• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.159-162
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• 2001

근년의 "따뜻한 겨울" 추세와는 달리 2001년 1월 중순은 일주일 이상 혹독한 한파가 지속되었다. 최저기온이 영하 $25^{\circ}C$ 이하를 기록한 지점만도 철원(-29.2$^{\circ}C$), 홍천(-26.7$^{\circ}C$), 동두천(-26.2$^{\circ}C$), 제천(-26.$0^{\circ}C$), 대관령(-25.6$^{\circ}C$) 등 다섯이며, 순천, 진주, 정읍 등 남부지방 여러 곳에서도 영하 15$^{\circ}C$ 이하의 최저기온이 관측되었다.(중략)관측되었다.(중략)

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.208-217
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• 2023

Accurate estimation of dormancy breaking and first bloom dates is crucial for effective fire blight control by disease model such as Maryblyt in apple orchards. The duration from dormancy breaking to first bloom in apple trees was influenced by daily minimum temperatures during the dormant period. The purpose of this study is to investigate the relationship between minimum temperatures during this period and the time taken for flowering to commence. Webcam data from eight apple orchards, equipped by the National Institute of Horticultural and Herbal Science, were observed from 2019 to 2023 to determine the dates of starting bloom (B1). Additionally, the dormancy breaking dates for these eight sites were estimated using an apple chill day model, with a value of -100.5 DD, based on collected weather data. Two regressions were performed to analyze the relationships: the first regression between the number of days under 0℃ (X₁) and the time from calculated dormancy breaking to observed first bloom (Y), resulting in Y = 0.87 × X₁ + 40.76 with R² = 0.84. The second regression examined the starting date of breaking dormancy (X₂) and the duration from dormancy breaking to observed first bloom (Y), resulting in Y = -1.07 × X₂ + 143.62 with R² = 0.92. These findings suggest that apple anti-chill days are significantly affected by minimum temperatures during the period from dormancy breaking to flowering, indicating their importance in fire blight control measures.

• Journal of Korean Society of Steel Construction
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• v.23 no.3
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• pp.283-294
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• 2011

The variation of temperature in the steel girder bridge by air temperature is measured. A correlation between the daily temperature range, the maximum and minimum temperatures of the day, and the temperature of the bridge are analyzed. With the statistical data from the Korea Meteorological Administration, the temperature correlations analyzed in this study is able to predict temperature variations between the upper flange and the lower flange which calculates the realistic displacement values of a movable support and an expansion joint in design.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.04b
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• pp.88-89
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• 2001

꿀벌의 실내월동에 이용되는 월동용 저온양봉사의 내부환경에 영향을 주는 요소에는 외기온, 저장봉군수, 환기량 등이 있다. 이러한 환경요인을 고려하여 설계 제작된 국내 월동용 저온양봉사의 성능 및 저장봉군수와 양봉사 내부온도의 관계를 분석하고자 경상북도의 7개 지역에 설치된 월동용 저온양봉사(내부크기 폭4.5m×길이3m×높이3m)에 대하여 2000. 11. 25부터 2001, 2. 15까지 실내월동 실험을 수행하였다. 실험대상 지역은 포항, 문경, 상주, 칠곡, 성주, 영양, 안동이며, 지역별 저장봉군수는 각각 14, 74, 85, 110, 163, 170, 260군이다(Table 1). 꿀벌의 월동기간 중 안동과 성주지역을 제외한 5개 지역의 실내 월동성적은 폐사율이 10％미만으로 대체적으로 우수한 것으로 조사되었으나, 월동기간중 지역별 외기온을 분석한 결과, 평균외기온 및 최저외기온이 가장 낮은 지역은 안동이었으며, 그 값이 각각 -3.1℃와 -9.4℃일 때 양봉사 내부의 평균온도와 최저온도는 5.2℃와 3.8℃로 나타났다. 반면에 평균외기온 및 최저외기온이 가장 높은 지역은 포항이었으며 그 값이 각각 1.3℃와 -4.1℃일 때 양봉사 내부의 평균온도와 최저온도는 각각 3.1℃와 1.2℃로 나타나 저온양봉사 내부의 온도환경 조절성능이 모두 우수한 것으로 판단되었다(Table 1). 또한 월동기간중 주.야간으로 양봉사 내.외부의 온도변화를 분석한 결과, 저장봉군수의 증가에 따라 주야간 모두 양봉사 내.외부 온도편차가 증가하는 경향을 나타내었으며 양봉사 내부의 주.야간 평균온도는 모두 꿀벌의 월동에 적정한 범위인 2℃-9℃를 유지하는 것으로 분석되었다(Table 2). 그리고, 월동기간중 외기온이 가장 낮은 시기(1월 13-19일)의 평균 외기온이 -8℃--9℃로 유사한 문경, 상주, 영양, 안동지역의 월동용 저온양봉사의 평균 내부온도는 각각 -2.0℃, -1.0℃, 0.2℃, 4.2℃로 나타나 저장봉군수가 증가함에 따라 월동용 저온양봉사의 내부온도가 증가하여 꿀벌의 월동에 적합한 온도범위를 유지함을 알 수 있었다. 실험기간동안 대부분의 저온양봉사 내부온도는 꿀벌이 월동하기에 적정한 온도범위(2℃-9℃)로 유지하였다(Fig. 1).

