• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• Journal of Korean Society on Water Environment
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• v.34 no.1
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• pp.67-76
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• 2018

There are 34 mega-cities with a population of more than 10 million in the world. One of the highly populated cities in the world is Seoul in South Korea. Seoul receives $1,140million\;m^3/year$ for domestic water, $2million\;m^3/year$ for agricultural water and $6million\;m^3/year$ for industrial water from multi-purpose dams. The maintenance water used for water conservation, ecosystem protection and landscape preservation is $158million\;m^3/year$, which is supplied from natural precipitation. Recently, the use of the other water for preservation of water quality and ecosystem protection in urban areas is increasing. The objectives of this study is to develop the seasonal forecast method of environmental water in urban areas (Seoul, Daejeon, Gwangju, Busan) and to evaluate its predictability. In order to estimate the seasonal outlook information of environmental water from Land Surface Model (LSM), we used the observation weather data of Automated Synoptic Observing System (ASOS) sites, forecast and hind cast data of GloSea5. In the past 30 years (1985 ~ 2014), precipitation, natural runoff and Urban Environmental Water Index (UEI) were analyzed in the 4 urban areas. We calculated the seasonal outlook values of the UEI based on GloSea5 for 2015 year and compared it to UEI based on observed data. The seasonal outlook of UEI in urban areas presented high predictability in the spring, autumn and winter. Studies have depicted that the proposed UEI will be useful for evaluating urban environmental water and the predictability of UEI using GloSea5 forecast data is likely to be high in the order of autumn, winter, spring and summer.

• Ocean and Polar Research
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• v.34 no.2
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• pp.185-195
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• 2012

This paper focused on forecasting a short-term production of oysters, which have been farmed in Korea, with distinct periodicity of production by year, and different production level by month. To forecast a short-term oyster production, this paper uses monthly data (260 observations) from January 1990 to August 2011, and also adopts several econometrics methods, such as Multiple Regression Analysis Model (MRAM), Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Vector Error Correction Model (VECM). As a result, first, the amount of short-term oyster production forecasted by the multiple regression analysis model was 1,337 ton with prediction error of 246 ton. Secondly, the amount of oyster production of the SARIMA I and II models was forecasted as 12,423 ton and 12,442 ton with prediction error of 11,404 ton and 11,423 ton, respectively. Thirdly, the amount of oyster production based on the VECM was estimated as 10,425 ton with prediction errors of 9,406 ton. In conclusion, based on Theil inequality coefficient criterion, short-term prediction of oyster by the VECM exhibited a better fit than ones by the SARIMA I and II models and Multiple Regression Analysis Model.

• Atmosphere
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• v.25 no.2
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• pp.271-281
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• 2015

The objectives of this study are to develop a hydrological drought outlook system using GloSea5 (Global Seasonal forecasting system 5) which has recently been used by KMA (Korea Meteorological Association) and to evaluate the forecasting capability. For drought analysis, the bilinear interpolation method was applied to spatially downscale the low-resolution outputs of GloSea5 and PR (Predicted Runoff) was produced for different lead times (i.e., 1-, 2-, 3-month) running LSM (Land Surface Model). The behavior of PR anomaly was similar to that of HR (Historical Runoff) and the estimated values were negative up to lead times of 1- and 2-month. For the evaluation of drought outlook, SRI (Standardized Runoff Index) was selected and PR_SRI estimated using PR. ROC score was 0.83, 0.71, 0.60 for 1-, 2- and 3-month lead times, respectively. It also showed the hit rate is high and false alarm rate is low as shorter lead time. The temporal Correlation Coefficient (CC) was 0.82, 0.60, 0.31 and Root Mean Square Error (RMSE) was 0.52, 0.86, 1.20 for 1-, 2-, 3-month lead time, respectively. The accuracy of PR_SRI was high up to 1- and 2-month lead time on local regions except the Gyeonggi and Gangwon province. It can be concluded that GloSea5 has high applicability for hydrological drought outlook.

