Seasonal prediction of regional surface air temperature and first‐flowering date over South Korea

Abstract

ABSTRACTThe forecast capability of the first‐flowering date (FFD) over South Korea is evaluated using the seasonal (1‐ to 3‐month lead) prediction from the global [Pusan National University (PNU) coupled general circulation model (CGCM) v1.1] and regional [Weather Research and Forecast (WRF) v3.0] climate models. Gridded data with high spatial (3 km) and temporal (daily) resolution are produced using the physically based dynamical models. Dynamical downscaling is performed using WRF v3.0 with the lateral forcing from hourly outputs of PNU CGCM v1.1. Statistical correction is then used to eliminate systematic bias in the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999–2008 by applying the corrected daily temperature predictions to the phenological thermal‐time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) clearly represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predicted the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. Even though the upcoming flowering phenology could not be accurately predicted, the present study approach may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically based atmospheric dynamics.