• Title/Summary/Keyword: High Impact Weather

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Effects of Surface Compaction Treatment on Soil Loss from Disturbed Bare Slopes under Simulated Rainfalls (인공강우 시 나지교란사면 토사유출에 미치는 다짐처리의 영향)

  • Park, Sang Deog;Shin, Seung Sook;Kim, Seon Jeong;Choi, Byoungkoo
    • Journal of Korea Water Resources Association
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    • v.46 no.5
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    • pp.559-568
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    • 2013
  • Surface compaction significantly impacts runoff and soil erosion under rainfall since it leads to changes of soil physical characteristics such as increase of bulk density and shear stress, change of microporosity, and decrease of hydraulic conductivity. This study addressed surface compaction effects on runoff and soil loss from bare and disturbed soils that are commonly distributed on construction sites. Thirty-six rainfall simulations from three replicates of each involving rainfall intensities (68.5 mm/hr, 95.6 mm/hr) and plot gradients ($5^{\circ}$, $12.5^{\circ}$, $20^{\circ}$) were conducted to measure runoff and soil loss for two different soil surface treatments (compacted surface, non-compacted surface). Compacted surface increased significantly soil bulk density and soil strength. However, the effect of surface treatments on runoff changed with rainfall intensity and plot gradient. Rainfall intensity and plot gradient had a positive effect on mean soil loss. In addition, the effect of surface treatments on soil loss responded differently with rainfall intensity and plot gradient. Compacted surfaces increased soil loss at gentle slope ($5^{\circ}$) while they decreased soil loss at steep slope ($20^{\circ}$). These results indicate that there exists transitional slope range ($10{\sim}15^{\circ}$) between gentle and steep slope by surface compaction effects on soil loss under disturbed bare soils and simulated rainfalls.

Bias Characteristics Analysis of Himawari-8/AHI Clear Sky Radiance Using KMA NWP Global Model (기상청 전구 수치예보모델을 활용한 Himawari-8/AHI 청천복사휘도 편차 특성 분석)

  • Kim, Boram;Shin, Inchul;Chung, Chu-Yong;Cheong, Seonghoon
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.1101-1117
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    • 2018
  • The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing

  • Liu, Dengying;Chen, Zhenliang;Zhang, Zhe;Sun, Hao;Ma, Peipei;Zhu, Kai;Liu, Guanglei;Wang, Qishan;Pan, Yuchun
    • Asian-Australasian Journal of Animal Sciences
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    • v.32 no.3
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    • pp.320-333
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    • 2019
  • Objective: The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction. Methods: In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA). Results: The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle. Conclusion: Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

Molecular epidemiologic trends of norovirus and rotavirus infection and relation with climate factors: Cheonan, Korea, 2010-2019 (노로바이러스 및 로타바이러스 감염의 역학 및 기후요인과의 관계: 천안시, 2010-2019)

  • Oh, Eun Ju;Kim, Jang Mook;Kim, Jae Kyung
    • Journal of Digital Convergence
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    • v.18 no.12
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    • pp.425-434
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    • 2020
  • Background: Viral infection outbreaks are emerging public health concerns. They often exhibit seasonal patterns that could be predicted by the application of big data and bioinformatic analyses. Purpose: The purpose of this study was to identify trends in diarrhea-causing viruses such as rotavirus (Gr.A), norovirus G-I, and norovirus G-II in Cheonan, Korea. The identified related factors of diarrhea-causing viruses may be used to predict their trend and prevent their infections. Method: A retrospective analysis of 4,009 fecal samples from June 2010 to December 2019 was carried out at Dankook University Hospital in Cheonan. Reverse transcription-PCR (RT-PCR) was employed to identify virus strains. Information about seasonal patterns of infection was extracted and compared with local weather data. Results: Out of the 4,009 fecal samples tested using multiplex RT-PCR (mRT-PCR), 985 were positive for infection with Gr.A, G-I, and G-II. Out of these 985 cases, 95.3% (n = 939) were under 10 years of age. Gr.A, G-I, and G-II showed high infection rates in patients under 10 years of age. Student's t-test showed a significant correlation between the detection rate of Gr.A and the relative humidity. The detection rate of G-II significantly correlated with wind-chill temperature. Conclusion: Climate factors differentially modulate rotavirus and norovirus infection patterns. These observations provide novel insights into the seasonal impact on the pathogenesis of Gr.A, G-I, and G-II.

