• 제목/요약/키워드: Meteorological Information

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천리안위성 해수면온도 자료 기반 동북아시아 해수고온탐지(2012-2021) (Marine Heat Waves Detection in Northeast Asia Using COMS/MI and GK-2A/AMI Sea Surface Temperature Data (2012-2021))

  • 우종호;정대성;심수영;김나연;박성우;손은하;김미자;한경수
    • 대한원격탐사학회지
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    • 제39권6_1호
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    • pp.1477-1482
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    • 2023
  • 본 연구는 2012년부터 2021년까지 동북아시아 해역에서 발생한 해수고온현상을 Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager sensor (MI)와 GEO-KOMPSAT-2A (GK-2A)/Advanced Meteorological Imager sensor (AMI) 정지궤도 위성 해수면온도 자료를 통해 탐지하였다. 특히 2018년 이후 및 2020년에 해수고온현상의 빈도와 강도가 눈에 띄게 증가하였음을 발견하였다. Optimal Interpolation Sea Surface Temperature (OISST) 자료와 천리안위성 자료를 활용한 T-test 통계적 검증은 해수면 온도가 통계학적으로 유의미하게 상승했다는 것을 확인시켜 주었으며, 이는 기후 변화의 직접적 영향이라는 결론을 뒷받침한다. 이 연구 결과는 해수고온현상의 지속적인 모니터링과 정밀한 분석의 중요성을 강조한다. 복잡한 지형과 다양한 기후 조건을 가진 동북아시아에서 이루어진 연구는 글로벌 기후 변화가 지역 환경에 미치는 영향을 이해하는 데 있어 중요한 통찰을 제공한다.

관측망 밀도 변화가 기상변수의 공간분포에 미치는 영향: 2019 강원영동 입체적 공동관측 캠페인 (Effects of Observation Network Density Change on Spatial Distribution of Meteorological Variables: Three-Dimensional Meteorological Observation Project in the Yeongdong Region in 2019)

  • 김해민;정종혁;김현욱;박창근;김백조;김승범
    • 대기
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    • 제30권2호
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    • pp.169-181
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    • 2020
  • We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

HYSPLIT 모델을 이용한 김해지역의 PM10 수송 경로 분석 (Analysis on the PM10 Transportation Route in Gimhae Region Using the HYSPLIT Model)

  • 정우식;박종길;이보람;김은별
    • 한국환경과학회지
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    • 제22권8호
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    • pp.1043-1052
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    • 2013
  • This study was conducted to investigate the correlations between the $PM_{10}$ concentration trend and meteorological elements in the Gimhae region and analyze the transportation routes of air pollutants through back-trajectory analysis. Among the air quality measuring stations in the Gimhae regions, the $PM_{10}$ concentration of the Sambangdong station was higher than that of the Dongsangdong station. Also, an examination of the relationships between $PM_{10}$ concentration and meteorological elements showed that the greater the number of yellow dust occurrence days was and the lower the temperature and precipitation were, the higher the $PM_{10}$ concentration appeared. Furthermore, a cluster analysis through the HYSPLIT model showed that there were 4 clusters of trajectories that flowed into the Gimhae region and most of them originated in China. The meteorological characteristics of the four clusters were analyzed and they were similar to those of the air masses that influence South Korea. These analyses found that meteorological conditions affect the $PM_{10}$ concentration.

기상 및 소셜미디어 정보를 활용한 인플루엔자 예측모형 (Influenza prediction models by using meteorological and social media informations)

  • 황은지;나종화
    • Journal of the Korean Data and Information Science Society
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    • 제26권5호
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    • pp.1087-1095
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    • 2015
  • 인플루엔자는 흔히 독감으로 불리는 질병으로 인플루엔자 바이러스가 호흡기 (코, 인후, 기관지, 폐 등)에 감염되어 생기는 병이다. 감기와는 달리 심한 증상을 나타내거나 생명이 위험한 합병증 (폐렴 등)을 유발할 수도 있다. 본 연구에서는 인플루엔자에 대한 예측모형을 다루었으며, 주로 회귀적인 모형을 고려하였다. 기존의 연구들이 주로 기상요인을 예측변수로 사용한 반면, 본 연구에서는 소셜요인의 효과를 살펴보았으며 그 결과 기상요인과 대등한 설명력을 가짐을 확인하였다. 반응변수로는 국민건강보험공단에서 제공하는 인플루엔자 진료건수가 사용되었고, 설명변수에는 기상청에서 제공하는 기상정보와 트위터에서의 인플루엔자 연관키워드 빈도가 사용되었다. 모형의 비교를 위해 시계열 모형도 함께 제시되었다.

기상자료 보간 방법에 의한 GPS기반 가강수량 산출 정확도 분석 (Accuracy Analysis of GPS-derived Precipitable Water Vapor According to Interpolation Methods of Meteorological Data)

  • 김두식;원지혜;김혜인;김경희;박관동
    • Spatial Information Research
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    • 제18권4호
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    • pp.33-41
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    • 2010
  • 우리나라에는 100여개의 GPS 상시관측소가 설치되어 있으나 대략 10개의 관측소만이 GPS 전용 기상센서를 보유하고 있다. 따라서 전국을 대상으로 하는 GPS 가강수량 산출을 위해서는 주변 AWS의 가상자료 보간에 의한 GPS 관측소 기상정보의 생성이 필요하다. 이 연구에서는 가상자료 보간 방법인 역해면경정과 크리깅의 보간 정확도를 분석하였다. 그 결과 역해변경정법의 RMSE가 기압의 경우 약 7배, 기온의 경우 약 2배 더 정확함을 확인하였다. PWV 정확도 분석을 위해 역해면경정법으로 보간된 기상자료와 GPS 관측자료를 이용해 2008년 여름철에 대한 GPS PWV를 산출하였다. 보간 기상 자료를 이용한 GPS PWV를 GPS 전용 기상센서의 값을 사용한 PWV, 라디오존데 PWV와 비교하였다. 비교 결과 보간 기상자료를 이용한 GPS PWV 가 요구 정확도 3mm이내를 만족함을 확인하였다.

