the continuous similar topographic. The primary reason for the phenomenon was that a linear regression slope between elevation and wind speed used in interpolation process was changed rapidly in some areas. This study used the landform classification data to address this problem. The improved model controlled similarly the slope of the linear regression equation in the continuous valley, slope, and ridge. Therefore, the slope of the linear regression equation does not change dramatically in the improved model. The improved model was named MK-PRISM-Wind in this study. The wind speed was similar on the ridge continuously in the wind speed distribution produced by MK-PRISM-Wind. In addition, the wind speed was more gradually changed compared to the previous model on the plains and foothills. The results mean that MK-PRISM-Wind can produce wind speed maps more reasonable than the previous model, and it can be applied to the wind speed interpolation of South Korea. High-resolution gridded wind speed map produced by MK-PRISM-Wind is expected to be utilized for various studies.

This study has calculated the change of wind speed according to the features of land surface roughness using the surface wind data provided by the Korean peninsula data of HadGEM3-RA and has analyzed the characteristics of the future upper wind over South Korea driven by several climate change scenarios. The simulation found that the more the time passes, the more the wind speed increases in the previous time period of upper wind and annual average wind speed time series analysis of three kinds of Representative Concentration Pathways (RCP). The wind speed of all three kinds of RCP increased in the summer and winter but decreased in the spring and fall in the analysis of seasonal time series and spatial distribution. The wind speed would be expected to increase in most months except April and November in the analysis of the monthly mean maximum wind speed. The histogram analysis shows the mean wind speed of upper wind over 3m/s. As the time passes, the wind speed increases more than in the past. Certain areas such as the areas under the urbanization development would be anticipated to raise the wind speed throughout all months.

This study investigates the theoretical background of the interpolation methods that regards the topographical effect on the climate data, such as Co-kriging, Artificial Neural Network and MK-PRISM(Modified Korean Parameter-elevation Regressions on Independent Slopes Model). Prior to applying the MK-PRISM to the interpolation of wind speed, this study has improved the model to be closer to the fundamental concept of the PRISM and verified it‘s validity. Since each method has individual advantages and disadvantages, there will be a need for comparative studies in order to select an interpolation method that is suitable for the topography of Korea. This study has added a weighted value that considers the existence of clusters at the known point, and has supplemented the digital elevation models and aspects distribution of multiple scales for application. In addition, this study has allowed the consideration of sharp changes between the known point and unknown point when calculating the topographic facet weighting. The supplement model was verified through the interpolation of rainfall in Jeju Island. The coefficient of determination and KGE(Kling and Gupta Efficiency) of the model displayed the results of 0.86 and 0.87, respectively for August 2010 monthly precipitation in Jeju Island, and the model was accordingly verified. This study is able to provide the necessary information to the researchers who wish to interpolate the observation data of wind speed. Furthermore, the supplement MK-PRISM becomes available to the research on the interpolation of wind speed.

This study examines the relationship between urbanization rate and extreme climate indices in South Korea for the period 1981-2010. In the analysis five extreme climate indices related to air temperature and four types urbanization rates are used. In particular, this paper adopts frequency of warm nights(TN90p), intra-annual extreme temperature range(ATR), growing season length(GSL), number of frost days(FD) and heat warm spell duration indicator(HWDI) as extreme climate indices. As a measure of urbanization rate, four kinds of urbanization rate are used: (1) three urbanization rates within a radius of 1km, 5km or 10km of weather station and (2) a urbanization rate of sub-watershed where weather station is located. The trend of extreme climate indices is calculated based on Mann-Kendall trend analysis and Sen’s slope, and this trend is contrasted with urbanization rates in eleven climatic regions. The results show that TN90p, GSL, and FD have a relatively high correlation with urbanization rate. This study also shows that a urbanization rate within a radius of 1km of weather station affects GSL and FD. while a urbanization rate within 5km buffer zone of weather station affects TN90p. It is Daegwallyeong, Inje, Yangpyeong, and Hongcheon where extreme climate indices responded sensitively despite the low urbanization rates of these areas. Continual attention is needed to these areas because they are relatively sensitive to climate changes of synoptic scale.