Spatial Analysis of Wind Trajectory Prediction According to the Input Settings of HYSPLIT Model (HYSPLIT 모형 입력설정에 따른 바람 이동경로 예측 결과 공간 분석)

  • Kim, Kwang Soo;Lee, Seung-Jae;Park, Jin Yu
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.222-234
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    • 2021
  • Airborne-pests can be introduced into Korea from overseas areas by wind, which can cause considerable damage to major crops. Meteorological models have been used to estimate the wind trajectories of airborne insects. The objective of this study is to analyze the effect of input settings on the prediction of areas where airborne pests arrive by wind. The wind trajectories were predicted using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The HYSPLIT model was used to track the wind dispersal path of particles under the assumption that brown plant hopper (Nilaparvata lugens) was introduced into Korea from sites where the pest was reported in China. Meteorological input data including instantaneous and average wind speed were generated using meso-scale numerical weather model outputs for the domain where China, Korea, and Japan were included. In addition, the calculation time intervals were set to 1, 30, and 60 minutes for the wind trajectory calculation during early June in 2019 and 2020. It was found that the use of instantaneous and average wind speed data resulted in a considerably large difference between the arrival areas of airborne pests. In contrast, the spatial distribution of arrival areas had a relatively high degree of similarity when the time intervals were set to be 1 minute. Furthermore, these dispersal patterns predicted using the instantaneous wind speed were similar to the regions where the given pest was observed in Korea. These results suggest that the impact assessment of input settings on wind trajectory prediction would be needed to improve the reliability of an approach to predict regions where airborne-pest could be introduced.

Impact of Recent Weather Variation on Yield Components and Growth Stages of Winter Barley in Korea (최근의 기상환경 변화에 따른 가을보리의 수량구성요소 및 생육단계 변화)

  • 심교문;윤성호;정영상;이정택;황규홍
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.4 no.1
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    • pp.38-48
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    • 2002
  • This study examines the relationships between atmospheric influences and grain yields including yield components as well as growth stages. Data used in this study were collected from the long-term field experiment at Suwon for the period between 1974 and 2000. Mean grain yield of barley cultivar, Olbori, for the recent 14 years(1987∼2000) with warm winters was higher by 0.42 ton per hectare than that for 27 years(1974∼2000) at Suwon as a result of the higher numbers of spikes per unit land area and grains per spike. However, the 1000-grain weight decreased by about 0.6 gram. Mean first day of regrowth for the recent 14 years was earlier by five days than that for 27 years. Also, beginning date of regrowth was positively correlated with that of heading and ripening. Mean period of ripening for the years of 1987 through 2000 was similar to that for 27 years, but mean period of overwintering was shorter by nine days than that for 27 years. On the other hand, mean periods of seedling and tillering were longer by three days than those for 27 years. Meteorological elements at various growth stages affecting grain yield of winter barley were air temperature (positive correlation) and sunshine hour (negative correlation) of overwintering stage, precipitation (negative correlation) of tillering stage, and potential evapotranpiration (positive correlation) of tillering stage. The 1000-grain weight was not significantly correlated with the meteorological elements. Culm length was negatively influenced by high temperature and dry weather situations during the ripening period, but spike length was positively influenced. Overall, it was found that grain yield of barley, cultivar Olbori, was iufluenced by meteorological elements of overwintering, tillering, and ripening stages.

Preliminary Result of Uncertainty on Variation of Flowering Date of Kiwifruit: Case Study of Kiwifruit Growing Area of Jeonlanam-do (기후변화에 따른 국내 키위 품종 '해금'의 개화시기 변동과 전망에 대한 불확실성: 전남 키위 주산지역을 중심으로)

