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加利福尼亚附近的海温强迫及其与北太平洋年代际振荡的可能联系

张海燕 陶丽 徐川

张海燕, 陶丽, 徐川. 2022. 加利福尼亚附近的海温强迫及其与北太平洋年代际振荡的可能联系[J]. 大气科学, 46(4): 859−872 doi: 10.3878/j.issn.1006-9895.2107.21012
引用本文: 张海燕, 陶丽, 徐川. 2022. 加利福尼亚附近的海温强迫及其与北太平洋年代际振荡的可能联系[J]. 大气科学, 46(4): 859−872 doi: 10.3878/j.issn.1006-9895.2107.21012
ZHANG Haiyan, TAO Li, XU Chuan. 2022. SST Forcing off California Coast and Its Relationship to the Decadal Variation of North Pacific [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(4): 859−872 doi: 10.3878/j.issn.1006-9895.2107.21012
Citation: ZHANG Haiyan, TAO Li, XU Chuan. 2022. SST Forcing off California Coast and Its Relationship to the Decadal Variation of North Pacific [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(4): 859−872 doi: 10.3878/j.issn.1006-9895.2107.21012

加利福尼亚附近的海温强迫及其与北太平洋年代际振荡的可能联系

doi: 10.3878/j.issn.1006-9895.2107.21012
基金项目: 国家重点研发计划项目2016YFA0600402
详细信息
    作者简介:

    张海燕,女,1995年出生,硕士研究生,主要从事海气相互作用研究。E-mail: 15951619515@163.com

    通讯作者:

    陶丽,E-mail: taoli@nuist.edu.cn

  • 中图分类号: P47

SST Forcing off California Coast and Its Relationship to the Decadal Variation of North Pacific

Funds: National Key Research and Development Program (Grant 2016YFA0600402)
  • 摘要: 本文利用1958~2018年期间海表面温度(SST)异常和湍流热通量异常变化的关系,探讨了其与北太平洋年代际振荡(PDO)相关的年际和年代际时间尺度上在不同海域的海气相互作用特征。结果表明:在年际尺度上,黑潮—亲潮延伸区(KOE)表现为显著大气强迫海洋,赤道中东太平洋表现为显著海洋强迫大气;在年代际尺度上,PDO北中心表现为大气强迫海洋,加利福尼亚附近则表现为显著海洋强迫大气。进一步分析表明:加利福尼亚附近区域是北太平洋准12年振荡的关键区域之一,与PDO准十年的周期类似,加利福尼亚附近的冷(暖)海温对应其上有反气旋(气旋)型环流,赤道中太平洋海水上翻和北太平洋东部副热带区域经向风应力的变化是北太平洋准12年振荡的另外两个重要环节。
  • 图  1  1958~2018年(a)标准化PDO指数逐月时间序列(柱状)以及经过96个月Lanczos高通/低通滤波后的PDO指数的逐月时间序列,(b)PDO逐月时间序列的功率谱分析,红色虚线、黑色点线、黑色点虚线分别表示通过红噪音检验、90%、95%的置信水平检验,黑点及数字表示周期在10年以上的显著周期

    Figure  1.  (a) Monthly standardized PDO (Pacific Decadal Oscillation) index (bars) and PDO index with the 96-month Lanczos high-pass/low-pass filtering, (b) power spectrum of the monthly PDO index from 1958 to 2018. In Fig. b, the red dashed, black-dotted, and dot-dashed lines are the red noise test line, statistically at 90%, and 95% confidence levels, respectively. The black dot and number indicate the significant period over a decade

    图  2  1985~2018年(a)潜热通量湍流交换系数(Ce)、(b)感热通量湍流交换系数(Ch)估计值分布(×10−3

    Figure  2.  Estimate of turbulent exchange coefficients (×10−3) of (a) latent heat flux (Ce), (b) sensible heat flux (Ch) during 1985–2018

