• 한국수자원학회논문집
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• 제47권7호
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• pp.643-656
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• 2014

우리나라 전국 43개 기후관측지점을 대상으로 기후 건조지수 추세의 시간적(월별, 계절별, 연별) 동질성을 분석하였다. 또한 43개 기후관측지점을 9개 지역으로 구분하여 이들 각 지역과 전체 9개 지역을 대상으로 시간적 및 지역적인 기후 건조지수 추세의 동질성 유무와 추세정도를 파악하였다. 분석을 위해 43개 기후관측지점의 월별, 계절별 그리고 연별 건조지수를 강수량과 FAO Penman-Monteith식으로 계산된 잠재증발산량으로부터 산정하였다. 또한 산정된 지수를 이용하여 Mann-Kendall 추세분석을 실시하였고, 추세분석 결과(Z scores)를 이용하여 기후 건조지수 추세의 시간적 및 지역적 동질성 분석을 실시하였다. 분석결과에 의하면 9개 각 지역과 전체 9개 지역에서 기후 건조지수 추세는 시간적 및 지역적으로 동질성이 있는 것으로 나타났으나, 추세의 동질성 정도 및 추세정도는 시간적 및 지역적으로 다른 양상을 보였다.

• 한국환경과학회지
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• 제22권8호
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• pp.953-963
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• 한국대기환경학회지
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• 제22권2호
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• pp.223-233
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• 2006

We analyzed the monthly and seasonal mean of the daily Erythemal Ultraviolet-B (EUV-B, $280{\sim}320nm$) irradiance operating in Pohang, Anmyeon, Gosan, Mokpo and Kangnung with UV-Biometer (Solar Light Co., Model No. 501) at clear-sky noon during the period from 1999 to 2004. Also, we investigated the seasonal and regional characteristics for the UV index over the Korean Peninsula. The daily maximum occurred near solar southing time and the highest monthly accumulated EUV-B irradiance appeared in July and August at each regional observatory. The monthly mean value of the clear-sky EUV-B irradiance in Pohang, Anmyeon, Gosan, Mokpo and Kangnung showed 196.6, 161.8, 221.9, $171.5mWm^{-2}\;and\;179.7mWm^{-2}$ near noon in July respectively. The annual mean value of the daily accumulated EUV-B irradiance in Pohang, Anmyeon, Gosan, Mokpo and Kangnung were 1.8, 2.1, 2.2, $1.8kJm^{-2}\;and\;1.5kJm^{-2}$ respectively. The UV Index (UVI) showed above UVI 7(High) more than 90 days during one year over the Korean Peninsula.

• 한국어류학회지
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• 제32권2호
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• pp.91-96
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• 2020

여수 낭도 연안에서 낭장망에 어획된 어류의 종조성 및 계절 변동을 연구하기 위해 2017년에 계절별로 4개의 정점에서 진행하였다. 어획된 어류는 총 9목 26과 37종, 10,208개체가 어획되었다. 농어목이 11과 16종으로 가장 많이 출현하였고, 우점종은 멸치(4,886개체, 47.9%), 보구치(842개체, 8.2%), 준치(369개체, 3.6%) 순이었다. 다양도는 1.24~3.23 범위를 보이며 5월이 가장 높았고, 우점도는 22.4~78.7% 범위를 보이며 11월이 가장 높았다.

• 한국양식학회지
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• 제4권1호
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• pp.19-30
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• 1991

가리비, Patinopecten yesso두냔의 소화맹낭 및 그 상피세포의 지방에 대한 계절변동과 생식소 발달과의 관계를 알아보기 위하여, 일본 북해도의 오호츠크해에 면한 망주만산 방류양식 개체를 1982년 9월부터 1984년 5월까지 월별로 채집하여 조사한 결과는 다음과 같다. 1. 소화맹낭의 지수는 $5{\~}6$월에 가장 높았으며, 12월 및 유빙에 최저치를 나타냈다. 2. 소화맹낭의 조직단면적 1 $mm^{2}$당 세관수는 $9{\~}10$월에 최소치를 나타냈으나, 3월에 최다치를 보였다. 3. 생식소 지수(X)와 소화맹낭의 지방세관 비율(Y)은 $Y=145.6X^{-0793}$의 역지수함수적 관계를 나타냈다. 4. 소화맹낭의 지방은 생식소의 발달과 함께 생식소로 전이되는 계절변동을 보였다.

