• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 추계학술대회
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• pp.423-426
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• 2005

The purpose of this research is to understand the role of safety climate in the safety management system. Based on the 121 responses from facilities got Occupational Health &Safety Assessment Series (OHSAS) 18000 certification, the results of statistic analysis show that there is significant relationship between safety climate, work attitudes and Organizational Citizenship Behaviors (OCB).

• 대기
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• 제23권2호
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• pp.237-243
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• 2013

A set of scripts for GrADS (Grid Analysis and Display System) and R was implemented to produce agricultural climate information using the future climate scenarios based on the Representative Concentration Pathways. The GrADS script was used to calculate agricultural climate indices including growing degree days and cooling degree days. The script generated agricultural climate maps of these indices, which are compatible with common Geographic Information System (GIS) applications. To perform a statistical analysis using the agricultural climate maps, a script for R, which is open source statistical software, was used. Because a large number of spatial climate data were produced, parallel processing packages such as SNOW, doSNOW, and foreach were used to perform a simple statistical analysis in the R script. The parallel script of R had speedup on workstations with multi-CPU cores.

• 한국농공학회논문집
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• 제57권5호
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• pp.69-80
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• 2015

The majority of projections of future climate come from Global Circulation Models (GCMs), which vary in the way they were modeled the climate system, and so it produces different projections about conceptualizing of the weather system. To implement climate change impact assessment, it is necessary to analyze trends of various GCMs and select appropriate GCM. In this study, climate data in 25 GCMs 41 outputs provided by Coupled Model Intercomparison Project Phase 5 (CMIP5) was downscaled at eight stations. From preliminary analysis of variations in projected temperature, precipitation and evapotranspiration, five GCM outputs were identified as candidates for the climate change impact analysis as they cover wide ranges of the variations. Also, GCM outputs are compared with trends of HadGCM3-RA, which are established by the Korean Meteorological Administration. From the results, it can contribute to select appropriate GCMs and to obtain reasonable results for the assessment of climate change.

• 한국기후변화학회지
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• 제9권1호
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• pp.75-80
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• 2018

The problem of water shortages and water related disasters caused by climate change has increased the seriousness of water problems and the importance of water treatment technology capable of securing clean water is expanding. In this study, we analyzed not only the water pollutant generated by the filtration system technology of various water treatment technologies but also the indirect greenhouse gas emissions generation, and analyzed the influence on the environment. The subjects of study are Fabric Filter, Reverse Osmosis System and Pressurized Microfiltration Device which are widely used for water treatment and we analyzed the impact on the environment using the Life Cycle Assessment (LCA) method using the electricity amount necessary for use, the water purification efficiency, the throughput per ton and the cost. The amount of greenhouse gas generated when the Pressurized Microfiltration Device operates for 1 year is $2.15E+04kg\;CO_2-eq$., Fabric Filter is $3.29E+04kg\;CO_2-eq$., and Reverse Osmosis System is $1.68E+05kg\;CO_2-eq$. As a result of analyzing the amount of greenhouse gas generated at the time of purifying 1 ton of the Pressurized Microfiltration Device and the conventional filtration system, the Pressurized Microfiltration Device was $20.5g\;CO_2-eq$., Fabric Filter was $34.7g\;CO_2-eq$., and Reverse Osmosis System was $191.7g\;CO_2-eq$. The amount of greenhouse gas generated was calculated to be 41.0% less than that of the Fabric Filter by the Pressurized Microfiltration Device and 89.3% less than the Reverse Osmosis System. From the viewpoint of climate change, it is necessary to select a filtration system that takes climate change into account, not from the viewpoint of water quality removal efficiency and economic efficiency according to future water treatment applications, and it is necessary to select a water treatment filtration system more researches and improvements will be made for.

• 한국초지조사료학회지
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• 제43권3호
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate 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).