    图  3  1958~2018年(a)SSTA(单位:°C)和(c、e、g)湍流热通量异常(HF,单位:W m−2)对年际PDO指数的回归分布,打点区域表示通过95%的置信水平检验,SST来自于HadISST数据集,图c、e、g的湍流热通量分别来自于1958~2018年OAFlux数据集、1958~2018年NCEP数据集和1958~2013年JRA-55数据集。(b、d、f、h)同(a、c、e、g),但为对年代际PDO指数的回归分布,打点区域表示通过90%的置信水平

    Figure  3.  Distribution of the regressed (a) SSTA (units: °C) and (c, e, g) turbulent heat flux anomalies (HF; units: W m−2) upon the interannual PDO index from 1958 to 2018, the areas with dots are statistically above the 95% confidence level. SST is from HadISST data, and turbulent heat fluxes in Figs. c, e, g from OAFlux data during 1958–2018, NCEP data during 1958–2018, JRA-55 data during 1958–2013, respectively. (b, d, f, h) As in (a, c, e, g), but upon the decadal PDO index, the areas with dots are statistically above the 90% confidence level

    图  4  1958~2018年年际PDO指数与湍流热通量异常各分量(单位:W m−2)的线性回归分布(彩色阴影):(a)风速异常引起的湍流热通量异常分量$ \left\{ {\mathop U\nolimits_{\text{a}}' \left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \left( {\overline {\mathop q\nolimits_{\text{s}} } - \overline {\mathop q\nolimits_{\text{a}} } } \right) + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \left( {\overline {\mathop t\nolimits_{\text{s}} } - \overline {\mathop t\nolimits_{\text{a}} } } \right)} \right]} \right\} $,图中矢量箭头表示10 m纬向风(ua)和经向风(va)的气候场(单位:m s−1);(b)海气温差和比湿差异常共同引起的湍流热通量异常分量$ \left\{ {\left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop q\nolimits_{\text{s}}' - \mathop q\nolimits_{\text{a}}' } \right) + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop t\nolimits_{\text{s}}' - \mathop t\nolimits_{\text{a}}' } \right)} \right]} \right\} $;(c)海气比湿差异常引起的湍流热通量异常分量$ \left\{ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop q\nolimits_{\text{s}}' - \mathop q\nolimits_{\text{a}}' } \right)} \right\} $;(d)海气温差异常引起的湍流热通量异常分量$ \left\{ {\mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop t\nolimits_{\text{s}}' - \mathop t\nolimits_{\text{a}}' } \right)} \right\} $;(e)SSTA引起的湍流热通量异常分量$ \left\{ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \mathop q\nolimits_{\text{s}}' + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \mathop t\nolimits_{\text{s}}' } \right\} $;(f)大气比湿和气温异常共同引起的湍流热通量异常分量$ \left\{ { - \left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \mathop q\nolimits_{\text{a}}' + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \mathop t\nolimits_{\text{a}}' } \right]} \right\} $。打点区域表示通过95%的置信水平检验。uava来自于NCEP数据集,10 m全风速(Ua)、海表面温度(ts)、大气2 m比湿(qa)和气温(ta)均来自于OAFlux数据集,海表饱和比湿qsts计算得到

