• 제목/요약/키워드: Climatology

검색결과 180건 처리시간 0.026초

정식일 이동에 따른 배추 잠재수량성의 시공간적 변화 전망 (Projecting the Spatio-Temporal Change in Yield Potential of Kimchi Cabbage (Brassica campestris L. ssp. pekinensis) under Intentional Shift of Planting Date)

  • 김진희;윤진일
    • 한국농림기상학회지
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    • 제18권4호
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    • pp.298-306
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    • 2016
  • 주산지 배추재배농가에서 기후변화 적응수단의 하나로 사용할 수 있는 것이 정식기 이동이다. 본 연구에서는 여름배추 품종을 대상으로 주어진 정식일부터 매일 기온의 경과에 의해 최적수확기를 예측하고, 결정된 생육 기간 중 기온자료에 의해 배추의 잠재수량(생체중)을 추정할 수 있는 방법을 고안하였다. 이를 위해 정식기 이동에 따른 생육기간 중 기후조건 변화를 온도 기반 열단위로 표현하고, 이를 생육기와 결구기에 맞게 조절한 발육 속도함수에 적용하여 생리적 성숙기를 추정하는 생물계절모형을 개발하였다. 다음에는 생물계절모형에 의해 결정된 재배가능기간에 대하여 매일 열단위 누적에 의해 여름배추의 잠재수량을 계산할 수 있는 수량예측모형(Ahn et al., 2014)을 결합하였다. 이 생물계절-수량 결합모형을 RCP8.5 기반의 남한 상세 기후시나리오(2000-2100)에 적용하여 7월 1일, 8월 1일, 9월 1일, 그리고 10월 1일 등 다양한 날짜에 배추를 정식할 경우 현재평년(2001-2010)과 미래평년(2011-2040, 2041-2070, 2071-2100)에 예상되는 수량성을 잠재수량에 대한 백분율로 표현하였다. 그 결과를 토대로 남한 전역을 810개 집수역으로 나누고 임의 집수역의 최적정식일을 사용자가 손쉽게 찾을 수 있는 시간 - 공간 - 수량 3차원 평가도표를 고안하였다. 이 방법은 미래 새로운 재배적지 탐색은 물론 기존 주산지에서 품종변경 없이 기후변화 적응이 가능한 작부체계 개발에도 유용할 것으로 기대된다.

전구 대양의 극저 해수면온도 공간 분포와 지구과학교과서 데이터 시각화 분석 (Spatial Distribution of Extremely Low Sea-Surface Temperature in the Global Ocean and Analysis of Data Visualization in Earth Science Textbooks)

  • 박경애;손유미
    • 한국지구과학회지
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    • 제41권6호
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    • pp.599-616
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    • 2020
  • 해수면온도는 해양-대기 상호작용, 열속 변화, 대양의 해양 순환을 이해할 수 있는 가장 중요한 해양 변수들 중의 하나이다. 0℃ 이하 -2℃까지 극저 해수면온도는 기후변화 및 지구환경 변화를 유도하고 조절하기 때문에 다른 범위의 해수면온도보다 더 중요하게 다루어져야 한다. 전구 대양에서 이러한 극저 해수면온도의 시간적 공간적 변동성을 이해하기 위하여 1982년부터 2018년까지의 기간 동안 관측된 인공위성 일별 해수면온도 데이터베이스를 활용하여 평균 기후장을 산출하였다. 또한 장기간의 해양 실측 자료에 기반하여 생산된 표층 수온의 기후 평균장을 활용하여 극저 해수면온도가 전구 대양에서 존재하는 해역과 0℃ 등온선의 월별 공간 변동을 분석하였다. 그 결과 극저 해수면온도는 북극해와 남극해와 같은 극지 해역과 고위도의 연해에서 상당한 해양의 표면적을 차지하고 있었다. 이러한 극저 해수면 온도가 어떻게 시각화되어 있는지 검토하기 위하여 6종 지구과학교과서를 분석하였다. 대부분의 교과서에서 해수면온도 삽화는 0℃ 혹은 그 이상 수온에서 부터 도시하여 학생들이 극저 해수면온도에 대한 개념과 역할에 대한 이해를 획득하는 것을 저해하고 있었다. 데이터 시각화는 데이터 리터러시의 주요한 요소 중에 하나이므로 위성 해수면온도 자료가 교과서에 적절하게 시각화되도록 교과서 삽화의 개선이 필요하다. 본 연구는 인공위성 해수면온도 자료와 해양 실측 자료를 활용하여 해양 데이터의 시각화를 통하여 해양학적 소양과 데이터 리터러시가 동시에 함양되고 강화될 수 있음을 강조하였다.

