• 한국측량학회지
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• 제35권5호
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• pp.423-430
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• 2017

Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.

• 한국농공학회논문집
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• 제54권6호
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• pp.133-142
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• 2012

The objective of this study was to correct the bias of the Representative Concentration Pathways (RCP)-based future precipitation data using a quantile mapping method. This method was adopted to correct extreme values because it was designed to adjust simulated data using probability distribution function. The Generalized Extreme Value (GEV) distribution was used to fit distribution for precipitation data obtained from the Korea Meteorological Administration (KMA). The resolutions of precipitation data was 12.5 km in space and 3-hour in time. As the results of bias correction over the past 30 years (1976~2005), the annual precipitation was increased 16.3 % overall. And the results for 90 years (divided into 2011~2040, 2041~2070, 2071~2100) were that the future annual precipitation were increased 8.8 %, 9.6 %, 11.3 % respectively. It also had stronger correction effects on high value than low value. It was concluded that a quantile mapping appeared a good method of correcting extreme value.

• 한국농공학회논문집
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• 제52권4호
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• pp.83-91
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• 2010

Generally, the GCM (General Circulation Model) data by IPCC climate change scenarios are used for future weather prediction. IPCC GCM models predict well for the continental scale, but is not good for the regional scale. This paper tried to generate future temperature and precipitation of 8 scattered meteorological stations in South Korea by using the MIROC3.2 hires GCM data and applying LARS-WG downscaling method. The MIROC3.2 A1B scenario data were adopted because it has the similar pattern comparing with the observed data (1977-2006) among the scenarios. The results showed that both the future precipitation and temperature increased. The 2080s annual temperature increased $3.8{\sim}5.0^{\circ}C$. Especially the future temperature increased up to $4.5{\sim}7.8^{\circ}C$ in winter period (December-February). The future annual precipitation of 2020s, 2050s, and 2080s increased 17.5 %, 27.5 %, and 39.0 % respectively. From the trend analysis for the future projected results, the above middle region of South Korea showed a statistical significance for winter precipitation and south region for summer rainfall.

• Journal of Preventive Medicine and Public Health
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• 제43권5호
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• pp.436-444
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• 2010

Objectives: Infectious diseases are known to be affected by climate change. We investigated if the infectious diseases were related to meteorological factors in Korea. Methods: Scrub typhus, hemorrhagic fever with renal syndrome (HFRS), leptospirosis, malaria and Vibrio vulnificus sepsis among the National Notifiable Infectious Diseases were selected as the climate change-related infectious diseases. Temperature, relative humidity and precipitation were used as meteorological factors. The study period was from 2001 through 2008. We examined the seasonality of the diseases and those correlations with meteorological factors. We also analyzed the correlations between the incidences of the diseases during the outbreak periods and monthly meteorological factors in the hyper-endemic regions. Results: All of the investigated diseases showed strong seasonality; malaria and V. vulnificus sepsis were prevalent in summer and scrub typhus, HFRS and leptospirosis were prevalent in the autumn. There were significant correlations between the monthly numbers of cases and all the meteorological factors for malaria and V. vulnificus sepsis, but there were no correlation for the other diseases. However, the incidence of scrub typhus in hyper-endemic region during the outbreak period was positively correlated with temperature and humidity during the summer. The incidences of HFRS and leptospirosis had positive correlations with precipitation in November and temperature and humidity in February, respectively. V. vulnificus sepsis showed positive correlations with precipitation in April/May/July. Conclusions: In Korea, the incidences of the infectious diseases were correlated with meteorological factors, and this implies that the incidences could be influenced by climate change.