    Figure  4.  Distribution of the regressed turbulent HF anomaly components of caused by (a) abnormal wind speed $ \left\{ {\mathop U\nolimits_{\text{a}}' \left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \left( {\overline {\mathop q\nolimits_{\text{s}} } - \overline {\mathop q\nolimits_{\text{a}} } } \right) + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \left( {\overline {\mathop t\nolimits_{\text{s}} } - \overline {\mathop t\nolimits_{\text{a}} } } \right)} \right]} \right\} $, and the red vectors represent the climatology (units: m s−1) of 10 m zonal speed (ua) and meridional speed (va), (b) abnormal differences in air–sea temperature and specific humidity $ \left\{ {\left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop q\nolimits_{\text{s}}' - \mathop q\nolimits_{\text{a}}' } \right) + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop t\nolimits_{\text{s}}' - \mathop t\nolimits_{\text{a}}' } \right)} \right]} \right\} $, (c) abnormal differences in air–sea specific humidity $ \left\{ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop q\nolimits_{\text{s}}' - \mathop q\nolimits_{\text{a}}' } \right)} \right\} $, (d) abnormal differences in air–sea temperature $ \left\{ {\mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \left( {\mathop t\nolimits_{\text{s}}' - \mathop t\nolimits_{\text{a}}' } \right)} \right\} $, (e) SSTA $\left\{ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \mathop q\nolimits_{\text{s}}' + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \mathop t\nolimits_{\text{s}}' } \right\}$, and (f) abnormal specific humidity and temperature $ \left\{ { - \left[ {\mathop \rho \nolimits_{\text{a}} \mathop L\nolimits_{\text{e}} \mathop C\nolimits_{\text{e}} \overline {\mathop U\nolimits_{\text{a}} } \mathop q\nolimits_{\text{a}}' + \mathop \rho \nolimits_{\text{a}} \mathop c\nolimits_p \mathop C\nolimits_{\text{h}} \overline {\mathop U\nolimits_{\text{a}} } \mathop t\nolimits_{\text{a}}' } \right]} \right\} $ (units: W m−2) upon the interannual PDO index from 1958 to 2018. The areas with dots are statistically significant at the 95% confidence level. ua and va are from NCEP. 10 m wind speed (Ua), SST (ts), 2 m specific humidity (qa) and temperature (ta) obtained from OAFlux. Sea surface saturation specific humidity (qs) is calculated by ts

    图  5  同图4,但为年代际PDO指数的回归分布,打点区域表示通过90%的置信水平检验

    Figure  5.  As in Fig. 4, but for decadal PDO index, the areas with dots are statistically above the 90% confidence level

    图  6  1958~2018年年代际尺度冬季(a)SSTA(单位:°C)和(b)湍流热通量异常(单位:W m−2)对PDO指数的回归分布。(c、d)同(a、b),但为夏季的结果。打点区域表示通过90%的置信水平检验。SST来自于HadISST数据集,湍流热通量来自于OAFlux数据集

    Figure  6.  Distributions of the regressed (a) SSTA (units: °C), (b) turbulent heat flux anomalies (units: W m−2) upon the decadal PDO index in winter (DJF-mean) from 1958 to 2018. (c, d) As in (a, b), but for results in summer (JJA-mean). The areas with dots are statistically above the 90% confidence level. SST is from HadISST data, and turbulent heat fluxes are from OAFlux data

    图  7  1958~2018年(a)加利福尼亚附近(20°~40°N,140°~110°W)SSTA区域平均(CaI)的标准化逐月时间序列,(b)CaI的功率谱,红色虚线、黑色点线、黑色点虚线分别表示通过红噪音检验、90%、95%的置信水平,黑点及数字表示周期在10年以上的显著周期。SST来自于HadISST数据集

    Figure  7.  (a) Standardized monthly time series of SSTA averaged over the area off the California coast (CaI, 20°–40°N, 140°–110°W), (b) power spectrum of CaI during 1958–2018. In Fig. b, the red dashed, black-dotted, and dot-dashed lines are the red noise test line, statistically above the 90% confidence level, and 95% confidence level, respectively. The black dot and number indicate the significant period over a decade. SST is from HadISST data

    图  8  1958~2018年96~240个月带通滤波的CaI与(a1–a9)5°S~5°N平均次表层海温异常(单位:°C)、(b1–b9)30°~40°N平均次表层海温异常(单位:°C)、(c1–c9)SSTA(单位:°C)、(d1–d9)风应力异常(单位:N m−2)的超前—滞后回归分布。图b1–b9中,箭头表示洋流纬向流速uo(单位:cm s−1)和垂直流速wo(单位:10−5 cm s−1)的气候场;图d1–d9中,黄色阴影区域表示通过90%的置信水平检验。图a1–a9、b1–b9、c1–c9中打点区域表示通过90%的置信水平检验。Lag表示CaI滞后,Lead表示CaI超前。SST来自于HadISST数据集,次表层海温来自于EN4.2.1数据集,风应力来自于NCEP数据集,uowo来自于GECCO3数据集

