• Title/Summary/Keyword: 기후예측

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Comparative assessment of frost event prediction models using logistic regression, random forest, and LSTM networks (로지스틱 회귀, 랜덤포레스트, LSTM 기법을 활용한 서리예측모형 평가)

  • Chun, Jong Ahn;Lee, Hyun-Ju;Im, Seul-Hee;Kim, Daeha;Baek, Sang-Soo
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.667-680
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    • 2021
  • We investigated changes in frost days and frost-free periods and to comparatively assess frost event prediction models developed using logistic regression (LR), random forest (RF), and long short-term memory (LSTM) networks. The meteorological variables for the model development were collected from the Suwon, Cheongju, and Gwangju stations for the period of 1973-2019 for spring (March - May) and fall (September - November). The developed models were then evaluated by Precision, Recall, and f-1 score and graphical evaluation methods such as AUC and reliability diagram. The results showed that significant decreases (significance level of 0.01) in the frequencies of frost days were at the three stations in both spring and fall. Overall, the evaluation metrics showed that the performance of RF was highest, while that of LSTM was lowest. Despite higher AUC values (above 0.9) were found at the three stations, reliability diagrams showed inconsistent reliability. A further study is suggested on the improvement of the predictability of both frost events and the first and last frost days by the frost event prediction models and reliability of the models. It would be beneficial to replicate this study at more stations in other regions.

Rainfall Prediction using the QPM by Province of the Korean Peninsula (고해상도 강수량 진단 모형(QPM)을 이용한 한반도 도별 강수 예측)

  • Kim, Ji-Hye;Oh, Jai-Ho;Jung, Yoo-Rim;Her, Mo-Rang
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.34-34
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    • 2011
  • 최근 우리나라에서는 기상이변과 기후변화에 의한 국지성 집중호우의 발생으로 인해 인명 및 재산 피해가 증가하는 추세이다. 따라서 이러한 기상현상을 좀 더 정확하게 예측하고 이를 대응하고자 악기상 모형의 개발과 구축 및 활용에 대한 연구들이 활발하게 진행 중에 있다. GCM이 제공하고 있는 많은 유용한 정보에도 불구하고 대부분의 모델이 시 공간 분해능과 물리 과정의 한계점으로 인해 지역적인 기후 특성이나 변화를 예측하기에는 많은 문제점들이 나타나고 있다. GCM의 한계점을 극복하기 위한 방법으로 세밀한 규모의 기후 정보를 얻기 위해 복잡한 지형과 해안선, 호수, 식생, 지표특성과 같은 아격자 규모의 강제 효과를 반영할 수 있는 고해상도 지역 기후 모델(Regional Climate Model, RCM)의 필요성이 제기되었다. 본 연구에서는 전지구 20km 격자자료를 입력장으로 하여 8km 격자로 한반도를 포함하는 도메인에 대해 비정역학 완전 압축성 중규모 모델인 WRF를 이용하여 상세예측자료를 생산하고자 하였다. 강수 예측의 경우 돌발적으로 발생하는 경우가 많아, 이를 예측하기 위해서는 상세한 강수량 정보를 빠른 시간 내에 정확히 제공할 수 있는 모델을 사용하여야 한다. 강수의 경우 온도와는 달리 공간적 편차가 매우 커 지역적으로 정확한 강수량을 예측 하는데 어려움이 있다. 상세강수 예측을 위해 미세 격자 규모의 비 정역학 모형을 사용할 경우 계산양이 매우 늘어나기 때문에 장시간의 모형 적분 시간뿐 아니라, 상당한 컴퓨터 자원을 필요로 하므로 이에 대한 대안으로 지형효과를 포함한 강수량 진단 모형인 QPM(Quantitative Precipitation Model)을 사용하였다. 최종적으로 한반도의 복잡한 지형적 영향을 반영하기 위해 1 km의 수평해상도를 가지는 고해상도 강수량 진단 모형(QPM)과 상세한 지리적, 공간적 분석을 할 수 있는 ARCGIS를 이용하여 한반도 도별 상세 강수자료를 생산하고자 한다.

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One-month lead dam inflow forecast using climate indices based on tele-connection (원격상관 기후지수를 활용한 1개월 선행 댐유입량 예측)

  • Cho, Jaepil;Jung, Il Won;Kim, Chul Gyium;Kim, Tae Guk
    • Journal of Korea Water Resources Association
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    • v.49 no.5
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    • pp.361-372
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    • 2016
  • Reliable long-term dam inflow prediction is necessary for efficient multi-purpose dam operation in changing climate. Since 2000s the teleconnection between global climate indices (e.g., ENSO) and local hydroclimate regimes have been widely recognized throughout the world. To date many hydrologists focus on predicting future hydrologic conditions using lag teleconnection between streamflow and climate indices. This study investigated the utility of teleconneciton for predicting dam inflow with 1-month lead time at Andong dam basin. To this end 40 global climate indices from NOAA were employed to identify potential predictors of dam inflow, areal averaged precipitation, temperature of Andong dam basin. This study compared three different approaches; 1) dam inflow prediction using SWAT model based on teleconneciton-based precipitation and temperature forecast (SWAT-Forecasted), 2) dam inflow prediction using teleconneciton between dam inflow and climate indices (CIR-Forecasted), and 3) dam inflow prediction based on the rank of current observation in the historical dam inflow (Rank-Observed). Our results demonstrated that CIR-Forecasted showed better predictability than the other approaches, except in December. This is because uncertainties attributed to temporal downscaling from monthly to daily for precipitation and temperature forecasts and hydrologic modeling using SWAT can be ignored from dam inflow forecast through CIR-Forecasted approach. This study indicates that 1-month lead dam inflow forecast based on teleconneciton could provide useful information on Andong dam operation.

