Cross-Seasonal Effect on Tropical Pacific Precipitation: Implication of South Pacific Quadrupole Simulation in CMIP6

Jianhuang Qin aKey Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing, China
dState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

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Ruiqiang Ding bState Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China

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Lei Zhou cSchool of Oceanography, Shanghai Jiao Tong University, Shanghai, China

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Heng Liu dState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

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Shang-min Long aKey Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing, China

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Lijun Tao dState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

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Abstract

The tropical Pacific convergence zone plays a crucial role in the global climate system. Previous research studies emphasized the cross-seasonal influence of the South Pacific quadrupole (SPQ) mode on the tropical Pacific climate. This study assesses the relationship between austral summer SPQ and austral winter tropical precipitation in phase 6 of the Coupled Model Intercomparison Project (CMIP6) models. The analysis emphasizes the historical experiments conducted within this time frame, spanning from 1979 to 2014. Our findings reveal that the SPQ is accurately represented in all CMIP6 models, but the connection between SPQ and precipitation is inadequately simulated in most models. To investigate the reasons behind these intermodel differences in reproducing SPQ-related processes, we categorize models into two groups. The comparisons demonstrate that the fidelity of model simulations in replicating the SPQ–tropical precipitation relationship hinges significantly on their capacity to reproduce the positive wind–evaporation–sea surface temperature (WES; SST) feedback over both the southwestern Pacific (25°–10°S; 150°E–160°W) and the southeastern Pacific (30°–10°S; 140°–80°W). This positive WES feedback propagates the SPQ signal into the tropics, intensifying the meridional gradient of SST anomaly in the tropical western-central Pacific, which consequently amplifies convection and rainfall in that area. In the group of models that failed to simulate this relationship accurately, the weakened WES feedback can be traced back to biases in wind speed and its variation. Furthermore, this WES feedback establishes a connection between SPQ and El Niño–Southern Oscillation (ENSO). A better rendition of the SPQ–tropical rainfall connection tends to result in a better simulation of the onset of SPQ-related ENSO events. As a result, this study advances our comprehension of extratropical impacts on the tropics, with the potential to enhance the accuracy of tropical climate simulation and prediction.

Significance Statement

Tropical rainfall plays an important role in the global climate system. Beyond the well-known influence of El Niño–Southern Oscillation (ENSO) on the tropical rainfall, the sea surface temperature (SST) anomaly in the South Pacific has a cross-seasonal impact on the precipitation over the tropical Pacific via air–sea coupled processes. Such SST anomaly pattern shows a quadrupole structure in the extratropical South Pacific, known as the South Pacific quadrupole (SPQ) mode. However, the relationship between SPQ and tropical precipitation remains poorly simulated in most state-of-the-art climate models. One primary reason for this gap between observed and simulated relationships is the underestimation of wind speed and its variation over the south tropical Pacific in these models. This limitation undermines their ability to accurately represent the air–sea interactions that drive tropical precipitation patterns, leading to inaccuracies in simulations. Our study aims to bridge this knowledge gap by enhancing our understanding of the extratropical effects on the tropical Pacific. By exploring the mechanisms underlying the SPQ–precipitation connection, we expect to improve the simulation and prediction capabilities of tropical climate models, thereby enhancing our ability to forecast and adapt to future climatic changes.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ruiqiang Ding, drq@bnu.edu.cn

