• Title/Summary/Keyword: Synoptic weather

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A Feasibility Study of a Field-specific Weather Service for Small-scale Farms in a Topographically Complex Watershed (지형이 복잡한 집수역의 소규모농장에 맞춘 기상서비스의 실현가능성)

  • Yun, Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.17 no.4
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    • pp.317-325
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    • 2015
  • An adequate downscaling of synoptic forecasts is a prerequisite for improved agrometeorological service to rural areas in South Korea where complex terrains and small farms are common. In this study, geospatial schemes based on topoclimatology were used to scale down the Korea Meteorological Administration (KMA) temperature forecasts to the local scale (~30 m) across a rural catchment. Then, using these schemes, local temperatures were estimated at 14 validation sites at 0600 and 1500 LST in 2013/2014 and were compared with the observations. The estimation errors were substantially reduced for both 0600 and 1500 LST temperatures when compared against the uncorrected KMA products. The improvement was most notable at low lying locations for the 0600 temperature and at the locations on west- and south-facing slopes for the 1500 LST temperature. Using the downscaled real-time temperature data, a pilot service has started to provide the field-specific weather information tailored to meet the requirements of small-scale farms. For example, the service system makes a daily outlook on the phenology of crop species grown in a given field using the field-specific temperature data. When the temperature forecast is given for next morning, a frost risk index is calculated according to a known relationship of phenology and frost injury. If the calculated index is higher than a pre-defined threshold, a warning is issued and delivered to the grower's cellular phone with relevant countermeasures to help protect crops against frost damage.

A Case Study on the Meteorological Observation in Spring for the Atmospheric Environment Impact Assessment at Sangin-dong Dalbi Valley, Daegu (대기환경영향평가를 위한 대구광역시 상인동 달비골의 봄철 기상관측 사례분석)

  • Park, Jong-Kil;Jung, Woo-Sik;Hwang, Soo-Jin;Yoon, Ill-Hee;Park, Gil-Un;Kim, Sin-Ho;Kim, Seok-Cheol
    • Journal of Environmental Science International
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    • v.17 no.9
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    • pp.1053-1068
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    • 2008
  • This study aims to produce fundamental database for Environment Impact Assessment by monitoring vertical structure of the atmosphere due to the mountain valley wind in spring season. For this, we observed surface and upper meteorological elements in Sangin-dong, Daegu using the rawinsonde and automatic weather system(AWS). In Sangin-dong, the weather condition was largely affected by mountains when compared to city center. The air temperature was low during the night time and day break, and similar to that of city center during the day time. Relative humidity also showed similar trend; high during the night time and day break and similar to that of city center during the day time. Solar radiation was higher than the city, and the daily maximum temperature was observed later than the city. The synoptic wind during the measurement period was west wind. But during the day time, the west wind was joined by the prevailing wind to become stronger than the night time. During the night time and daybreak, the impact of mountain wind lowered the overall temperature, showing strong geographical influence. The vertical structure of the atmosphere in Dalbi valley, Sangin-dong had a sharp change in air temperature, relative humidity, potential temperature and equivalent potential temperature when measured at the upper part of the mixing layer height. The mixing depth was formed at maximum 1896m above the ground, and in the night time, the inversion layer was formed by radiational cooling and cold mountain wind.

A Case Analysis of Volcanic Ash Dispersion under Various Volcanic Explosivity Index of the Mt. Baegdu (백두산 분화 강도에 따른 화산재 확산 사례 분석)

  • Lee, Soon-Hwan;Jang, Eun-Suk;Lee, Hyun-Mi
    • Journal of the Korean earth science society
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    • v.33 no.3
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    • pp.280-293
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    • 2012
  • In order to clarify the characteristics of dispersion of volcanic tephra emitted from the Mt. Baegdu with various eruption environment, numerical analysis were performed using numerical models, Weather Research and Forecast (WRF) and FLEXPART. Synoptic conditions at 12 October 2010 was adopted because the volcanic ash of Mt. Baegdu can reach the Korean peninsula and its dispersion pattern was compared with different Volcanic Explosivity Index (VEI) and particle size. Predominant size of falling out ash flowing in the peninsular is smaller than 0.5 mm and the ash large than the size is difficult to get in the peninsular due to the its weak ability of truculent diffusion. the difference of ash distribution with various VEI scenarios is not so much but number density of ash in the air is dramatically changed. Volcanic ash tends to be deposited easily in eastern coastal area such as Gangneung and Busan, because of the inflow of ash from East Sea and barrier effect of the Taeback mountains along the east coast of the Korean Peninsula. Accumulated amount of ash deposition can be increased in short period in several urban areas.