    Figure  8.  Lead–lag regression between the 96–240-month band-pass CaI and (a1–a9) subsurface ocean temperature anomalies (units: °C) averaged over 5°S–5°N, (b1–b9) subsurface ocean temperature anomalies (units: °C) averaged over 30°–40°N, (c1–c9) SSTA (units: °C), (d1–d9) wind stress anomalies (units: N m−2) during 1958–2018. In Figs. b1–b9, arrows represent the climatological ocean circulation of the zonal speed uo (units: cm s−1) and vertical speed wo (units: 10−5 cm s−1); in Figs. d1–d9, the yellow shadings indicate statistically above the 90% confidence level; in Figs. a1–a9, b1–b9, c1–c9, the dots areas indicate statistically above the 90% confidence level. Lag indicates CaI lagging, and Lead indicates CaI leading. SST, sub-surface ocean temperature, wind stress, and uo, wo obtained from HadISST data, EN4.2.1 data, NCEP data, and GECCO3 data, respectively

    图  9  1958~2018年(a)赤道中太平洋(5°S~5°N,180°~120°W)区域平均逐月SSTA、(b)北太平洋东部副热带地区(20°~40°N,140°~110°W)区域平均逐月经向风应力的功率谱,红色虚线、黑色点线、黑色点虚线分别表示通过红噪音检验以及通过90%、95%的置信水平检验,黑点及数字表示周期在10年以上的显著周期。SST来自于HadISST数据集,经向风应力来自于NCEP数据集

    Figure  9.  Power spectrum of (a) monthly SSTA averaged over the equatorial central Pacific (5°S–5°N, 180°–120°W) and (b) monthly meridional wind stress averaged over the subtropical eastern North Pacific (20°–40°N, 140°–110°W) during 1958–2018. The red dashed, black-dotted, and dot-dashed lines indicate the red noise test line, statistically above the 90% confidence level, and 95% confidence level, respectively. The black dot and number indicate the significant period of over a decade

  • [1] Alexander M A, Bladé I, Newman M, et al. 2002. The atmospheric bridge: The influence of ENSO teleconnections on air–sea interaction over the global oceans [J]. J. Climate, 15(16): 2205−2231. doi: 10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2
    [2] Amaya D J. 2019. The Pacific meridional mode and ENSO: A review [J]. Curr. Climate Change Rep., 5(4): 296−307. doi: 10.1007/s40641-019-00142-x
    [3] Bjerknes J. 1964. Atlantic air–sea interaction [J]. Advances in Geophysics, 10: 1−82. doi: 10.1016/S0065-2687(08)60005-9
    [4] Cayan D R, Kammerdiener S A, Dettinger M D, et al. 2001. Changes in the onset of spring in the western United States [J]. Bull. Amer. Meteor. Soc., 82(3): 399−416. doi: 10.1175/1520-0477(2001)082<0399:CITOOS>2.3.CO;2
    [5] Cessi P, Louazel S. 2001. Decadal oceanic response to stochastic wind forcing [J]. J. Phys. Oceanogr., 31(10): 3020−3029. doi: 10.1175/1520-0485(2001)031<3020:DORTSW>2.0.CO;2
    [6] Chiang J C H, Vimont D J. 2004. Analogous Pacific and Atlantic meridional modes of tropical atmosphere–ocean variability [J]. J. Climate, 17(21): 4143−4158. doi: 10.1175/JCLI4953.1
    [7] Di Lorenzo E, Schneider N, Cobb K M, et al. 2008. North Pacific Gyre Oscillation links ocean climate and ecosystem change [J]. Geophys. Res. Lett., 35(8): L08607. doi: 10.1029/2007GL032838
    [8] Di Lorenzo E, Liguori G, Schneider N, et al. 2015. ENSO and meridional modes: A null hypothesis for Pacific climate variability [J]. Geophys. Res. Lett., 42(21): 9440−9448. doi: 10.1002/2015GL066281
    [9] Fang J B, Yang X Q. 2016. Structure and dynamics of decadal anomalies in the wintertime midlatitude North Pacific ocean–atmosphere system [J]. Climate Dyn., 47(5): 1989−2007. doi: 10.1007/s00382-015-2946-x
    [10] Frankignoul C, Hasselmann K. 1977. Stochastic climate models. Part II: Application to sea surface temperature anomalies and thermocline variability [J]. Tellus, 29(4): 289−305. doi: 10.1111/j.2153-3490.1977.tb00740.x
    [11] Graham N E. 1994. Decadal-scale climate variability in the tropical and North Pacific during the 1970s and 1980s: Observations and model results [J]. Climate Dyn., 10(3): 135−162. doi: 10.1007/BF00210626
    [12] Graham N E, Barnett T P, Wilde R, et al. 1994. On the roles of tropical and midlatitude SSTs in forcing interannual to interdecadal variability in the winter Northern Hemisphere circulation [J]. J. Climate, 7(9): 1416−1441. doi: 10.1175/1520-0442(1994)007<1416:OTROTA>2.0.CO;2
    [13] Gu D F, Philander S G H. 1997. Interdecadal climate fluctuations that depend on exchanges between the tropics and extratropics [J]. Science, 275(5301): 805−807. doi: 10.1126/science.275.5301.805
    [14] Gulev S K, Latif M, Keenlyside N, et al. 2013. North Atlantic Ocean control on surface heat flux on multidecadal timescales [J]. Nature, 499(7459): 464−467. doi: 10.1038/nature12268
    [15] 韩子轩, 苏涛, 支蓉, 等. 2017. 不同太平洋年代际振荡和ENSO位相下大气水分收支变化对北半球冬季太平洋蒸发量的影响 [J]. 大气科学, 41(6): 1316−1331. doi: 10.3878/j.issn.1006-9895.1702.16257

