논문 상세보기
pp.56-61
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.
Ⅰ. 서 론
Ⅱ. 재료 및 방법
1. 자료 수집
2. 수치입력 및 자료가공
3. 분석용 data set
4. 일평균기온 추정가능성 분석통계분석
Ⅲ. 결과 및 고찰
1. 연월평균기온의 정규분포 확인
2. 위치정보와 평균기온과의 관계
3. 위치정보를 이용한 일평균기온 추정 가능성
Ⅳ. 요 약
Ⅵ. REFERENCES
