• 제목/요약/키워드: climate model

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기상방재 대책수립을 위한 아시아지역 기상모형에 필요한 지표경계조건의 구축 (Construction of Surface Boundary Conditions for the Regional Climate Model in Asia Used for the Prevention of Disasters Caused by Climate Changes)

  • 최현일
    • 한국방재학회 논문집
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    • 제7권5호
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    • pp.73-78
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    • 2007
  • 전세계적으로 지구온난화와 기상이변으로 인한 인명과 재산의 피해는 해마다 증가하고 있으며, 최근 한반도의 기후와 기온은 지구평균치보다 큰 변화가 일어나고 있다. 지구전체기상모형(Global Climate Model 또는General Circulation Model GEM)보다 고해상도의 모의가 가능한 지역기상모형(Regional Climate Model RCM)은 기후 변동, 변화 및 그 영향과 관련된 여러 문제들을 파악하는데 사용된다. 이러한 기상모형을 위한 기존 입력자료들의 가용성, 정확도, 그리고 일관성의 결여로 인하여 제한되고 있는 모형의 예측능력 향상을 위해 새로운 지표경계조건들(Surface Boundary Condition SBC)의 필요성이 요구되고 있다. 따라서, 정확도 높은 측정자료의 확보와 과학적 근거에 의한 자료선택 및 결측보정이 새로운 지표경계조건 구축에 선결조건이 되어야 한다. 이 연구의 목적은, 기상방재 수립을 위한 아시아 지역기상모형에 필요한 정확도 높은 지표경계조건 자료를 구축하는데 있다. 산정된 지표경계조건들은 30km 크기의 격자망으로 구성된 한반도를 포함한 아시아 지역기상모형의 계산망에 대해 구축되어, 이 지역의 기상 및 수문 예측모의를 위한 다른 분포형모형들의 입력자료로도 사용이 가능하다.

지역 기후 모형을 이용한 한반도 강수 모의에서 수평 해상도의 영향 (Impact of Horizontal Resolution of Regional Climate Model on Precipitation Simulation over the Korean Peninsula)

  • 이영호;차동현;이동규
    • 대기
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    • 제18권4호
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    • pp.387-395
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    • 2008
  • The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.

서리발생 예측 정확도 향상을 위한 방법 연구 (Study on Improvement of Frost Occurrence Prediction Accuracy)

  • 김용석;최원준;심교문;허지나;강민구;조세라
    • 한국농림기상학회지
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    • 제23권4호
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    • pp.295-305
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    • 2021
  • 본 연구에서는 서리발생과 관련된 기상요인을 선정하여 랜덤포레스트(RF)를 이용한 서리발생 유무 분류모형을 구축하였고, 이와 더불어 기상인자의 중요도와 데이터 세트를 구성하는 방법들을 비교하는 실험을 수행하였다. 그 결과, 서리발생에 대한 분류 모형을 구축할 경우에 데이터 세트의 양이 많더라도 모형 구축을 위해 학습하기 위한 데이터 세트에서 특정 값이 월등히 많은 불균형은 모형의 예측력에 좋지 못한 영향을 미치는 것으로 분석되었다. 또한, 이번 연구에서 수집된 25지역의 서리발생과 관련된 기상요인에 대해 지역별로 그룹화하여 중요도가 높은 기상요인을 반영한 모형 구축하는 것보다 하나의 통합된 모형을 구축하는 것이 더 효율적인 것으로 나타났다. 이번 연구를 통해 분석된 결과와 서리예측을 위한 기상요인에 대한 추가분석 연구를 수행한다면 정확도 높은 서리발생 예측모형을 구축할 수 있을 것이라 예상한다.

CLIMATE CHANGE IMPACT OVER INDIAN AGRICULTURE - A SPATIAL MODELING APPROACH

  • Priya, Satya;Shibasaki, Ryosuke
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.107-114
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    • 1999
  • The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

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지역기후모형 자료를 이용한 낙동강 권역의 논 관개용수 수요량 예측 (Prediction of Paddy Irrigation Demand in Nakdong River Basin Using Regional Climate Model Outputs)

  • 정상옥
    • 한국농공학회논문집
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    • 제51권4호
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    • pp.7-13
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    • 2009
  • The paddy irrigation demand for Nakdong river basin in Korea due to the climate change have been analyzed using regional climate model outputs. High-resolution (27 ${\times}$ 27 km) climate data for SRES A2 scenario produced by the Meteorological Research Institute (METRI), South Korea, and the observed baseline climatology dataset (1971-2000) were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by METRI. Maps showing the predicted spatial variations of changes in climate parameters and paddy irrigation requirements have been produced using the geographic information system. The results of this study showed that the average growing season temperature will increase steadily by 1.5 $^{\circ}C$ (2020s A2), 3.2 $^{\circ}C$ (2050s A2) and 5.2 $^{\circ}C$ (2080s A2) from the baseline (1971-2000) 19.8 $^{\circ}C$. The average growing season rainfall will change by -3.4 % (2020s A2), 0.0 % (2050s A2) and +16.5 % (2080s A2) from the baseline value 886 mm. Assuming paddy area and cropping pattern remain unchanged the average volumetric irrigation demands were predicted to increase by 5.3 % (2020s A2), 8.1 % (2050s A2) and 2.2 % (2080s A2) from the baseline value 1.159 ${\times}$ $10^6\; m^3$. These projections are different from the previous study by Chung (2009) which used a different GCM and downscaling method and projected decreasing irrigation demands. This indicates that one should be careful in interpreting the results of similar studies.

