• Title/Summary/Keyword: global warming phenomena

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Littoral Drift by the combined impact of Wind, Wave and Current ant the coastal Development Environment (해안개발환경하에서 바람 ${\cdot}$ 파랑 ${\cdot}$ 흐름의 중첩에 의한 연안표사)

  • Lee, Seung-Chul;Lee, Joong-Woo;Kim, Ki-Dam;Kang, Seok-Jin
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2007.12a
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    • pp.141-142
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    • 2007
  • In recent years, the rate of mean sea level rise is increasing rapidly from the phenomena of global warming, together with the increasing trend of the storm scale. The issue of sea level rise is multifaceted and produces a range of environmental problems. Especially, high tides and the tidal currents become higher, and wave base increases, so the energy received at the coastal boundary may increase. This brings that many coastal environments go into disequilibrium, such as damages to the structures, erosion, and deposition Similarly it was known that the problems of nearshore processes and damage of berth and counter facilities during storm period had appeared at the small fishery port. Here we try to analyze the impact of the rearrangement of counter facilities and berth layout adopted for tranquility of its'inner harbor. Because this harbor is being connected to channel and open sea, the rearrangement of the structures might affect to the current speed and direction and wave height, so do to the sea bottom undulation. Therefore, we made model test for the several layouts of the berth and breakwater in this area.

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Development for the function of Wind wave Damage Estimation at the Western Coastal Zone based on Disaster Statistics (재해통계기반 서해 연안지역의 풍랑피해예측함수 개발)

  • Choo, Tai Ho;Kwak, Kil Sin;Ahn, Si Hyung;Yang, Da Un;Son, Jong Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.2
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    • pp.14-22
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    • 2017
  • The frequency and scale of natural disasters due to the abnormal climate phenomena caused by global warming have being increasing all over the world. Various natural disasters, such as typhoons, earthquakes, floods, heavy rain, drought, sweltering heat, wind waves, tsunamis and so on, can cause damage to human life. Especially, the damage caused by natural disasters such as the Earthquake of Japan, hurricane Katrina in the United States, typhoon Maemi and so on, have been enormous. At this stage, it is difficult to estimate the scale of damage due to (future) natural disasters and cope with them. However, if we could predict the scale of damage at the disaster response level, the damage could be reduced by responding to them promptly. In the present study, therefore, among the many types of natural disaster, we developed a function to estimate the damage due to wind waves caused by sea winds and waves. We collected the damage records from the Disaster Report ('91~'14) published by the Ministry of Public Safety and Security about wind waves and typhoons in the western coastal zone and, in order to reflect the inflation rate, we converted the amount of damage each year into the equivalent amount in 2014. Finally, the meteorological data, such as the wave height, wind speed, tide level, wave direction, wave period and so on, were collected from the KMA (Korea Meteorological Administration) and KHOA (Korea Hydrographic and Oceanographic Agency)'s web sites, for the periods when wind wave and typhoon damage occurred. After that, the function used to estimate the wind wave damage was developed by reflecting the regional characteristics for the 9 areas of the western coastal zone.

An Analysis of Local Quantity of Carbon Absorption, Fixation and Emission by Using GIS

  • Kim, Hyeon-Tae;Moon, Byeong-Eun;Choi, Eun-Gyu;Kim, Chi-Ho;Ryou, Young-Sun;Kim, Jong-Goo
    • Journal of the Korea Organic Resources Recycling Association
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    • v.22 no.1
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    • pp.40-48
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    • 2014
  • Due to increasing greenhouse gas emissions, global warming and abnormal weather phenomena it has become important on a national level to keep a count of greenhouse gases being emitted. We want to take advantage of any selected area, as the basic data for the calculation of greenhouse gas emissions, Forest and Grassland, Paddy fields, and Fields(crops), Greenhouse(crops), Pig farm, Cattle farm, Farm household(populations, agricultural machinery) and Vehicle, the basic building blocks shots with a small amount of per-unit basis, the statistics calculated based on regional carbon emissions through the literature and experimental. Carbon absorption 772,960 ton C/year, amount of fixation 487,477 ton C/year, amount of emission 1,112,607 ton C/year were noted in Gimje-si, and amount of carbon absorption 55,559 ton C/year, amount of fixation 25,864 ton C/year, amount of emissions 58,355 ton C/year in Gongdeok-myeon, respectively. The carbon absorption at Hwangsan-ri is 25,107 ton C/year, fixation 4,301 ton C/year, and emission 20,330 ton C/year respectively. We were able to estimate the amount of carbon according to the specific characteristics of each unit village, then expanding it to a large-scale and comparative analysis, therefore we were able to obtain basic data on the national levels of carbon absorption.

