• 제목/요약/키워드: Climate normal data

검색결과 116건 처리시간 0.031초

식물계절모형 입력자료로서 확률추정 기상자료의 이용 가능성 (Feasibility of Stochastic Weather Data as an Input to Plant Phenology Models)

  • 김대준;정유란;윤진일
    • 한국농림기상학회지
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    • 제14권1호
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    • pp.11-18
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    • 2012
  • 월별 기후통계량의 조화해석에 의해 생성한 일 기온 자료가 생물계절모형의 입력자료로서 적합한지 여부를 평가하여 농림업 부문 기후시나리오 응용정보 제작 상오류를 제거하기 위해 본 연구를 수행하였다. 서울관측소의 1971-2000 평년 월별 일 최고기온과 최저기온 평균값으로부터 조화해석에 의해 365일 간 기온자료를 생성하였다. 이것을 널리 검증된 온도시간 기반의 벚꽃 개화모형에 입력하여 휴면, 발아, 개화 등 주요 식물계절을 추정하였다. 같은 기간 중 실측기온자료에 의해 모형을 구동시켜 얻은 결과와 비교한 바, 연차변이를 전혀 반영하지 못하는 것은 물론, 휴면해제 25일 단축, 강제 휴면기간 57일 연장, 발아 14일 지연, 개화 13일 지연등 평균값도 크게 달라 식물계절을 크게 왜곡시키는 것으로 판단되었다. 대안으로서 확률추정기법에 의해 일기상자료를 생성하고 이를 이용하여 모형을 구동한 결과 실측결과에 비해 휴면해제 6일 단축, 강제휴면기간 10일 단축, 발아 3일 지연, 개화 2일 지연 등으로 조화해석자료 사용에 비해 크게 개선되었음을 확인하였다. 연차변이양상 역시 실측기온에 의한 모의결과와 크게 다르지 않아, 향후 이 자료를 농업부문 전자기후도 제작에 적용하면 기후변화 적응정책 수립을 실용수준에서 지원할 수 있을 것으로 보인다.

연속적 결측이 존재하는 기온 자료에 대한 결측복원 기법의 비교 (A comparison of imputation methods for the consecutive missing temperature data)

  • 김희경;강인경;이재원;이영섭
    • 응용통계연구
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    • 제29권3호
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    • pp.549-557
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    • 2016
  • 장기간의 기후 자료가 누적되다 보면 자료의 수집과정에서 시스템적 오류나 측정 장비의 고장 등으로 인하여 연속적 결측이 종종 발생하게 된다. 연속적인 결측 형태를 갖는 경우 시계열 결측 자료를 대체하는 것에 어려움이 따른다. 이러한 경우 참조시계열을 이용하여 결측값을 대체할 수 있다. 참조시계열은 결측이 발생한 시계열과 관련성이 높은 주변지점의 시계열로 구성할 수 있다. 본 연구에서는 결측값을 대체시킬 수 있는 3가지 결측복원 기법-수정된 정규화비율 방법, 회귀 방법, IDW 방법-을 비교하는 시뮬레이션을 수행하였다. 우리나라 14개 지점의 기후관측소의 일평균기온값을 대상으로 비교한 결과 남쪽 해안가에 위치한 기후관측소의 자료에 대해서는 IDW 방법이 가장 정확한 것으로 나타났으며, 그 외 지역의 기후관측소 자료에 대해서는 회귀 방법이 가장 정확한 것으로 나타났다.

지구온난화에 따른 벼 생육 및 생산성 변화 예측 (Assessing Impacts of Global Warming on Rice Growth and Production in Korea)

