A Study On Predicting Cherry Blossoming Date in S. KOREA Using A New Growing Degree Days.

Accurate prediction of cherry blossoming date is an important information for apiaries as well as local governments preparing spring cherry blossom festivals. Dozens of studies have attempted to predict cherry blossoming date using growing degree days (GDD) derived from meteorological prediction data. 

However, most of previous studies on GDD are somewhat lack of theoretical basis since, first of all, monthly mean meteorological data is used and, secondly, only temperature is considered in estimating the GDD.   

In this study, we developed a new GDD estimating method considering both temperature and daylight hours, and applied it to the results from a regional climate model, Weather Research and Forecasting (WRF). For the study, WRF model, which has three nested domains of 3kmúI3km resolution in the last domain centered at S. Korea, is integrated under griven initial and lateral boundary conditions from Pusan National University Coupled General Circulation Model (PNU CGCM) for 10 years from 1999 to 2008. Using the long-term prediction data of high-resolution in time and space, new GDD and cherry blossoming date are hindcasted. According to the analysis of the cherry blossoming date predictability, the new method has better performance compared to the previous one in terms of RMSE and correlation coefficient.

Acknowledgments

This work was funded by “The Rural Development Administration Research and Development Program”

Keywords: Growing Degree Days, Cherry blossom flowering, WRF