A Study on the Factors Affecting Air Temperature on Roadside : Focusing on Road Conditions and Traffic Characteristics (도로 주변부 기온에 영향을 미치는 요인에 관한 연구: 도로조건과 교통특성을 중심으로)

  • Lee, Yuhwa;Yang, Inchul;Kim, Do-Gyeong;Lim, Ji Hyun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.4
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    • pp.1619-1629
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    • 2013
  • It turned out that there was a direct or an indirect relationship among global warming, urban heat island effects, urban and traffic environments, and public's health. In particular, unusual climate phenomena such as frequent heavy rainfall and scorching heat in a row that had rarely happened before have a negative effect on quality of life for people living in urban areas. This study focuses on the effects of roadway geometric design and traffic conditions on air temperature of roadside in Seoul Metropolitan Areas, controlling of roadway micro-climate environment. Five roadway segments containing different roadway and traffic conditions in terms of traffic median with trees, street trees, traffic volume and average travel speeds were surveyed. According to statistical results(t-test) from three roadway air temperature regression model estimations, air temperature is found to be different from one another in three periods-morning, afternoon and evening. Regarding roadway geometric design, air temperature of urban roads with vegetated median strips is lower about 1.3~2.2 degrees in celcius. Higher traffic volumes per lane and lower average travel speeds will tend to increase roadside air temperature, and efficient traffic operation policies can protect from increasing roadside air temperature in urban areas.

Abnormal Water Temperature Prediction Model Near the Korean Peninsula Using LSTM (LSTM을 이용한 한반도 근해 이상수온 예측모델)

  • Choi, Hey Min;Kim, Min-Kyu;Yang, Hyun
    • Korean Journal of Remote Sensing
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    • v.38 no.3
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    • pp.265-282
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    • 2022
  • Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R2=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R2=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

Short-term Variability of Carbon Dioxide within and across the Korean Peninsula: Case Study during 1995-1997 (이산화탄소의 단주기적 농도변화 특성)

  • Song, Ki-Bum;Youn, Yong-Hoon;Kim, Ki-Hyun
    • Journal of the Korean earth science society
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    • v.21 no.5
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    • pp.623-634
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    • 2000
  • This study was conducted to analyze the patterns associated with the short-term variability of CO$_2$ concentrations over 24-h scale within and across the Korean Peninsula. In the course of our study, we compared the data sets obtained from Moo-Ahn (MAN) station located in the far western coastal area of Korea with those determined from major background observatory stations around the world from the periods of Aug. 1995 to Dec. 1997. The mean CO$_2$ concentration of the MAN area for the whole study periods, when computed using the daily mean values, was found out to be 374.5${\pm}$6.6 ppm (N=884); seasonal mean values were found out to be 378${\pm}$5.2 (spring: N=181), 372${\pm}$10.2 (summer: N =210), 372${\pm}$7.2 (fall: N=243), and 376${\pm}$5.4 ppm (winter: N=206). When the data from MAN was compared with those of major background stations, the effects of both daily and seasonal components appear to vary distinctively across different stations. Those effects are expected to reflect the mixed effects of various factors which include: seasonal pollution patterns, weather conditions, vegetation, and so forth. Based upon this comparative analysis, we suspect that the MAN area is under the strong influence of anthropogenic source processes relative to all the other stations under consideration. If that is not the case, the existence of enhanced CO$_2$ level may be rather ubiquitous phenomena in Korea. More detailed inspection of CO$_2$ behavior from various respects is strongly desired in the future.

