• Title/Summary/Keyword: 기상요인

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A Study of Influence Factors for Reservoir Evaporation Using Multivariate Statistical Analysis (다변량 통계분석을 이용한 저수지증발량 영향인자에 관한 연구)

  • Lee, Kyungsu;Kwak, Sunghyun;Seo, Yong Jae;Lyu, Siwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.237-240
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    • 2017
  • 지구온난화로 인해 세계 곳곳에서 기온상승이 관측되고 있으며, 이는 전지구적 기후시스템의 변화를 보여주는 대표적인 예이다. 온도를 비롯한 강수량, 풍속, 증발량 등의 기상학적, 수문학적 인자들이 각각 서로에게 영향을 주고 받으며 복잡하게 변화할 것이고, 그 변화폭도 점점 커질 것이다. 증발에 영향을 미치는 인자들은 크게 세 가지로 나뉘는데, 태양복사에너지, 온도, 바람, 기압, 습도와 같은 기상학적인자, 증발표면의 특성인자 그리고 수질인자로 분류할 수 있다. 증발에 영향을 주는 인자들은 예전부터 알려져 있지만 이들 간의 복잡한 상호작용에 대해 정확히 이해하기는 쉽지 않다. 본 연구에서는 댐유역의 증발량에 영향을 미치는 기상인자 파악을 위해 2008부터 2016년까지 관측된 낙동강수계 내 안동댐과 남강댐의 기상자료(기온, 강수량, 풍속, 상대습도, 기압, 일사량, 일조시간, 전운량)를 이용한 변화를 분석하였으며, 다변량 통계기법인요인분석을 통해 증발량과 상관성이 높은 인자들을 분류하였다. 안동댐과 남강댐 공통적으로 증발량과 기온, 기압이 같은 요인으로 분류되고 높은 상관성을 보였으며, 강수량, 일조시간, 일사량, 전운량이 같은 요인으로 분류되었다. 국내의 증발량 측정지점에 대한 추가적인 분석과 영향인자를 이용한 다변량회귀식과 인공신경망 통해 증발량 미측정 지점의 증발량 산정이 가능할 것으로 판단된다.

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The Relationship between Meteorogical Factors and Soybean Seed Yield (기상요인이 대두종실수량에 미치는 영향)

  • Won, J.L.;Choi, Y.H.;Song, H.S.;Kwon, S.H.
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.28 no.3
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    • pp.351-357
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    • 1983
  • To study the relationships between soybean seed yield and meteorological elements, the investigation into the important agronomic characters of Bongeui cultivar and climatic factors such as precipitation, rainy days, and temperature from 1970 to 1981 was made. The results obtained were summarized as follows: 1) Coefficients of variabilities for pod-filling rate, seed yield, number of pods per plant, and seed weight were about 38%, 30%, 30%, and 5.5%, respectively. 2) Weather conditions mainly in July and August influenced soybean production. Particularly, high temperature played an important role in soybean yield reduction. 3) Correlation coefficients between maximum, minimum, or average temperature of July (and, in the case of August, maximum temperature only) and yield or seed weight, and between those of August and podfilling rate were significantly negative. 4) Regression equations between average temperature of July or maximum temperature of August and yield were Y=-42.46X +1200.86 and Y=-37.95X + 1210.42, respectively. 5) High temperature during the flowering stage affected soybean seed yield reduction significantly.

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Fire Risk Assessment Based on Weather Information Using Data Mining (데이터마이닝을 이용한 기상정보에 따른 화재 위험 평가)

  • Ryu, Joung Woo;Kwon, Seong-Pil
    • Fire Science and Engineering
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    • v.29 no.5
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    • pp.88-95
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    • 2015
  • We propose a weather-related service for fire risk assessment in order to increase fire safety awareness in everyday life. The proposed service offers a fire risk assessment level according to weather forecasts and a degree of fire risk according to fire factors under certain weather conditions. In order to estimate the fire risk, we produced a risk matrix through data mining with a decision tree using investigation data and weather data. Through the proposed service, residents can calculate the degree of fire risk under certain weather conditions using the fire factors around them. In addition, they can choose from various solutions to reduce fire risk. In order to demonstrate the feasibility of the proposed services, we developed a system that offers the services. Whenever weather forecasting is carried out by the Korea Meteorological Administration, the system produces the fire risk assessment levels for seven major cities and nine provinces of South Korea in an online process, as well as the fire risk according to fire factors for the weather conditions in each region.

