• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.211-211
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• 2018

미해양대기청 기후예측센터(Climate Prediction Center, NOAA)에서 제공하고 있는 기후지수(climate indices)를 예측인자로 하고 금강유역의 5~6월의 강우량을 예측대상으로 하는 원격상관기반 통계모형을 구축하였다. 1988년부터 2017년까지의 30년 자료에 대해 예측인자와 예측대상간의 시간지연상관분석을 수행한 결과 NAO(North Atlantic Oscillation), EP/NP(East Pacific/North Pacific Oscillation), EA(East Atlantic Pattern), WP(Western Pacific Index) 등과 상관성이 높은 것으로 분석되었으며, 이러한 시간지연 기후지수를 이용하여 4개월전에 5,6월 강수량을 예측할 수 있는 다중회귀모형을 개발하였다. 관측 강우량 아노말리가 큰 경우에는 다소 과소 예측되고, 아노말리가 작은 경우에는 다소 과다 예측되는 경향을 보였지만 관측 강우량과 예측 강우량간의 상관계수가 0.75로서 비교적 우수한 예측 결과를 나타내었다. 5~6월 강우량 아노말리의 3분위 예측성을 평가한 결과 평년이상 적중률은 77.8%, 평년수준은 81.8%로서 예측 성공률이 높았으며, 5, 6월 누적강우량이 매우 작았던 92년과 95년을 제외하고는 강우량이 적은 해에도 예측성이 우수하여 평년이하 적중률이 70.0%를 나타내었다. 따라서 본 개발모형은 최소 4개월 이전 선행시간을 가지고 늦봄, 초여름강우량을 예측할 수 있는 저비용의 가뭄 예측 도구로 유용하게 활용될 수 있을 것이다.

• Journal of Agricultural Extension & Community Development
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• v.30 no.4
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• pp.213-227
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• 2023

This paper aims to examine the farmers' perceptions of the importance and feasibility of climate change awareness and adaptive measures in agriculture, utilizing paired sample t-tests and Importance-Performance Analysis (IPA). Significant differences were found in farmers' views on the importance and urgency of climate change issues, with specific factors standing out. The IPA analysis identified key issues requiring sustained attention, including climate change magnitude, extreme weather events, livestock damage scale, pest fluctuations, and variability in flowering periods. Additionally, the study revealed significant disparities in farmers' perceptions of the importance and feasibility of adaptive measures, except for specific items related to heat indices.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.4
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• pp.564-573
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• 2006

Purposes: This study was to provide basic data to explain the effect of the organizational effectiveness factor on hospital nursing, to construct an appropriate model to examine the validation and relationship with variables and to provide basic data for improving the organizational effectiveness of hospital nursing. Method: This study was a descriptive correlation research. Subjects of the study were 348 nurses, 219 patients, and 89 nurses for nursing quality. Twelve measurement variables and nine paths were established in the hypothetical model. Results: The fitness indices of the model were GFI=0.91, NFI=0.90, and PGFI=0.49. Five among the nine paths proved to be statistically significant : level of nurse manpower to organizational effectiveness, conflict to organizational effectiveness, organizational climate to organizational effectiveness, level of nurse manpower to organizational climate, and leadership to organizational climate. Level of nurse manpower and leadership influenced organizational climate. Organizational climate accounted for 43% by the predictor variables, and the level of nurse manpower, conflict, and organizational climate influenced the organizational effectiveness, which accounted for 77% by the predictor variables. Conclusion: This study identified that the level of nurse manpower, leadership, conflict, and organizational climate are important factors affecting organizational effectiveness.

• Journal of Environmental Science International
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• v.26 no.12
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• pp.1399-1405
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• 2017

We compared the spatial distribution of several heat stress indices (the Wet-Bulb Globe Temperature(WBGT) index, Environmental Stress Index (ESI), and Modified Discomfort Index(MDI)) for the heat wave of June 6~August 26, 2016, in Daegu. We calculated the heat stress indices using data from the high density urban climate observation network in Daegu. The observation system was established in February. 2013. We used data from a total of 38 air temperature observation points (23 thermometers and 18 automatic weather stations). The values of the heat stress indices indicated that the danger level was very high from 0900-2000h in downtown Daegu. The daily maximum value of the WBGT was greater than or equal to $35^{\circ}C$. The differences in the heat stress indices from downtown and rural areas were higher in the daytime than at nighttime. The maximum difference was about 4 before and after 1400h, and the time variations of the heat stress indices corresponded well. Thus, we were able to confirm that the ESI and MDI can be substituted with the WBGT index.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1441-1444
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• 2007

It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.149-162
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• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.4
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• pp.113-120
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• 2008

The increase in average air temperature over the past 100 years in northern Asia including Korea is the greatest (about ${1.5}^{\circ}C$) among the various regions of the world. Considering a further warming projected by the IPCC, fluctuations of agro-climatic indices under climate change must precede an evaluation of vulnerability. The purpose of this study is to analyze how climate changes represented by global warming have altered agro-climatic indices in Korea over various time scales. Drought index during the rice-transplanting period of 15 May to 5 June has changed toward the favorable with recently increased precipitation in the Taebaek Alpine and Semi-Alpine Zone, and Yeongnam Basin and Inland Zone. The frequency of low temperature occurrence below $13^{\circ}C$ during the rice transplanting has decreased, while climatic production index (CPI) has fallen because of the decreased sunshine hour and increased temperature during the rice ripening period. We therefore concluded that the recent change of climate conditions was against the rice productivity in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• Atmosphere
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• v.23 no.2
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• pp.221-229
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• 2013

There has been an increasing need to assess the effects of climate change on human health. It is hard to use climate data to evaluate health effects because such data have a grid format, which could not represent specific cities or provinces. Therefore, the grid-format climate data of South Korea based on RCP (Representative Concentration Pathway) scenarios were modified into area-format climate data according to the major cities or provinces of the country, up to the year 2100. Moreover, heat index (HI) and discomfort index (DI) databases were developed from the modified climate database. These databases will soon be available for experts via a Website, and the expected HI and DI of any place in the country, or at any time, can be found in the country's climate homepage (http://www.climate.go.kr). The HI and DI were analyzed by plotting the average indices every ten years, and by comparing cities or provinces with index level changes, using the geographic information system (GIS). Both the HI and DI are expected to continually increase from 2011 to 2100, and to reach the most dangerous level especially in August 2100. Among the major cities of South Korea, Gwangju showed the highest HI and DI, and Gangwon province is expected to be the least affected area in terms of HI and DI among all the country's provinces.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.681-690
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• 2009

In this research, design precipitation was calculated by reflecting the climatic indices and its uncertainty assessment was evaluated. Climatic indices used the sea surface temperature and moisture index which observed globally. The correlation coefficients were calculated between the annual maximum precipitation and the climatic indices. and then climatic indices which have the larger correlation coefficient were selected. Therefore, the regression relationship was established by a locally weighted polynomial regression. Next, climatic indices were generated by montecarlo simulation using kernel function. Finally, the design rainfall was calculated by the locally weighted polynomial regression using generated climatic indices. At the result, the comparison of design rainfall between the reflection of the climatic indices and the frequency analysis did not indicate a significant difference. Also, this result can be used as basic data for calculation of probability precipitation to reflect climate change.