• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.23-26
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• 2003

월별 최고기온 및 최저기온 분포도를 작성하였다. 그림은 4월의 기온으로서, 기온의 변이폭은 최고기온이 12 ~ 2$0^{\circ}C$, 최저기온이 -2 ~ 8$^{\circ}C$ 이다. 사과원 B 주변은 최고기온 18$^{\circ}C$, 최저기온 2$^{\circ}C$로 추정된다. 후지품종의 개화는 남서쪽에서 4월 26일 처음 시작되어 서부지역이 4월말, 동부지역이 5월 초에 만개 한다.(중략)

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.7-10
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• 2003

월별 최고기온 및 최저기온 분포도를 작성하였다. 그림은 4월의 기온으로서, 기온의 변이폭은 최고기온이 2 ~ 2$0^{\circ}C$, 최저기온이 -4 ~ 7$^{\circ}C$ 이다. 사과원 A는 최고기온 16$^{\circ}C$ ,최저기온 4$^{\circ}C$로 추정된다. 후지품종의 개화는 남서쪽에서 4월 26일 처음 시작되어 서부지역이 4월말, 동부지역이 5월 초에 만개 한다. (중략)

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.19-22
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• 2003

월별 최고기온 및 최저기온 분포도를 작성하였다. 그림은 4월의 기온으로서, 기온의 변이폭은 최고기온이 4 ~ 2$0^{\circ}C$, 최저기온이 -4 ~ 6$^{\circ}C$ 이다. 사과원 D 주변은 최고기온 17$^{\circ}C$, 최저기온 3$^{\circ}C$로 추정된다. 후지품종의 개화는 남서쪽에서 4월 26일 처음 시작되어 서부지역이 4월말, 동부지역이 5월 초에 만개 한다.(중략)

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.31-34
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• 2003

월별 최고기온 및 최저기온 분포도를 작성하였다. 그림은 4월의 기온으로서, 기온의 변이폭은 최고기온이 9 ~ 19$^{\circ}C$, 최저기온이 -1 ~ 6$^{\circ}C$ 이다. 사과원 0 주변은 최고기온 17$^{\circ}C$, 최저기온 4$^{\circ}C$로 추정된다. 후지품종의 개화는 남서쪽에서 4월 26일 처음 시작되어 서부지역이 4월말, 동부지역이 5월 초에 만개 한다.(중략)

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.3
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• pp.215-221
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• 1988

The hop yield prediction model developed based on meteorological elements in Hoeongseong was Y=6,042.846-17.665 $X_1$-0.919 $X_2$-96.538 $X_3$-138.105 $X_4$＋86.910 $X_{5}$ ＋ $X_{6}$ with MS $E_{p}$ of 25.258, $R_{p}$$^{2}$ of 0.9991, R $a_{p}$$^{2}$ of 0.9962 and $C_{p}$ of 7.00. The minimum air temperature at early growing stage ( $X_1$), the total precipitation at cone ripening stage ( $X_2$), the maximum air temperature at flower bud differentiation stage ( $X_3$) and the maximum air temperature at flowering stage ( $X_4$) influenced on hop yield as decrement weather elements. The average air temperature at early growing stage ( $X_{5}$ ) and the total sunshine hours at cone development stage ( $X_{6}$ ) influenced on hop yield as increment weather elements.lements.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.4
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• pp.323-328
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• 1988

The hop alpha-acid content prediction model developed with meteorological elements in Hoeongseong was Y=28.369-0.003X$_1$＋1.558X$_2$-1.953X$_3$-0.335X$_4$-0.003X$\sub$5/-0.119X$\sub$6/, with MSEp of 0.004, Rp$^2$ of 0.9987, Rap$_2$ of 0.9949 and Cp of 7.00. The total sunshine hours (X$_1$), the maximum temperature (X$_3$) and the total precipitation (X$\sub$5/) at flowering stage. the maximum temperature at flower bud differentiation stage (X$_4$) and the maximum temperature at cone ripening stage (X$\sub$6/) influenced on hop alpha .acid content as decrement weather elements. The maximum temperature at cone development stage(X$_2$) effected on ${\alpha}$-acid content as increment weather element.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.206-206
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• 2023