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 공동학술발표회
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• pp.212-212
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• 2017

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.222-222
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• 2015

Vietnam is one of the most vulnarable countries affected by climate change and sea level rise. One of the consequences of climate change and sea level rise is the increase of salinity intrusion into the rivers which is challenging to irrigation systems in coastal areas. This indicates the necessary to study the ability of taking water through sluice gates of irrigation systems in coastal zones, especially in the dry season with the effects of climate change and sea level rise in the future. In this paper, Nam Thai Binh irrigation system is selected as a case study. The irrigation system is one of 22 biggest irrigation systems of the Red River delta in Vietnam located in coastal region. The computed duration is selected in dry season to irrigate for Winter-Spring crops. The irrigation water for the study area is taken from different sluice gates along the Red River and the Tra Ly River. In this paper, MIKE-11 model was applied to assess the ability of taking water for irrigation of the study area in current situation and in the context of climate change and sea level rise senario in 2050 (under the medium emissions scenario (B2) published by the Ministry of Natural Resources and Environment of Vietnam published in 2012) with different condition of water availability. The operation of the gates depends on the water levels and sanility conditions. The sanility and water level at different water intake gates of Nam Thai Binh irrigation system were simulated with different senarios with and without climate change and sea level rise. The result shows that, under climate change and sea water level rise, some gates can take more water but some can not take water because of salinity excess and the total water taking from the different gates along the rivers decrease while the water demand is increase. The study indicates the necessary to study quantitatively some recommended solutions in the study area particularly and in coastal region generally in Vietnam to ensure water demand for irrigation and other purposes in the context of climate change and sea level rise in the future.

• 한국농림기상학회지
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• 제26권3호
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• pp.209-218
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• 2024

농촌진흥청 국립농업과학원은 공동연구를 통해 개발한 Pusan National University/Rural Development Administration (PNU/RDA) 전지구-한반도 앙상블 장기예측시스템을 운영 중이다. 이 시스템은 1~6개월의 미래 상세기후예측자료를 생산한다. 일최고, 일최저, 일평균기온, 강수량 등 20종의 변수로 구성되어 있으며, 농업예측 분야에서 필요로 하는 일사량, 토양수분, 지중온도 등과 같은 농업기상 변수를 포함한다. 시간해상도는 일단위이며, 공간해상도는 5km 간격의 격자형태로, 지점형태로 값을 추출(내삽)하거나 행정구역 평균하여 활용이 가능하다. 최종 생산된 상세기후예측자료의 계절별 평년 기온 및 강수분포를 살펴봤을 때, 평년값을 관측과 비슷한 값으로 나타냈으며 공간적 분포 또한 상세한 지형적 효과를 반영하여 관측과 유사하게 모의하여 신뢰성을 입증하였다. 따라서 국립농업과학원의 장기(1~6개월) 상세기후예측 자료는 농업 전망 및 계획 수립에 유용한 자료로 활용될 수 있을 것으로 기대된다. 이러한 상세기후예측자료는 국립농업과학원 기후변화평가과를 통해 제공받을 수 있다.

• 대기
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• 제17권4호
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• pp.483-492
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• 2007

The objective of this study is to describe scientific progresses in understanding of climate change in the Intergovernmental Panel on Climate Change (IPCC) assessment reports, contributed by Working group I. Since 1988, IPCC's four assessment reports showed significant improvements in understanding of observed climate change, drivers of climate change, detection and attribution of climate change, climate models, and future projection. The results are based on large amounts of observation data, sophisticated analyses of data, improvements of climate models and the simulations. While the First Assessment Report (FAR) in 1990 reported that a detectable anthropogenic influence on climate has little observational evidence, the Fourth Assessment Report (AR4) reported that warming of the climate system is unequivocal and is very likely due to human influences. It is also noted that anthropogenic warming and sea level rise would continue for centuries due to the time scales associated with climate processes and feedbacks, even if greenhouse gas were to be stabilized.

• 대기
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• 제23권3호
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• pp.347-356
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• 2013

The climate projection with a high spatial resolution is required for the studies on regional climate changes. The Korea Meteorological Administration (KMA) has provided downscaled RCP (Representative Concentration Pathway) scenarios over Korea with 1 km spatial resolution. If there are additional climate projections produced by dynamically downscale, the quality of impacts and vulnerability assessments of Korea would be improved with uncertainty information. This technical note intends to instruct the methods to downscale the climate projections dynamically from the Community Earth System Model (CESM) to the Weather Research and Forecast (WRF) model. In particular, here we focus on the instruction to utilize CAM2WRF, a sub-program to link output of CESM to initial and boundary condition of WRF at Linux platform. We also provide the example of the dynamically downscaled results over Korean Peninsula with 50 km spatial resolution for August, 2020. This instruction can be helpful to utilize global scale climate scenarios for studying regional climate change over Korean peninsula with further validation and uncertainty/bias analysis.