• Title/Summary/Keyword: 지역규모 기후모델

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Seasonal Prediction of Tropical Cyclone Activity in Summer and Autumn over the Western North Pacific and Its Application to Influencing Tropical Cyclones to the Korean Peninsula (북서태평양 태풍의 여름과 가을철 예측시스템 개발과 한반도 영향 태풍 예측에 활용)

  • Choi, Woosuk;Ho, Chang-Hoi;Kang, KiRyong;Yun, Won-Tae
    • Atmosphere
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    • v.24 no.4
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    • pp.565-571
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    • 2014
  • A long-range prediction system of tropical cyclone (TC) activity over the western North Pacific (WNP) has been operated in the National Typhoon Center of the Korea Meteorological Administration since 2012. The model forecasts the spatial distribution of TC tracks averaged over the period June~October. In this study, we separately developed TC prediction models for summer (June~August) and autumn (September~November) period based on the current operating system. To perform the three-month WNP TC activity prediction procedure readily, we modified the shell script calling in environmental variables automatically. The user can apply the model by changing these environmental variables of namelist parameter in consideration of their objective. The validations for the two seasons demonstrate the great performance of predictions showing high pattern correlations between hindcast and observed TC activity. In addition, we developed a post-processing script for deducing TC activity in the Korea emergency zone from final forecasting map and its skill is discussed.

Review of the Weather Hazard Research: Focused on Typhoon, Heavy Rain, Drought, Heat Wave, Cold Surge, Heavy Snow, and Strong Gust (위험기상 분야의 지난 연구를 뒤돌아보며: 태풍, 집중호우, 가뭄, 폭염, 한파, 강설, 강풍을 중심으로)

  • Chang-Hoi Ho;Byung-Gon Kim;Baek-Min Kim;Doo-Sun R. Park;Chang-Kyun Park;Seok-Woo Son;Jee-Hoon Jeong;Dong-Hyun Cha
    • Atmosphere
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    • v.33 no.2
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    • pp.223-246
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    • 2023
  • This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.

Habitat characteristics and prediction of potential distribution according to climate change for Macromia daimoji Okumura, 1949 (Odonata: Macromiidae) (노란잔산잠자리(Macromia daimojiOkumura, 1949)의 서식지 특성 및 기후변화에 따른 잠재적 분포 예측)

  • Soon Jik Kwon;Hyeok Yeong Kwon;In Chul Hwang;Chang Su Lee;Tae Geun Kim;Jae Heung Park;Yung Chul Jun
    • Journal of Wetlands Research
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    • v.26 no.1
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    • pp.21-31
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    • 2024
  • Macromia daimoji Okumura, 1949 was designated as an endangered species and also categorized as Class II Endangered wildlife on the International Union for Conservation of Nature (IUCN) Red List in Korea. The spatial distribution of this species ranged within a region delimited by northern latitude from Sacheon-si(35.1°) to Yeoncheon-gun(38.0°) and eastern longitude from Yeoncheon-gun(126.8°) to Yangsan-si(128.9°). They generally prefer microhabitats such as slowly flowing littoral zones of streams, alluvial stream islands and temporarily formed puddles in the sand-based lowland streams. The objectives of this study were to analyze the similarity of benthic macroinvertebrate communities in M. daimoji habitats, to predict the current potential distribution patterns as well as the changes of distribution ranges under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from April 2009 to September 2022. We adopted MaxEnt model to predict the current and future potential distribution for M. daimoji using downloaded 19 variables from the WorldClim database. The differences of benthic macroinvertebrate assemblages in the mainstream of Nakdonggang were smaller than those in its tributaries and the other streams, based on the surrounding environments and stream sizes. MaxEnt model presented that potential distribution displayed high inhabiting probability in Nakdonggang and its tributaries. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), SSP1 scenario was predicted to expand in a wide area and SSP5 scenario in a narrow area, comparing with current potential distribution. M. daimoji is not only directly threatened by physical disturbances (e.g. river development activities) but also vulnerable to rapidly changing climate circumstances. Therefore, it is necessary to monitor the habitat environments and establish conservation strategies for preserving population of M. daimoji.

Climate Change Impact on Nonpoint Source Pollution in a Rural Small Watershed (기후변화에 따른 농촌 소유역에서의 비점오염 영향 분석)

  • Hwang, Sye-Woon;Jang, Tae-Il;Park, Seung-Woo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.4
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    • pp.209-221
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    • 2006
  • The purpose of this study is to analyze the effects of climate change on the nonpoint source pollution in a small watershed using a mid-range model. The study area is a basin in a rural area that covers 384 ha with a composition of 50% forest and 19% paddy. The hydrologic and water quality data were monitored from 1996 to 2004, and the feasibility of the GWLF (Generalized Watershed Loading function) model was examined in the agricultural small watershed using the data obtained from the study area. As one of the studies on climate change, KEI (Korea Environment Institute) has presented the monthly variation ratio of rainfall in Korea based on the climate change scenario for rainfall and temperature. These values and observed daily rainfall data of forty-one years from 1964 to 2004 in Suwon were used to generate daily weather data using the stochastic weather generator model (WGEN). Stream runoff was calibrated by the data of $1996{\sim}1999$ and was verified in $2002{\sim}2004$. The results were determination coeff, ($R^2$) of $0.70{\sim}0.91$ and root mean square error (RMSE) of $2.11{\sim}5.71$. Water quality simulation for SS, TN and TP showed $R^2$ values of 0.58, 0.47 and 0.62, respectively, The results for the impact of climate change on nonpoint source pollution show that if the factors of watershed are maintained as in the present circumstances, pollutant TN loads and TP would be expected to increase remarkably for the rainy season in the next fifty years.

