• 한국농림기상학회지
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• 제6권4호
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• pp.272-289
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• 2004

The spatial resolution of local weather and climate information for agronomic practices exceeds the current weather service scale. To supplement the insufficient spatial resolution of official forecasts and observations, gridded climate data are frequently generated. Most ecological models can be run using gridded climate data to produce ecosystem responses at landscape scales. In this lecture, state of the art techniques derived from geospatial climatology, which can generate gridded climate data by spatially interpolating point observations at synoptic weather stations, will be introduced. Removal of the urban effects embedded in the interpolated surfaces of daily minimum temperature, incorporation of local geographic potential for cold air accumulation into the minimum temperature interpolation scheme, and solar irradiance correction for daytime hourly temperature estimation are presented. Some experiences obtained from their application to real landscapes will be described.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.120-122
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• 2003

Geographical position and associated climatic influences can be a negative environmental condition that affects sustainable use of land resources, especially pastoral livestock production. Vegetation condition of the country is sensitively changes upon climate changes and human impacts. Within last 60 years data the annual air temperature has increased in 1.66 degrees in average and the total precipitation amount had almost no change. The main goal of this work is to relate climate change within last 20 years with pasture condition, estimated by NOAA/NDVI data set.

• 대한원격탐사학회지
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• 제36권3호
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• pp.475-486
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• 2020

기후변화 시나리오는 기후변화 대응 연구의 기반이 되는 사항으로, 대용량 시공간 데이터로 구성되어 있다. 데이터의 관점에서는 1종의 시나리오가 약 83 기가바이트(Giga bytes) 이상의 대용량이며, 데이터 형식은 반정형으로 검색, 추출, 저장 및 분석 등 활용상 제약이 있다. 본 연구에서는 대용량, 다중시기 기후변화 시나리오의 활용을 편리하게 개선하기 위하여 공간정보 기반의 극단적 기후사상 분석 도구를 개발하였다. 또한, 개발된 도구를 RCP8.5 기후변화 시나리오에 적용하여 과거 발생한 집중호우 임계치가 미래 발생 가능한 시기와 공간에 대한 시범 분석을 수행하였다. 분석결과, 3일 누적 강우량 587.6 mm 이상인 날이 2080년대 약 76회 발생하는 것으로 분석되었으며, 집중호우는 국지적으로 발생하였다. 개발된 분석도구는 초기 설정부터 분석결과를 도출하는 전 과정이 단일 플랫폼에서 구현되도록 하였다. 더불어 상용 소프트웨어가 없어도 분석결과를 다양한 형식(웹 문서형식(HTML), 이미지(PNG), 기후변화 시나리오(ESR), 통계(XLS))으로 구현되도록 하였다. 따라서 본 분석도구 활용을 통해 기후변화에 대한 미래 전망이나 취약성 평가 등의 활용에 도움이 될 것으로 사료되며, 향후 제공될 기후변화 보고서에 따른 기후변화 시나리오 분석 도구 개발에도 사용될 것으로 기대된다.

• 산경연구논집
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• 제11권3호
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• pp.39-50
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• 2020

Purpose: Agriculture, which is heavily influenced by climate conditions, is one of the industries most affected by climate change. In this respect, various studies on the impact of climate change on the agricultural market have been conducted. Since climate change is a long-term phenomenon for more than a decade, long-term projections of agricultural prices as well as climate variables are needed to properly analyze the impact of climate change on the agricultural market. However, these long-term price projections are often major constraints on studies of climate changes. The purpose of this study is to analyze the impacts of climate changes on the Korean onion market using ex-post analysis approach in order to avoid the difficulties of long-term price projections. Research design, data and methodology: This study develops an annual dynamic partial equilibrium model of Korean onion market. The behavioral equations of the model were estimated by OLS based on the annual data from 1988 to 2018. The modelling system is first simulated to have actual onion market conditions from 2014 to 2018 as a baseline and then compared it to the scenario assuming the climatic conditions under RCP8.5 over the same period. Scenario analyses were simulated by both comparative static and dynamic approach to evaluate the differences between the two approaches. Results: According to the empirical results, if the climate conditions under RCP8.5 were applied from 2014 to 2018, the yield of onion would increase by about 4%, and the price of onion would decrease from 3.7% to 17.4%. In addition, the average price fluctuation rate over the five years under RCP8.5 climate conditions is 56%, which is more volatile than 46% under actual climate conditions. Empirical results also show that the price decreases have been alleviated in dynamic model compared with comparative static model. Conclusions: Empirical results show that climate change is expected to increase onion yields and reduce onion prices. Therefore, the appropriate countermeasures against climate change in Korean onion market should be found in the stabilization of supply and demand for price stabilization rather than technical aspects such as the development of new varieties to increase productivity.