• Korean journal of applied entomology
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• v.55 no.2
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• pp.139-148
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• 2016

A seasonal outlook for crop insect pests is most valuable when it provides accurate information for timely management decisions. In this study, we investigated probable tele-connections between climatic phenomena and pest infestations in Korea using a statistical method. A rice insect pest, brown planthopper (BPH), was selected because of its migration characteristics, which fits well with the concept of our statistical modelling - utilizing a long-term, multi-regional influence of selected climatic phenomena to predict a dominant biological event at certain time and place. Variables of the seasonal climate forecast from 10 climate models were used as a predictor, and annual infestation area for BPH as a predictand in the statistical analyses. The Moving Window Regression model showed high correlation between the national infestation trends of BPH in South Korea and selected tempo-spatial climatic variables along with its sequential migration path. Overall, the statistical models developed in this study showed a promising predictability for BPH infestation in Korea, although the dynamical relationships between the infestation and selected climatic phenomena need to be further elucidated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.655-669
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• 2018

In this study, we developed a hybrid forecasting model based on a four-parameter distribution which allows a simultaneous season-ahead forecasting for both seasonal rainfall and sub-daily rainfall in Han-River and Geum-River basins. The proposed model is mainly utilized a set of time-varying predictors and the associated model parameters were estimated within a Bayesian nonstationary rainfall frequency framework. The hybrid forecasting model was validated through an cross-validatory experiment using the recent rainfall events during 2014~2017 in both basins. The seasonal precipitation results showed a good agreement with the observations, which is about 86.3% and 98.9% in Han-River basin and Geum-River basin, respectively. Similarly, for the extreme rainfalls at sub-daily scale, the results showed a good correspondence between the observed and simulated rainfalls with a range of 65.9~99.7%. Therefore, it can be concluded that the proposed model could be used to better consider climate variability at multiple time scales.

• Journal of environmental and Sanitary engineering
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• v.21 no.1 s.59
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• pp.66-75
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• 2006

When we looked at the seasonal food dregs of the eastern side of gangwondo, gangneung city's summer and winter food dregs showed 25.9 and 25.8% respectively due to the presence of beach areas and ski resorts. Sokcho city showed 28.12% in summer and yangyang gun's summer food dregs showed 40.2%. Yangyang gun's august food dregs showed 2.7 times larger than annual average amount. Outlook density showed regional characteristics. Data showed that food dregs' amount rate has been reduced gradually from 2005 because of the prohibition of direct filling up. As a result of compositions analysis, the eastern side of gangwondo's water fraction of living dregs were lower than that of chuncheon city where is located at the gangwondo's inland area. chuncheon city's data showed residential areas 53.5%, community areas 56.8% and commercial areas 55.6%. These discrepancies caused by the characteristics of dregs discharge type and climate. The caloric value of dregs has been increased incrementally after the ban of food dregs' direct filling up. Therefore, heating value of the dregs exceeds the existing furnace design spec and it can cause high caloric value problems, so we need additional research to solve these problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.97-97
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• 2016

