• 대기
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• 제30권2호
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• pp.183-193
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• 2020

In this study, Yeongdong cold air damming (YCAD) cases that occur in winters have been selected using automatic weather station data of the Yeongdong region of Korea. The vertical and horizontal scales of YCAD were analyzed using rawinsonde and numerical weather model. YCAD occurred in two typical synoptic patterns such that low pressure and trough systems crossing and passing over Korea (low crossing type: LC and low passing type: LP). When the Siberian high does not expand enough to the Korean peninsula, low pressure and trough systems are likely to move over Korea. Eventually this could lead to surface temperature (3.1℃) higher during YCAD than the average in the winter season (1.6℃). The surface temperature during YCAD, however, was decrease by 1.3℃. The cold air layer was elevated around 120 m~450 m for LP-type. For LC-type, the cold layer were found at less than approximately 400 m and over 1,000 m, which could be thought of combined phenomena with synoptic and local weather forcing. The cross-sectional analysis results indicate the accumulation of cold air on the east mountain slope. Additionally, the north or northeasterly winds turned to the northwesterly wind near the coast in all cases. The horizontal wind turning point of LC-type was farther from the top of the mountain (52.2 km~71.5 km) than that of LP-type (20.0 km~43.0 km).

• 대기
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• 제21권2호
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• pp.197-208
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• 2011

The objective of this study is to describe the short-range forecast system of the Korea Air Force (KAF) and to verificate its performace in 2009 summer. The KAF weather prediction model system, based on the Weather Research and Forecasting (WRF) model (i.e., the KAF-WRF), is configured with a parent domain overs East Asia and two nested domains with the finest horizontal grid size of 2 km. Each domain covers the Korean peninsula and South Korea, respectively. The model is integrated for 84 hour 4 times a day with the initial and boundary conditions from National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data. A quantitative verification system is constructed for the East Asia and Korean peninsula domains. Verification variables for the East Asia domain are 500 hPa temperature, wind and geopotential height fields, and the skill score is calculated using the difference between the analysis data from the NCEP GFS model and the forecast data of the KAF-WRF model results. Accuracy of precipitation for the Korean penisula domain is examined using the contingency table that is made of the KAF-WRF model results and the KMA (Korea Meteorological Administraion) AWS (Automatic Weather Station) data. Using the verification system, the operational model and parallel model with updated version of the WRF model and improved physics process are quantitatively evaluated for the 2009 summer. Over the East Aisa region, the parallel experimental model shows the better performance than the operation model. Errors of the experimental model in 500 hPa geopotential height near the Tibetan plateau are smaller than errors in the operational model. Over the Korean peninsula, verification of precipitation prediction skills shows that the performance of the operational model is better than that of the experimental one in simulating light precipitation. However, performance of experimental one is generally better than that of operational one, in prediction.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.43-45
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• 2021

초단기 강수예측 시스템은 단시간 발생하는 집중호우와 같은 위험기상에 대응하기 위해 사회·경제적으로 중요하다. 최근 국내·외에서 심층신경망을 활용한 초단기 강수예측 연구가 활발히 진행되고 있다. 심층신경망을 이용한 강수예측 모델은 훈련 데이터를 만들 때 기상데이터의 구조와 종류가 복잡하고 방대하므로 기상학적 이해를 바탕으로 복잡한 전처리 과정이 필요하다. 또한, 비선형적인 패턴의 강수 현상을 예측하기 위하여 기상의 상호작용에 대한 이해를 바탕으로 입력 데이터를 구성해야 한다. 따라서 본 연구에서는 다음과 같은 접근법을 제안하고자 한다. i) 기상레이더 합성 강수장과 강수발달에 영향을 줄 수 있는 주요 인자(레이더, 지형, 온도, 등)를 훈련 데이터 구축을 위해 패턴 분석에 적합한 형태로 정제하고 이를 구조화하여 통합한다. ii) 합성곱 신경망과 합성곱 장단기 기억 신경망을 접목하여 초단기 예측 강수장을 산출한다. 2020년 강수 사례를 이용하여 제안한 모델의 정확성을 검증하였다. 제안한 모델은 비선형적인 패턴의 강수 현상을 잘 모의하였고, 강수의 규모 및 강도에 대한 예측성능이 향상되었다. 이는 강수를 동반한 초단기 위험기상의 방재에 활용할 수 있을 것으로 기대된다.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.477-484
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• 2009

