• Title/Summary/Keyword: Meteorological disaster

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Traits of Agro-meteorological Disasters in 20th Century Korea (20세기 한국의 농업기상재해 특징)

  • 심교문;이정택;이양수;김건엽
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.5 no.4
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    • pp.255-260
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    • 2003
  • Recently, both climate change and unusual meteorological disasters are becoming a more frequent and serious threat to agricultural production. Destruction of the stabilizing base of agricultural productivity in Korea is a concern. This study provides basic information for stabilizing agricultural production by clarifying and analyzing the features of agro-meteorological disasters which have occurred recently in Korea. The occurrence of meteorological disasters has increased rapidly since the 1940s. A 19-fold increase in occurrence is noted over the past 60 years from 1941 to 2000. Meteorological disasters occurred mostly in August, then in July, and least often in October, In terms of regional occurrences, the frequency of meteorological disasters was the highest in Gangwon (751 times) and in Jeonnam (703 times) provinces, and the lowest in Jeju (459 times) province for the 97 years from 1904 to 2000. Agro-meteorological disasters which caused the most serious damage to cropland were rain storms and typhoons for the 10 years from 1991 to 2000, and they occurred 52 and 18 times during this period, respectively. Agro-meteorological disasters occurred mainly during the summer season (from June to September) when major crops are cultivated in Korea.

Estimation on the Power Spectral Densities of Daily Instantaneous Maximum Fluctuation Wind Velocity (변동풍속의 파워 스펙트럴 밀도에 관한 평가)

  • Oh, Jong Seop
    • Journal of Korean Society of Disaster and Security
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    • v.10 no.2
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    • pp.21-28
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    • 2017
  • Wind turbulence data is required for engineering calculations of gust speeds, mean and fluctuating loading. Spectral densities are required as input data for methods used in assessing dynamic response. This study is concerned with the estimation of daily instantaneous maximum wind velocity in the meteorological major cities (selected each 6 points) during the yearly 1987-2016.12.1. The purpose of this paper is to present the power spectral densities of the daily instantaneous maximum wind velocity. In the processes of analysis, used observations data obtained at Korea Meteorological Adminstration(KMA), it is assumed as a random processes. From the analysis results, in the paper estimated power spectral densities function(Blunt model) shows a very closed with von Karman and Solari's spectrum models.

Construction of Agricultural Meteorological Data by the New Climate Change Scenario for Forecasting Agricultural Disaster - For 111 Agriculture Major Station - (농업재해 예측을 위한 신 기후변화 시나리오의 농업기상자료 구축 - 111개 농업주요지점을 대상으로 -)

  • Joo, Jin-Hwan;Jung, Nam-Su;Seo, Myung-Chul
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.6
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    • pp.87-99
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    • 2013
  • For analysis of climate change effects on agriculture, precise agricultural meteorological data are needed to target period and site. In this study, agricultural meteorological data under new climate change scenario (RCP 8.5) are constructed from 2011 to 2099 in 111 agriculture major station suggested by Rural Development Administration (RDA). For verifying constructed data, comparison with field survey data in Suwon shows same trend in maximum temperature, minimum temperature, average temperature, and precipitation in 2011. Also comparison with normals of daily data in 2025, 2055, and 2085 shows reliability of constructed data. In analysis of constructed data, we can calculate sum of days over temperature and under temperature. Results effectively show the change of average temperature in each region and odd days of precipitation which means flood and dry days in target region.

Analysis of the Impact of Heatwaves in Gwangju using Logistic Regression and Discriminant Analysis (로지스틱 회귀분석과 판별분석을 활용한 광주광역시의 폭염에 미치는 영향분석)

