Are North Atlantic Tropical Cyclones Modulated by the Madden–Julian Oscillation in HighResMIP AGCMs?

Chuan-Chieh Chang Pacific Northwest National Laboratory, Richland, Washington

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Ming Zhao NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Sandro W. Lubis Pacific Northwest National Laboratory, Richland, Washington

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Ziming Chen Pacific Northwest National Laboratory, Richland, Washington

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Karthik Balaguru Pacific Northwest National Laboratory, Richland, Washington

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Samson Hagos Pacific Northwest National Laboratory, Richland, Washington

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L. Ruby Leung Pacific Northwest National Laboratory, Richland, Washington

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Wenyu Zhou Pacific Northwest National Laboratory, Richland, Washington

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Abstract

This study assesses the representation of the observed relationship between Atlantic tropical cyclones (TCs) and the Madden–Julian oscillation (MJO) across nine models participating in CMIP6 High Resolution Model Intercomparison Project (HighResMIP). Most models struggle to faithfully reproduce the observed impacts of the MJO on Atlantic TCs, with the primary issue being the underestimated TC activity over the Atlantic main development region (MDR). The negative biases in genesis frequency within the MDR can be further attributed to weaker-than-observed African easterly wave (AEW) activity south of ∼12°N. Errors in the diabatic heating profile within the Atlantic intertropical convergence zone lead to insufficient potential vorticity production in the lower troposphere and constrain the amplification of AEWs. In addition to the biased TC climatology, the eastward-propagating power of the MJO is consistently underestimated across all models. Nevertheless, in models with a higher eastward–westward power ratio, the simulated MJO demonstrates a stronger capacity to modulate subseasonal TC activity. Models with relatively realistic eastward propagation of the MJO also exhibit greater variance in tropical intraseasonal convection. Stronger contrasts in convective heating over the North Atlantic between phases 2–3 and phases 6–7 drive larger fluctuations in MDR shear and AEW activity over the Gulf of Mexico and West Africa, resulting in a more pronounced TC response to the MJO. Overall, our findings suggest that improved MDR TC climatology and MJO propagation are essential for models to accurately capture the observed modulations of Atlantic TCs by the MJO.

© 2025 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: Chuan-Chieh Chang, jay.chang@pnnl.gov

Abstract

This study assesses the representation of the observed relationship between Atlantic tropical cyclones (TCs) and the Madden–Julian oscillation (MJO) across nine models participating in CMIP6 High Resolution Model Intercomparison Project (HighResMIP). Most models struggle to faithfully reproduce the observed impacts of the MJO on Atlantic TCs, with the primary issue being the underestimated TC activity over the Atlantic main development region (MDR). The negative biases in genesis frequency within the MDR can be further attributed to weaker-than-observed African easterly wave (AEW) activity south of ∼12°N. Errors in the diabatic heating profile within the Atlantic intertropical convergence zone lead to insufficient potential vorticity production in the lower troposphere and constrain the amplification of AEWs. In addition to the biased TC climatology, the eastward-propagating power of the MJO is consistently underestimated across all models. Nevertheless, in models with a higher eastward–westward power ratio, the simulated MJO demonstrates a stronger capacity to modulate subseasonal TC activity. Models with relatively realistic eastward propagation of the MJO also exhibit greater variance in tropical intraseasonal convection. Stronger contrasts in convective heating over the North Atlantic between phases 2–3 and phases 6–7 drive larger fluctuations in MDR shear and AEW activity over the Gulf of Mexico and West Africa, resulting in a more pronounced TC response to the MJO. Overall, our findings suggest that improved MDR TC climatology and MJO propagation are essential for models to accurately capture the observed modulations of Atlantic TCs by the MJO.

© 2025 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: Chuan-Chieh Chang, jay.chang@pnnl.gov

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  • Adames, Á. F., D. Kim, A. H. Sobel, A. Del Genio, and J. Wu, 2017: Changes in the structure and propagation of the MJO with increasing CO2. J. Adv. Model. Earth Syst., 9, 12511268, https://doi.org/10.1002/2017MS000913.

    • 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
  • Ahn, M.-S., D. Kim, K. R. Sperber, I.-S. Kang, E. Maloney, D. Waliser, and H. Hendon, 2017: MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis. Climate Dyn., 49, 40234045, https://doi.org/10.1007/s00382-017-3558-4.