현업 기후예측시스템에서의 지면초기화 적용에 따른 예측 민감도 분석 (Application of Land Initialization and its Impact in KMA's Operational Climate Prediction System)

  • 임소민;현유경;지희숙;이조한
    • 대기
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    • 제31권3호
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    • pp.327-340
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    • 2021
  • In this study, the impact of soil moisture initialization in GloSea5, the operational climate prediction system of the Korea Meteorological Administration (KMA), has been investigated for the period of 1991~2010. To overcome the large uncertainties of soil moisture in the reanalysis, JRA55 reanalysis and CMAP precipitation were used as input of JULES land surface model and produced soil moisture initial field. Overall, both mean and variability were initialized drier and smaller than before, and the changes in the surface temperature and pressure in boreal summer and winter were examined using ensemble prediction data. More realistic soil moisture had a significant impact, especially within 2 months. The decreasing (increasing) soil moisture induced increases (decreases) of temperature and decreases (increases) of sea-level pressure in boreal summer and its impacts were maintained for 3~4 months. During the boreal winter, its effect was less significant than in boreal summer and maintained for about 2 months. On the other hand, the changes of surface temperature were more noticeable in the southern hemisphere, and the relationship between temperature and soil moisture was the same as the boreal summer. It has been noted that the impact of land initialization is more evident in the summer hemispheres, and this is expected to improve the simulation of summer heat wave in the KMA's operational climate prediction system.

데이터 기반 모델에 의한 강제환기식 육계사 내 기온 변화 예측 (Data-Based Model Approach to Predict Internal Air Temperature in a Mechanically-Ventilated Broiler House)

  • 최락영;채영현;이세연;박진선;홍세운
    • 한국농공학회논문집
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    • 제64권5호
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    • pp.27-39
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    • 2022
  • The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.

우리나라 16개 지자체 벼논에서 DNDC 모델을 이용한 온실가스 배출량 평가 (Evaluation of Greenhouse Gas Emissions using DNDC Model from Paddy Fields of 16 Local Government Levels)

  • 정현철;이종식;최은정;김건엽;서상욱;소규호
    • 한국기후변화학회지
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    • 제5권4호
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    • pp.359-366
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    • 2014
  • This research was conducted to estimate methane emission from paddy field of 16 local government levels using the DNDC(DeNitrification-DeComposition) model from 1990 to 2010. Four treatments used in DNDC model for methane emission calculations were (1) midseason drainage with rice straw, (2) midseason drainage without rice straw, (3) continuous flooding with rice straw, and (4) continuous flooding without rice straw. Methane emissions at continuous flooding with rice straw were the highest ($471kg\;C\;ha^{-1}$) while were the lowest ($187kg\;C\;ha^{-1}$) at midseason drainage without rice straw. The average methane emission for 21 years was the highest ($1,406Gg\;CO_{2-eq}$.) in Jeonnam province because of its large cultivation area. Jeju province had the highest the average methane emission per unit area due to the organic content in soil.

기후변화 시나리오를 고려한 농업용 저수지의 미래 용수공급 지속가능성 전망 (Projection of Future Water Supply Sustainability in Agricultural Reservoirs under RCP Climate Change Scenarios)

  • 남원호;홍은미;김태곤;최진용
    • 한국농공학회논문집
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    • 제56권4호
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    • pp.59-68
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    • 2014
  • Climate change influences multiple environmental aspects, certain of which are specifically related to agricultural water resources such as water supply, water management, droughts and floods. Understanding the impact of climate change on reservoirs in relation to the passage of time is an important component of water resource management for stable water supply maintenance. Changes on rainfall and hydrologic patterns due to climate change can increases the occurrence of reservoir water shortage and affect the future availability of agricultural water resources. It is a main concern for sustainable development in agricultural water resources management to evaluate adaptation capability of water supply under the future climate conditions. The purpose of this study is to predict the sustainability of agricultural water demand and supply under future climate change by applying an irrigation vulnerability assessment model to investigate evidence of climate change occurrences at a local scale with respect to potential water supply capacity and irrigation water requirement. Thus, it is a recommended practice in the development of water supply management strategies on reservoir operation under climate change.

수자원 영향평가를 위한 기후변화 시나리오의 불확실성 평가 (Uncertainties estimation of AOGCM-based climate scenarios for impact assessment on water resources)

  • 박이형;임은순;권원태;이은정
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2005년도 학술발표회 논문집
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    • pp.138-142
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    • 2005
  • The change of precipitation and temperature due to the global. warming eventually caused the variation of water availability in terms of potential evapotranspiration, soil moisture, and runoff. In this reason national long-term water resource planning should be considered the effect of climate change. Study of AOGCM-based scenario to proposed the plausible future states of the climate system has become increasingly important for hydrological impact assessment. Future climate changes over East Asia are projected from the coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios using multi-model ensembles (MMEs) method (Min et al. 2004). MME method is used to reduce the uncertainty of individual models. However, the uncertainty increases are larger over the small area than the large area. It is demonstrated that the temperature increases is larger over continental area than oceanic area in the 21st century.

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