Prediction Skill of East Asian Precipitation and Temperature Associated with El Niño in GloSea5 Hindcast Data

In this study, we investigate the performance of Global Seasonal Forecasting System version 5 (GloSea5) in Korea Meteorological Administration on the relationship between El $Ni{\tilde{n}}o$ and East Asian climate for the period of 1991~2010. It is found that the GloSea5 has a great prediction skill of El $Ni{\tilde{n}}o$ whose anomaly correlation coefficients of $Ni{\tilde{n}}o$ indices are over 0.96 during winter. The eastern Pacific (EP) El $Ni{\tilde{n}}o$ and the central Pacific (CP) El $Ni{\tilde{n}}o$ are considered and we analyze for EP El $Ni{\tilde{n}}o$, which is well simulated in GloSea5. The analysis period is divided into the developing phase of El $Ni{\tilde{n}}o$ summer (JJA(0)), mature phase of El $Ni{\tilde{n}}o$ winter (D(0)JF(1)), and decaying phase of El $Ni{\tilde{n}}o$ summer (JJA(1)). The GloSea5 simulates the relationship between precipitation and temperature in East Asia and the prediction skill for the East Asian precipitation and temperature varies depending on the El $Ni{\tilde{n}}o$ phase. While the precipitation and temperature are simulated well over the equatorial western Pacific region, there are biases in mid-latitude region during the JJA(0) and JJA(1). Because the low level pressure, wind, and vertical stream function are simulated weakly toward mid-latitude region, though they are similar with observation in low-latitude region. During the D(0)JF(1), the precipitation and temperature patterns analogize with observation in most regions, but there is temperature bias in inland over East Asia. The reason is that the GloSea5 poorly predicts the weakening of Siberian high, even though the shift of Aleutian low is predicted. Overall, the predictability of precipitation and temperature related to El $Ni{\tilde{n}}o$ in the GloSea5 is considered to be better in D(0)JF(1) than JJA(0) and JJA(1) and better in ocean than in inland region.

GloSea5의 과거기후 모의자료에서 나타난 El Niño와 관련된 동아시아 강수 및 기온 예측성능