    • Search Google Scholar
    • Export Citation
  • Ahn, M.-S., and Coauthors, 2020: MJO propagation across the maritime continent: Are CMIP6 models better than CMIP5 models? Geophys. Res. Lett., 47, e2020GL087250, https://doi.org/10.1029/2020GL087250.

    • Search Google Scholar
    • Export Citation
  • Aiyyer, A., and J. Molinari, 2008: MJO and tropical cyclogenesis in the Gulf of Mexico and eastern Pacific: Case study and idealized numerical modeling. J. Atmos. Sci., 65, 26912704, https://doi.org/10.1175/2007JAS2348.1.

    • Search Google Scholar
    • Export Citation
  • Alaka, G. J., Jr., and E. D. Maloney, 2012: The influence of the MJO on upstream precursors to African easterly waves. J. Climate, 25, 32193236, https://doi.org/10.1175/JCLI-D-11-00232.1.

    • Search Google Scholar
    • Export Citation
  • Alaka, G. J., Jr., and E. D. Maloney, 2014: The intraseasonal variability of African easterly wave energetics. J. Climate, 27, 65596580, https://doi.org/10.1175/JCLI-D-14-00146.1.

    • Search Google Scholar
    • Export Citation
  • Arnault, J., and F. Roux, 2011: Characteristics of African easterly waves associated with tropical cyclogenesis in the Cape Verde Islands region in July–August–September of 2004–2008. Atmos. Res., 100, 6182, https://doi.org/10.1016/j.atmosres.2010.12.028.

    • Search Google Scholar
    • Export Citation
  • Avila, L. A., and R. J. Pasch, 1992: Atlantic tropical systems of 1991. Mon. Wea. Rev., 120, 26882696, https://doi.org/10.1175/1520-0493(1992)120<2688:ATSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Avila, L. A., R. J. Pasch, and J.-G. Jiing, 2000: Atlantic tropical systems of 1996 and 1997: Years of contrasts. Mon. Wea. Rev., 128, 36953706, https://doi.org/10.1175/1520-0493(2000)128<3695:ATSOAY>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Balaguru, K., L. R. Leung, S. M. Hagos, and S. Krishnakumar, 2021: An oceanic pathway for Madden–Julian Oscillation influence on Maritime Continent tropical cyclones. npj Climate Atmos. Sci., 4, 52, https://doi.org/10.1038/s41612-021-00208-4.

    • Search Google Scholar
    • Export Citation
  • Barnston, A. G., N. Vigaud, L. N. Long, M. K. Tippett, and J.-K. E. Schemm, 2015: Atlantic tropical cyclone activity in response to the MJO in NOAA’s CFS model. Mon. Wea. Rev., 143, 49054927, https://doi.org/10.1175/MWR-D-15-0127.1.

    • Search Google Scholar
    • Export Citation
  • Barrett, B. S., and L. M. Leslie, 2009: Links between tropical cyclone activity and Madden–Julian oscillation phase in the North Atlantic and northeast Pacific basins. Mon. Wea. Rev., 137, 727744, https://doi.org/10.1175/2008MWR2602.1.

    • Search Google Scholar
    • Export Citation
  • Barrett, B. S., C. R. Densmore, P. Ray, and E. R. Sanabia, 2021: Active and weakening MJO events in the Maritime Continent. Climate Dyn., 57, 157172, https://doi.org/10.1007/s00382-021-05699-8.

    • Search Google Scholar
    • Export Citation
  • Barton, N., and Coauthors, 2021: The Navy’s Earth System Prediction Capability: A new global coupled atmosphere-ocean-sea ice prediction system designed for daily to subseasonal forecasting. Earth Space Sci., 8, e2020EA001199, https://doi.org/10.1029/2020EA001199.

    • Search Google Scholar
    • Export Citation
  • Belanger, J. I., J. A. Curry, and P. J. Webster, 2010: Predictability of North Atlantic tropical cyclone activity on intraseasonal time scales. Mon. Wea. Rev., 138, 43624374, https://doi.org/10.1175/2010MWR3460.1.

    • Search Google Scholar
    • Export Citation
  • Bell, G. D., and Coauthors, 2000: Climate assessment for 1999. Bull. Amer. Meteor. Soc., 81, S1S50, https://doi.org/10.1175/1520-0477(2000)81[s1:CAF2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bercos-Hickey, E., and C. M. Patricola, 2024: African easterly wave strength and observed Atlantic tropical cyclone genesis and characteristics. J. Geophys. Res. Atmos., 129, e2024JD040858, https://doi.org/10.1029/2024JD040858.