    Han Zixuan, Su Tao, Zhi Rong, et al. 2017. Effects of moisture budget changes on Pacific evaporation associated with Pacific Decadal Oscillation and ENSO in boreal winter [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 41(6): 1316−1331. doi: 10.3878/j.issn.1006-9895.1702.16257
    [16] Hasselmann K. 1976. Stochastic climate models. Part I: Theory [J]. Tellus, 28(6): 473−485. doi: 10.1111/j.2153-3490.1976.tb00696.x
    [17] Horel J D, Wallace J M. 1981. Planetary-scale atmospheric phenomena associated with the Southern Oscillation [J]. Mon. Wea. Rev., 109(4): 813−829. doi: 10.1175/1520-0493(1981)109<0813:PSAPAW>2.0.CO;2
    [18] Kleeman R, McCreary Jr J P, Klinger B A. 1999. A mechanism for generating ENSO decadal variability [J]. Geophys. Res. Lett., 26(12): 1743−1746. doi: 10.1029/1999GL900352
    [19] Latif M, Barnett T P. 1994. Causes of decadal climate variability over the North Pacific and North America [J]. Science, 266(5185): 634−637. doi: 10.1126/science.266.5185.634
    [20] 李博, 周天军, 林鹏飞, 等. 2011. 冬季北太平洋海表面热通量异常和海气相互作用的耦合模式模拟 [J]. 气象学报, 69(1): 52−63. doi: 10.11676/qxxb2011.005

    Li Bo, Zhou Tianjun, Lin Pengfei, et al. 2011. The wintertime North Pacific surface heat flux anomaly and air–sea interaction as simulated by the LASG/IAP ocean–atmosphere coupled model FGOALS_s1.0 [J]. Acta Meteorologica Sinica (in Chinese), 69(1): 52−63. doi: 10.11676/qxxb2011.005
    [21] 梁苏洁, 丁一汇, 赵南, 等. 2014. 近50年中国大陆冬季气温和区域环流的年代际变化研究 [J]. 大气科学, 38(5): 974−992. doi: 10.3878/j.issn.1006-9895.1401.13234

    Liang Sujie, Ding Yihui, Zhao Nan, et al. 2014. Analysis of the interdecadal changes of the wintertime surface air temperature over mainland China and regional atmospheric circulation characteristics during 1960–2013 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 38(5): 974−992. doi: 10.3878/j.issn.1006-9895.1401.13234
    [22] Liu Z. 2003. Tropical ocean decadal variability and resonance of planetary wave basin modes. Part I: Theory [J]. J. Climate, 16(10): 1539−1550. doi: 10.1175/1520-0442(2003)016<1539:TODVAR>2.0.CO;2
    [23] 吕俊梅, 祝从文, 琚建华, 等. 2014. 近百年中国东部夏季降水年代际变化特征及其原因 [J]. 大气科学, 38(4): 782−794. doi: 10.3878/j.issn.1006-9895.1401.13227