Measurement of Time-Varying Failure Rate for Power Distribution System Equipment Considering Weather Factor (기후인자를 고려한 배전계통 설비의 시변 고장률 추정)

  • Kim, Jae-Chul
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.8
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    • pp.14-20
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    • 2009
  • In this paper, the time-varying failure rate to consider climate effect was extracted. Even if the same kind of equipments is estimated for extracting the time-varying failure rate, the failure rates could be different depending on external effect such as climate. With the consequence, the failure rate extracted to consider the climate effect is necessary for using the failure rate on the optimal investment plan or asset management, To consider the characteristic of climate effects(Classified into 5 categories, heavy rain, thunderbolt, strong wind, tidal waves, no character), the survey of officers charging the operation of equipment in KEPCO branch office was done. With this consequence, this paper suggest the failure rate extraction method to consider the climate effect analyzed by the survey.

Assessing the Effects of Climate Change on Irrigation Water Requirement for Corn in Zimbabwe (기후변화가 짐바브웨 옥수수 필요수량에 미치는 영향 평가)

  • Nkomozepi, Temba;Chung, Sang-Ok
    • Journal of The Korean Society of Agricultural Engineers
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    • v.53 no.1
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    • pp.47-55
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    • 2011
  • 기후변화는 피할 수 없으며 다음 세기에도 계속될 것이다. 이는 생태계와 토지와 물과 같은 자연자원의 이용에도 영향을 미칠 것이다. 연구 결과에 의하면 아프리카는 낮은 경제수준과 지역적 다양성으로 인하여 기후변화에 가장 취약한 지역 중의 하나이다. 짐바브웨는 한계농지가 황폐화가 되는 등 농업분야가 특히 기후변화에 취약하다. 본 논문에서는 짐바브웨의 주요 옥수수 재배지역에 대하여 기후변화가 옥수수의 필요수량에 미치는 영향을 공간적 및 시간적으로 분석하였다. 미래 기후예측은 HadCM3 전지구 모형 결과에 change factor를 곱하여 추정하였다. 배출가스 시나리오는 A2b 및 B2a를 선정하였고, 시간대는 2020s, 2050s 및 2080s 각각 30년간에 대하여 분석하였다. 기준작물 증발산량은 Penman-Monteith 공식으로, 순관개량은 CROPWAT 모형을 이용하여 구하였다. 순관개량의 공간적인 분석은 GIS를 이용하였다. 분석 결과 대상지역은 강우량이 감소하고 관개의 필요성이 크게 증가할 것으로 나타났다. 2080s의 필요수량은 기준년도 (1961-1990)에 비하여 93 내지 115 % 증가할 것으로 예측되었다. 이 증가는 기온의 증가와 강우량의 감소에 기인한다. 대상 지역에 대한 기후변화 대응 전략 수립과 영향 저감대책에 대한 추가적인 연구가 필요하다고 하겠다.

Estimation of groundwater content by climate change (기후변화에 의한 지하수 함양량 추정)

  • Choi, Gwang Bok;Park, Ki Bum;Ahn, Seung Seop
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.273-273
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    • 2021
  • 기후변화는 미래세대의 문제뿐만 아니라 현재를 살고 있는 우리들에게도 매우 심각한 화두가 되고 있다. 또한 OECD 환경전망 2050 보고서를 비롯한 많은 연구에서 온실가스 증가로 인한 지구 평균기온 상승을 경고하고 있다. 평균기온 상승은 강우패턴의 변화를 일으켜 극한기후상황인 가뭄, 폭염, 홍수 등의 증가로 이어지며, 많은 피해가 예상된다. 우리나라 연평균기온은 1981년~2010년 1.2℃ 상승 했으며, RCP8.5 시나리오에서는 2100년경 4.7℃ 증가하는 것으로 전망된다. 이로 인해 열대야일수, 폭염일수, 여름일수와 같은 극한지수가 증가하고 강수량 변동이 매우 클 것으로 예상되며, 가뭄관련 최대무강수 지속기간도 길어지며, 극심한 물부족이 예상된다. 따라서 가뭄 재해를 대비하고, 지하수의 활용에 대한 계획 수립에 바탕이 되는 연구가 필요하다. 본 연구에서는 기후변화에 의한 가뭄기간 동안의 지하수위 변동 특성을 예측하고자 한다. 기후변화 예측은 IPCC 대표농도경로 RCP2.6, RCP4.5, RCP6.0, RCP8.5 시나리오에 의한 기상청의 미래 기후전망 프로그램을 활용하여 경주지역의 2021년~2100년 까지의 평균기온, 강수량을 분석하였다. 연구대상 유역의 도시개발계획을 조사하고 장래 토지피복도를 추정하여 SWAT모형에 적용하여 지하수 함양에 영향을 미칠 수 있는 인자들에 대한 보정 및 모델링을 실시하여 장래 기후변화에 의한 지하수 함양량을 추정하였다.

