• Atmosphere
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• v.24 no.2
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• pp.131-140
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• 2014

The "Barents Oscillation (BO)", first designated by Paul Skeie (2000), is an anomalous recurring atmospheric circulation pattern of high relevance for the climate of the Nordic Seas and Siberia, which is defined as the second Emperical Orthogonal Function (EOF) of monthly winter sea level pressure (SLP) anomalies, where the leading EOF is the Arctic Oscillation (AO). BO, however, did not attracted much interest. In recent two decades, variability of BO tends to increase. In this study, we analyzed the spatio-temporal structures of Atmospheric internal modes such as Arctic Oscillation (AO) and Barents Oscillation (BO) and examined how these are related with Arctic warming in recent decade. We identified various aspects of BO, not dealt in Skeie (2000), such as upper-level circulation and surface characteristics for extended period including recent decade and examined link with other surface variables such as sea-ice and sea surface temperature. From the results, it was shown that the BO showed more regionally confined spatial pattern compared to AO and has intensified during recent decade. The regional dipolelar structure centered at Barents sea and Siberia was revealed in both sea-level pressure and 500 hPa geopotential height. Also, BO showed a stronger link (correlation) with sea-ice and sea surface temperature especially over Barents-Kara seas suggesting it is playing an important role for recent Arctic amplification. BO also showed high correlation with Ural Blocking Index (UBI), which measures seasonal activity of Ural blocking. Since Ural blocking is known as a major component of Eurasian winter monsoon and can be linked to extreme weathers, we suggest deeper understanding of BO can provide a missing link between recent Arctic amplification and increase in extreme weathers in midlatitude in recent decades.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.203-214
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• 2017

There are two references of genetic information in Korean soybean cultivar. This study suggested that the new seven genetic information to supplement the uncertainty on prediction of potential yield of two references in soybean, and assessed the availability of two references and seven genetic information for future research. We carried out evaluate the prediction on flowering time and potential yield of the two references of genetic parameters and the new seven genetic parameters (New1~New7); the new seven genetic parameters were calibrated in Jinju, Suwon, Chuncheon during 2003-2006. As a result, in the individual and regional combination genetic parameters, the statistical indicators of the genetic parameters of the each site or the genetic parameters of the participating stations showed improved results, but did not significant. In Daegu, Miryang, and Jeonju, the predictability on flowering time of genetic parameters of New7 was not improved than that of two references. However, the genetic parameters of New7 showed improvement of predictability on potential yield. No predictability on flowering time of genetic parameters of two references as having the coefficient of determination ($R^2$) on flowering time respectively, at 0.00 and 0.01, but the predictability of genetic parameter of New7 was improved as $R^2$ on flowering time of New7 was 0.31 in Miryang. On the other hand, $R^2$ on potential yield of genetic parameters of two references were respectively 0.66 and 0.41, but no predictability on potential yield of genetic parameter of New7 as $R^2$ of New7 showed 0.00 in Jeonju. However, it is expected that the regional combination genetic parameters with the good evaluation can be utilized to predict the flowering timing and potential yields of other regions. Although it is necessary to analyze further whether or not the input data is uncertain.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.21-30
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• 2020

In this paper, we predicted the propagation loss for the air-to-ground (A2G) channel between the ground control system and the unmanned aerial vehicle (UAV) using the prediction model for the aircraft recommended by the International Telecommunication Union (ITU). We analyzed the network coverage of the aerial relay system based on the medium altitude UAVs by expanding it into the air-to-air (A2A) channel. Climate and geographic factors in Korea were used to predict propagation loss due to atmospheres. We used the measured data published by the Telecommunication Technology Association (TTA) for regional rainfall-rate and effective earth radius factors to increase accuracy. In addition, the aerial relay communication system used the key parameter of the common data link (CDL) system developed in Korea recently. Prediction results show that the network coverage of the aerial relay system broadens at higher altitude.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.221-230
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• 2011