Characteristics of the Erythemal Ultraviolet-B (EUV-B) Irradiance in Anmyeon (Korea Global Atmosphere Watch Center)

  • Hong, Gi-Man;Park, Jeong-Gyoo
    • Journal of Korean Society for Atmospheric Environment
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    • 제24권E2호
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    • pp.74-82
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    • 2008
  • We have examined seasonal and annual means of clear-sky solar noon and daily erythemal ultraviolet-B irradiances measured in Anmyeon. The intensity of the EUV-B irradiance is mainly dependent on solar zenith angle (SZA) and total ozone amounts on clear day conditions. The daily maximum occurs near solar noon time and the highest monthly accumulated EUV-B is seen in July in Anmyeon. The maximum daily variation occurs in June and July due to precipitation and clouds. The 7-year trend of EUV-B irradiance shows that it is slightly increasing. Additionally, we could confirm that aerosol effects such as Asian Dust decreases the EUV-B irradiance reaching the ground surface by 35% to 60%. For more than 45% of the summer days, EUV-B irradiacne was high enough that the UV index registered higher than category Extremely High. This information will be very important for evaluation of the UV index for prevention of both skin cancer and ecosystem damages as well as to understand UV climatology over the Korean Peninsula.

클러스터 분석을 통한 종관기단분류 및 서울에서의 일 사망률과의 관련성 연구 (Synoptic Air Mass Classification Using Cluster Analysis and Relation to Daily Mortality in Seoul, South Korea)

  • 김지영;이대근;최병철;박일수
    • 대기
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    • 제17권1호
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    • pp.45-53
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    • 2007
  • In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

녹색섬 풍력자원평가 - 독도 (Wind Resource Assessment for Green Island - Dokdo)

  • 김현구;김건훈;강용혁
    • 한국태양에너지학회 논문집
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    • 제32권5호
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    • pp.94-101
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    • 2012
  • A Dokdo wind resource map has been drawn up for the Green Island Energy Master Plan according to Korea's national vision for 'Low Carbon Green Growth'. The micro-siting software WindSim v5.1,which is based on Computational Flow Analysis, is used with MERRA reanalysis data as synoptic climatology input data, and sensitivity analysis on turbulence model is accompanied. A wind resource assessment has been conducted for the Dokdo wind power dissemination plan, which consists of two 10kW wind turbines to be installed at the Dongdo dock and Dokdo guard building. It is evaluated that the capacity factors at Dongdo dock and Dokdo guard building are about 20% and 30% respectively, and annual and hourly variations of wind power generation have been analyzed, but summertime energy production is predicted to be only 40% of wintertime energy production.

대기중 $CO_2$ 증가에 따른 한반도 강수량 변화 (Precipitation Change in Korea due to Atmospheric $CO_2$ Increase)

  • 오재호;홍성길
    • 물과 미래
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    • 제28권3호
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    • pp.143-157
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    • 1995
  • 대기중 $CO_2$ 배증에 따른 한반도 강수량 변화가 3개 GCM(CCC, UI와 GFDL)의 기후변화 실험에 따른 광역적 강수변동 자료로부터 Robinson과 Finkelstein이 제시한 혼합적 방법에 의하여 계산되었다. 계산 결과 도출된 대기중 CO$ 배증에 따라 예상되는 강수량 변화는 다음과 같다. 봄철에 예상되는 강수량 증가는 약 25mm/yr정도이며 여름철과 가을철의 강수량 증가는 50mm/yr를 상회하였다. 그러나 겨울철에는 13mm/yr 감소하였다. 현 강수량에 대한 백분율로 보면 봄철, 여름철과 가을철에 각각 10%, 13%와 24%의 강수량 증가를 보인 반면에 겨울철에는 현재보다 다소 감소할 것이 예상된다.