Climatic Influence on Seed Oil Concentration in Soybean (Glycine max) (기상요인이 대두의 지방함량에 미치는 영향)

  • 양무희
    • Korean Journal of Plant Resources
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    • v.10 no.2
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    • pp.151-158
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    • 1997
  • This study was carried out to identify how soybean seed oil is influenced by climatic factors and to investigate how genotypes differ in their responses. Twelve lines selected were studied in 13 environments of North Carolina. Responses of oil concentration and total seed oil to climatic variables were investigated using a linear regression model. The best response models were determined. There were wide climatic effects in oil concentration and total seed oil. The lowest oil concentration environment was characterized by the most HTD and the smallest VADTRg and the lowest total oil environment was distinguished by the largest VADTRa and the smallest VMnDT. For oil concentration, most lines except for NC107 responded negatively to MxDT, HTD, ADT, and ADTRg, although they had different degrees of sensitivities, indication that warmer temperature may result in decreased oil concentration. All lines responded positively to VMnDT, VADTRg, and ADRa, although they had different degrees of sensitivities, suggesting that larger variation in minimum daily temperature and average daily temperature range and more average daily rain may result in increased oil concentration. Eleven lines had best response models with 1 to 3 variables. However, although NC109 did not show a significant sensitivity to any variable, it had the best response model with 2 significant variables, demonstrating that an interaction between 2 variables might be more critical in determining oil concentration than one variable.

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Development of Traffic Accident Safety Index under Different Weather Conditions (기상특성에 따른 교통사고 안전성 평가지표 개발 (고속도로를 대상으로))

  • Park, Jun-Tae;Hong, Ji-Yeon;Lee, Su-Beom
    • Journal of Korean Society of Transportation
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    • v.28 no.1
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    • pp.157-163
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    • 2010
  • It is well known that weather conditions are closely related with the number and severity of traffic accidents. At present, installation of safety countermeasures including systems is common approach to reduce the damage of traffic accidents at expressways. In this study, the differences of causation factors to influence traffic accidents considering road alignment characteristics and weather conditions. In order to identify the relationship between road and weather conditions, discriminant analysis has been performed with 500 traffic accident data at expressways. Weather conditions are divided into several categories such as snow, sunny, rain, fog, and cloud. Also, road conditions such as types of pavements, grades are analyzed. As the results, major impacting road conditions to traffic accidents are concrete pavement and 3% or more down grades. In these road conditions, visible distance will be reduced and actual braking distances will be increased. This study shows that the expressway sections under concrete pavement and down grades should be more cautious than other sections. It also shows that fog condition is the mose dangerous situation in terms of traffic accidents.

Meteorological Factor Analysis of Algific Talus Slope and Distribution of Rare and Vulnerable Plants to Climate Change (풍혈의 미기상요인분석과 희귀 및 기후변화 취약식물 분포 연구)