The climate change has been observed in Korea as well as in the entire world recently. The rainstorm has been gradually increased and then the damage has been grown. It is getting important to predict short-term rainfall. The Korea Meteorological Administration (KMA) generates numerical model outputs which are computed by Global Data Assimilation and Prediction System (GDAPS) and Regional Data Assimilation and Prediction System (RDAPS). The KMA predicts rainfall using RDAPS results. RDAPS model generates 48 hours data which is organized 3 hours data accumulated at 00UTC and 12UTC. RDAPS results which are organized 3 hours time scale are converted into daily rainfall to compare observed daily rainfall. In this study, 9 cases are applied to convert RDAPS results to daily rainfall data. The MAP (mean areal precipitation) in Geum river basin are computed by using KMA which are 2005 are used. Finally, the best case which gives the close value to the observed rainfall data is obtained using the average absolute relative error (AARE) especially for the Geum River basin.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.7
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• pp.1017-1035
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• 2018

The European Union (EU) is the world's third largest producer of beef. This contributes to the economy, rural development, social life, culture and gastronomy of Europe. The diversity of breeds, animal types (cows, bulls, steers, heifers) and farming systems (intensive, extensive on permanent or temporary pastures, mixed, breeders, feeders, etc) is a strength, and a weakness as the industry is often fragmented and poorly connected. There are also societal concerns regarding animal welfare and environmental issues, despite some positive environmental impacts of farming systems. The EU is amongst the most efficient for beef production as demonstrated by a relative low production of greenhouse gases. Due to regional differences in terms of climate, pasture availability, livestock practices and farms characteristics, productivity and incomes of beef producers vary widely across regions, being among the lowest of the agricultural systems. The beef industry is facing unprecedented challenges related to animal welfare, environmental impact, origin, authenticity, nutritional benefits and eating quality of beef. These may affect the whole industry, especially its farmers. It is therefore essential to bring the beef industry together to spread best practice and better exploit research to maintain and develop an economically viable and sustainable beef industry. Meeting consumers' expectations may be achieved by a better prediction of beef palatability using a modelling approach, such as in Australia. There is a need for accurate information and dissemination on the benefits and issues of beef for human health and for environmental impact. A better objective description of goods and services derived from livestock farming is also required. Putting into practice "agroecology" and organic farming principles are other potential avenues for the future. Different future scenarios can be written depending on the major driving forces, notably meat consumption, climate change, environmental policies and future organization of the supply chain.

• Journal of Environmental Science International
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• v.25 no.1
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• pp.67-83
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• 2016

In order to improve the prediction of the regional air quality modeling in the Seoul metropolitan area, a sensitivity analysis using two PBL and microphysics (MP) options of the WRF model was performed during four seasons. The results from four sets of the simulation experiments (EXPs) showed that meteorological variables (especially wind field) were highly sensitive to the choice of PBL options (YSU or MYJ) and no significant differences were found depending on MP options (WDM6 or Morrison) regardless of specific time periods, i.e. day and night, during four seasons. Consequently, the EXPs being composed of YSU PBL option were identified to produce better results for meteorological elements (especially wind field) regardless of seasons. On the other hand, the accuracy of all simulations for summer and winter was somewhat lower than those for spring and autumn and the effect according to physics options was highly volatile by geographical characteristics of the observation site.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.47-64
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• 2021

In this study, the annual and monthly groundwater recharge for the Sapgyo-cheon upstream basin in Chungnam Province was evaluated by water balance analysis utilizing WetSpass-M model. The modeling input data such as topography, climate parameters, LAI (Leaf Area Index), land use, and soil characteristics were established using ArcGIS, QGIS, and Python programs. The results showed that the annual average groundwater recharge in 2001 - 2020 was 251 mm, while the monthly groundwater recharge significantly varied over time, fluctuating between 1 and 47 mm. The variation was high in summer, and relatively low in winter. Variation in groundwater recharge was the largest in July in which precipitation was heavily concentrated, and the variation was closely associated with several factors including the total amount of precipitation, the number of days of the precipitation, and the daily average precipitation. This suggests the extent of groundwater recharge is greatly influenced not only by quantity of precipitation but also the precipitation pattern. Since climate condition has a profound effect on the monthly groundwater recharge, evaluation of monthly groundwater recharge need to be carried out by considering both seasonal and regional variability for better groundwater usage and management. In addition, the mathematical tools for groundwater recharge analysis need to be improved for more accurate prediction of groundwater recharge.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.83-91
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• 2010