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Oceanic Application of Satellite Synthetic Aperture Radar - Focused on Sea Surface Wind Retrieval - (인공위성 합성개구레이더 영상 자료의 해양 활용 - 해상풍 산출을 중심으로 -)

  • Jang, Jae-Cheol;Park, Kyung-Ae
    • Journal of the Korean earth science society
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    • v.40 no.5
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    • pp.447-463
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    • 2019
  • Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

A Study on the Effects of Meterological Factors on the Distribution of Agricultural Products: Focused on the Distribution of Chinese Cabbages (기상요인이 농산물 유통에 미치는 영향에 관한 연구: 배추 유통 사례를 중심으로)

  • Lee, Hyunjoung;Hong, Jinhwan
    • Journal of Distribution Research
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    • v.17 no.5
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    • pp.59-83
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    • 2012
  • Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in

    and
    . The type of chinese cabbages are categorized by 5 types, i.e. alpine, gimjang for winter, spring, summer, and winter crop, and all of the regression models are shown significant relationship. In addition, meterological factors in shipment and wholesale period are entered more in regression model than those in seeding and harvest period. This result implies that weather in consuming region is also important in the distribution of chinese cabbages. Based on the result of this study, we find several implications and recommendations for policy makers of agricultural product distribution. The goal of agricultural product distribution policy is to insure proper price and production cost for farmers and provide proper price and quality, and stable supply for consumers. Therefore, coping with the uncertainty of weather is very essential to make a fruitful effect of the policy. In reality, very big part of consumer price of chinese cabbage is made up of the margin of intermediaries, because they take the risk. In addition, policy makers make efforts for farmers to utilize AWIS (Agricultural Weather Information System). In order to do that, it should integrate the relevant information including distribution and marketing as well as production. Offering a consulting service to farmers about weather management is also expected to be a good option in agriculture and weather industry. Reflecting on the result of this study, the distribution authorities can offer the guideline for the timing and volume of harvest, and it is expected to contribute to the stable equilibrium of supply and demand of agricultural products.

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  • Characteristics of Spectra of Daily Satellite Sea Surface Temperature Composites in the Seas around the Korean Peninsula (한반도 주변해역 일별 위성 해수면온도 합성장 스펙트럼 특성)

    • Woo, Hye-Jin;Park, Kyung-Ae;Lee, Joon-Soo
      • Journal of the Korean earth science society
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      • v.42 no.6
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      • pp.632-645
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      • 2021
    • Satellite sea surface temperature (SST) composites provide important data for numerical forecasting models and for research on global warming and climate change. In this study, six types of representative SST composite database were collected from 2007 to 2018 and the characteristics of spatial structures of SSTs were analyzed in seas around the Korean Peninsula. The SST composite data were compared with time series of in-situ measurements from ocean meteorological buoys of the Korea Meteorological Administration by analyzing the maximum value of the errors and its occurrence time at each buoy station. High differences between the SST data and in-situ measurements were detected in the western coastal stations, in particular Deokjeokdo and Chilbaldo, with a dominant annual or semi-annual cycle. In Pohang buoy, a high SST difference was observed in the summer of 2013, when cold water appeared in the surface layer due to strong upwelling. As a result of spectrum analysis of the time series SST data, daily satellite SSTs showed similar spectral energy from in-situ measurements at periods longer than one month approximately. On the other hand, the difference of spectral energy between the satellite SSTs and in-situ temperature tended to magnify as the temporal frequency increased. This suggests a possibility that satellite SST composite data may not adequately express the temporal variability of SST in the near-coastal area. The fronts from satellite SST images revealed the differences among the SST databases in terms of spatial structure and magnitude of the oceanic fronts. The spatial scale expressed by the SST composite field was investigated through spatial spectral analysis. As a result, the high-resolution SST composite images expressed the spatial structures of mesoscale ocean phenomena better than other low-resolution SST images. Therefore, in order to express the actual mesoscale ocean phenomenon in more detail, it is necessary to develop more advanced techniques for producing the SST composites.

    Modeling of Vegetation Phenology Using MODIS and ASOS Data (MODIS와 ASOS 자료를 이용한 식물계절 모델링)

    • Kim, Geunah;Youn, Youjeong;Kang, Jonggu;Choi, Soyeon;Park, Ganghyun;Chun, Junghwa;Jang, Keunchang;Won, Myoungsoo;Lee, Yangwon
      • Korean Journal of Remote Sensing
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      • v.38 no.5_1
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      • pp.627-646
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      • 2022
    • Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.