  • Kim, Kwang-Hyung;Jeong, Yeo Min;Cho, Youn-Sup;Chung, Uran
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.1
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    • pp.42-54
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    • 2016
  • It is highly anticipated that warming temperature resulting from global climate change will affect the phenological pattern of kiwifruit, which has been commercially grown in Korea since the early 1980s. Here, we present the potential impacts of climate change on the variations of flowering day of a gold kiwifruit cultivar, Haegeum, in the Jeonnam Province, Korea. By running six global climate models (GCM), the results from this study emphasize the uncertainty in climate change scenarios. To predict the flowering day of kiwifruit, we obtained three parameters of the 'Chill-day' model for the simulation of Haegeum: $6.3^{\circ}C$ for the base temperature (Tb), 102.5 for chill requirement (Rc), and 575 for heat requirement (Rh). Two separate validations of the resulting 'Chill-day' model were conducted. First, direct comparisons were made between the observed flowering days collected from 25 kiwifruit orchards for two years (2014-15) and the simulated flowering days from the 'Chill-day' model using weather data from four weather stations near the 25 orchards. The estimation error between the observed and simulated flowering days was 5.2 days. Second, the model was simulated using temperature data extracted, for the 25 orchards, from a high-resolution digital temperature map, resulting in the error of 3.4 days. Using the RCP 4.5 and 8.5 climate change scenarios from six GCMs for the period of 2021-40, the future flowering days were simulated with the 'Chill-day' model. The predicted flowering days of Haegeum in Jeonnam were advanced more than 10 days compared to the present ones from multi-model ensemble, while some individual models resulted in quite different magnitudes of impacts, indicating the multi-model ensemble accounts for uncertainty better than individual climate models. In addition, the current flowering period of Haegeum in Jeonnam Province was predicted to expand northward, reaching over Jeonbuk and Chungnam Provinces. This preliminary result will provide a basis for the local impact assessment of climate change as more phenology models are developed for other fruit trees.

Changes of Yield and Quality in Potato (Solanum tuberosum L.) by Heat Treatment (폭염처리에 의한 감자의 수량성과 품질 변화)

  • Lee, Gyu-Bin;Choi, Jang-Gyu;Park, Young-Eun;Jung, Gun-Ho;Kwon, Do-Hee;Jo, Kwang-Ryong;Cheon, Chung-Gi;Chang, Dong Chil;Jin, Yong-Ik
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.3
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    • pp.145-154
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    • 2022
  • Due to abnormal weather conditions caused by climate change, natural disasters and damages are gradually increasing around the world. Global climate change as accompanied by warming is projected to exert adverse impact on production of potato, which is known as cool season crop. Even though, role of potato as a food security crop is expected to increase in the future, the climate change impacts on potato and adaption strategies are not sufficiently established. Therefore, this study was conducted to analyze the damage pattern of potatoes due to high temperature treatment and to evaluate the response of cultivars. T he high temperature treatment (35~38℃) induced heat stress by sealing the plastic house in midsummer (July), and the quantity and quality characteristics of potatoes were compared with the control group. T otal yield, marketable yield (>80 g) and the number of tubers per plants decreased when heat treatment was performed, and statistical significance was evident. In the heat treatment, 'Jayoung' cultivar suffered a high heat damage with an 84% reduction in yield of >80 g compared to the control group. However, in Jopung cultivar, the decrease was relatively small at 26%. Tuber physiological disturbances (Secondary growth, Tuber cracking, Malformation) tended to increase in the heat stress. Under heat conditions, the tubers were elongated overall, which means that the marketability of potatoes was lowered. T he tuber firmness and dry matter content tended to decrease significantly in the heat-treated group. T herefore, the yield and quality of tubers were damaged when growing potatoes in heat conditions. T he cultivar with high heat adaptability was 'Jopung'. T his result can be used as basic data for potato growers and breeding of heat-resistant cultivars.

A stratified random sampling design for paddy fields: Optimized stratification and sample allocation for effective spatial modeling and mapping of the impact of climate changes on agricultural system in Korea (농지 공간격자 자료의 층화랜덤샘플링: 농업시스템 기후변화 영향 공간모델링을 위한 국내 농지 최적 층화 및 샘플 수 최적화 연구)

  • Minyoung Lee;Yongeun Kim;Jinsol Hong;Kijong Cho
    • Korean Journal of Environmental Biology
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    • v.39 no.4
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    • pp.526-535
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    • 2021
  • Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

The KALION Automated Aerosol Type Classification and Mass Concentration Calculation Algorithm (한반도 에어로졸 라이다 네트워크(KALION)의 에어로졸 유형 구분 및 질량 농도 산출 알고리즘)

  • Yeo, Huidong;Kim, Sang-Woo;Lee, Chulkyu;Kim, Dukhyeon;Kim, Byung-Gon;Kim, Sewon;Nam, Hyoung-Gu;Noh, Young Min;Park, Soojin;Park, Chan Bong;Seo, Kwangsuk;Choi, Jin-Young;Lee, Myong-In;Lee, Eun hye
    • Korean Journal of Remote Sensing
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    • v.32 no.2
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    • pp.119-131
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    • 2016
  • Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.