• 제목/요약/키워드: impact-based forecasts

검색결과 32건 처리시간 0.024초

인지온도 확률예보기반 폭염-건강영향예보 지원시스템 개발 및 2019년 온열질환자를 이용한 평가 (Development of Impact-based Heat Health Warning System Based on Ensemble Forecasts of Perceived Temperature and its Evaluation using Heat-Related Patients in 2019)

  • 강미선;벨로리드 밀로슬라브;김규랑
    • 대기
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    • 제30권2호
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    • pp.195-207
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    • 2020
  • This study aims to introduce the structure of the impact-based heat health warning system on 165 counties in South Korea developed by the National Institute of Meteorological Sciences. This system was developed using the daily maximum perceived temperature (PTmax), which is a human physiology-based thermal comfort index, and the Local ENSemble prediction system for the probability forecasts. Also, A risk matrix proposed by the World Meteorological Organization was employed for the impact-based forecasts of this system. The threshold value of the risk matrix was separately set depending on regions. In this system, the risk level was issued as four levels (GREEN, YELLOW, ORANGE, RED) for first, second, and third forecast lead-day (LD1, LD2, and LD3). The daily risk level issued by the system was evaluated using emergency heat-related patients obtained at six cities, including Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, for LD1 to LD3. The high-risks level occurred more consistently in the shorter lead time (LD3 → LD1) and the performance (rs) was increased from 0.42 (LD3) to 0.45 (LD1) in all cities. Especially, it showed good performance (rs = 0.51) in July and August, when heat stress is highest in South Korea. From an impact-based forecasting perspective, PTmax is one of the most suitable temperature indicators for issuing the health risk warnings by heat in South Korea.

EWMA 피드백 공정 조정에서 이상원인의 영향 (Impact of Special Causes on EWMA Feedback Process Adjustment)

  • 이재준;전상표;이종선
    • 품질경영학회지
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    • 제31권2호
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    • pp.183-193
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    • 2003
  • A special cause producing temporary deviation in the underlying process can influence on process adjustment in responsive feedback control system. In this paper, the impact of special causes on the EWMA(Exponentially Weighted Moving Average) forecasts and the process adjustment that is based on the EWMA forecasts are derived. For some special causes with patterned type of contamination, the influence of the causes on the output process are explicitly investigated. A data set, contaminated by a special cause of level shift, is analyzed to evaluate the impact numerically.

공정 모니터링과 조절에 있어 이상원인의 문제 (Problems of Assignable Causes in Process Monitoring and Adjustment)

  • 이성철;전상표
    • 대한안전경영과학회지
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    • 제2권4호
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    • pp.19-32
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    • 2000
  • Assignable causes producing temporary deviation from the underlying system can influence on process adjustment and process monitoring in dynamic feedback control system. In this paper, the impact of assignable causes on EWMA forecasts and process adjustment which is based on the EWMA forecasts are derived for optimum control methods.

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First-Order System 피드백 공정 조정에서 이상원인의 영향 (Impact of Special Causes on First-Order System Feedback Process Adjustment)

  • 전상표
    • 대한안전경영과학회지
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    • 제9권5호
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    • pp.49-55
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    • 2007
  • A special cause producing temporary deviation in the underlying process can influence on process adjustment in First-Order System feedback control system. In this paper, the impact of special causes on the forecasts and the process adjustment that is based on the EWMA forecasts are derived for a first-order system. For some special causes with patterned type of contamination, the influence of the causes on the output process are explicitly investigated. A data set, contaminated by a special cause of level shift, is analyzed to confirm the impact numerically.