스마트 의류가 고객 중심으로 다변화 되어가는 생활환경 속에서 날씨정보를 제공하는 것은 서비스 전략의 중요한 성공요소가 되고 있다. 최근에는 스마트 의류의 다양한 어플리케이션이 연구자와 개발자에 의해 제시되고 있다. 그 중 센서 기반의 스마트 의류는 시장에서 가장 수요가 높을 것으로 기대된다. 본 논문에서는 웨어러블 기반의 스마트 모자를 이용한 생활기상지수 모니터링 시스템을 제안하였다. 제안된 스마트 모자를 착용하여, 기상상태를 수집하고 신호를 UMPC로 무선 전송되어 이를 실시간으로 모니터링 할 수 있도록 고안하였다. 센서에 따른 생활기상지수를 제공하기 위해서, 기상지수를 6가지 요소(열지수, 식중독지수, 불쾌지수, 자외선지수, 체감온도지수, 동파가능지수)에 따라 분석하였다. 생활기상지수 모니터링 시스템을 개발하여 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다. 따라서 스마트 의류에서 서비스의 만족도와 질을 향상시켰다.

• 한국지능시스템학회논문지
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• 제24권4호
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• pp.360-365
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• 2014

기상 레이더, 인공위성, 라디오존데 등 날씨 예보를 수행하기 위해 많은 종류의 첨단 장비들이 사용되고 있다. 이들 중에서 지상에 설치된 기상 레이더는 넓은 탐지영역, 높은 시간 및 공간 분해능 등과 같은 많은 장점을 가지고 있기 때문에 기상예보 과정에서 필수적인 장비이다. 이러한 기상 레이더 데이터의 내부에는 기상현상 이외에도 여러 가지 외부 요인에 의해 발생하는 비기상현상이 관측되는데, 이는 기상 예보의 정확도를 감소시키는 원인이 된다. 본 논문에서는 기상 레이더 데이터를 이용한 연구를 통하여 비기상현상이 레이더에 관측되어 에코 형태로 나타난 것들 중에서 선 모양으로 발생하는 비기상에코를 제거하는 방법을 제안한다. 원시 레이더 데이터에서 선에코를 구분하여 그 특성을 추출한 후, 이들을 바탕으로 데이터 페어를 구성하여 나이브 베이지안 분류기를 학습시켰다. 그리고 학습된 나이브 베이지안 분류기를 선에코와 기상에 코가 혼재된 사례에 적용하였다. 실제 사례를 바탕으로 한 실험을 통해서 제안한 나이브 베이지안 분류기가 효과적으로 선에코를 식별할 수 있음을 확인하였다.

• 한국작물학회지
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• 제27권4호
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• pp.291-295
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• 1982

The biosphere of the earth is not only about to overpass the limit to meet the food demand of the world but also the stability of its food production has been also jeopardized by the disasters and pests, especially by the unpredictable weather disasters. In addition the agricultural and industrial pollution against biosphere aggravates the unstability of agricultural production and constitutes a threat in securing the food of the world. In Korea the yield level of crops has been greatly enhanced by the improved agrotechnologies and varietal improvement, but the yield variability due to unfavorable weather events and pests remained unchanged with the change in time. Among weather-related disasters the drought and flood damages has occurred most frequently and impacted most greatly on the agricultural production and its stability. During last decade (1970-l980) the rice production experienced the average annual loss of 0.544 million metric ton which was composed of 0.21 million M/T by climatic disaster, 0.21 million M/T by disease and 0.12 million M/T by insects, and the annual loss of upland crop production from climatic disasters amounted to 0.06 million metric tons. Especially in 1980, the global climatic disasters due to cold or hot temperature endangered the agricultural production all over the world and also the rice production of Korea recorded the unprecedented yield reduction of about 30 percent due to cool summer weather. Nowadays, the unusual weather conditions are prevaling throughout the world, and agro-meteologists predict that the unpredictable cool summer and drought will often attack the rice and other crops in 1980's. To meet the coming weather unstability and to secure the stable crop production, multilateral efforts should be rendered. Therefore, the Korea Society of Crop Science, which commemorates the 20th anniversary of its founding, prepared the symposium on Meteological Stress in Crop Production and its Countermeasures to discuss the decrease in agricultural production due to weather-related disasters and to devise the multilateral counter-measures against the unfavorable weather events.