Abstract

The tropical Pacific convergence zone plays a crucial role in the global climate system. Previous research studies emphasized the cross-seasonal influence of the South Pacific quadrupole (SPQ) mode on the tropical Pacific climate. This study assesses the relationship between austral summer SPQ and austral winter tropical precipitation in phase 6 of the Coupled Model Intercomparison Project (CMIP6) models. The analysis emphasizes the historical experiments conducted within this time frame, spanning from 1979 to 2014. Our findings reveal that the SPQ is accurately represented in all CMIP6 models, but the connection between SPQ and precipitation is inadequately simulated in most models. To investigate the reasons behind these intermodel differences in reproducing SPQ-related processes, we categorize models into two groups. The comparisons demonstrate that the fidelity of model simulations in replicating the SPQ–tropical precipitation relationship hinges significantly on their capacity to reproduce the positive wind–evaporation–sea surface temperature (WES; SST) feedback over both the southwestern Pacific (25°–10°S; 150°E–160°W) and the southeastern Pacific (30°–10°S; 140°–80°W). This positive WES feedback propagates the SPQ signal into the tropics, intensifying the meridional gradient of SST anomaly in the tropical western-central Pacific, which consequently amplifies convection and rainfall in that area. In the group of models that failed to simulate this relationship accurately, the weakened WES feedback can be traced back to biases in wind speed and its variation. Furthermore, this WES feedback establishes a connection between SPQ and El Niño–Southern Oscillation (ENSO). A better rendition of the SPQ–tropical rainfall connection tends to result in a better simulation of the onset of SPQ-related ENSO events. As a result, this study advances our comprehension of extratropical impacts on the tropics, with the potential to enhance the accuracy of tropical climate simulation and prediction.

Significance Statement

Tropical rainfall plays an important role in the global climate system. Beyond the well-known influence of El Niño–Southern Oscillation (ENSO) on the tropical rainfall, the sea surface temperature (SST) anomaly in the South Pacific has a cross-seasonal impact on the precipitation over the tropical Pacific via air–sea coupled processes. Such SST anomaly pattern shows a quadrupole structure in the extratropical South Pacific, known as the South Pacific quadrupole (SPQ) mode. However, the relationship between SPQ and tropical precipitation remains poorly simulated in most state-of-the-art climate models. One primary reason for this gap between observed and simulated relationships is the underestimation of wind speed and its variation over the south tropical Pacific in these models. This limitation undermines their ability to accurately represent the air–sea interactions that drive tropical precipitation patterns, leading to inaccuracies in simulations. Our study aims to bridge this knowledge gap by enhancing our understanding of the extratropical effects on the tropical Pacific. By exploring the mechanisms underlying the SPQ–precipitation connection, we expect to improve the simulation and prediction capabilities of tropical climate models, thereby enhancing our ability to forecast and adapt to future climatic changes.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ruiqiang Ding, drq@bnu.edu.cn

Supplementary Materials

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  • Adam, O., T. Schneider, and F. Brient, 2018: Regional and seasonal variations of the double-ITCZ bias in CMIP5 models. Climate Dyn., 51, 101117, https://doi.org/10.1007/s00382-017-3909-1.

    • Search Google Scholar
    • Export Citation
  • Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163172, https://doi.org/10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bond, N. A., J. E. Overland, M. Spillane, and P. Stabeno, 2003: Recent shifts in the state of the North Pacific. Geophys. Res. Lett., 30, 2183, https://doi.org/10.1029/2003GL018597.

    • Search Google Scholar
    • Export Citation
  • Brown, J. R., A. F. Moise, and R. A. Colman, 2013: The South Pacific Convergence Zone in CMIP5 simulations of historical and future climate. Climate Dyn., 41, 21792197, https://doi.org/10.1007/s00382-012-1591-x.

    • Search Google Scholar
    • Export Citation
  • Cai, W., and Coauthors, 2012: More extreme swings of the South Pacific convergence zone due to greenhouse warming. Nature, 488, 365369, https://doi.org/10.1038/nature11358.

    • Search Google Scholar
    • Export Citation
  • Chiang, J. C. H., and C. M. Bitz, 2005: Influence of high latitude ice cover on the marine Intertropical Convergence Zone. Climate Dyn., 25, 477496, https://doi.org/10.1007/s00382-005-0040-5.

    • Search Google Scholar
    • Export Citation
  • Dai, A., and T. M. L. Wigley, 2000: Global patterns of ENSO‐induced precipitation. Geophys. Res. Lett., 27, 12831286, https://doi.org/10.1029/1999GL011140.