적설의 동질지역 구분과 지역 차등화 (Homogeneous Regions Classification and Regional Differentiation of Snowfall)

  • 김현욱;심재관;최병철
    • 한국지리정보학회지
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    • 제20권3호
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    • pp.42-51
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    • 2017
  • 대설은 우리나라의 법적 자연재해 중 하나이다. 최근 기상현상에 의한 사회경제적 영향력을 함께 예보하는 영향예보가 부각되고 있으며, 이를 위해서는 먼저 각 지역의 기후적 특징을 분석할 필요가 있다. 본 연구에서는 영향예보의 기반마련을 위해 자기조직화지도를 활용하여 적설동질지역을 구분하여 지역별 적설 특징을 분석했다. 연구결과 적설동질지역은 7개 군집으로 나타났으며, 강설량 및 관측일수, 최대강설량을 이용하여 각 그룹의 특징을 구분했다. 대관령, 강릉시, 정읍시는 강설량이 많은 지역으로, 경상도는 강설량이 적은 지역으로 구분되었다. 선행연구와 비교결과 대표적인 지역이 잘 구분되었으나 강설의 특징은 차이가 있는 것으로 나타났다. 본 연구의 결과는 각 지역의 영향예보를 위한 정책결정에 기초자료로 활용될 수 있다.

고해상도 KMAPP 자료를 활용한 제주국제공항에서 저층 윈드시어 예측 (Low-Level Wind Shear (LLWS) Forecasts at Jeju International Airport using the KMAPP)

  • 민병훈;김연희;최희욱;정형세;김규랑;김승범
    • 대기
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    • 제30권3호
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    • pp.277-291
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    • 2020
  • Low-level wind shear (LLWS) events on glide path at Jeju International Airport (CJU) are evaluated using the Aircraft Meteorological Data Relay (AMDAR) and Korea Meteorological Administration Post-Processing (KMAPP) with 100 m spatial resolution. LLWS that occurs in the complex terrains such as Mt. Halla on the Jeju Island affects directly aircraft approaching to and/or departing from the CJU. For this reason, accurate prediction of LLWS events is important in the CJU. Therefore, the use of high-resolution Numerical Weather Prediction (NWP)-based forecasts is necessary to cover and resolve these small-scale LLWS events. The LLWS forecasts based on the KMAPP along the glide paths heading to the CJU is developed and evaluated using the AMDAR observation data. The KMAPP-LLWS developed in this paper successfully detected the moderate-or-greater wind shear (strong than 5 knots per 100 feet) occurred on the glide paths at CJU. In particular, this wind shear prediction system showed better performance than conventional 1-D column-based wind shear forecast.

한반도에 발생한 위험 기상 사례에 대한 관측 민감도 분석 (Forecast Sensitivity to Observations for High-Impact Weather Events in the Korean Peninsula)

  • 김세현;김현미;김은정;신현철
    • 대기
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    • 제23권2호
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    • pp.171-186
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    • 2013
  • Recently, the number of observations used in a data assimilation system is increasing due to the enormous amount of observations, including satellite data. However, it is not clear that all of these observations are always beneficial to the performance of the numerical weather prediction (NWP). Therefore, it is important to evaluate the effect of observations on these forecasts so that the observations can be used more usefully in NWP process. In this study, the adjoint-based Forecast Sensitivity to Observation (FSO) method with the KMA Unified Model (UM) is applied to two high-impact weather events which occurred in summer and winter in Korea in an effort to investigate the effects of observations on the forecasts of these events. The total dry energy norm is used as a response function to calculate the adjoint sensitivity. For the summer case, TEMP observations have the greatest total impact while BOGUS shows the greatest impact per observation for all of the 24-, 36-, and 48-hour forecasts. For the winter case, aircraft, ATOVS, and ESA have the greatest total impact for the 24-, 36-, and 48-hour forecasts respectively, while ESA has the greatest impact per observation. Most of the observation effects are horizontally located upwind or in the vicinity of the Korean peninsula. The fraction of beneficial observations is less than 50%, which is less than the results in previous studies. As an additional experiment, the total moist energy norm is used as a response function to measure the sensitivity of 24-hour forecast error to observations. The characteristics of the observation impact with the moist energy response function are generally similar to those with the dry energy response function. However, the ATOVS observations were found to be sensitive to the response function, showing a positive (a negative) effect on the forecast when using the dry (moist) norm for the summer case. For the winter case, the dry and moist energy norm experiments show very similar results because the adjoint of KMA UM does not calculate the specific humidity of ice properly such that the dry and moist energy norms are very similar except for the humidity in air that is very low in winter.

