• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.455-460
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• 2008

본 연구에서는 1997년 1월부터 2006년 12월까지의 기상청에서 제공하는 31개 자동기상관측망(AWS: Automatic Weather Stations)에 의한 지표 근처 기온($^{\circ}C$) 및 강수(mm) 자료를 이용하여 서울 지역 기상인자의 시 공간 구조 분석 및 변화경향과 변이성을 도출하였다. 미관측지점의 값을 추정하기 위하여 주변 관측지점들을 고려하여, 그 영향은 거리에 반비례함을 반영하는 공간통계학적 방법 중 IDSW(Inverse Distance Squared Weighing:거리자승역산가중)를 적용하여 보관하였다. 그 결과 서울시의 기온과 강수량 모두 1997년에 비해 2006년의 기온이 약 $1.03^{\circ}C$, 강수량이 약 483mm 증가한 것으로 나타났다. 기후변이성의 특성은 과거 10년 동안 기온의 경우 산림지역에서는 변화의 폭이 높게 나타났으며, 시간이 지나면서 감소하는 경향을 보였다. 주거 지역의 경우 변화이 폭이 낮게 나타났으며, 시간이 지나면서 증가하는 경향을 보였다. 그러나 강수량의 경우 산림지역과 주거지역의 변이성의 차이가 나타나지 않았다.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.190-203
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• 2015

VRI(Vulnerability-Resilience Index), which is defined as a function of 3 variables: climate exposure, sensitivity, and adaptive capacity, has been quantified for the case of Typhoon which is one of the extreme weathers that will become more serious as climate change proceeds. Because VRI is only indicating the relative importance of vulnerability between regions, the VRI quantification is prerequisite for the effective adaptation policy for climate in Korea. For this purpose, damage statistics such as amount of damage, occurrence frequency, and major damaged districts caused by Typhoon over the past 20 years, has been employed. According to the VRI definition, we first calculated VRI over every district in the case of both with and without weighting factors of climate exposure proxy variables. For the quantitative estimation of weighting factors, we calculated correlation coefficients (R) for each of the proxy variables against damage statistics of Typhoon, and then used R as weighting factors of proxy variables. The results without applying weighting factors indicates some biases between VRI and damage statistics in some regions, but most of biases has been improved by applying weighting factors. Finally, due to the relations between VRI and damage statistics, we are able to quantify VRI expressed as a unit of KRW, showing that VRI=1 is approximately corresponding to 500 hundred million KRW. This methodology of VRI quantification employed in this study, can be also practically applied to the number of future climate scenario studies over Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.181.1-181.1
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• 2010

기후변화의 주요인이 되는 온실가스 감축을 목표로 화석연료를 대체하기 위한 대체 에너지 개발을 위한 많은 노력이 진행되고 있다. 풍력 에너지와 같은 신재생에너지는 이러한 하나의 해결 수단이 될 수 있으며 풍력 에너지 사업의 활성화를 위해서는 정확한 풍력 정보 제공이 우선이다. 풍력-기상자원지도는 풍력 발전에 유용한 정보 제공을 위한 목적으로 중규모 수치 모델을 이용하여 작성된다. 본 연구에서는 중규모 수치 모델의 정확도 향상을 위한 자료동화 방법으로써 Four-Dimensional Data Assimilation (FDDA) 방법을 이용한다. 풍력-기상자원지도는 공간분해능 1 km 해상도로 개발된다. 풍력-기상자원지도는 1998-2008년까지의 평균적인 상태에 대하여 모의를 하기 위하여 통계적인 방법으로 11년 기간의 평균과 유사한 기간을 선정하였다. 풍력-기상자원지도는 연 평균, 월 평균 풍속과 주 풍향, 주풍향 발생 비율 등의 정보를 제공한다. 우리나라 풍속의 평균 분포는 내륙 산악지역, 남해안, 제주도에서 강풍이 발생하며 주 풍향은 대체로 북서풍이다. 주 풍향의 발생비율은 산악 지역과 남 동해안에서 높아 풍력 발전의 최적지 정보를 제공한다. 1 km 해상도의 모델과 관측의 오차는 서해안 등의 해안지역보다 강원 산악지역에서 오차가 더욱 증가하였다. 이러한 산악 지역의 오차는 복잡한 지형에서는 1km 미만의 수 백 m 해상도 수치모의가 필요함을 지시한다. 따라서 본 연구에서는 WRF-LES 모형을 이용하여 333m 해상도의 기상자원지도를 개발한다. 333m 해상도의 자원지도 영역은 강원도 지역에 대하여 모의되었다. 333m 해상도의 풍속 분포는 1km 해상도의 풍속 분포와 비교하였을 때 풍속의 분포가 보다 세밀하게 표현되었다. 정량적인 검증을 하였을 때 관측소에 따라 차이는 있었으나 1km 해상도에서 과대 모의된 풍속의 분포가 현저히 개선이 되었으며, 시간적인 경향도 잘 일치함을 보였다.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.474-481
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• 2017

When designing photovoltaic power plants in Korea, the prediction of photovoltaic power generation at the design phase is carried out using PVSyst, PVWatts (Overseas power generation prediction software), and overseas weather data even if the test site is a domestic site. In this paper, for a comparative study to predict power generation using weather information, domestic photovoltaic power plants in two regions were selected as target sites. PVsyst, which is a commercial power generation forecasting program, was used to compare the accuracy between the predicted value of power generation (obtained using overseas weather information (Meteonorm 7.1, NASA-SSE)) and the predicted value of power generation obtained by the Korea Meteorological Administration (KMA). In addition, we have studied ways to improve the prediction of power generation through comparative analysis of meteorological data. Finally, we proposed a revised solar power generation prediction model that considers climatic factors by considering the actual generation amount.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.284-301
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• 2023