• 한국기후변화학회지
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• 제7권4호
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• pp.433-442
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• 2016

In this study, we examine future changes in surface radiation associated with cloud amount and aerosol emission over East Asia. Data in this study is HadGEM2-CC (Hadley Centre Global Environmental Model version 2, Carbon Cycle) simulations of the Representative Concentration Pathways (RCPs) 2.6/4.5/8.5. Results show that temperature and precipitation increase with rising of the atmosphere $CO_2$. At the end of $21^{st}$ century (2070~2099) relative to the end of $20^{st}$ century (1981~2005), changes in temperature and precipitation rate are expected to increase by $+1.85^{\circ}C/+6.6%$ for RCP2.6, $+3.09^{\circ}C/+8.5%$ for RCP4.5, $+5.49^{\circ}C/10%$ for RCP8.5. The warming results from increasing Net Down Surface Long Wave Radiation Flux (LW) and Net Down Surface Short Wave Radiation Flux (SW) as well. SW change increases mainly from reduced total Aerosol Optical Depth (AOD) and low-level cloud amount. LW change is associated with increasing of atmospheric $CO_2$ and total cloud amount, since increasing cloud amounts are related to absorb LW radiation and remit the energy toward the surface. The enhancement of precipitation is attributed by increasing of high-level cloud amount. Such climate conditions are favorable for vegetation growth and extension. Expansion of C3 grass and shrub is distinct over East Asia, inducing large latent heat flux increment.

• 한국산림과학회지
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• 제105권3호
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• pp.351-359
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• 2016

본 연구는 기후변화가 잣나무의 연륜생장에 미치는 영향을 평가하기 위해 수행하였다. 잣나무의 연도별 생장패턴을 분석하기 위해 제5차 국가산림자원조사에서 수집된 연륜생장 자료를 정리하였다. 기후조건의 유사성에 근거한 군집분석 결과 잣나무 분포지역은 5개의 군집의 분류되었다. 시군별로 정리된 1951년부터 2010년까지 60년 동안의 월별 평균기온과 강수량 자료에 근거하여 각 군집의 연도별 생장도일과 표준강수지수를 산출하였다. 이 정보를 이용하여 기후조건이 생장에 미치는 영향을 분석하기 위해 각 군집에 대한 연도별 온도효과지수와 강수효과지수를 추정하였다. 온도효과지수와 강수효과지수의 곱으로 표현되는 독립변수에 의해 연륜생장을 추정할 수 있는 연륜생장 추정식을 군집별로 개발하였다. 이 추정식을 기후변화 시나리오 RCP 4.5와 RCP 8.5에 적용함으로써 기후변화가 군집별 잣나무의 연륜생장에 미치는 영향을 예측하였다. 본 연구에서 얻어진 결과는 잣나무의 지역별 생장특성의 추정뿐만 아니라 기후변화에 따른 생장패턴의 변화 예측에 필요한 유용한 정보로 활용될 수 있을 것으로 기대된다.

• 응용통계연구
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• 제13권2호
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• pp.525-540
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• 2000

본 논문에서는 측우기 관측자료와 현대 관측자료로 이루어진 서울 강수량 시계열 자료에 나타난 시간에 따른(년도별 및 계절별)변화 및 변동 특성을 파악하고자 한다. 이를 위하여 먼저 200여년 간의 강수량 시계열에 어떤 특정한 증감 추세가 있는지를 알아보는 추세분석을 실시하였다. 그리고 추세뿐만 아니라 시간에 따른 강수량의 주기성 및 변동성을 더 자세히 알기 위하여 파엽 변환(wavelet transform)을 실시하여 여러 진동 모드들의 시간에 따른 변화 양상을 분석하였다.

• 한국지진공학회논문집
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• 제26권4호
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• pp.149-156
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• 2022

Magneto-Rheological Fluid (MRF) is a functional fluid in which flow characteristics change into magnetic force due to its magnetic particles. When the semi-active control device does not use MRF for a long time, precipitation of magnetic particles and abnormal control force occur. Thus, Electro Magneto-Rheological Fluid (EMRF), which improves the precipitation of magnetic particles for MRF and exhibits existing control performance, was developed in this study. First, the optimal mix proportion ratio was selected by conducting a precipitation experiment and a controlled force test by varying the content of grease based on the existing MRF components. Also, EMRF was applied to the shear-type damper to evaluate the control performance when applied to the control device. The cylinder-type damper was developed to apply to the structure, and control performance evaluation was conducted. The result confirmed that the precipitation of the magnetic particles was improved, while the damper using EMRF exhibited excellent control performance.

