• 대기
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• 제18권4호
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• pp.441-458
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• 2008

A TP/WVP-3000A, ground-based microwave radiometer, that was first introduced to South Korea has been operated since August 22, 2007 at the National Center for Intensive Observation of Severe Weathers (NCIO). Using the dual-band, the radiometer provides temperature and humidity soundings from the surface up to 10 km height with the high-temporal resolution of a few minutes. In this study, the performance of the radiometer on the predictability of the high impact weathers was evaluated and various practical applications were investigated. To verify the retrieved profile data from the radiometer, temperature and relative humidity soundings are compared with those from the rawinsonde launched at the NCIO and Gwangju station. The root mean squared errors for temperature and relative humidity soundings were smaller under rainy weather conditions. The correlation coefficient between PWVs (Precipitable Water Vapors) obtained from the radiometer and Global Positioning System satellite at Mokpo station is 0.92 on average. In order to investigate the structure and characteristics of precipitation, stability indexes related to rainfall such as the Convective Available Potential Energy (CAPE), K-index, and Storm RElative Helicity (SREH) were calculated using windprofiler at the NCIO from 14 to 16 September, 2007. CAPE and K-index tended to be large when the thermodynamic unstability was strong. On the other hand, SREH index was dominantly large when the dynamic unstability was strong due to the passage of the typhoon 'Nari'.

• 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 (r_s) was increased from 0.42 (LD3) to 0.45 (LD1) in all cities. Especially, it showed good performance (r_s = 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.

• 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.

• 한국수자원학회논문집
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• 제52권2호
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• pp.125-132
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• 2019

본 연구에서는 기존의 정량적인 강수량 정보를 제공하는 방식에서 벗어나 호우발생에 따른 생활환경의 변화에 끼치는 영향을 고려한 호우영향예보서비스의 필요성을 기반으로 호우위험영향도 평가가 가능한 호우재해 위험영향 매트릭스를 개발하고, 이를 통해 호우위험영향을 평가하는 방법을 제시하였다. 사당동 일대를 대상으로 실제 발생 호우사상(2011년 7월 27일)을 적용하였으며, 호우에 의한 침수로 영향을 받는 대상별(사람, 교통, 시설) 호우위험영향평가를 수행하였다. 이를 위해 1 km 격자기반으로 호우위험정도(Impact Level)를 산정하고, 침수심 결과를 조합하여 격자기반의 잠재호우위험영향(Potential Risk Impact)을 산정하였다. 여기에 강우발생가능성 Likelihood와의 조합을 통해 호우영향예보가 가능한 호우위험영향(Heavy Rainfall Risk Impact) 값을 산정하여 사당동 지역의 호우영향정도를 격자기반으로 4개의 등급으로 분석, 제시하였다.

• 한국환경과학회지
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• 제30권12호
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• pp.1053-1065
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• 2021

In this study, the prediction technology of Hydrological Quantitative Precipitation Forecast (HQPF) was improved by optimizing the weather predictors used as input data for machine learning. Results comparison was conducted using bias and Root Mean Square Error (RMSE), which are predictive accuracy verification indicators, based on the heavy rain case on August 21, 2021. By comparing the rainfall simulated using the improved HQPF and the observed accumulated rainfall, it was revealed that all HQPFs (conventional HQPF and improved HQPF 1 and HQPF 2) showed a decrease in rainfall as the lead time increased for the entire grid region. Hence, the difference from the observed rainfall increased. In the accumulated rainfall evaluation due to the reduction of input factors, compared to the existing HQPF, improved HQPF 1 and 2 predicted a larger accumulated rainfall. Furthermore, HQPF 2 used the lowest number of input factors and simulated more accumulated rainfall than that projected by conventional HQPF and HQPF 1. By improving the performance of conventional machine learning despite using lesser variables, the preprocessing period and model execution time can be reduced, thereby contributing to model optimization. As an additional advanced method of HQPF 1 and 2 mentioned above, a simulated analysis of the Local ENsemble prediction System (LENS) ensemble member and low pressure, one of the observed meteorological factors, was analyzed. Based on the results of this study, if we select for the positively performing ensemble members based on the heavy rain characteristics of Korea or apply additional weights differently for each ensemble member, the prediction accuracy is expected to increase.