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Prediction of Shift in Fish Distributions in the Geum River Watershed under Climate Change (기후변화에 따른 금강 유역의 어류 종분포 변화 예측)

  • Bae, Eunhye;Jung, Jinho
    • Ecology and Resilient Infrastructure
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    • v.2 no.3
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    • pp.198-205
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    • 2015
  • Impacts of climate change on aquatic ecosystems range from changes in physiological processes of aquatic organisms to species distribution. In this study, MaxEnt that has high prediction power without nonoccurrence data was used to simulate fish distribution changes in the Geum river watershed according to climate change. The fish distribution in 2050 and 2100 was predicted with RCP 8.5 climate change scenario using fish occurrence data (a total of 47 species, including 17 endemic species) from 2007 to 2009 at 134 survey points and 9 environmental variables (monthly lowest, highest and average air temperature, monthly precipitation, monthly lowest, highest and average water temperature, altitude and slope). The fitness of MaxEnt modeling was successful with the area under the relative operating characteristic curve (AUC) of 0.798, and environmental variables that showed a high level of prediction were as follows: altitude, monthly average precipitation and monthly lowest water temperature. As climate change proceeds until 2100, the probability of occurrence for Odontobutis interrupta and Acheilognathus yamatsuatea (endemic species) decreases whereas the probability of occurrence for Microphysogobio yaluensis and Lepomis macrochirus (exotic species) increases. In particular, five fish species (Gnathopogon strigatus, Misgurnus mizolepis, Erythroculter erythropterus, A. yamatsuatea and A. koreensis) were expected to become extinct in the Geum river watershed in 2100. In addition, the species rich area was expected to move to the northern part of the Geum river watershed. These findings suggest that water temperature increase caused by climate change may disturb the aquatic ecosystem of Geum river watershed significantly.

Estimating the Change of Potential Forest Distribution and Carton Stock by Climate Changes - Focused on Forest in Yongin-City - (기후변화에 따른 임상분포 변화 및 탄소저장량 예측 - 용인시 산림을 기반으로 -)

  • Jeong, Hyeon yong;Lee, Woo-Kyun;Nam, Kijun;Kim, Moonil
    • Journal of Climate Change Research
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    • v.4 no.2
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    • pp.177-188
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    • 2013
  • In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

Estimation of Waxy Corn Harvest Date over South Korea Using PNU CGCM-WRF Chain (PNU CGCM-WRF Chain을 활용한 남한지역 찰옥수수 수확일 추정)

  • Hur, Jina;Kim, Yong Seok;Jo, Sera;Shim, Kyo Moon;Ahn, Joong-Bae;Choi, Myeong-Ju;Kim, Young-Hyun;Kang, Mingu;Choi, Won Jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.405-414
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    • 2021
  • This study predicted waxy corn harvest date in South Korea using 30-year (1991-2020) hindcasts (1-6 month lead) produced by the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. To estimate corn harvest date, the cumulative temperature is used, which accumulated the daily observed and predicted temperatures from the seeding date (5 April) to the reference temperature (1,650~2,200℃) for harvest. In terms of the mean air temperature, the hindcasts with a bias correction (20.2℃) tends to have a cold bias of about 0.1℃ for the 6 months (April to September) compared to the observation (20.3℃). The harvest date derived from bias-corrected hindcasts (DOY 187~210) well simulates one from observation (DOY 188~211), despite a slight margin of 1.1~1.3 days. The study shows the possibility of obtaining the gridded (5 km) daily temperature and corn harvest date information based on the cumulative temperature in advance for all regions of South Korea.

An Analysis of Decision-Making in Extreme Weather using an ABM Approach Application of Mode Choice in Heavy Rain & Heavy Snow (극한기후 시 의사결정 변화를 고려한 ABM 연구 - 폭우.폭설 시 교통수단 선택을 사례로 -)

  • Na, Yu-Gyung;Lee, Seung-Ho;Joh, Chang-Hyeon
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.2
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    • pp.304-313
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    • 2012
  • Uncertainty increases as a result of environment change and change of individual decision-making in extreme weather. This study consider individual decision-making which has been not covered until now. The purpose of this study is making Agent-Based Model to predict it more accurate that how much change travel demand in heavy rain and heavy snow. Through this model, it can be utilized to forecast travel demand, changes in travel behavior and traffic patterns. It will be also possible to predict discomfort index and risk of accidents.

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