• 한국산림과학회지
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• 제103권2호
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• pp.159-164
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• 2014

소나무 묘목을 대상으로 한반도 기후변화 시나리오에 근거한 50년 후 온도 $3^{\circ}C$ 증가와 강수량 30% 변화의 영향을 모의하고자 실외에서 온난화 처리와 강수 조절을 수행할 수 있는 시스템을 설계하였다. 이를 위하여 2013년 4월에 묘포장을 조성하고 2년생 소나무 묘목을 식재한 다음 5월부터 적외선등을 이용하여 온난화 처리구(W)의 대기온도를 대조구(C)에 비하여 $3.0^{\circ}C$ 높게 설정하여 가열하였으며, 강수 대조구($P^0$)와 강수 차단 덮개를 이용한 강수 감소(대조구 대비 -30%; $P^-$) 조절, 그리고 펌프와 점적관수를 통한 강수 증가(대조구 대비 +30%; $P^+$) 조절을 실행하였다. 온난화 처리구의 대기 온도는 초기에 대조구에 비하여 평균 $2.2^{\circ}C$ 높았으나 이후 점차 목표치에 근접한 $3.0^{\circ}C$로 유지되었다. 또한 온난화 처리에 따른 평균 토양 온도는 온난화 처리구에서 대조구보다 평균 $3.1^{\circ}C$ 높게 나타났다. 강수 증가 및 감소 조절에 따른 평균 토양 수분 함량은 온난화 처리구에서 $P^0W$에 비하여 $P^+W$는 13.9% 증가하고, $P^-W$는 10.0% 감소하였으며, 온난화 대조구 중에서 $P^+C$는 23.7% 증가하고, $P^-C$는 7.6% 감소하였다. 환경요인의 모니터링을 통하여 실외 실험적 온난화와 강수 조절 시스템이 적정하게 설계되고 가동됨을 확인할 수 있었다.

• 한국수자원학회논문집
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• 제53권11호
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• pp.999-1013
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• 2020

전세계적으로 기상조절 연구가 활발히 수행되어져 왔으나 연구 효과를 보다 정량적으로 검증할 수 있는 기술이 필요하다. 본 연구에서는 기상조절 실험에 대한 강수 증가 효율인 시딩효과(seeding effect)를 레이더 자료를 이용하여 검증하였다. 또한, 시딩물질이 대기수상체 변화에 미치는 영향을 분석하였다. 이를 위해 레이더 자료, 기상조건, 확산 수치모의 자료가 사용되었다. 먼저, 시딩전, 시딩중, 시딩후의 세 단계로 시딩효과를 분석할 수 있는 방법을 제안하였다. 제안한 방법을 강원도와 서해 지역을 대상으로 수행된 세 개의 기상조절 실험 사례에 적용하였다. 그 결과, 자연강수가 없을 때는 강수 변화가 예측된 구역에서 감지된 레이더 반사도가 시딩효과로 판단되었다. 자연강수가 발생하면 관측된 최대 반사도에서 자연강수의 영향을 제외하여 시딩효과를 결정하였다. 적용사례에 대해 시딩효과로 강수강도가 0.1 mm/h 증가한 것으로 나타났다. 아울러 시딩 구름에 빙정이나 과냉각 수적, 혼합상의 수상체가 분포한 것으로 나타났다. 이러한 기상조절 연구 결과는 수자원 확보와 구름 물리 연구에 활용할 수 있을 것으로 판단된다.