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http://dx.doi.org/10.5333/KGFS.2021.41.1.56

Possibility of Estimating Daily Mean Temperature for Improving the Accuracy of Temperature in Forage Yield Prediction Model  

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)
Publication Information
Journal of The Korean Society of Grassland and Forage Science / v.41, no.1, 2021 , pp. 56-61 More about this Journal
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.
Keywords
Daily mean temperature; Estimation possibility; Longitude; Latitude; Altitude;
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  • Reference
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