가뭄은 홍수와 더불어 매우 심각한 자연재해이며, 그 특성상 광역적이고 장기간 발생함에 따라 구체적인 발생시점, 규모, 범위 등을 규명하기가 어렵다. 다만, 적시에 경보해야 하는 홍수와 달리 진행속도가 느리고 시간적으로 대처할 여유가 있어 진행중 일지라도 초기에 감지한다면 그 피해를 최소화할 수 있다. 미국 등 수문기상 선진국에서는 수문기상 장기예보자료를 활용한 가뭄전망정보 생산 및 제공하고 있으며, 활용성을 검증한바 있다. 국내의 경우 기상청에서는 대기-해양-해빙 모델을 접합한 GloSea5 (Global Seasonal forecasting system version 5) 모델을 도입하였으며, 가뭄예보를 목적으로 장기예보자료 기반의 가뭄전망정보 생산체계를 구축한 바 있다(기상청, 2012; 손경환 등, 2015). 본 연구에서는 장기예보자료 기반의 수문기상 전망정보를 이용하여 2014-15년 가뭄사례에 대한 가뭄감시 및 전망정보를 생산 및 평가하였다. 수문기상전망 정보는 기상청 현업예보 모델인 GloSea5와 지면모델을 이용하여 생산하였으며, 관측자료와 수문전망정보 기반의 가뭄지수를 산정하였다. 매스컴 및 언론 보도 자료부터 2014-15년 가뭄에 대한 행정구역별 피해사례를 수집하였으며, 이를 기반으로 시계열, 지역별 및 통계적(CC, RMSE) 분석을 이용하여 선행시간별 정확도를 평가하였다. 1개월 및 2개월 전망정보의 정확도가 높음을 확인하였으며, 가뭄심도가 심각한 시기의 가뭄상황을 적절히 재현하는 것으로 나타났다.

• Journal of Conservation Science
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• v.36 no.4
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• pp.255-263
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• 2020

Paulownia coreana has various advantages as a convenient workability, aesthetic outlook, beautiful patterns, low weight and high strength, and its permeability. P. coreana has been widely used for storage but there are no empirical researches proving its functionality in a field of conservation science until now. In this study, the seasonal and daily temperature and relative humidity control, and microbe and insect repellent activity were evaluated under the controlled and uncontrolled circumstances from 2015 to 2016. The results showed to be mainly excellent in relative humidity control and the buffering effect was good to adjust the average daily relative humidity range from the outside. With respect to the antimicrobial properties of P. coreana, we observed that its water-soluble extract produced visible zones of inhibition against five bacteria. However, it was difficult to predict the antimicrobial and/or insecticidal properties.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1784-1788
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• 2010

APEC 기후센터(APEC Climate Center, APCC)에서 제공하는 다중모형앙상블(Multi-model Ensemble, MME) 형태의 계절예측정보를 이용하여 3개월 가뭄전망을 수행하였다. APCC MME는 기후예측모형이 가지는 불확실성을 최소화하기 위한 방법으로, 아시아 태평양 지역 내 9개 회원국 16개 기관 21개 기후모형의 계절예측정보를 활용하여, 개별 모형이 가지는 계통오차(Systematic error)를 앙상블 기법을 통하여 상쇄함으로써 최적의 예측자료를 도출한다. 또한, 기후예측 모형이 예측한 대기순환장은 관측 지점변수와 경험적 통계적 관련성을 가지므로, 이를 바탕으로 상세지역의 이상기후에 대한 정보를 도출할 수 있다. 본 연구에서는 가뭄 관리 및 전망을 위한 입력 자료로서, 기상전문 기관인 APEC 기후센터 (APEC Climate Center, APCC)에서 제공하는 전구 규모의 기온 및 강수 전망자료를 기상청 산하 59개 지점의 전망자료로 통계적 규모 축소화 기법을 통해 3개월 예보를 실시하였다. APCC 계절예측자료를 가뭄모니터링시스템의 자료입력 포맷에 따라 적절히 가공한 뒤, 가뭄 관리 및 전망을 위하여 SPI(Standard Precipitation Index) 및 PDSI(Palmer Drought Severity Index)지수의 입력자료로 사용하여 SPI 및 PDSI 지수를 산정하였다. 또한 분위사상법(Quantile Mapping)을 이용하여 총 59개 지점의 과거 월평균 관측값과 최근 2009년에 대한 모의값의 누적확률분포값을 계산하고 모의값의 확률분포를 관측값의 확률분포에 사상시켜 가뭄 전망을 위한 기상변수의 오차를 보정하고자 하였다. 이러한 계절예측정보를 이용하여 가뭄 전망에 대한 신뢰도가 높아진다면, 사전예방 및 피해완화로 가뭄상황에 대한 신속한 대처 및 피해의 경감이 이루어질 수 있을 것이다.