  • 심교문;노기안;소규호;김건엽;정현철;이덕배
    • 한국기후변화학회지
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    • 제1권2호
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    • pp.121-131
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    • 2010
  • 본 연구에서는 미국에서 개발되어 IBSNAT(International Benchmark Site Network for Agrotechnology Transfer) 사업에 의해 국제적으로 널리 보급된 DSSAT 패키지(CERES-Rice 모형)의 최근 윈도우 버전(DSSAT v4)을 국내에 도입하여, 우리나라 벼 품종과 기상요소, 그리고 국립농업과학원의 정밀농업토양자료 등을 적용하여, 출수생태형별 품종유전모수를 추정한 후, GCM 기후시나리오에 따른 벼 생육 및 생산량의 변동을 시뮬레이션 방법으로 평가하였다. 온도가 상승함에 따라 출수 기간은 단축하는 것으로 조사되었다. 온도가 $2^{\circ}C$ 상승하였을 때는 7~8일 단축되는 것으로 모의되었고, $5.2^{\circ}C$ 상승하는 UKMO 기후시나리오를 적용하면 최대 16~18일 단축되는 것으로 추정되었다. 출수 기간은 출수생태형의 구분 없이 온도 상승에 따라 비슷하게 단축되는 것으로 분석되었지만, 벼 등숙 기간의 변화는 출수생태형에 따라 다른 경향을 나타내었다. 즉, 생육 기간이 길은 중만생종의 출수 기간은 온도 상승 정도에 따라 14~18일 짧아졌는데 반하여, 생육 기간이 짧은 조생종의 경우에는 1~3일 짧아져, 단축 정도가 상대적으로 적은 것으로 조사되었다. 온도가 30년 평년 기후(1971~2000년)보다 $2^{\circ}C$$3^{\circ}C$ 상승하는 조건에서, 전국적인 평균 벼 수량은 평년 기후에 의해 추정된 것보다 각각 4.5%와 8.2% 감소하는 것으로 전망되었고, $CO_2$ 배증에 따라 온도 상승을 가장 높게 예측하는 UKMO 전지구 기후변화모델을 적용하여, 전국적으로 벼 수량을 모의하였을 때는 평년기후에 적용하여 추정한 수량보다 전국 평균 14.9% 감소하는 것으로 분석되었다. 이는 온난화로 인한 등숙 기간의 단축뿐 아니라 고온에서의 임실율 저하, 그리고 야간고온에 의한 호흡손실 때문인 것으로 판단된다. 따라서 지역별 정밀농업기후 추정과 이에 근거한 최적 품종의 선택, 이앙기 및 수확기 등 생육 기간의 조절 등 온난화 대응기술의 개발이 필요하다.

경기북부지역 정밀 수치기후도 제작 및 활용 - II. 콩 생육모형 결합에 의한 재배적지 탐색 (Development and Use of Digital Climate Models in Northern Gyunggi Province - II. Site-specific Performance Evaluation of Soybean Cultivars by DCM-based Growth Simulation)

  • 김성기;박중수;이영수;서희철;김광수;윤진일
    • 한국농림기상학회지
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    • 제6권1호
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    • pp.61-69
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    • 2004
  • A long-term growth simulation was performed at 99 land units in Yeoncheon county to test the potential adaptability of each land unit for growing soybean cultivars. The land units for soybean cultivation(CZU), each represented by a geographically referenced land patch, were selected based on land use, soil characteristics, and minimum arable land area. Monthly climatic normals for daily maximum and minimum temperature, precipitation, number of rain days and solar radiation were extracted for each CZU from digital climate models(DCM). The DCM grid cells falling within a same CZU were aggregated to make spatially explicit climatic normals relevant to the CZU. A daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CROPGRO-soybean model suitable for 2 domestic soybean cultivars were derived from long-term field observations. Three foreign cultivars with well established parameters were also added to this study, representing maturity groups 3, 4, and 5. Each treatment was simulated with the randomly generated 30 years' daily weather data(from planting to physiological maturity) for 99 land units in Yeoncheon to simulate the growth and yield responses to the inter-annual climate variation. The same model was run with input data from the Crop Experiment Station in Suwon to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for evaluation. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific cultivar. A computer program(MAPSOY) was written to help utilize the results in a decision-making procedure for agrotechnology transfer. transfer.

로지스틱 회귀분석과 판별분석을 활용한 광주광역시의 폭염에 미치는 영향분석 (Analysis of the Impact of Heatwaves in Gwangju using Logistic Regression and Discriminant Analysis)

  • 김윤수;공영선;장인홍
    • 통합자연과학논문집
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    • 제17권2호
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    • pp.33-41
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    • 2024
  • Abnormal climate is a phenomenon in which meteorological factors such as temperature and precipitation are significantly higher or lower than normal, and is defined by the World Meteorological Organization as a 30-year period. However, over the past 30 years, abnormal climate phenomena have occurred more frequently around the world than in the past. In Korea, abnormal climate phenomena such as abnormally high temperatures on the Korean Peninsula, drought, heatwave and heavy rain in summer are occurring in March 2023. Among them, heatwaves are expected to increase in frequency compared to other abnormal climates. This suggests that heatwave should be recognised as a disaster rather than just another extreme weather event. According to several previous studies, greenhouse gases and meteorological factors are expected to affect heatwaves, so this paper uses logistic regression and discriminant analysis on meteorological element data and greenhouse gas data in Gwangju from 2008 to 2022. We analyzed the impact of heatwaves. As a result of the analysis, greenhouse gases were selected as effective variables for heatwaves compared to the past, and among them, chlorofluorocarbons were judged to have a stronger effect on heatwaves than other greenhouse gases. Since greenhouse gases have a significant impact on heatwaves, in order to overcome heatwaves and abnormal climates, greenhouse gases must be minimized to overcome heatwaves and abnormal climates.