• The Plant Pathology Journal
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• 제26권1호
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• pp.37-48
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• 2010

This paper describes a web-based information system for plant disease forecast that was developed for crop growers in Gyeonggi-do, Korea. The system generates hourly or daily warnings at the spatial resolution of $240\;m{\times}240\;m$ based on weather data. The system consists of four components including weather data acquisition system, job process system, data storage system, and web service system. The spatial resolution of disease forecast is high enough to estimate daily or hourly infection risks of individual farms, so that farmers can use the forecast information practically in determining if and when fungicides are to be sprayed to control diseases. Currently, forecasting models for blast, sheath blight, and grain rot of rice, and scab and rust of pear are available for the system. As for the spatial interpolation of weather data, the interpolated temperature and relative humidity showed high accuracy as compared with the observed data at the same locations. However, the spatial interpolation of rainfall and leaf wetness events needs to be improved. For rice blast forecasting, 44.5% of infection warnings based on the observed weather data were correctly estimated when the disease forecast was made based on the interpolated weather data. The low accuracy in disease forecast based on the interpolated weather data was mainly due to the failure in estimating leaf wetness events.

• 대기
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• 제27권4호
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• pp.385-398
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• 2017

Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

• 한국환경과학회지
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• 제23권6호
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• pp.1121-1130
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• 2014

This study aims to find the perception and utilization of the citizen about the dryness watch warning (DWW) among special weather reports. For this we have made up a descriptive questionnaire including the perception, utilization of special weather reports. Using the SPSS 17.0 program, descriptive statistics, t-test, ANOVA and Scheffe test were used to analyze the collected data. The results are as follows; The perception of DWW is measured by 4 point Likert scale and the average is $15.97{\pm}3.70$ (percentile=57.0). This value shows that the awareness level is not that high and according to the occupation, college students show the lowest awareness and housewives show the highest awareness. According to the age, the teens and twenties show the lowest awareness and fifties and sixties show the highest awareness. Although the perception of the teens and college students are rather poor, there were many positive answers that it is necessary to establish the advanced disaster prevention plan according to the questionnaire about the utilization of DWW. Therefore, if we come up with an effective plan to improve the perception than we can expect a large-effect in terms of fire and forest fire prevention. The perception of DWW can be improved by providing weather information and weather related education program on TV or internet which have the high level of preference. Also, it is necessary to provide online and offline program of advertising education and disaster management education through the weather forecast bureau which is the host organization of delivering weather information.

• 한국환경과학회지
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• 제29권10호
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• pp.1003-1010
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• 2020

In this study, the necessity for a village unit Automatic Weather System (AWS) was suggested to obtain correct agricultural weather information by comparing the data of AWS of the weather station with the data of AWS installed in agricultural villages 7 km away. The comparison sites are Hyogyo-ri and Hongseong weather station. The seasonal and monthly averaged and cumulative values of data were calculated and compared. The annual time series and correlation was analyzed to determine the tendency of variation in AWS data. The average values of temperature, relative humidity and wind speed were not much different in comparison with each season. The difference in precipitation was ranged from 13.2 to 91.1 mm. The difference in monthly precipitation ranged from 1.2 to 75.4 mm. The correlation coefficient between temperature, humidity and wind speed was ranged from 0.81 to 0.99 and it of temperature was the highest. The correlation coefficient of precipitation was 0.63 and the lowest among the observed elements. Through this study, precipitation at the weather station and village unit area showed the low correlation and the difference for a quantitative comparison, while the elements excluding precipitation showed the high correlation and the similar annual variation pattern.