Development of typhoon forecasting system using satellite data

  • Ryu, Seung-Ah;Chung, Hyo-Sang;Lee, Yong-Seob;Suh, Ae-Sook
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.127-131
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    • 1999
  • Typhoons were known by contributing to transporting plus heat or kinetic energy from equatorial region to midlatitude region. Due to the strong damage from typhoon, we acknowledged the theoretical study and the importance of accurate forecast about typhoon. In this study, typhoon forecasting system was developed to search the tracks of past typhoons or to display similar track of past typhoon in comparison with the path of current forecasting typhoon. It was programmed using Interactive Data Language(IDL), which was a complete computing environment for the interactive analysis and visualization of data. Typhoon forecasting system was also included satellite image and auxiliary chart. IR, Water Vapor, Visible satellite images helped users analyze an accurate forecast of typhoon. They were further refined the procedures for generating water vapor winds and gave an initial indication of their utility for numerical weather prediction(NWP), in particular for typhoon track forecasting where they could provide important information. They were also available for its utility in typhoon tracer or intensity.

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WRF-UCM (Urban Canopy Model)을 이용한 서울 지역의 도시기상 예보 평가 (Evaluation of Urban Weather Forecast Using WRF-UCM (Urban Canopy Model) Over Seoul)

  • 변재영;최영진;서범근
    • 대기
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    • 제20권1호
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    • pp.13-26
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    • 2010
  • The Urban Canopy Model (UCM) implemented in WRF model is applied to improve urban meteorological forecast for fine-scale (about 1-km horizontal grid spacing) simulations over the city of Seoul. The results of the surface air temperature and wind speed predicted by WRF-UCM model is compared with those of the standard WRF model. The 2-m air temperature and wind speed of the standard WRF are found to be lower than observation, while the nocturnal urban canopy temperature from the WRF-UCM is superior to the surface air temperature from the standard WRF. Although urban canopy temperature (TC) is found to be lower at industrial sites, TC in high-intensity residential areas compares better with surface observation than 2-m temperature. 10-m wind speed is overestimated in urban area, while urban canopy wind (UC) is weaker than observation by the drag effect of the building. The coupled WRF-UCM represents the increase of urban heat from urban effects such as anthropogenic heat and buildings, etc. The study indicates that the WRF-UCM contributes for the improvement of urban weather forecast such nocturnal heat island, especially when an accurate urban information dataset is provided.

Socio-demographic Characteristics and Leading Causes of Death Among the Casualties of Meteorological Events Compared With All-cause Deaths in Korea, 2000-2011

  • Lee, Kyung Eun;Myung, Hyung-Nam;Na, Wonwoong;Jang, Jae-Yeon
    • Journal of Preventive Medicine and Public Health
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    • 제46권5호
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    • pp.261-270
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    • 2013
  • Objectives: This study investigated the socio-demographic characteristics and medical causes of death among meteorological disaster casualties and compared them with deaths from all causes. Methods: Based on the death data provided by the National Statistical Office from 2000 to 2011, the authors analyzed the gender, age, and region of 709 casualties whose external causes were recorded as natural events (X330-X389). Exact matching was applied to compare between deaths from meteorological disasters and all deaths. Results: The total number of deaths for last 12 years was 2 728 505. After exact matching, 642 casualties of meteorological disasters were matched to 6815 all-cause deaths, which were defined as general deaths. The mean age of the meteorological disaster casualties was 51.56, which was lower than that of the general deaths by 17.02 (p<0.001). As for the gender ratio, 62.34% of the meteorological event casualties were male. While 54.09% of the matched all-cause deaths occurred at a medical institution, only 7.6% of casualties from meteorological events did. As for occupation, the rate of those working in agriculture, forestry, and fishery jobs was twice as high in the casualties from meteorological disasters as that in the general deaths (p<0.001). Meteorological disaster-related injuries like drowning were more prevalent in the casualties of meteorological events (57.48%). The rate of amputation and crushing injury in deaths from meteorological disasters was three times as high as in the general deaths Conclusions: The new information gained on the particular characteristics contributing to casualties from meteorological events will be useful for developing prevention policies.

야외활동 의사결정을 위한 가중치 기반 기상정보 분석 알고리즘 (Meteorological Information Analysis Algorithm based on Weight for Outdoor Activity Decision-Making)

  • 이무훈;김민규
    • 디지털융복합연구
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    • 제14권3호
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    • pp.209-217
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    • 2016
  • 최근 경제성장과 더불어 삶의 질이 향상됨에 따라 야외활동이 증가되었으며, 야외활동의 진행여부 의사결정은 기상여건과 밀접한 관계를 갖고 있다. 현재 이러한 야외활동 의사결정은 기상청의 일기예보와 주관적인 경험에 의해 결정되어지고 있다. 따라서, 야외활동 의사결정을 위해 기상정보를 기반으로 객관적 근거를 제시할 수 있는 분석 방법이 필요하다. 논문에서는 데이터마이닝을 기반으로 기상정보를 분석하여 야외활동 의사결정을 지원할 수 있는 기상정보 분석 알고리즘을 제안한다. 또한, 프로야구 일정 히스토리와 자동기상관측장비의 관측 자료를 데이터마이닝의 분류 알고리즘을 적용하여 실험을 수행하고, 제안한 알고리즘의 향상된 성능을 검증하였다.