Inner harbour wave agitation using boussinesq wave model

  • Panigrahi, Jitendra K.;Padhy, C.P.;Murty, A.S.N.
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제7권1호
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    • pp.70-86
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    • 2015
  • Short crested waves play an important role for planning and design of harbours. In this context a numerical simulation is carried out to evaluate wave tranquility inside a real harbour located in east coast of India. The annual offshore wave climate proximity to harbour site is established using Wave Model (WAM) hindcast wave data. The deep water waves are transformed to harbour front using a Near Shore spectral Wave model (NSW). A directional analysis is carried out to determine the probable incident wave directions towards the harbour. Most critical threshold wave height and wave period is chosen for normal operating conditions using exceedence probability analysis. Irregular random waves from various directions are generated confirming to Pierson Moskowitz spectrum at 20m water depth. Wave incident into inner harbor through harbor entrance is performed using Boussinesq Wave model (BW). Wave disturbance experienced inside the harbour and at various berths are analysed. The paper discusses the progresses took place in short wave modeling and it demonstrates application of wave climate for the evaluation of harbor tranquility using various types of wave models.

Spatial Prediction Based on the Bayesian Kriging with Box-Cox Transformation

  • Choi, Jung-Soon;Park, Man-Sik
    • Communications for Statistical Applications and Methods
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    • 제16권5호
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    • pp.851-858
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    • 2009
  • In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

Vulnerability assessment of upland public groundwater wells against climate change

  • Shin, Hyung Jin;Lee, Jae Young;Jo, Sung Mun;Cha, Sang Sun;Park, Chan Gi
    • 농업과학연구
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    • 제47권3호
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    • pp.577-596
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    • 2020
  • Drought is a natural disaster that directly affects agriculture, which has a great impact on the global agricultural production system and yield. The lack of water storage in most parts of the country due to the lack of precipitation has caused a great increase in social interest in drought due to the dryness of rice fields and crops. As the drought period increases and the drought intensity becomes stronger, it is believed that drought damage to crops will continue; thus, it is necessary to understand the vulnerability to irrigation performance and the ability of irrigation facilities. Therefore, this study conducted a vulnerability assessment of irrigation facilities (public Groundwater well) in cities across the country. The survey was conducted using statistical data from 2007 to 2016, and the vulnerability score was calculated according to the vulnerability evaluation procedure for drought in the irrigation facilities (public groundwater wells). Among 157 regions, 136 areas were very vulnerable; 14 areas were vulnerable; 3 areas were normal; 4 areas were good, and 0 areas were excellent. The vulnerability assessment can be used as basic data for the development or maintenance of field irrigation facilities in the future by understanding the vulnerability of irrigation facilities.

Construction of a Remote Monitoring System in Smart Dust Environment

  • Park, Joonsuu;Park, KeeHyun
    • Journal of Information Processing Systems
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    • 제16권3호
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    • pp.733-741
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    • 2020
  • A smart dust monitoring system is useful for obtaining information on rough terrain that is difficult for humans to access. One of ways to deploy sensors to gather information in smart dust environment is to use an aircraft in the Amazon rainforest to scatter an enormous amount of small and cheap sensors (or smart dust devices), or to use an unmanned spacecraft to throw the sensors on the moon's surface. However, scattering an enormous amount of smart dust devices creates the difficulty of managing such devices as they can be scattered into inaccessible areas, and also causes problems such as bottlenecks, device failure, and high/low density of devices. Of the various problems that may occur in the smart dust environment, this paper is focused on solving the bottleneck problem. To address this, we propose and construct a three-layered hierarchical smart dust monitoring system that includes relay dust devices (RDDs). An RDD is a smart dust device with relatively higher computing/communicating power than a normal smart dust device. RDDs play a crucial role in reducing traffic load for the system. To validate the proposed system, we use climate data obtained from authorized portals to compare the system with other systems (i.e., non-hierarchical system and simple hierarchical system). Through this comparison, we determined that the transmission processing time is reduced by 49%-50% compared to other systems, and the maximum number of connectable devices can be increased by 16-32 times without compromising the system's operations.

시스템 구성요소 통합 및 현업서비스 구축 (Implementation of a Weather Hazard Warning System at a Catchment Scale)

  • 신용순
    • 한국농림기상학회:학술대회논문집
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    • 한국농림기상학회 2014년도 추계 학술발표논문집
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    • pp.74-85
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    • 2014
  • This study is a part of "Early Warning Service for Weather Risk Management in Climate-smart Agriculture", describes the delivery techniques from 840 catchment scale weather warning information using 150 counties unit special weather report(alarm, warning) released from KMA(Korea Meteorological Administration) and chronic weather warning information based on daily weather data from 76 synoptic stations. Catchment weather hazard warning service express a sequential risk index map generated by countries report occurs and report grade(alarm, warning) convert to catchment scale using zonal summarizing method. Additional services were chronic weather warning service at crop growth and accumulated more than 4 weeks, based on an unsuitable weather conditions, representing a relative risk compared to its catchment climatological normal conditions (normal distribution ) in addition to special weather report. Service provided by a real-time catchment scale map overlaid with VWORLD open platform operated by Ministry of Land, Infrastructure and Transport. Also provide a foundation for weather risk information to inform individual farmers to farm located within the catchment zone warning occur.

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