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.1
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• pp.84-90
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• 1986

An experiment was conducted to know the effects of planting dates (March 5, 15, and 25 and April 4) and transparent polyethylene (P.E.) film treatments(tunnel, tunnel slit, and mulch) on air and soil temperatures and growth and yield of a sweet corn variety, Great Bell. Maximum air and soil temperatures and minimum air and soil temperatures were greater at tunnel>tunnel slit>mulch in that order. Differences in maximum air and soil temperatures among the P.E. film treatments were much greater than those in minimum air and soil temperatures. However, when film was opened due to high air temperature over 40$^{\circ}C$ in the tunnel, air temperature was similar but soil temperature was lower com-pared to mulch. High temperature stress could be avoided in tunnel slit without opening film by increase in the number of slits. Cold damage of corn seedlings was avoided by tunnel and reduced by tunnel slit, and frost-damaged seedlings under the mulch were recovered in few days. The number of days from planting to silking was reduced as planting date delayed. At early plantings, tunnel enhanced early growth and silking, but it delayed at late plantings because tunnel was opened during the most of day time due to high temperature. Black streaked dwarf virus(BSDV) disease was more severe at early plantings and it was reduced in tunnel slit at late plantings because plants were grown under the film at the time of infection. The number of marketable ears was similar among all treatments except mulch at March 5 planting where BSDV was severely infected. Gross income was high in tunnel and tunnel slit at March 25 planting which had more larger marketbale ears and tunnel and tunnel slit at March 5 planting which had higher market price.

• Journal of the Korean Geographical Society
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• v.34 no.4
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• pp.385-393
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• 1999

본 연구에서는 한라산의 고도별, 사면별, 계절별 기온(일평균, 일최고, 일최저) 분포와 고산식물의 수직적 분포역을 기초로 고산식물별 온도적 범위를 분석한 후 제주도의 온난화에 따른 한라산 고산식물의 미래를 논의하였다. 아울러 고산지에서의 고도별 기온 분포와 수직적 기온 체감이 환산되어 산악지역에서의 기온 분포를 이해하는데 중요한 자료가 확보되었다. 한라산에서의 100m당 기온체감율은 일평균기온이 -0.58$^{\circ}C$, 일최고기온이 -0.53$^{\circ}C$ 범위내에서 분포가 주로 결정되어, 상대적으로 낮은 최고기온 체감율이 고산식물의 생존에 유리하게 작용한 것으로 보인다. 본 연구에서 얻어진 결과는 온난화에 따른 생태계 변화의 모니터링과 경관 보전 측면에서 유용한 생태적 정보를 축적하여, 한라산에 분포하는 희귀하거나, 멸종위기 상태에 있는 고산식물들의 보전과 관련된 지식이 수립될 수 있다.