• Title/Summary/Keyword: 기상정보활용

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Comparison of Wind Vectors Derived from GK2A with Aeolus/ALADIN (위성기반 GK2A의 대기운동벡터와 Aeolus/ALADIN 바람 비교)

  • Shin, Hyemin;Ahn, Myoung-Hwan;KIM, Jisoo;Lee, Sihye;Lee, Byung-Il
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1631-1645
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    • 2021
  • This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

Monthly temperature forecasting using large-scale climate teleconnections and multiple regression models (대규모 기후 원격상관성 및 다중회귀모형을 이용한 월 평균기온 예측)

  • Kim, Chul-Gyum;Lee, Jeongwoo;Lee, Jeong Eun;Kim, Nam Won;Kim, Hyeonjun
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.731-745
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    • 2021
  • In this study, the monthly temperature of the Han River basin was predicted by statistical multiple regression models that use global climate indices and weather data of the target region as predictors. The optimal predictors were selected through teleconnection analysis between the monthly temperature and the preceding patterns of each climate index, and forecast models capable of predicting up to 12 months in advance were constructed by combining the selected predictors and cross-validating the past period. Fore each target month, 1000 optimized models were derived and forecast ranges were presented. As a result of analyzing the predictability of monthly temperature from January 1992 to December 2020, PBIAS was -1.4 to -0.7%, RSR was 0.15 to 0.16, NSE was 0.98, and r was 0.99, indicating a high goodness-of-fit. The probability of each monthly observation being included in the forecast range was about 64.4% on average, and by month, the predictability was relatively high in September, December, February, and January, and low in April, August, and March. The predicted range and median were in good agreement with the observations, except for some periods when temperature was dramatically lower or higher than in normal years. The quantitative temperature forecast information derived from this study will be useful not only for forecasting changes in temperature in the future period (1 to 12 months in advance), but also in predicting changes in the hydro-ecological environment, including evapotranspiration highly correlated with temperature.

A case study on monitoring the ambient ammonia concentration in paddy soil using a passive ammonia diffusive sampler (논 토양에서 암모니아 배출 특성 모니터링을 위한 수동식 암모니아 확산형 포집기 이용 사례 연구)

  • Kim, Min-Suk;Park, Minseok;Min, Hyun-Gi;Chae, Eunji;Hyun, Seunghun;Kim, Jeong-Gyu;Koo, Namin
    • Korean Journal of Environmental Biology
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    • v.39 no.1
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    • pp.100-107
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    • 2021
  • Along with an increase in the frequency of high-concentration fine particulate matter in Korea, interest and research on ammonia (NH3) are actively increasing. It is obvious that agriculture has contributed significantly to NH3 emissions. However, studies on the long-term effect of fertilizer use on the ambient NH3 concentration of agricultural land are insufficient. Therefore, in this study, NH3 concentration in the atmosphere of agricultural land was monitored for 11 months using a passive sampler. The average ambient NH3 concentration during the total study period was 2.02 ㎍ m-3 and it was found that the effect of fertilizer application on the ambient NH3 concentration was greatest in the month immediately following fertilizer application (highest ambient NH3 concentration as 11.36㎍ m-3). After that, it was expected that the NH3 volatilization was promoted by increases in summer temperature and the concentration in the atmosphere was expected to increase. However, high NH3 concentrations in the atmosphere were not observed due to strong rainfall that lasted for a long period. After that, the ambient NH3 concentration gradually decreased through autumn and winter. In summary, when studying the contribution of fertilizer to the rate of domestic NH3 emissions, it is necessary to look intensively for at least one month immediately after fertilizer application, and weather information such as precipitation and no-rain days should be considered in the field study.

Data-driven Analysis for Developing the Effective Groundwater Management System in Daejeong-Hangyeong Watershed in Jeju Island (제주도 대정-한경 유역 효율적 지하수자원 관리를 위한 자료기반 연구)

  • Lee, Soyeon;Jeong, Jiho;Kim, Minchul;Park, Wonbae;Kim, Yuhan;Park, Jaesung;Park, Heejeong;Park, Gyeongtae;Jeong, Jina
    • Economic and Environmental Geology
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    • v.54 no.3
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    • pp.373-387
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    • 2021
  • In this study, the impact of clustered groundwater usage facilities and the proper amount of groundwater usage in the Daejeong-Hangyeong watershed of Jeju island were evaluated based on the data-driven analysis methods. As the applied data, groundwater level data; the corresponding precipitation data; the groundwater usage amount data (Jeoji, Geumak, Seogwang, and English-education city facilities) were used. The results show that the Geumak usage facility has a large influence centering on the corresponding location; the Seogwang usage facility affects on the downstream area; the English-education usage facility has a great impact around the upstream of the location; the Jeoji usage facility shows an influence around the up- and down-streams of the location. Overall, the influence of operating the clustered groundwater usage facilities in the watershed is prolonged to approximately 5km. Additionally, the appropriate groundwater usage amount to maintain the groundwater base-level was analyzed corresponding to the precipitation. Considering the recent precipitation pattern, there is a need to limit the current amount of groundwater usage to 80%. With increasing the precipitation by 100mm, additional groundwater development of approximately 1,500m3-1,900m3 would be reasonable. All the results of the developed data-driven estimation model can be used as useful information for sustainable groundwater development in the Daejeong-Hangyeong watershed of Jeju island.

Development of Summer Leaf Vegetable Crop Energy Model for Rooftop Greenhouse (옥상온실에서의 여름철 엽채류 작물에너지 교환 모델 개발)

  • Cho, Jeong-Hwa;Lee, In-Bok;Lee, Sang-Yeon;Kim, Jun-Gyu;Decano, Cristina;Choi, Young-Bae;Lee, Min-Hyung;Jeong, Hyo-Hyeog;Jeong, Deuk-Young
    • Journal of Bio-Environment Control
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    • v.31 no.3
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    • pp.246-254
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    • 2022
  • Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.