지구온난화로 인한 기후변화에 따라 평균강수량과 증발량이 증가하며 강우지역 집중화와 강우강도가 높아질 가능성이 크다. 우리나라의 경우 협소한 국토면적과 높은 인구밀도로 기후변동의 영향이 크기 때문에 한반도에 적합한 유역규모의 수자원 예측과 대응방안을 마련해야 한다. 이를 위한 수자원 관리를 위해서는 유역에서 강수량, 유출량, 증발량 등의 장기적인 자료가 필요하며 경험식, 물리적 강우-유출 모형 등이 사용되었고, 최근들어 연구의 확장성과 비 선형성 등을 고려하기 위해 딥러닝등 인공지능 기술들이 접목되고 있다. 본 연구에서는 ASOS(동해, 태백)와 AWS(삼척, 신기, 도계) 5곳의 관측소에서 2011년~2020년까지의 일 단위 기상관측자료를 수집하고 WAMIS에서 같은 기간의 오십천 하구 일 유출량 자료를 수집 후 5개 관측소를 기준으로Thiessen 면적비를 적용해 기상자료를 구축했으며 Angstrom & Hargreaves 공식으로 잠재증발산량 산정해 3개의 모델에 각각 기상자료(일 강수량, 최고기온, 최대 순간 풍속, 최저기온, 평균풍속, 평균기온), 일 강수량과 잠재증발산량, 일 강수량 - 잠재증발산량을 학습 후 관측 유출량과 비교결과 기상자료(일 강수량, 최고기온, 최대 순간 풍속, 최저기온, 평균풍속, 평균기온)로 학습한 모델성능이 가장 높아 최적 모델로 선정했으며 일, 월, 연 관측유출량 시계열과 비교했다. 또한 같은 학습자료를 사용해 다층 퍼셉트론(Multi Layer Perceptron, MLP) 앙상블 모델을 구축하여 수자원 분야에서의 인공지능 활용성을 평가했다.

• Journal of the Korean Wood Science and Technology
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• v.38 no.1
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• pp.66-74
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• 2010

This study was carried out to investigate the optimum condition for sap exudation of Acer mono Max. tree in a site of Mt. Baekun, Kwangyang city, Korea. Amount of sap exudation, air temperature, relative air humidity and tree diameter at breast height (DBH) were monitored for the period of January 5 through March 28, 2008, and correlation analysis of several factors affecting on sap exudation was carried out. As the diameter of Acer mono at breast height increased, the amount of sap was linearly proportional. Sap exudation initiated at February 18, and occurred intensively in the period of February 28 through March 10, resulting in 84% of total sap amount by volume. During sap exudation, the minimum temperature was averaged at $-2.4{\pm}1.5^{\circ}C$ and the maximum at $6.0{\pm}1.8^{\circ}C$, while there was no sap exudation whenever temperature was below or above $0^{\circ}C$ all the day long. The maximum temperature, range of temperature and the maximum, minimum and mean humidities in air were significant factors affecting on amount of sap. The maximum air temperature had the highest correlation coefficient with 0.768 (P < 0.01) and was also considered as the principal factor by partial-correlation analysis. These results showed that sap exudation required daily air-temperature fluctuation from below to above $0^{\circ}C$, and the amount of sap was strongly dependent on the highest daily-temperature and DBH of tree.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.1
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• pp.25-31
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• 2008

Information on daily maximum air temperature is important in predicting the status of plants and insects, but the uneven and sparse distribution of weather stations prohibits timely access to the data in regions with complex topography. Since cumulative solar irradiance plays a critical role in determining daily maximum temperature on any sloping surfaces, derivation of a quantitative relationship between cumulative solar irradiance and the resultant daily maximum temperature is a prerequisite to development of such estimation models. Air temperatures at 8 sideslope locations with similar elevation and slope angle but aspect, circumventing a cone-shaped, grass-covered parasitic volcano (c.a., 570 m diameter for the bottom circle and 90m bottom-to-top height), were measured from June to December in 2007. Daily maximum temperatures from each location were compared with the average of 8 locations (assumed to be the temperature measured at a "horizontal reference" position). The temperature deviation at all locations increased with the day of year (or sun elevation) from summer solstice to winter solstice. Averaged over the entire period, the south facing location was warmer by $1^{\circ}C$ in daily maximum temperature than "horizontal reference" and the north facing location was cooler by $0.8^{\circ}C$ than the reference, resulting in the year round average south-north temperature difference of $1.8^{\circ}C$. In November, both south and north facing slopes showed the greatest deviation of $+2.0^{\circ}C$ and $-1.3^{\circ}C$, respectively in daily maximum temperature at monthly scale. On a daily scale, the greatest deviation was +3.8 and $2.7^{\circ}C$ at the south and north slope, respectively. The cumulative solar irradiance (on the slope for 4 hours from 11:00 to 15:00 TST) explained >60% of the variance in daily maximum temperature deviations among 8 locations, suggesting a feasibility of developing an estimation model for daily maximum temperature over complex topography at landscape scales.