• 대한토목학회논문집
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• 제37권3호
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• pp.593-601
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• 2017

우리나라는 1970년 이후 급격한 산업발달로 인해 도시의 팽창과 집중현상, 그리고 자동차등록대수의 증가로 교통량이 증가하게 됨으로써 교통의 지정체, 주차문제와 같은 다양한 교통문제가 야기되고 있는 실정이다. 특히, 이웃주민과의 다툼 등 사회적 문제로도 제기되고 있는 주차문제를 해결하기 위해 주차장 설치 및 관리에 관한 시행령 및 규칙을 재정하여 운영하고 있으나, 시설별 용도의 다양성과 복합적인 기능으로 인해 탄력적인 법정주차면 산정에는 그 한계를 내포하고 있다. 이에 본 연구에서는 주차면 공급에 법정주차대수 및 평균 원단위를 이용한 주차수요예측방법의 단점을 보완하기 위해 기존의 연구문헌 고찰을 통해 변수를 선정하여, 변수에 따른 현장조사 자료를 수집하고 주차수요에 영향을 미치는 요인을 다중회귀분석을 통해 적정 주차면을 산정하였으며, 누적주차대수를 기준으로 평균 원단위로 산정된 주차면과 예측모형으로 산정된 주차면을 비교하였다. 그 결과, 평균원단위법으로 산정된 주차면은 누적주차대수보다 9.99% 더 적게 산정되었고, 모형식을 활용한 주차면의 경우에는 4.37% 더 많게 산정되었다. 이는 주차면 산정방식에 있어서 주차면 예측모형이 보다 더 효율적임을 알 수 있다. 본 연구에서 구축한 주차면 산정 모형은 주차수요에 영향을 미칠 수 있는 다양한 환경 요인들을 고려하게 됨으로써, 지역의 특성에 맞는 현실적인 주차수요 예측이 가능하게 되었고, 효율적인 주차면의 공급이 이루어질 수 있을 것으로 판단된다.

• 대기
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• 제30권2호
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• 지적과 국토정보
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• 제47권1호
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• pp.37-51
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• 2017

호우 예측 정확도의 향상에도 불구하고 호우재해로 인한 사회경제적 비용이 지속적으로 증가하고 있는 것은 기상이 미치는 영향에 대한 이해의 부족 때문이다. 본 연구에서는 WMO에서 제시한 영향예보 핵심개념인 재해, 취약성, 노출 개념을 활용하여 지역별 호우잠재영향을 평가하고 호우발생과 연계하여 호우재해의 위험도를 분석하였다. 노출과 취약성 변수로 호우잠재영향을 구성하였고, 호우재해지수는 호우특보 기준에 따라 선정한 3개의 변수를 선정하여 산정하였다. 호우잠재영향 지수의 가중치는 주성분분석을 이용하여 산정하였으며, 호우재해지수는 동일한 가중치를 부여하여 산정하였다. 호우잠재영향지수와 실제 호우피해액과의 상관분석 결과 높은 상관관계가 증명되어 호우잠재영향지수는 실제의 피해양상을 적절히 반영하고 있음을 확인할 수 있었다. 호우재해위험도는 호우잠재영향지수와 호우재해지수로 구성된 위험도 매트릭스를 이용하여 산정하였다. 본 연구는 시공간적으로 변화하는 호우예특보를 위한 호우영향분석 연구의 토대를 제공하고 지역별 호우방재대책을 수립하는데 유용한 자료로 활용될 수 있을 것이다.

• 대기
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• 제23권3호
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• pp.321-329
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• 2013

This study examines the effect of aerosols on the vertical invigoration of continental stratiform clouds, using a dataset of Atmospheric Radiation Measurement (ARM) Intensive Operational Period (IOP, March 2000) at the Southern Great Plains (SGP) site. To provide further support to our observation-based findings, the weather research and forecasting (WRF) sensitivity simulations with changing cloud condensation nuclei (CCN) concentrations have been carried out for the golden episode over SGP. First, cross correlation between observed aerosol scattering coefficient and cloud liquid water path (LWP) with a 160-minutes lag is the highest of r = 0.83 for the selected episode, which may be attributable to cloud vertical invigoration induced by an increase in aerosol loading. Modeled cloud fractions in a control run are well matched with the observation in the perspective of cloud morphology and lasting period. It is also found through a simple sensitivity with a change in CCN that aerosol invigoration (AIV) effect on stratiform cloud organization is attributable to a change in the cloud microphysics as well as dynamics such as the corresponding modification of cloud number concentrations, drop size, and latent heating rate, etc. This study suggests a possible cloud vertical invigoration even in the continental stratiform clouds due to aerosol enhancement in spite of a limited analysis based on a few observed continental cloud cases.

• 한국대기환경학회지
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• 제25권2호
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• pp.167-174
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• 2009

The AIRWARE System was developed from one of the EUREKA PROJECT E!3266-EUROENVIRON WEBAIR System. The AIRWARE can nowcast and forecast the air quality of Seoul and Gyeonggi-do regions. To nowcast and forecast concentration of pollutants, MM5, AERMOD/CAMx, and SMOKE Models were used for each meteorologic data, measured data, and emission data. All DB were constructed for 2001 year. The episode analysis and time series analysis were accomplished to analyze the AIRWARE reliability. The simulated results were very well agreed with measured result for measured pollutants and meteorological data. The developed AIRWARE system can analyze with real-time, support web-based air quality information. This information can used with policy data to manage the air quality and prepare reduction plan in air impact assessment or air environmental plan.