An Analysis of the Application Effect of LID Technology in Urban Inundation Using Two-Dimensional Model (2차원 모델을 이용한 도시침수지역에서의 LID기법 적용효과 분석)

  • Minjin Jung;Juho Kim;Changdeok Jang;Kyewon Jun
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.1
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    • pp.13-22
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    • 2023
  • The importance of preemptive flood preparation is growing as the importance of preparing for climate change increases due to record heavy rains in the Seoul metropolitan area in August 2022. Although it is responding to flood control through reservoirs and sediment sites, the government is preparing excellent spill reduction measures through a preliminary consultation system for Low Impact Development (LID). In this study, the depth of flooding was simulated when LID technologies were applied to the Sillim 2-drain region in Dorimcheon Stream basin, an urban stream, using XP-SWMM, a two-dimensional model. In addition, the analysis and applicability of the effect of reducing rainfall runoff for the largest rainfall in a day were reviewed, and it was judged to be effective as a method of reducing flooding in urban areas. Although there is a limitation in which the reduction effect is overestimated, it is thought that the LID technologies can be a significant countermeasure as a countermeasure for small-scale flooded areas where some flooding occurs after structural flooding measures are established.

Detection of Wildfire Burned Areas in California Using Deep Learning and Landsat 8 Images (딥러닝과 Landsat 8 영상을 이용한 캘리포니아 산불 피해지 탐지)

  • Youngmin Seo;Youjeong Youn;Seoyeon Kim;Jonggu Kang;Yemin Jeong;Soyeon Choi;Yungyo Im;Yangwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1413-1425
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    • 2023
  • The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

Estimation of Climatological Standard Deviation Distribution (기후학적 평년 표준편차 분포도의 상세화)

  • Kim, Jin-Hee;Kim, Soo-ock;Kim, Dae-jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.19 no.3
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    • pp.93-101
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    • 2017
  • The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

Effect Analysis of Offshore Wind Farms on VHF band Communications (VHF 대역 통신에 대한 해상풍력 발전단지의 영향성 분석)

  • Oh, Seongwon;Park, Taeyong
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.2
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    • pp.307-313
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    • 2022
  • As the development of renewable energy expands internationally to cope with global warming and climate change, the share of wind power generation has been gradually increasing. Although wind farms can produce electric power for 24 h a day compared to solar power plants, Their interfere with the operation of nearby radars or communication equipment must be analyzed because large-scale wind power turbines are installed. This study analyzed whether a land radio station can receive sufficient signals when a ship sailing outside the offshore wind farm transmits distress signals on the VHF band. Based on the geographic information system digital map around the target area, wind turbine CAD model, and wind farm layout, the area of interest and wind farm were modeled to enable numerical analysis. Among the high frequency analysis techniques suitable for radio wave analysis in a wide area, a dedicated program applying physical optics (PO) and shooting and bouncing ray (SBR) techniques were used. Consequently, the land radio station could receive the electromagnetic field above the threshold of the VHF receiver when a ship outside the offshore wind farm transmitted a distress communication signal. When the line of sight between the ships and the land station are completely blocked, the strength of the received field decreases, but it is still above the threshold. Hence, although a wind farm is a huge complex, a land station can receive the electromagnetic field from the ship's VHF transmitter because the wave length of the VHF band is sufficiently long to have effects such as diffraction or reflection.

Distribution Status and Age Structure of Abies holophylla Population in Sudo-Am Temple Forest (수도암 사찰림의 전나무 개체군 분포현황과 연령구조분석)

  • Choi, Byoung-Ki;Lee, Chang-Woo
    • Korean Journal of Ecology and Environment
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    • v.47 no.3
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    • pp.160-166
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    • 2014
  • This study was aimed at looking into the distribution status and age structure of Abies holophylla population in Sudo-Am temple forest. It was found that a total of 302 individuals of Abies holophylla existed which were more than 2m in height within the study area. Furthermore the population size is one of the largest in the southern region of Korea. The CBH of Abies holophylla ranged from 1.5 cm to 500.8 cm. Age structure of Abies holophylla looks like a gourd-shaped bottle. This means that they have an unstable structure status and do not survive very long. This status results from a variety of factors including, vegetation succession, anthropogenic activities, and global warming. The environmental characteristics of Abies holophylla population was $931{\pm}64.5m$ in mean altitude, $19.2{\pm}8.7^{\circ}$ in mean slope in the northeastern and southeastern area of the slope direction, and $1,324,323{\pm}174,459wh\;m^{-2}$ in average of direct normal irradiation. Among the site environmental factors, the significant ones which influence the potential habitat for Abies holophylla distribution were chosen using the MaxEnt model. According to the results of this study, altitude and slope were found as the important factors. The average value of environmental conditions by ROC analysis were altitude 903.2 m, slope $20.04^{\circ}$, irradiation $1,352.248wh\;m^{-2}$, and the southeastern aspect.

Estimation of Precipitable Water from the GMS-5 Split Window Data (GMS-5 Split Window 자료를 이용한 가강수량 산출)

  • 손승희;정효상;김금란;이정환
    • Korean Journal of Remote Sensing
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    • v.14 no.1
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    • pp.53-68
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    • 1998
  • Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.