The changes in rice climatic yield potential (CYP) across the Korean Peninsula are evaluated based on the new climate change scenario produced by the National Institute of Agricultural Sciences with 18 ensemble members at 1 km resolution under a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) emission scenarios. To overcome the data availability, we utilize solar radiation f or CYP instead of sunshine duration which is relatively uncommon in the climate prediction f ield. The result show that maximum CYP(CYPmax) decreased, and the optimal heading date is progressively delayed under warmer temperature conditions compared to the current climate. This trend is particularly pronounced in the SSP5-85 scenario, indicating faster warming, except for the northeastern mountainous regions of North Korea. This shows the benef its of lower emission scenarios and pursuing more efforts to limit greenhouse gas emissions. On the other hand, the CYPmax shows a wide range of feasible futures, which shows inherent uncertainties in f uture climate projections and the risks when analyzing a single model or a small number of model results, highlighting the importance of the ensemble approach. The f indings of this study on changes in rice productivity and uncertainties in temperature and solar radiation during the 21st century, based on climate change scenarios, hold value as f undamental information for climate change adaptation efforts.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.242-249
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• 2006

Potential impacts of the future climate change on crop production can be inferred by crop simulations at a landscape scale, if the climate data may be provided at appropriate spatial scales. Northern Gyunggi Province is one of the few prospective regions in South Korea for growing quality soybeans. Any geographical shift of production areas under the changing climate may influence the current land planning policy in this region. A soybean growth simulation was performed at 342 land units in northern Gyunggi province to test the potential geographical shift of the current production areas for quality soybeans in the near future (form 2011 to 2100). The land units for soybean cultivation were selected by the land use, the soil characteristics, and the minimum arable land area. Daily maximum and minimum temperature, precipitation, the number of rain days and solar radiation were extracted for each land unit from the future digital climate models (DCM, 2011-2040, 2041-2070, 2071-2100). Daily weather data for 30 years were randomly generated for each land unit for each normal year by using a well-known statistical method. They were used to run CROPGRO-Soybean model to simulate the growth, phonology, and yields of 3 cultivars representing different maturity groups grown at 342 land units. According to the model calculations, the warming trend in this region will accelerate the flowering and physiological maturity of all cultivars, resulting in a 7 to 9 days reduction in overall growing season and a 1 to 15% reduction in grain yield of early to medium maturity cultivars. There was a slight increase in grain yield of the late maturing cultivar under the projected climate by 2070, but a decreasing tend was dominant by the year 2100.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.103-105
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• 2019

오늘날 우리나라는 기후변화로 인하여 하절기 국지성 집중호우의 발생빈도가 증가하고 있으며 이로 인해 발생하는 돌발홍수로 매년 인명피해가 발생하고 있다. 이러한 돌발홍수는 작은 지역에서 빠르게 발생하기 때문에 일반적인 홍수예보로는 대비하기 적합하지 않다. 따라서 이렇게 국지적으로 발생하는 돌발홍수를 대비하기 위해서는 최대한 빠른 시간 안에 집중호우 지역에 대한 기상정보 분석이 필수적이다. 본 논문에서는 보다 신속 정확한 기상정보 분석을 위하여 고성능컴퓨터(High Performance Computer) 기반의 홍수예보모형을 운영하는 방안을 제시하였다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• The Journal of Bigdata
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• v.2 no.1
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• pp.17-26
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• 2017

The gradual desertification in Northeastern China brought about by the industrial development and global warming, has affected the Korean peninsula as evident by the ultrafine dust geographically and seasonally. People with severe respiratory problems, senior citizens and the infants are susceptible to the ill effects of fine dust which could prove fatal to them. Hence, we need to study the root cause of fine dust emergence and the correlation verification between fine dust and its side effects. This study firstly analyzed clean and contaminated areas classified by industrial elements. We utilized air, weather and industrial data in the area. Next, we detected a change of fine dust in terms of weather and climate. We analyzed correlation of air and weather by influence from domestic and neighboring country. The result indicated that China is the culprit of the emergence of fine dust predicament. Consequently, we can prove that fine dust ($PM_{10}$) and ultrafine dust ($PM_{2.5}$) could arise from geographical, seasonal, and pollutant elements. Therefore, we propose the optimum to make countermeasures about fine dust in terms of industry, topography, population and living residence.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.368-383
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• 2014

Climate change is expected to affect population density, phenology, distribution, morphological traits, reproduction and genetics of insects, and even in the extinction of insects. To develop novel research subjects for predicting climate change effect, basic information about biological and ecological data on insect species should be compiled and reviewed. For this reason, this study was conducted to collect the biological information on insect pests that are essential for predicting potential damage caused by insect pests in future environment. In addition, we compared domestic and foreign research trends regarding climate change effect and suggested future research subjects. Domestic researchers were rather narrow in the subject, and were mostly conducted based on short-term monitoring data to determine relationship between insects and environmental variables. On the other hand, foreign researches studied on various subjects to analyze the effect of climate change, such as changes in distribution of insect using long-term monitoring data or their prediction using population parameters and models, and monitoring of the change of the insect community structure. To determine change of the phenology, distribution, overwintering characteristics, and genetic structures of insects under climate change through development of monitoring technique, in conclusion, further researches are needed. Also, development of population models for major or potential pests is important for prediction of climate change effects.