  • Tae-Young Hwang;Jong-Won Lee;Ho-Geun Yun;Jong-Bin An
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2022.09a
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    • pp.58-58
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    • 2022
  • 본 연구는 국내 6곳의 풍혈의 기능과 식물분포를 통하여 풍혈의 보전대책과 관리방안을 위한 기초자료를 확보하기 위해 진행하였다. 조사는 홍천 방내리, 정선 여탄리, 정선 운치리, 연천 동막리, 제천 금수산, 보은 구병산에 위치하는 풍혈 6곳을 선정하였고 풍혈에 기상측정장비를 설치하여 2021년 3월부터 2022년 3월까지 온도와 습도의 미기상요인을 측정하였다. 풍혈이 위치하는 지역의 미기상요인은 기상청 자료를 활용하였고 측정된 풍혈의 미기상요인과 비교 분석하였으며, 관속식물상은 계절별로 진행하여 각 풍혈에 서식하는 희귀식물과 북방계식물, 기후변화 취약식물을 분석하였다. 풍혈 6곳의 미기상요인 분석결과 온도는 보은 구병산 풍혈을 제외한 5곳의 풍혈은 여름철 냉혈의 기능을 나타냈고, 보은 구병산 풍혈은 겨울철 온혈의 기능을 하는 것으로 나타났으며, 습도는 6곳 모두 주변 지역보다 높게 나타났다. 멸종위기종 2급은 백부자, 산작약, 연잎꿩의다리 3분류군, 희귀식물은 산개나리, 월귤 등 23분류군, 북방계식물은 과남풀, 꽃개회나무 등 129분류군, 기후변화취약식물은 검종덩굴, 도깨비부채 등 23분류군으로 확인되었다. 풍혈은 기후변화 취약식물의 피난처로서 역할을 하는 것으로 나타났으나 산림유전자원보호구역으로 지정된 홍천 방내리 풍혈을 제외한 나머지 풍혈은 관리가 미흡하다. 정선 여탄리 풍혈은 인근 도로에서의 외래식물의 유입, 정선 운치리 풍혈은 인근의 양봉장과 관광객 등의 인간활동에 의한 훼손, 연천 동막리 풍혈은 인근 경작지 등의 사유지로 인한 관리의 어려움, 제천 금수산 풍혈은 관광지화로 인한 훼손, 보은 구병산 풍혈은 등산객의 답압으로 인한 훼손이 진행되고 있는 것으로 나타났다. 이에 따라 풍혈과 희귀 및 기후변화 취약식물들의 정기적인 모니터링과 풍혈 주변의 팬스 설치 등의 적극적인 보전방안이 필요하다고 판단된다.

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Developing Forest Fire Occurrence Probability Model Using Meteorological Characteristics (기상자료(氣象資料)를 이용(利用)한 산불발생확률모형(發生確率模型)의 개발(開發))

  • Choi, Kwan;Han, Sang Yoel
    • Journal of Korean Society of Forest Science
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    • v.85 no.1
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    • pp.15-23
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    • 1996
  • Preparing the era of forest resources management requires studies on forest fire. This study attempted to develop forest fire occurrence model using meteorological characteristics for the practical purposes of forecasting forest fire danger rate. To accomplish this goal, the relationships between forest fire occurrence and meteorological characteristics are estimated. In the process, the forest fire occurrence pattern of the study region(Taegu-Kyungpook) is categorized by employing qualification IV method. The study region was divided into three areas such as, Taegu, Andong and Pohang area. The meteorological variables emerged as affective to forest fire occurrence are relative humidity, longitude of sunshine, and duration of precipitation. To estimate the probability of forest fire danger, forest fire occurrence of three areas are regressed on the time series data of affective meteorological variables using logistic and probit model. The effectiveness of the models estimated are tested and showed acceptable degree of goodness. Those models developed would be helpful to increase the efficiency of forest fire management such as detection of forest fire occurrence and effective disposition of forest fire fight equipments.

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Real-Time Micro-Weather Factors of Growing Field to the Epidemics of Rice Blast (벼 도열병 Epidemics에 미치는 재배 포장 실황기상 요인)

  • Kwon, Jae-Oun;Lee, Soon-Gu
    • Research in Plant Disease
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    • v.8 no.4
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    • pp.199-206
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    • 2002
  • It was investigated on the relationship of the rice blast epidemics and the real-time meteorological factors, at the experimental paddy field in 1997. Weather factors(temperature, relative humidity, irradiation, precipitation, the direction of wind, wind speed, soil temperature and leaf-wetness, etc) were measured by using the automated weather station. The most influenced weather factor to blast epidemics, was the average max-temp($R^2$= 0.95) during 10 days before leaf blast epidemics, while the least thing was wind speed($R^2$= 0.24). The most potential weather factors correlated with the blast epidemics were T-ave(average temperature), T-max(maximum temperature), RH(Relative Humidity) and RD(Relative Humidity > 90% hrs). A statistics model(the regression equation) of the blast epidemics with the potential weather factors, was established as tallows ; Y = -3410.91 - 23.91 $\times$ T-ave + 28.56 $\times$ T-max + 41.0 $\times$ RH - 3.75 $\times$ RD, ($R^2$= 0.99). (T-ave >= 19$^{\circ}C$, T-max - T-ave >= 5.2$^{\circ}C$ and RH% >= 90.4%). According to the fitness test($\chi$$^2$) of the model, the observed blast disease severity was quite close to those expected.

A study on the estimation of onion's bulb weight using multi-level model (다층모형을 활용한 양파 구중 추정 연구)

  • Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.763-776
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    • 2020
  • Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.