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周洁安, 陶丽, 谢子璜. 2023. 西北太平洋7~8月热带气旋累积能量的统计预报[J]. 大气科学, 47(4): 1151−1170. doi: 10.3878/j.issn.1006-9895.2202.21207
引用本文: 周洁安, 陶丽, 谢子璜. 2023. 西北太平洋7~8月热带气旋累积能量的统计预报[J]. 大气科学, 47(4): 1151−1170. doi: 10.3878/j.issn.1006-9895.2202.21207
ZHOU Jiean, TAO Li, XIE Zihuang. 2023. Statistical Prediction of the Accumulated Cyclone Energy in the Western North Pacific from July to August [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(4): 1151−1170. doi: 10.3878/j.issn.1006-9895.2202.21207
Citation: ZHOU Jiean, TAO Li, XIE Zihuang. 2023. Statistical Prediction of the Accumulated Cyclone Energy in the Western North Pacific from July to August [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(4): 1151−1170. doi: 10.3878/j.issn.1006-9895.2202.21207

西北太平洋7~8月热带气旋累积能量的统计预报

Statistical Prediction of the Accumulated Cyclone Energy in the Western North Pacific from July to August

  • 摘要: 本文主要利用信息流特有的因果关系,从海表面温度(Sea Surface Temperature,SST)场和各种海—气指数中挑选引起西北太平洋(Western North Pacific,WNP)1979~2020年7~8月份热带气旋累积能量(Accumulated Cyclone Energy,ACE)主导模态年际变化的因子,利用多元线性逐步回归方法进一步筛选预报因子并建立预报方程。由经验正交函数(Empirical Orthogonal Function,EOF)分解得到的7~8月ACE前两个主导模态分别是海盆一致型和偶极型,海盆一致型主导模态对应的主成分时间序列(Principal Component,PC)预报因子为:超前3个月的海洋性大陆和北太平洋中部SST、超前5个月的准两年振荡(Quasi-biennial Oscillation,QBO)指数以及超前11个月的热带印度洋偶极子(Tropical Indian Ocean Dipole,TIOD)指数;偶极型主导模态对应的PC预报因子为:超前2个月的北大西洋北部SST、超前12个月的日本海沟SST、超前7个月的大西洋经向模(Atlantic Meridional Mode,AMM)指数和超前8个月的北大西洋涛动(North Atlantic Oscillation,NAO)指数。根据这些预报因子建立PC预报方程,预报的PC和观测PC的相关系数分别达到0.75和0.77,均通过0.01显著性水平的显著性检验。进而运用交叉验证法检验预报模型的后报技巧及稳定性,发现所建的两个模型预报效果较好。1980~2020年间预报和观测的WNP区域平均ACE距平值的时间相关系数达到0.76,WNP范围内ACE距平场的空间相关系数平均达到0.35,预报模型对主导模态重构拟合较好的年份预报技巧也较高。

     

    Abstract: Based on the causality of information flow, sea surface temperature (SST), and air–sea indices are used to determine the factors that can affect the interannual variation of the dominant modes of the accumulated cyclone energy (ACE) in the Western North Pacific (WNP) from July to August during 1979–2020. Then, multiple linear stepwise regression is used to select the most significant predictors. The first two modes of July–August ACE are the basin and dipole modes, as determined by empirical orthogonal function (EOF) analysis. The prediction factors for the principal component (PC) of the basin mode include the 3-month leading SST in Marine Continent and Central North Pacific, the 5-month leading quasi-biennial oscillation index (QBO), and the 11-month leading tropical Indian Ocean dipole mode index (TIOD). On the other hand, the predictive factors for the PC of the dipole mode include the 2-month leading SST in North Atlantic, the 12-month leading SST in the Japanese trench, the 7-month leading Atlantic meridional mode index (AMM), and the 8-month leading North Atlantic Oscillation index (NAO). The prediction equations are established based on these prediction factors. The correlation coefficients between the predicted PCs and the observed PCs of the first two modes are 0.75 and 0.77, respectively, both statistically significant at the level of 0.01. The cross-validation method indicates the prediction equations are stable and have good hindcasting ability. The temporal correlation coefficient skill of the WNP area averaged ACE anomaly is 0.76. The averaged pattern correlation coefficient skill of the ACE anomaly is 0.35 over the WNP basin during 1980–2020. The prediction model performs well in the years when the ACE can be reconstructed by the first two modes.

     

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