  • Youn Su Kim;Yeong Seon Kong;In Hong Chang
    • Journal of Integrative Natural Science
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    • v.17 no.2
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    • pp.33-41
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    • 2024
  • Abnormal climate is a phenomenon in which meteorological factors such as temperature and precipitation are significantly higher or lower than normal, and is defined by the World Meteorological Organization as a 30-year period. However, over the past 30 years, abnormal climate phenomena have occurred more frequently around the world than in the past. In Korea, abnormal climate phenomena such as abnormally high temperatures on the Korean Peninsula, drought, heatwave and heavy rain in summer are occurring in March 2023. Among them, heatwaves are expected to increase in frequency compared to other abnormal climates. This suggests that heatwave should be recognised as a disaster rather than just another extreme weather event. According to several previous studies, greenhouse gases and meteorological factors are expected to affect heatwaves, so this paper uses logistic regression and discriminant analysis on meteorological element data and greenhouse gas data in Gwangju from 2008 to 2022. We analyzed the impact of heatwaves. As a result of the analysis, greenhouse gases were selected as effective variables for heatwaves compared to the past, and among them, chlorofluorocarbons were judged to have a stronger effect on heatwaves than other greenhouse gases. Since greenhouse gases have a significant impact on heatwaves, in order to overcome heatwaves and abnormal climates, greenhouse gases must be minimized to overcome heatwaves and abnormal climates.

Structural Improvement of the Shading Structures against Meteorological Disasters in Ginseng Fields (인삼재배 해가림시설의 기상재해와 구조개선대책)

  • 남상운
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.4
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    • pp.98-106
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    • 2003
  • In order to set up structural improvement strategy against meteorological disasters of the shading structures in ginseng fields, structural safety analyses as well as some case studies of structural damage patterns were carried out. According to the results of structural safety analysis, allowable safe snow depth for type B(wood frame with single span) was 25.9 cm, and those for type A(wood frame with multi span) and type C and D (steel frame with multi span) were 17.6 cm, 25.8 cm, and 20.0 cm respectively. So types of shading structures should be selected according to the regional design snow depth. An experiential example study on meteorological disasters indicated that a strong wind damage was experienced once every 20 years, and a heavy snow damage once every 9.5 years. The most serious disasters were caused by heavy snow and it was found that a half break and complete collapse of structures were experienced by about 70% of snow damage. In addition to maintenance, repair and reinforcement, it is also recommended that improved model of shading structures for ginseng cultivation should be developed as a long term countermeasures against meteorological disasters.

A Statistical Study on the Meterorological Disasters in Korea caused by the Typhoons (태풍에 의한 우리나라의 기상재해에 관한 통계적 연구)

  • 설동일;민병언
    • Journal of the Korean Institute of Navigation
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    • v.16 no.4
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    • pp.47-54
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    • 1992
  • The purpose of this study is to provide against to the meteorological disasters in Korea caused by the typhoons by means of the statistical analyses for the relation between the intensities of the typhoons and the meteorological disasters. The data are extracted from the "TYPHOON REPORT OF KOREA" and the "TYPHOON WHITE BOOK" issued by the Central Meteorological Office. The results are summarized as follows : (1) The annual mean frequency and the total number of the typhoon causing the disasters during 30 years (1956∼1985) are 2.2, 65 respectively, and the highest number appears in August followed by September and the third is July. And the degrees of themeteorolgocal disasters are alsio the same order. (2) The more serious disasters occurred by the TS degree typhoons, and the TS degree typhoons occupy the highest frequency. (3) The more serious disasters occurred by the TS degree typhoons, and the TS degree typhoons occupy the highest frequency. (3) The meteorological disaster per typhoon is most severe in August, and the July and September are alike in the degree of the disasters per typhoon. (4) The meteorological disasters are approximately a proportional relation to the intensities of the typhoons. (5) The frequency of the Rain typhoon , Wind typhoon and Rain·Wind typhoon are about 2 : 1: 3 in July, August and September respectively. And the severe disasters occur more frequently by the Rain typhoon than by the Wind typhoon.

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Meteorological Information for Red Tide : Technical Development of Red Tide Prediction in the Korean Coastal Areas by Meteorological Factors (적조기상정보 : 기상인자를 활용한 연안 적조예측기술 개발)

  • Yoon Hong-Joo
    • Proceedings of the KSRS Conference
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    • 2006.03a
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    • pp.105-108
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    • 2006
  • Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every you. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations). Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

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A Study for Estimation of High Resolution Temperature Using Satellite Imagery and Machine Learning Models during Heat Waves (위성영상과 머신러닝 모델을 이용한 폭염기간 고해상도 기온 추정 연구)

  • Lee, Dalgeun;Lee, Mi Hee;Kim, Boeun;Yu, Jeonghum;Oh, Yeongju;Park, Jinyi
    • Korean Journal of Remote Sensing
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    • v.36 no.5_4
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    • pp.1179-1194
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    • 2020
  • This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R2 (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R2 = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.