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Wind-induced tall building response: a time-domain approach

  • Simiu, Emil;Gabbai, Rene D.;Fritz, William P.
    • Wind and Structures
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    • 제11권6호
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    • pp.427-440
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    • 2008
  • Estimates of wind-induced wind effects on tall buildings are based largely on 1980s technology. Such estimates can vary significantly depending upon the wind engineering laboratory producing them. We describe an efficient database-assisted design (DAD) procedure allowing the realistic estimation of wind-induced internal forces with any mean recurrence interval in any individual member. The procedure makes use of (a) time series of directional aerodynamic pressures recorded simultaneously at typically hundreds of ports on the building surface, (b) directional wind climatological data, (c) micrometeorological modeling of ratios between wind speeds in open exposure and mean wind speeds at the top of the building, (d) a physically and probabilistically realistic aerodynamic/climatological interfacing model, and (e) modern computational resources for calculating internal forces and demand-to-capacity ratios for each member being designed. The procedure is applicable to tall buildings not susceptible to aeroelastic effects, and with sufficiently large dimensions to allow placement of the requisite pressure measurement tubes. The paper then addresses the issue of accounting explicitly for uncertainties in the factors that determine wind effects. Unlike for routine structures, for which simplifications inherent in standard provisions are acceptable, for tall buildings these uncertainties need to be considered with care, since over-simplified reliability estimates could defeat the purpose of ad-hoc wind tunnel tests.

윈드프로파일러 관측 자료를 이용한 장마철 강수 형태 분류와 관련된 종관장의 특성 분석: 2003년-2005년 (Classification of Precipitation Type Using the Wind Profiler Observations and Analysis of the Associated Synoptic Conditions: Years 2003-2005)

  • 원혜영;조천호;백선균
    • 대기
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    • 제16권3호
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    • pp.235-246
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    • 2006
  • Remote sensing techniques using satellites or the scanning weather radars depend mostly on the presence of clouds or precipitation, and leave the extensive regions of clear air unobserved. But wind profilers provide the most direct measurements of mesoscale vertical air motion in the troposphere, even in the context of heavy precipitation. In this paper, the precipitation events during the Changma period was classified into 4 precipitation types - stratiform, mixed stratiform/ convective, deep convective, and shallow convective. The parameters for the classification of analysis are the vertical structure of reflectivity, Doppler velocity, and spectral width measured with the wind profiler at Haenam for a three-year period (2003-2005). In addition, the synoptic fields and total amount of precipitation were analyzed using the Global Final Analyses (FNL) data and the Global Precipitation Climatology Project (GPCP) data. During the Changma period, the results show that the stratiform type was dominant under the moist-neutral atmosphere in 2003, whereas the deep convective type was under the moist unstable condition in 2004. The stratiform type was no less popular than the deep convective type among four seasons because the moist neutral layer was formed by the convergence between the upper-level jet and the low-level jet, and by the moisture transport along the western rim of the North Pacific subtropical anticyclone.

Sensitivity of Indian Summer Monsoon Precipitation to Parameterization Schemes

  • Singh, G.P.
    • 한국제4기학회지
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    • 제24권1호
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    • pp.1-10
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    • 2010
  • The Indian summer monsoon behaved an abnormal way in 2002 and as a result there was a large deficiency in precipitation (especially in July) over a large part of the Indian subcontinent. For the study of deficient monsoon of 2002, a recent version of the NCAR regional climate model (RegCM3) has been used to examine the important features of summer monsoon circulations and precipitation during 2002. The main characteristics of wind fields at lower level (850 hPa) and upper level (200 hPa) and precipitation simulated with the RegCM3 over the Indian subcontinent are studied using different cumulus parameterization schemes namely, mass flux schemes, a simplified Kuo-type scheme and Emanuel (EMU) scheme. The monsoon circulation features simulated by RegCM3 are compared with the NCEP/NCAR reanalysis and simulated precipitation is validated against observation from the Global Precipitation Climatology Centre (GPCC). Validation of the wind fields at lower and upper levels show that the use of Arakawa and Schubert (AS) closure in Grell convection scheme, a Kuo type and Emanuel schemes produces results close to the NCEP/NCAR reanalysis. Similarly, precipitation simulated with RegCM3 over different homogeneous zones of India with the AS closure in Grell is more close to the corresponding observed monthly and seasonal values. RegcM3 simulation also captured the spatial distribution of deficient rainfall in 2002.

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EFFECTS OF RANDOMIZING PATTERNS AND TRAINING UNEQUALLY REPRESENTED CLASSES FOR ARTIFICIAL NEURAL NETWORKS

  • Kim, Young-Sup;Coleman Tommy L.
    • 한국공간정보시스템학회:학술대회논문집
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    • 한국공간정보시스템학회 2002년도 춘계학술대회 논문집
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    • pp.45-52
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    • 2002
  • Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

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