    • Search Google Scholar
    • Export Citation
  • Ding, R., J. Li, Y.-h. Tseng, and C. Ruan, 2015a: Influence of the North Pacific Victoria mode on the Pacific ITCZ summer precipitation. J. Geophys. Res. Atmos., 120, 964979, https://doi.org/10.1002/2014JD022364.

    • Search Google Scholar
    • Export Citation
  • Ding, R., J. Li, and Y.-h. Tseng, 2015b: The impact of South Pacific extratropical forcing on ENSO and comparisons with the North Pacific. Climate Dyn., 44, 20172034, https://doi.org/10.1007/s00382-014-2303-5.

    • Search Google Scholar
    • Export Citation
  • Ding, R., Y.-h. Tseng, J. Li, C. Sun, F. Xie, and Z. Hou, 2019: Relative contributions of North and South Pacific sea surface temperature anomalies to ENSO. J. Geophys. Res. Atmos., 124, 62226237, https://doi.org/10.1029/2018JD030181.

    • Search Google Scholar
    • Export Citation
  • Ding, R., J. Li, W. Yang, Y.-h. Tseng, Y. Li, and K. Ji, 2020: On the differences between the South Pacific meridional and quadrupole modes. J. Geophys. Res. Oceans, 125, e2019JC015500, https://doi.org/10.1029/2019JC015500.

    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2019: Global reanalysis: Goodbye ERA-Interim, Hello ERA5. ECMWF Newsletter, No. 159, ECMWF, Reading, United Kingdom, 17–24.

  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and Coauthors, 1997: The Global Precipitation Climatology Project (GPCP) combined precipitation dataset. Bull. Amer. Meteor. Soc., 78, 520, https://doi.org/10.1175/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jiang, W., P. Huang, G. Huang, and J. Ying, 2021: Origins of the excessive westward extension of ENSO SST simulated in CMIP5 and CMIP6 models. J. Climate, 34, 28392851, https://doi.org/10.1175/JCLI-D-20-0551.1.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437472, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Li, G., S.-P. Xie, Y. Du, and Y. Luo, 2016: Effects of excessive equatorial cold tongue bias on the projections of tropical Pacific climate change. Part I: The warming pattern in CMIP5 multi-model ensemble. Climate Dyn., 47, 38173831, https://doi.org/10.1007/s00382-016-3043-5.

    • Search Google Scholar
    • Export Citation
  • Li, X., W. Zhang, R. Ding, and L. Shi, 2020: Joint impact of North Pacific Victoria mode and South Pacific quadrapole mode on Pacific ITCZ summer precipitation. Climate Dyn., 54, 45454561, https://doi.org/10.1007/s00382-020-05243-0.

    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., 2007: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean–atmosphere feedback analysis. J. Climate, 20, 44974525, https://doi.org/10.1175/JCLI4272.1.

    • Search Google Scholar
    • Export Citation
  • Liu, Z., D. Ostrenga, W. Teng, and S. Kempler, 2012: Tropical Rainfall Measuring Mission (TRMM) precipitation data and services for research and applications. Bull. Amer. Meteor. Soc., 93, 13171325, https://doi.org/10.1175/BAMS-D-11-00152.1.

    • Search Google Scholar
    • Export Citation
  • Pyper, B. J., and R. M. Peterman, 1998: Comparison of methods to account for autocorrelation in correlation analyses of fish data. Can. J. Fish. Aquat. Sci., 55, 21272140, https://doi.org/10.1139/f98-104.

    • Search Google Scholar
    • Export Citation
  • Qin, J., R. Ding, Z. Wu, J. Li, and S. Zhao, 2017: Relationships between the extratropical ENSO precursor and leading modes of atmospheric variability in the Southern Hemisphere. Adv. Atmos. Sci., 34, 360370, https://doi.org/10.1007/s00376-016-6016-z.