• 대기
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• 제26권1호
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• 한국농공학회논문집
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• 제61권1호
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• pp.61-74
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• 2019

In this study, the SPI (Standardized Precipitation Index) of meteorological drought and SDI (Streamflow Drought Index) of hydrological drought for 1, 3, 6, 9, and 12 months duration were estimated to analyse the characteristics of drought using rainfall and dam inflow data for Chungju dam ($6,661.8km^2$) with 31 years (1986-2016) and Boryeong dam ($163.6km^2$) watershed with 19 years (1998-2016) respectively. Using the estimated SPI and SDI, the drought forecasting was conducted using seasonal autoregressive integrated moving average (SARIMA) model for the 5 durations. For 2016 drought, the SARIMA had a good results for 3 and 6 months. For the 3 months SARIMA forecasting of SPI and SDI, the correlation coefficient of SPI3, SPI6, SPI12, SDI1, and SDI6 at Chungju Dam showed 0.960, 0.990, 0.999, 0.868, and 0.846, respectively. Also, for same duration forecasting of SPI and SDI at Boryeong Dam, the correlation coefficient of SPI3, SPI6, SDI3, SDI6, and SDI12 showed 0.999, 0.994, 0.999, 0.880, and 0.992, respectively. The SARIMA model showed the possibility to provide the future short-term SPI meteorological drought and the resulting SDI hydrological drought.

• 대기
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• 제25권2호
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• pp.323-337
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• 2015

This study explores the 6-month lead prediction skill of several climate indices that influence on East Asian climate in the GloSea5 hindcast experiment. Such indices include Nino3.4, Indian Ocean Diploe (IOD), Arctic Oscillation (AO), various summer and winter Asian monsoon indices. The model's prediction skill of these indices is evaluated by computing the anomaly correlation coefficient (ACC) and mean squared skill score (MSSS) for ensemble mean values over the period of 1996~2009. In general, climate indices that have low seasonal variability are predicted well. For example, in terms of ACC, Nino3.4 index is predicted well at least 6 months in advance. The IOD index is also well predicted in late summer and autumn. This contrasts with the prediction skill of AO index which shows essentially no skill beyond a few months except in February and August. Both summer and winter Asian monsoon indices are also poorly predicted. An exception is the Western North Pacific Monsoon (WNPM) index that exhibits a prediction skill up to 4- to 6-month lead time. However, when MSSS is considered, most climate indices, except Nino3.4 index, show a negligible prediction skill, indicating that conditional bias is significant in the model. These results are only weakly sensitive to the number of ensemble members.

• 한국수자원학회논문집
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• 제40권4호
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• pp.299-311
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• 2007

최근 들어 세계의 연중 기후 변화에 주된 요인으로써 엘니뇨와 같은 현상이 매우 잦아졌다. 많은 기상수문학자들이 강수와 유량에 대한 엘니뇨 남방진동의 영향에 대해 연구하고 있지만, 수문변량들은 큰 지역적 변동을 갖고 있기 때문에 결정적인 인과관계를 찾아내는데 있어서 많은 어려움이 있다. 본 연구에서는 엘니뇨-남방진동과 한국에서의 수문변량들 간의 계절석 관계를 고찰하였다. 엘니뇨-난방진동을 정량적으로 표현해 주는 지수로써 남방진동지수를 사용하였고, 월강수량 자료, 월평균기온 자료 그리고 댐의 월유입량 자료를 표준정규분포를 가지는 표준정규지수로 변환하여 사용하였다. 계절적 관계를 파악하기 위해 난방진동지수와 수문변량의 월 자료는 봄 (3월-5월), 여름(6윌-8월), 가을(9월-11월) 그리고 겨울 (12윌-2월)로 분류되었다. ENSO episode에 대한 수문변량들의 조건부 초과확률과 분포형태를 바탕으로 분석을 수행한 결과 전반적으로 Warm ENSO episode의 경우 강수량 증가와 기온 상승과 관련이 있고, Cold ENSO episode의 경우 강수량 감소와 기온 하강과 관계가 있다. 그러나 일부 지역에서는 이러한 전반적인 결과와 상이한 결과가 나타나기도 하였다.

• Water Engineering Research
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• 제1권2호
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• pp.107-117
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• 2000

Streamflow patterns at two gauging stations in Korea, An-Dong dam and Chung-Ju dam, are statistically analyzed in relation to EI Nino/Southern Oscillation (ENSO). As a measure of ENSO, the Southern Oscillation Index (SOI) is used on a monthly and seasonal basis. The traditional correlation analysis shows that cross correlations of the SOI with the seasonal streamflow are generally weak. To investigate the relationship between the extreme values of the SOI, which represent the EI Nino and La Nina events, and the corresponding streamflow patterns, the composite analysis is employed in this study. The composite analysis demonstrates that when EI Nino occurs, seasonal streamflows at An-Dong and Chung-Ju dams during the period from September of the EI Nino year to February of the following year appear to be drier than their means.