차량 전도 위험 영향 평가를 위한 도로 취약성 기준 산정에 관한 연구 (A Study on Estimation of Road Vulnerability Criteria for Vehicle Overturning Hazard Impact Assessment)

  • 추경수;강동호;김병식;송인재
    • 한국방재안전학회논문집
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    • 제16권2호
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    • pp.49-56
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    • 2023
  • 영향예보는 기존의 기상요소 중심의 예보에서 벗어나 기상상황에 따른 잠재적 사회경제적 위험도 정보를 함께 제공하는 것을 의미한다. 기상 선진국들은 영향정보 제공 및 확산을 위한 기술개발에 인력과 재정을 투입하고 있지만 국내에서는 영향예보에 대한 인식이 확산되어 있지 않다. 또한 영향예보 피해가 많이 발생하는 홍수, 태풍 등의 재난에 초점이 맞춰져 있으며 상대적으로 피해발생이 적은 교통 분야의 강풍으로 인한 차량 위험 영향 평가에 대한 연구는 부족한 실정이다. 국내에서는 강풍으로 인한 차량 전도에 대한 피해 사례는 많이 없지만 과거 피해 사례가 존재하며 연구에 대한 필요성이 높아지고 있다. 강풍으로 인한 차량의 위험(Risk) 평가를 위해서는 도로의 취약성(Vulnerability)이 필요하며 본 연구에서는 도로의 취약성 기준을 산정하는 것을 목적으로 하였다. 도로의 취약성 평가는 도로의 고도, 차선 수, 도로 유형으로 평가하였다. 분석결과 사고사례가 있던 지역의 취약성 지역을 잘 재현하는 것으로 나타났다. 본 연구의 성과를 이용하여 차량 운전자에게 잠재적 위험에 대한 객관적인 평가 마련에 대한 기준으로 활용할 수 있을 것이라 판단된다.

한국형 태풍 영향예보 구축을 위한 연구 -현황 및 구성- (Construction of Typhoon Impact Based Forecast in Korea -Current Status and Composition-)

  • 나하나;정우식
    • 한국환경과학회지
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    • 제32권8호
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    • pp.543-553
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    • 2023
  • Weather forecasts and advisories provided by the national organizations in Korea that are used to identify and prevent disaster associated damage are often ineffective in reducing disasters as they only focus on predicting weather events (World Meteorological Organization(WMO ), 2015). In particular, typhoons are not a single weather disaster, but a complex weather disaster that requires advance preparation and assessment, and the WMO has established guidelines for the impact forecasting and recommends typhoon impact forecasting. In this study, we introduced the Typhoon-Ready System, which is a system that produces pre-disaster prevention information(risk level) of typhoon-related disasters across Korea and in detail for each region in advance, to be used for reducing and preventingtyphoon-related damage in Korea.

Extended Forecasts of a Stock Index using Learning Techniques : A Study of Predictive Granularity and Input Diversity

  • ;이동윤
    • Asia pacific journal of information systems
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    • 제7권1호
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    • pp.67-83
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    • 1997
  • The utility of learning techniques in investment analysis has been demonstrated in many areas, ranging from forecasting individual stocks to entire market indexes. To date, however, the application of artificial intelligence to financial forecasting has focused largely on short predictive horizons. Usually the forecast window is a single period ahead; if the input data involve daily observations, the forecast is for one day ahead; if monthly observations, then a month ahead; and so on. Thus far little work has been conducted on the efficacy of long-term prediction involving multiperiod forecasting. This paper examines the impact of alternative procedures for extended prediction using knowledge discovery techniques. One dimension in the study involves temporal granularity: a single jump from the present period to the end of the forecast window versus a web of short-term forecasts involving a sequence of single-period predictions. Another parameter relates to the numerosity of input variables: a technical approach involving only lagged observations of the target variable versus a fundamental approach involving multiple variables. The dual possibilities along each of the granularity and numerosity dimensions entail a total of 4 models. These models are first evaluated using neural networks, then compared against a multi-input jump model using case based reasoning. The computational models are examined in the context of forecasting the S&P 500 index.

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