NCAM-LAMP를 이용한 고해상도 일단위 기상기후 DB 구축: 일조시간 자료를 중심으로

Shortwave radiation and sunshine hours (SHOUR) are important variables having many applications, including crop growth. However, observational data for these variables have low horizontal resolution, rendering its application to related research and decision making on farming practices challenging. In the present study, hourly solar radiation data were physically generated using the Land-Atmosphere Modeling Package (LAMP) at the National Center for Agro-Meteorology, and then daily SHOUR fields were calculated through statistical downscaling. After data quality evaluation, including case studies, the SHOUR data were added to the existing publically accessible LAMP daily database. The LAMP daily dataset, newly updated with SHOUR, has been provided operationally as input data to the “Gyeonggi-do Agricultural Drought Prediction System,” which predicts agricultural weather disasters and field crop growth status.