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季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响

胡榕 李建平 侯兆禄

胡榕, 李建平, 侯兆禄. 季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响[J]. 热带气象学报, 2024, 40(1): 85-100. doi: 10.16032/j.issn.1004-4965.2024.010
引用本文: 胡榕, 李建平, 侯兆禄. 季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响[J]. 热带气象学报, 2024, 40(1): 85-100. doi: 10.16032/j.issn.1004-4965.2024.010
HU Rong, LI Jianping, HOU Zhaolu. Impact of the Intraseasonal Indo-west Pacific Convective Oscillation on Subseasonal-seasonal Atmospheric Predictability[J]. Journal of Tropical Meteorology, 2024, 40(1): 85-100. doi: 10.16032/j.issn.1004-4965.2024.010
Citation: HU Rong, LI Jianping, HOU Zhaolu. Impact of the Intraseasonal Indo-west Pacific Convective Oscillation on Subseasonal-seasonal Atmospheric Predictability[J]. Journal of Tropical Meteorology, 2024, 40(1): 85-100. doi: 10.16032/j.issn.1004-4965.2024.010

季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响

doi: 10.16032/j.issn.1004-4965.2024.010
基金项目: 

国家自然科学重点基金 42130607

崂山实验室科技创新项目 LSKJ202202600

山东省自然科学基金重大基础研究项目 ZR2019ZD12

国家自然科学基金 42005049

详细信息
    通讯作者:

    李建平,男,山西省人,教授,主要从事气候动力学与可预报性、季风与海气相互作用等研究。E-mail:ljp@ouc.edu.cn

  • 中图分类号: P434

Impact of the Intraseasonal Indo-west Pacific Convective Oscillation on Subseasonal-seasonal Atmospheric Predictability

  • 摘要: 利用非线性局部Lyapunov指数和条件非线性局部Lyapunov指数定量估计了季节内印度洋-西太平洋对流涛动(IPCO)和实时多变量Madden-Julian指数(RMM指数)可预报期限,量化了季节内IPCO对S2S尺度大气可预报性的贡献,深入研究了季节内IPCO演变下S2S尺度可预报期限空间分布的变化规律。结果表明:(1)与RMM指数相比,季节内IPCO指数可预报性更强,可预报期限达到31天左右,比RMM指数高出2周以上;(2)印度洋-西太平洋区域S2S尺度大气可预报性最强,可预报期限达到30天以上,其中季节内IPCO是该地区的主要可预报性来源之一,其贡献达到6天,占总可预报期限的25%以上;(3)随着季节内IPCO的演变,印度洋-西太平洋地区S2S尺度大气可预报性有空间结构变化,表现为可预报期限异常的传播和振荡。S2S尺度大气可预报期限正负异常沿季节内IPCO传播路径,一支以赤道中西印度洋为起点北传至印度半岛,一支向东传播,经过海洋性大陆到赤道西太平洋后向北传播,到达日本南部。同时,可预报性异常的传播在在东印度洋和西太平洋表现出反向变化的特征,形成东西两极振荡,当季节内IPCO向正位相发展时,东印度洋具有更强的可预报性,西太平洋具有更弱的可预报性,反之亦然。季节内IPCO的发展(衰退)可使东印度洋(西太平洋)S2S尺度大气可预报性更强,表明模式预报技巧对此具有更大的提升空间。

     

  • 图  1  1979—2019年逐日RMM指数二维相空间中向量Z的平均误差随时间的增长(实线,单位:天)

    虚线表示误差饱和值的95%水平线。

    图  2  图 1,但对逐日IPCO指数的情形。

    图  3  1979—2019年850 hPa逐日风场(a)、位势高度场(b)S2S尺度平均可预报期限的空间分布,及其纬向平均(c、d)

    单位:天。

    图  4  图 3,但为季节内IPCO条件下平均可预报期限(单位:天)

    e、f分别为a、b中的条件可预报期限占各自总可预报期限的百分比(%)。

    图  5  (a)、(b)分别同图 3(a)(b),但对季节内IPCO演变的8个位相平均S2S尺度可预报期限的空间分布(单位:天)。(c)-(j)同(a),但分别对应季节内IPCO演变的8个位相的S2S尺度可预报期限异常的空间分布。P1到P8表示季节内IPCO的8个位相,此处的异常是分别相对于图(a)中季节内IPCO的8个位相平均的可预报期限。(k)~(r)同(c)~(j),但对位势高度场的情形以及相对于(b)的异常。图(c)中红色实线和绿色实线分别表示季节内IPCO沿(75 °E,2.5 °N)至(75 °E,20 °N)和(60 °E,2.5 °N)经(135 °E,2.5 °N)至(135°E,30°N)的传播路径,黑色矩形表示赤道东印度洋(EEIO;70~100 °E,5 °S~10 °N)和西北太平洋(WNP;110~160 °E,5~20 °N)区域。

    图  6  850 hPa逐日风场(a)、位势高度场(b)S2S尺度可预报期限异常沿路径(75 °E,2.5 °N)至(75 °E,20 °N)的经纬度-位相剖面(单位:天)

    图  7  图 6,但为路径(60 °E,2.5 °N)经(135 °E,2.5 °N)至(135 °E,30 °N)的情形

    图  8  850 hPa逐日风场(a)、位势高度场(b)EEIO(蓝点虚线)、WNP(红点虚线)区域平均S2S尺度可预报期限异常的变化曲线(单位:天)

    黑色实线表示季节内IPCO指数的变化。

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出版历程
  • 收稿日期:  2022-06-30
  • 修回日期:  2023-12-18
  • 刊出日期:  2024-02-20

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