一種預(yù)測西北太平洋熱帶氣旋逐月演變的新統(tǒng)計(jì)模型

doi:10.12306/2022jms.0034

首頁 > 過刊瀏覽>2024年第44卷第1期 >59-72. DOI:10.12306/2022jms.0034

一種預(yù)測西北太平洋熱帶氣旋逐月演變的新統(tǒng)計(jì)模型
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                        10.12306/2022jms.0034
                    
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中圖分類號:P466
基金項(xiàng)目:國家自然科學(xué)基金資助項(xiàng)目(41675077;41975090;41605072);國家重點(diǎn)研發(fā)計(jì)劃資助項(xiàng)目(2018YFC1505803)

A new statistical model for predicting month-to-month evolution of tropical cyclones in the western North Pacific

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本文提出一種月尺度西北太平洋熱帶氣旋生成頻數(shù)(Western North Pacific Tropical Cyclone Frequency, WNPTCF)預(yù)測的新方法。該方法利用全球次表層海溫(Subsurface Sea Temperature Anomaly, SubSSTA)和中國氣象局國家氣候中心發(fā)布的130項(xiàng)監(jiān)測指數(shù),構(gòu)建了既考慮熱力強(qiáng)迫因子、又考慮大氣動力因子,既考慮同期海洋強(qiáng)迫,又考慮前期海洋和大氣影響的集成預(yù)測模型。利用該預(yù)測模型對2011-2020年6-10月逐月WNPTCF進(jìn)行獨(dú)立樣本檢驗(yàn)預(yù)測,準(zhǔn)確率達(dá)70%以上,說明該預(yù)測模型對WNPTCF的逐月演變預(yù)測的效果良好。該預(yù)測模型對ENSO信號較強(qiáng)年份的WNPTCF預(yù)測效果要好于ENSO信號不強(qiáng)的年份,原因在于在ENSO信號不強(qiáng)的年份,SubSSTA可預(yù)報(bào)性較低,非線性變率大,海洋對WNPTC的強(qiáng)迫作用弱。

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In this paper,a new method for predicting the monthly Western North Pacific Tropical Cyclone Frequency (WNPTCF) was proposed.Based on the global Subsurface Sea Temperature Anomaly (SubSSTA) and 130 monitoring indexes released by the National Climate Center of China Meteorological Administration,this method constructs an integrated statistical prediction model that considers both thermal forcing factor and atmospheric dynamic factor,and both simultaneous oceanic forcing factor and the influence of previous ocean and atmosphere.The independent sample test prediction of monthly WNPTCF from June to October from 2011 to 2020 was carried out by using this prediction model,and the accuracy rate reached more than 70%,indicating that this prediction model has good prediction effect on the monthly evolution of WNPTCF.The prediction effect of this prediction model for WNPTCF in years with strong ENSO signal is better than that in years with weak ENSO signal.The reason is that in years with weak ENSO signal,the predictability of SubSSTA is low,the nonlinear variability is large,and the forcing effect of ocean on WNPTC is weak.

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呂碩,胡軼佳,孫源,鐘中.一種預(yù)測西北太平洋熱帶氣旋逐月演變的新統(tǒng)計(jì)模型.氣象科學(xué),2024,44(1):59-72 Lü Shuo, HU Yijia, SUN Yuan, ZHONG Zhong. A new statistical model for predicting month-to-month evolution of tropical cyclones in the western North Pacific. Journal of the Meteorological Sciences,2024,44(1):59-72

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收稿日期:2022-02-22
最后修改日期:2022-03-24
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在線發(fā)布日期: 2024-03-13
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