Past, Present and Future of Geospatial Scheme based on Topo-Climatic Model and Digital Climate Map (소기후모형과 전자기후도를 기반으로 한 지리공간 도식의 과거, 현재 그리고 미래)

  • Kim, Dae-Jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.268-279
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    • 2021
  • The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

Predicting the Pre-Harvest Sprouting Rate in Rice Using Machine Learning (기계학습을 이용한 벼 수발아율 예측)

  • Ban, Ho-Young;Jeong, Jae-Hyeok;Hwang, Woon-Ha;Lee, Hyeon-Seok;Yang, Seo-Yeong;Choi, Myong-Goo;Lee, Chung-Keun;Lee, Ji-U;Lee, Chae Young;Yun, Yeo-Tae;Han, Chae Min;Shin, Seo Ho;Lee, Seong-Tae
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.22 no.4
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    • pp.239-249
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    • 2020
  • Rice flour varieties have been developed to replace wheat, and consumption of rice flour has been encouraged. damage related to pre-harvest sprouting was occurring due to a weather disaster during the ripening period. Thus, it is necessary to develop pre-harvest sprouting rate prediction system to minimize damage for pre-harvest sprouting. Rice cultivation experiments from 20 17 to 20 19 were conducted with three rice flour varieties at six regions in Gangwon-do, Chungcheongbuk-do, and Gyeongsangbuk-do. Survey components were the heading date and pre-harvest sprouting at the harvest date. The weather data were collected daily mean temperature, relative humidity, and rainfall using Automated Synoptic Observing System (ASOS) with the same region name. Gradient Boosting Machine (GBM) which is a machine learning model, was used to predict the pre-harvest sprouting rate, and the training input variables were mean temperature, relative humidity, and total rainfall. Also, the experiment for the period from days after the heading date (DAH) to the subsequent period (DA2H) was conducted to establish the period related to pre-harvest sprouting. The data were divided into training-set and vali-set for calibration of period related to pre-harvest sprouting, and test-set for validation. The result for training-set and vali-set showed the highest score for a period of 22 DAH and 24 DA2H. The result for test-set tended to overpredict pre-harvest sprouting rate on a section smaller than 3.0 %. However, the result showed a high prediction performance (R2=0.76). Therefore, it is expected that the pre-harvest sprouting rate could be able to easily predict with weather components for a specific period using machine learning.

Using Spatial Data and Crop Growth Modeling to Predict Performance of South Korean Rice Varieties Grown in Western Coastal Plains in North Korea (공간정보와 생육모의에 의한 남한 벼 품종의 북한 서부지대 적응성 예측)

  • 김영호;김희동;한상욱;최재연;구자민;정유란;김재영;윤진일
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.4 no.4
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    • pp.224-236
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    • 2002
  • A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.

The Distribution of Aerosol Concentration during the Asian Dust Period over Busan Area, Korea in Spring 2009 (2009년 봄철 부산지역 황사 기간 중 에어로솔 농도 분포)

