[논문]QBO와 한반도 지상기온 간의 관계

박창현; 손석우

doi:10.14191/atmos.2022.32.1.039

QBO와 한반도 지상기온 간의 관계
Relationship between the QBO and Surface Air Temperature in the Korean Peninsula 원문보기

대기 = Atmosphere, v.32 no.1, 2022년, pp.39 - 49

박창현 (서울대학교 지구환경과학부) , 손석우 (서울대학교 지구환경과학부)

Abstract ▼ AI-Helper

The relationship between the Quasi-Biennial Oscillation (QBO) and the surface air temperature (SAT) in the Korean Peninsula is investigated for the period of 1979~2019. The QBO shows a statistically significant causal relationship with the Korean SAT in early spring when the El Niño-Southern Oscillation (ENSO)'s effect is relatively weak. In particular, when the QBO wind at 70 hPa is westerly, the Korean SAT becomes colder than normal in March. This relationship in March, which is statistically significant, is valid not only for March QBO but also for February QBO, indicating that the QBO is leading the Korean SAT. The Granger causality test indeed shows a causal relationship between February QBO and March Korean SAT. The QBO-Korean SAT relationship is more pronounced in the southeastern part of the Korean Peninsula. As the QBO-related circulation anomalies are evident in the North Pacific and the eastern Eurasia, they induce the horizontal temperature advection to the southeastern part of the Korean Peninsula. This result suggests that the QBO could be useful for improving seasonal prediction of the Korean SAT in March.

주제어

표/그림 (8)

표 Table 1. The list of 60 ASOS stations. Station number is denoted in parenthesis.
그림 Fig. 1. FPEs (shaded) and the selected optimal lags Og and Og* (red lines) for the (a) restricted and (b) unrestricted regression models in March. Mg and Mg* are the total numbers of parameters used in Eqs. (4) and (5), respectively.
표 Table 2. The values of Og and Og* in each month.
그림 Fig. 2. (a) Regression between the Korean SAT and the QBO. (b) Lagged correlation between the Korean SAT and the QBO. The white circle indicates the statistically significant coefficient at the 95% confidence level. Units of the regression coefficients in (a) are converted into Kelvin by multiplying the standard deviation of the QBO. The QBO lag month at y-axis in (b) denotes the QBO lag with respect to the Korean SAT. For instance, MAR-1 lag month [white circle in (b)] indicates the correlation between the March Korean SAT and the February QBO.
그림 Fig. 3. (a) Regression between the Korean SAT and the QBO in March. (b) Same as (a) but for the February QBO. (c) The Granger causality between the Korean SAT in March and the QBO in February. Blue colored circles indicate the statistically significant regressions at the 95% confidence level. Units of the regression coefficients are converted into Kelvin by multiplying the standard deviation of the QBO.
그림 Fig. 4. Same as Fig. 3c but for the partial Granger causality: (a) the QBO Granger-causes the Korean SAT when conditioned the ENSO's effect and (b) ENSO Granger-causes the Korean SAT when conditioned the QBO's effect. Units of the regression coefficients are converted into Kelvin by multiplying the standard deviation of the QBO (a) and ENSO (b).
그림 Fig. 5. (a) March SLP, (b) March UV1000 (arrows) and March SAT (shaded) regressed onto the February QBO index. The hatched areas in (a and b) and thick black arrows in (b) denote the statistically significant regressions at the 95% confidence level based on Student's t-test. Units of the regression coefficients are converted into Pa in (a), Kelvin and m s^-1 in (b) by multiplying the standard deviation of the QBO, respectively.
그림 Fig. 6. SLP (shaded), UV1000 (arrows) regressed onto the -1 lag month QBO index. For instance, the upper left panel indicates the SLP and UV1000 in August regressed on QBO index in July. Thick black arrows denote the statistically significant regressions at the 95% confidence level based on Student's t-test. Units of the regression coefficients are converted into Pa and m s^-1 by multiplying the standard deviation of the QBO, respectively.

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