    Lü Junmei, Zhu Congwen, Ju Jianhua, et al. 2014. Interdecadal variability in summer precipitation over East China during the past 100 years and its possible causes [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 38(4): 782−794. doi: 10.3878/j.issn.1006-9895.1401.13227
    [24] Mantua N J, Hare S R. 2002. The Pacific Decadal Oscillation [J]. Journal of Oceanography, 58(1): 35−44. doi: 10.1023/A:1015820616384
    [25] Mantua N J, Hare S R, Zhang Y, et al. 1997. A Pacific interdecadal climate oscillation with impacts on salmon production [J]. Bull. Amer. Meteor. Soc., 78(6): 1069−1080. doi: 10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2
    [26] Miller A J, Cayan D R, Barnett T P, et al. 1994. Interdecadal variability of the Pacific Ocean: Model response to observed heat flux and wind stress anomalies [J]. Climate Dyn., 9(6): 287−302. doi: 10.1007/BF00204744
    [27] Newman M, Alexander M A, Ault T R, et al. 2016. The Pacific Decadal Oscillation, revisited [J]. J. Climate, 29(12): 4399−4427. doi: 10.1175/JCLI-D-15-0508.1
    [28] Saravanan R, McWilliams J C. 1997. Stochasticity and spatial resonance in interdecadal climate fluctuations [J]. J. Climate, 10(9): 2299−2320. doi: 10.1175/1520-0442(1997)010<2299:SASRII>2.0.CO;2
    [29] Schneider N, Miller A J, Alexander M A, et al. 1999. Subduction of decadal North Pacific temperature anomalies: Observations and dynamics [J]. J. Phys. Oceanogr., 29(5): 1056−1070. doi: 10.1175/1520-0485(1999)029<1056:SODNPT>2.0.CO;2
    [30] Small R J, Bryan F O, Bishop S P, et al. 2019. Air–sea turbulent heat fluxes in climate models and observational analyses: What drives their variability? [J]. J. Climate, 32(8): 2397−2421. doi: 10.1175/JCLI-D-18-0576.1
    [31] Stuecker M F. 2018. Revisiting the Pacific meridional mode [J]. Sci. Rep., 8(1): 3216. doi: 10.1038/s41598-018-21537-0
    [32] Tanimoto Y, Nakamura H, Kagimoto T, et al. 2003. An active role of extratropical sea surface temperature anomalies in determining anomalous turbulent heat flux [J]. J. Geophys. Res., 108(C10): 3304. doi: 10.1029/2002JC001750
    [33] Tao L F, Yang X Q, Fang J B, et al. 2020. PDO-related wintertime atmospheric anomalies over the midlatitude North Pacific: Local versus remote SST forcing [J]. J. Climate, 33(16): 6989−7010. doi: 10.1175/JCLI-D-19-0143.1
    [34] Wang Y Q, Liu H L, Lin P F, et al. 2019. Record-low coastal sea levels in the Northeast Pacific during the winter of 2013–2014 [J]. Sci. Rep., 9(1): 3774. doi: 10.1038/s41598-019-40397-w
    [35] Wu L X, Liu Z Y. 2003. Decadal variability in the North Pacific: The eastern North Pacific mode [J]. J. Climate, 16(19): 3111−3131. doi: 10.1175/1520-0442(2003)016<3111:DVITNP>2.0.CO;2
    [36] Wu L X, Liu Z S, Gallimore R, et al. 2003. Pacific decadal variability: The tropical Pacific mode and the North Pacific mode [J]. J. Climate, 16(8): 1101−1120. doi: 10.1175/1520-0442(2003)16<1101:PDVTTP>2.0.CO;2
    [37] Xie S P, Philander S G H. 1994. A coupled ocean–atmosphere model of relevance to the ITCZ in the eastern Pacific [J]. Tellus A, 46(4): 340−350. doi: 10.3402/tellusa.v46i4.15484
    [38] 杨修群, 朱益民, 谢倩, 等. 2004. 太平洋年代际振荡的研究进展 [J]. 大气科学, 28(6): 979−992. doi: 10.3878/j.issn.1006-9895.2004.06.15