Generally, the GCM (General Circulation Model) data by IPCC climate change scenarios are used for future weather prediction. IPCC GCM models predict well for the continental scale, but is not good for the regional scale. This paper tried to generate future temperature and precipitation of 8 scattered meteorological stations in South Korea by using the MIROC3.2 hires GCM data and applying LARS-WG downscaling method. The MIROC3.2 A1B scenario data were adopted because it has the similar pattern comparing with the observed data (1977-2006) among the scenarios. The results showed that both the future precipitation and temperature increased. The 2080s annual temperature increased $3.8{\sim}5.0^{\circ}C$. Especially the future temperature increased up to $4.5{\sim}7.8^{\circ}C$ in winter period (December-February). The future annual precipitation of 2020s, 2050s, and 2080s increased 17.5 %, 27.5 %, and 39.0 % respectively. From the trend analysis for the future projected results, the above middle region of South Korea showed a statistical significance for winter precipitation and south region for summer rainfall.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.E1
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• pp.9-18
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• 2006

Aerosol hygroscopic properties were measured by a tandem differential mobility analyzer (TDMA) system during the Aerosol Characterization Experiment (ACE)-Asia campaign from 31 March to 1 May 2001. Two high flow differential mobility analyzers (DMAs) were used to maximize the count rate on board the Center for Interdisciplinary Remotely Piloted Aircraft (CIRPAS) Twin Otter aircraft. Hygroscopic growth factor distributions of particles having initial dry nanoparticle diameters of 0.040, 0.059, 0.086, 0.126, 0.186, 0.273, 0.400, and $0.586{\mu}m$ were measured during 19 research flights. Data collected during 12 of those flights were used to investigate aerosol mixing state and the influence of aerosol source region on size-resolved hygroscopicity. The uniformity in size-resolved hygroscopicity was quantified to facilitate comparison between measurements made in different air masses. Hygroscopic growth factors are strongly dependent on source region and sizes. Mean hygroscopic growth factors were observed to be greatest when the air mass origin was from the south. The mean growth factors for continental sources decreased with initial size from 1.47 to 1.27 for $0.040{\mu}m\;and\;0.586{\mu}m$, but increased with initial size from 1.44 to 1.8 for $0.040{\mu}m\;and\;0.400{\mu}m$ dry diameters for marine sources.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.948-948
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• 2012

합천댐유역에 대한 기후변화에 따른 수문학적 영향을 정량적으로 분석하기 위해, 기상청에서 제공하는 공간해상도 27km의 MM5 RCM(Regional Climate Model)을 사용하였다. RCM의 기상변수들은 공간적 스케일의 상이성과 RCM 기후변수들의 불확실성 때문에 유출모형인 SWAT의 입력자료로 사용하기에는 어려움이 있다. 특히, RCM 변수들 중 강수량의 경우 한반도 지역의 6월과 10월 사이에 연강수량의 67%이상이 집중되는 계절성을 반영하지 못하고 있는 실정이기 때문에 국내 유역의 유출량 산정에 사용하기 위해서는 지역적 상세화(Downscaling)가 필요하다. 본 연구에서는 RCM 기후변수에 내포된 공간적 스케일의 상이성과 불확실성을 최소화하기 위해 강우관측소 지점을 단위로 한 다지점 인공신경망 기법을 적용하여 강수량, 습도, 최고기온 및 최저기온에 대한 상세화를 실시하였다. 강수의 경우 여름철 태풍사상을 모의하기 위한 Stochastic Typhoon Simulation기법과 Baseline(1991~2010)과 Projection(2011~2100) 사이의 강수량 보정을 위한 Dynamic Quantile Mapping 기법을 적용하여, 강수량의 불확실성을 최소화 하고자 하였다. 상세화된 기후자료를 이용한 SWAT 모형의 일(Daily) 단위 강우-유출 모의결과를 2011~2040년, 2041~2070년, 2071~2100년으로 구분하여 추세분석을 실시하였다.