Journal of The Korean Society of Grassland and Forage Science (한국초지조사료학회지)

The Korean Society of Grassland and Forage Science (한국초지조사료학회)
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Possibility of Estimating Daily Mean Temperature for Improving the Accuracy of Temperature in Forage Yield Prediction Model

풀사료 수량예측모델의 온도 정밀도 향상을 위한 일평균온도 추정 가능성 검토

  • Kang, Shin Gon (National Institute of Animal Science, RDA) ;
  • Jo, Hyun Wook (College of Animal Life Sciences, Kangwon National University) ;
  • Kim, Ji Yung (College of Animal Life Sciences, Kangwon National University) ;
  • Kim, Kyeong Dae (Gangwondo Agricultural Research and Extension Services) ;
  • Lee, Bae Hun (National Institute of Animal Science, RDA) ;
  • Kim, Byong Wan (College of Animal Life Sciences, Kangwon National University) ;
  • Sung, Kyung Il (College of Animal Life Sciences, Kangwon National University)
  • 강신곤 (농촌진흥청, 국립축산과학원) ;
  • 조현욱 (강원대학교, 동물생명과학대학) ;
  • 김지융 (강원대학교, 동물생명과학대학) ;
  • 김경대 (강원도농업기술원) ;
  • 이배훈 (농촌진흥청, 국립축산과학원) ;
  • 김병완 (강원대학교, 동물생명과학대학) ;
  • 성경일 (강원대학교, 동물생명과학대학)
  • Received : 2021.03.13
  • Accepted : 2021.03.24
  • Published : 2021.03.31
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Abstract

This study was conducted to determine the possibility of estimating the daily mean temperature for a specific location based on the climatic data collected from the nearby Automated Synoptic Observing System (ASOS) and Automated Weather System(AWS) to improve the accuracy of the climate data in forage yield prediction model. To perform this study, the annual mean temperature and monthly mean temperature were checked for normality, correlation with location information (Longitude, Latitude, and Altitude) and multiple regression analysis, respectively. The altitude was found to have a continuous effect on the annual mean temperature and the monthly mean temperature, while the latitude was found to have an effect on the monthly mean temperature excluding June. Longitude affected monthly mean temperature in June, July, August, September, October, and November. Based on the above results and years of experience with climate-related research, the daily mean temperature estimation was determined to be possible using longitude, latitude, and altitude. In this study, it is possible to estimate the daily mean temperature using climate data from all over the country, but in order to improve the accuracy of daily mean temperature, climatic data needs to applied to each city and province.

본 연구는 기 개발된 풀사료 수량예측모델의 기후정밀도 향상을 위하여 지점별 일평균온도 추정의 가능성을 기상대 자료(종관기상관측지점 75개 와 방재기상관측지점 278개)의 연평균기온 및 월평균기온을 이용하여 검토하였다. 연평균기온과 월평균기온은 각각 정규성 확인, 위치정보(경도, 위도 및 해발고도)와의 상관관계 및 다중회귀분석을 실시하였다. 해발고도는 연평균기온 및 월평균기온에도 지속적인 영향을 미치는 것으로 나타났으며, 위도는 6월을 제외한 월평균기온에 영향을 미치는 것으로 나타났다. 경도는 6, 7, 8, 9, 10 및 11월의 월평균기온에 영향을 미치는 것으로 나타났다. 이상의 결과로 부터 일평균기온 추정은 경도, 위도 및 해발고도를 이용하여 가능할 것으로 판단하였다. 본 연구에서 전국의 기상자료를 사용하여 일평균기온의 추정은 가능하지만 보다 정확도를 높이기 위해서는 기상자료를 각 시·도로 세분화하여 적용할 필요가 있다.

Keywords

References

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