• 한국농림기상학회지
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• 제26권1호
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• pp.75-88
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• 2024

우리나라는 수요 곡물의 대부분을 수입으로 의존하기 때문에 주요 곡물 수출 국가의 재배 면적과 생산량 예측을 통해 식량안보를 증진시킬 수 있다. 특히, 밀 주요 수출국인 우크라이나를 대상으로 재배지역의 변화 전망을 파악하는 것이 장기적인 밀 수급에 대한 미래 정책 결정에 도움을 줄 수 있다. 본 연구에서는 작물의 기후적합도를 예측하는 Fuzzy Union 모델을 사용하여 과거 기후조건(1970~2000)에서 우크라이나 지역의 밀의 기후적합도를 평가하고자 하였다. 우크라이나 통계청으로부터 밀 생산량과 재배면적 통계자료를 수집하였다. 또한, 위성영상을 활용하여 작물의 재배면적과 수량에 대한 공간자료인 EarthStat 자료를 수집하였다. 모델로 계산된 기후적합도와 밀 관측지점과 비교하여 임계값을 설정하였다. EarthStat 자료와 실제 관측자료를 비교한 결과 일정 지역에서 재배면적과 수량이 일치하지 않는 지역들이 존재하였다. 과거 기후 조건에서 산출된 기후적합도의 경우에도 지역적인 차이를 보였다. 예를 들어, 우크라이나의 서북부 지역에서 0.8 이상의 높은 기후적합도의 분포를 보였으나 동남부 지역에서는 0.15 수준의 낮은 기후적합도를 보였다. 그러나, 기후적합도의 행정구역별 통계량과 실제 밀 재배면적과 생산량을 비교한 결과 일정 수준의 상관관계를 가졌다. 특히, 단위면적당 생산량과 기후적합도의 상관계수는 0.647로 중위 정상관을 나타냈다. 이러한 결과는 기후적합도를 활용하여 재배면적 추정 및 단위면적당 수량 예측이 가능함을 시사하였다.

• 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.

• 대기
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• 제22권1호
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• pp.129-135
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• 2012

This study restores rainfall measurements taken with the Chugugi (rain gauge) at Wonju, Hamheung, and Haeju from the Deungnok (government records from the Joseon Dynasty). We restored rainfall data corresponding to a total of 9, 13, and 18 years for Wonju, Hamheung, and Haeju, respectively. Based on the restored data, we reconstructed monthly rainfall data. Restoration was most successful for the rainy season months of June, July and August. The restored rainfall data were compared with the summer rainfall data for Seoul as recorded by the Seungjeongwon (Royal Secretariat). In June, the variation in the restored rainfall data was similar to that of the Seungjeongwon data for Seoul. In July and August, however, the variations in the reconstructed data were markedly different from those in the Seoul data (Seungjeongwon). In the case of the worst drought in the summer of 1888, a substantial shortage of rainfall was found in both the Seungjeongwon data for Seoul and the restored data for the three regional locations.

• KIEAE Journal
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• 제11권6호
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• pp.101-108
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• 2011

The weather data has important role for performative building design. If the data location is close to building site, the result of performative design can be accurate. The data which have used nowadays in Korea are from U.S. Department of Energy (DOE) and Korea Solar Energy Society (KSES) but they cover only several locations in Korea which are 4 in DOE and 11 in KSES and there are opinions which it could be served building design efficiently even if the data are not enough. However the weather data for micro-climate are exist which are Green Building Studio Virtual Weather Station (GBS VWS) and Meteonorm weather data. Each weather data has different generation methods which are TMY2, TRY, MM5, and extrapolation. In this research, the weather date for climate are compared with DOE and KSES to check correlation. The result shows the value of correlation in Dry Bulb Temp. and Dew Point Temp. is around 0.9 so they have high correlation in both but in Wind Speed case the correlation(around 0.2) is not exist. In overall result, the data has correlation with DOE and KSES as the value of correlation 0.648 of GBS VW and 0.656 of Meteonorm. Even if the correlation value is not high enough, the patterns of difference in each weather element are similar in scatter plot.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.112-115
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as support vector machine neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the monthly precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 2 grid points including $127.5^{\circ}E/35^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, which produced the best results from the previous study. The output node of neural networks models consist of the monthly precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of SVM-NNM and MLP-NNM performances for the downscaling of the monthly precipitation data. We should, therefore, construct the credible monthly precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• 환경영향평가
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• 제15권4호
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• pp.249-258
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• 2006

Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.