    • Search Google Scholar
    • Export Citation
  • Qin, J., L. Zhou, R. Ding, and J. Li, 2018: Influence of South Pacific quadrapole on austral winter precipitation over the SPCZ. Environ. Res. Lett., 13, 094024, https://doi.org/10.1088/1748-9326/aadd84.

    • Search Google Scholar
    • Export Citation
  • Raymond, D. J., G. B. Raga, C. S. Bretherton, J. Molinari, C. López-Carrillo, and Ž. Fuchs, 2003: Convective forcing in the intertropical convergence zone of the eastern Pacific. J. Atmos. Sci., 60, 20642082, https://doi.org/10.1175/1520-0469(2003)060<2064:CFITIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schneider, T., T. Bischoff, and G. H. Haug, 2014: Migrations and dynamics of the intertropical convergence zone. Nature, 513, 4553, https://doi.org/10.1038/nature13636.

    • Search Google Scholar
    • Export Citation
  • Stanfield, R. E., and Coauthors, 2016: A quantitative assessment of precipitation associated with the ITCZ in the CMIP5 GCM simulations. Climate Dyn., 47, 18631880, https://doi.org/10.1007/s00382-015-2937-y.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res., 106, 71837192, https://doi.org/10.1029/2000JD900719.

    • Search Google Scholar
    • Export Citation
  • Tian, B., 2015: Spread of model climate sensitivity linked to double‐Intertropical Convergence Zone bias. Geophys. Res. Lett., 42, 41334141, https://doi.org/10.1002/2015GL064119.

    • Search Google Scholar
    • Export Citation
  • Tian, B., and X. Dong, 2020: The double‐ITCZ bias in CMIP3, CMIP5, and CMIP6 models based on annual mean precipitation. Geophys. Res. Lett., 47, e2020GL087232, https://doi.org/10.1029/2020GL087232.

    • Search Google Scholar
    • Export Citation
  • Vimont, D. J., J. M. Wallace, and D. S. Battisti, 2003: The seasonal footprinting mechanism in the Pacific: Implications for ENSO. J. Climate, 16, 26682675, https://doi.org/10.1175/1520-0442(2003)016<2668:TSFMIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., L. Han, R. Ding, and J. Li, 2021: Evaluation of the performance of CMIP5 and CMIP6 models in simulating the South Pacific Quadrupole–ENSO relationship. Atmos. Ocean. Sci. Lett., 14, 100057, https://doi.org/10.1016/j.aosl.2021.100057.

    • Search Google Scholar
    • Export Citation
  • Wu, X., Y. M. Okumura, P. N. DiNezio, S. G. Yeager, and C. Deser, 2022: The equatorial Pacific cold tongue bias in CESM1 and its influence on ENSO forecasts. J. Climate, 35, 32613277, https://doi.org/10.1175/JCLI-D-21-0470.1.

    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., and S. G. H. Philander, 1994: A coupled ocean‐atmosphere model of relevance to the ITCZ in the eastern Pacific. Tellus, 46A, 340350, https://doi.org/10.3402/tellusa.v46i4.15484.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., C. Deser, G. A. Vecchi, J. Ma, H. Teng, and A. T. Wittenberg, 2010: Global warming pattern formation: Sea surface temperature and rainfall. J. Climate, 23, 966986, https://doi.org/10.1175/2009JCLI3329.1.

    • Search Google Scholar
    • Export Citation
  • You, Y., and J. C. Furtado, 2018: The South Pacific meridional mode and its role in tropical Pacific climate variability. J. Climate, 31, 10 14110 163, https://doi.org/10.1175/JCLI-D-17-0860.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, R., and T. L. Delworth, 2005: Simulated tropical response to a substantial weakening of the Atlantic thermohaline circulation. J. Climate, 18, 18531860, https://doi.org/10.1175/JCLI3460.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., H. Liu, and M. Zhang, 2015: Double ITCZ in coupled ocean‐atmosphere models: From CMIP3 to CMIP5. Geophys. Res. Lett., 42, 86518659, https://doi.org/10.1002/2015GL065973.

    • Search Google Scholar
    • Export Citation
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