    Yang Xiuqun, Zhu Yimin, Xie Qian, et al. 2004. Advances in studies of Pacific Decadal Oscillation [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 28(6): 979−992. doi: 10.3878/j.issn.1006-9895.2004.06.15
    [39] Yi D L, Gan B L, Wu L X, et al. 2018. The North Pacific Gyre Oscillation and mechanisms of its decadal variability in CMIP5 models [J]. J. Climate, 31(6): 2487−2509. doi: 10.1175/JCLI-D-17-0344.1
    [40] Yu B, Boer G J. 2004. The role of the western Pacific in decadal variability [J]. Geophys. Res. Lett., 31(2): L02204. doi: 10.1029/2003GL018471
    [41] Yu L S, Weller R A. 2007. Objectively analyzed air–sea heat fluxes for the global ice-free oceans (1981–2005) [J]. Bull. Amer. Meteor. Soc., 88(4): 527−540. doi: 10.1175/BAMS-88-4-527
    [42] Zhang Y L, Yu Y Q. 2011. Analysis of decadal climate variability in the tropical Pacific by coupled GCM [J]. Atmospheric and Oceanic Science Letters, 4(4): 204−208. doi: 10.1080/16742834.2011.11446930
    [43] Zhang L P, Wu L X, Lin X P, et al. 2010. Modes and mechanisms of sea surface temperature low-frequency variations over the coastal China seas [J]. J. Geophys. Res., 115(C8): C08031. doi: 10.1029/2009jc006025
    [44] 张雯, 董啸, 薛峰. 2020. 不同PDO位相下El Niño发展年和La Niña年东亚夏季风的季节内变化 [J]. 大气科学, 44(2): 390−406. doi: 10.3878/j.issn.1006-9895.1910.18269

    Zhang Wen, Dong Xiao, Xue Feng. 2020. Intraseasonal variations of the East Asian summer monsoon in El Niño developing years and La Niña years under different phases of the Pacific Decadal Oscillation [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(2): 390−406. doi: 10.3878/j.issn.1006-9895.1910.18269
    [45] Zhang Y, Yu S Y, Amaya D J, et al. 2021. Pacific meridional modes without equatorial Pacific influence [J]. J. Climate, 34(13): 5285−5301. doi: 10.1175/JCLI-D-20-0573.1
    [46] Zhi H, Lin P F, Zhang R H, et al. 2019. Salinity effects on the 2014 warm “Blob” in the Northeast Pacific [J]. Acta Oceanol. Sinica, 38(9): 24−34. doi: 10.1007/s13131-019-1450-2
    [47] Zhong Y F, Liu Z Y. 2009. On the mechanism of Pacific multidecadal climate variability in CCSM3: The role of the subpolar North Pacific Ocean [J]. J. Phys. Oceanogr., 39(9): 2052−2076. doi: 10.1175/2009JPO4097.1
    [48] Zhong Y F, Liu Z Y, Jacob R. 2008. Origin of Pacific multidecadal variability in Community Climate System Model, Version 3 (CCSM3): A combined statistical and dynamical assessment [J]. J. Climate, 21(1): 114−133. doi: 10.1175/2007JCLI1730.1
    [49] 朱益民, 杨修群. 2003. 太平洋年代际振荡与中国气候变率的联系 [J]. 气象学报, 61(6): 641−654. doi: 10.11676/qxxb2003.065

    Zhu Yimin, Yang Xiuqun. 2003. Relationships between Pacific Decadal Oscillation (PDO) and climate variabilities in China [J]. Acta Meteorologica Sinica (in Chinese), 61(6): 641−654. doi: 10.11676/qxxb2003.065
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出版历程
  • 收稿日期:  2021-01-23
  • 录用日期:  2021-10-19
  • 网络出版日期:  2021-08-12
  • 刊出日期:  2022-07-19

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