  • Jung, Woon-Seon;Park, Sung-Hwa;Lee, Dong-In;Kang, Deok-Du;Kim, Dong-Chul
    • Journal of the Korean earth science society
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    • v.34 no.7
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    • pp.693-710
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    • 2013
  • This study investigates the distribution of suspended particulates during the Asian dust period in Busan, Korea in the spring of 2009. Weather map and automatic weather system (AWS) data were used to analyze the synoptic weather conditions during the period. Particulate matter 10, laser particle counter data, satellite images and a backward trajectories model were used to analyze the aerosol particles distribution and their origins. In Case 1 (20 February 2009), when the $PM_{10}$ concentration increased, the aerosol volume distribution of small ($0.3-1.0{\mu}m$) particles decreased, while the concentration of large ($1.0-10.0{\mu}m$) particles increased. When the $PM_{10}$ concentration decreased, the aerosol volume distribution was observed to decrease as well. The prevailing winds changed from weak northerly winds to strong southwesterly winds when the concentration of the large particles increased. The correlation coefficient between the $PM_{10}$ concentration and aerosol volume distribution of large particles showed a high positive value of over 0.9. The results from the trajectory model show that the Asian dust originated in the Gobi desert and the Nei Mongol plateau. In Case 2 (25 April 2009), when the $PM_{10}$ concentration increased, the aerosol volume concentration of small ($0.3-0.5{\mu}m$) particles decreased, but the concentration of large ($0.5-10.0{\mu}m$) particles increased. The opposite was observed when the $PM_{10}$ concentration decreased. The prevailing winds changed from northeasterly winds to southwesterly and northeasterly winds. The correlation coefficient between the $PM_{10}$ concentration and aerosol volume distribution of large particles ($1.0-10.0{\mu}m$) showed a high positive value of about 0.9. The results from the trajectory model show that the Asian dust originated in Manchuria and the eastern coast of China.

Comparison between Solar Radiation Estimates Based on GK-2A and Himawari 8 Satellite and Observed Solar Radiation at Synoptic Weather Stations (천리안 2A호와 히마와리 8호 기반 일사량 추정값과 종관기상관측망 일사량 관측값 간의 비교)

  • Dae Gyoon Kang;Young Sang Joh;Shinwoo Hyun;Kwang Soo Kim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.1
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    • pp.28-36
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    • 2023
  • Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.

The Characteristics Asian Dust Observed in Japan Deflecting the Korean Peninsula (2010. 5. 22.-5. 25.) (한반도를 돌아 일본에서 관측된 황사의 특징 (2010년 5월 22일-5월 25일))

  • Ahn, Bo-Young;Chun, Young-Sin
    • Journal of the Korean earth science society
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    • v.32 no.4
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    • pp.388-401
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    • 2011
  • Asian dust was observed a total of 66 times in the springtime during the period from 2002 to 2010, with 26 cases in March, 23 cases in April and 17 cases in May. This study investigates a Asian dust episode that occurred during the period from 22 to 25 May 2010, based on synoptic weather patterns, wind vector at 850 hPa, relative humidity at 1000 hPa, Jet streams and wind vector at 300 hPa, PM10 concentration in Korea and satellite imagery. In this case, Asian dust originated on 22 May along the rear of a developing low pressure system in Mongolia. The Asian dust was then transported southeastward and bypassed the Korea peninsula from 23 to 24 May, before reaching Japan on 25 May. Jet streams on 24 May bypassed the Korean peninsula and induced the development of a surface low pressure centered over the peninsula. The resulting air flow was critical to the trajectory of the Asian dust, which likewise bypassed the Korean peninsula. 72-hour backward trajectory data reveal that the Shandong Peninsula and the East China Sea were the points of origin for the air flows that swept through the Japanese sites where Asian dust was observable to the naked eay. The Asian dust pathway is ascertained by horizontal distribution of the Asian dust of RGB imagery from MODIS satellites which captured the Asian dust moving over the Shandong Peninsula, the East China Sea, and northwest of the Kyushu region in Japan. Since the synoptic pattern and the transport way of the Asian dust case are far from typical ones, which Asian dust forecasting technique has long been based on, this study can be good example of exceptional Asian dust pattern and it will be used for more accurate Asian dust forecasting.

Damage of Whole Crop Maize in Abnormal Climate Using Machine Learning (이상기상 시 사일리지용 옥수수의 기계학습을 이용한 피해량 산출)

  • Kim, Ji Yung;Choi, Jae Seong;Jo, Hyun Wook;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.42 no.2
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    • pp.127-136
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    • 2022
  • This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMYnormal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).