    • Search Google Scholar
    • Export Citation
  • Bercos-Hickey, E., T. R. Nathan, and S.-H. Chen, 2022: Effects of Saharan dust aerosols and West African precipitation on the energetics of African easterly waves. J. Atmos. Sci., 79, 19111926, https://doi.org/10.1175/JAS-D-21-0157.1.

    • Search Google Scholar
    • Export Citation
  • Bercos-Hickey, E., C. M. Patricola, B. Loring, and W. D. Collins, 2023: The relationship between African easterly waves and tropical cyclones in historical and future climates in the HighResMIP-PRIMAVERA simulations. J. Geophys. Res. Atmos., 128, e2022JD037471, https://doi.org/10.1029/2022JD037471.

    • Search Google Scholar
    • Export Citation
  • Berry, G. J., and C. D. Thorncroft, 2012: African easterly wave dynamics in a mesoscale numerical model: The upscale role of convection. J. Atmos. Sci., 69, 12671283, https://doi.org/10.1175/JAS-D-11-099.1.

    • Search Google Scholar
    • Export Citation
  • Bessafi, M., and M. C. Wheeler, 2006: Modulation of South Indian Ocean tropical cyclones by the Madden–Julian oscillation and convectively coupled equatorial waves. Mon. Wea. Rev., 134, 638656, https://doi.org/10.1175/MWR3087.1.

    • Search Google Scholar
    • Export Citation
  • Bian, J., J. Räisänen, and Q. Zhang, 2023: Mechanisms for African easterly wave changes in simulations of the mid-holocene. Climate Dyn., 61, 31653178, https://doi.org/10.1007/s00382-023-06736-4.

    • Search Google Scholar
    • Export Citation
  • Boucher, O., and Coauthors, 2020: Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model. Earth Syst., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010.

    • Search Google Scholar
    • Export Citation
  • Brunet, G., and Coauthors, 2010: Collaboration of the weather and climate communities to advance subseasonal-to-seasonal prediction. Bull. Amer. Meteor. Soc., 91, 13971406, https://doi.org/10.1175/2010BAMS3013.1.

    • Search Google Scholar
    • Export Citation
  • Burpee, R. W., 1972: The origin and structure of easterly waves in the lower troposphere of North Africa. J. Atmos. Sci., 29, 7790, https://doi.org/10.1175/1520-0469(1972)029<0077:TOASOE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Caballero, R., 2008: Hadley cell bias in climate models linked to extratropical eddy stress. Geophys. Res. Lett., 35, L18709, https://doi.org/10.1029/2008GL035084.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., M. C. Wheeler, and A. H. Sobel, 2009: Diagnosis of the MJO modulation of tropical cyclogenesis using an empirical index. J. Atmos. Sci., 66, 30613074, https://doi.org/10.1175/2009JAS3101.1.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and Coauthors, 2019: Tropical cyclone prediction on subseasonal time-scales. Trop. Cyclone Res. Rev., 8, 150165, https://doi.org/10.1016/j.tcrr.2019.10.004.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and Coauthors, 2020: Characteristics of model tropical cyclone climatology and the large-scale environment. J. Climate, 33, 44634487, https://doi.org/10.1175/JCLI-D-19-0500.1.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., F. Vitart, C.-Y. Lee, and M. K. Tippett, 2021: Skill, predictability, and cluster analysis of Atlantic tropical storms and hurricanes in the ECMWF monthly forecasts. Mon. Wea. Rev., 149, 37813802, https://doi.org/10.1175/MWR-D-21-0075.1.

    • Search Google Scholar
    • Export Citation
  • Camp, J., P. Gregory, A. G. Marshall, J. Greenslade, and M. C. Wheeler, 2023: Multiweek tropical cyclone prediction for the Southern Hemisphere in ACCESS-S2: Maintaining operational skill and continuity of service. Quart. J. Roy. Meteor. Soc., 149, 34013422, https://doi.org/10.1002/qj.4563.

    • Search Google Scholar
    • Export Citation
  • Camp, J., P. Gregory, A. G. Marshall, and M. C. Wheeler, 2024: Skilful multiweek predictions of tropical cyclone frequency in the Northern Hemisphere using ACCESS-S2. Quart. J. Roy. Meteor. Soc., 150, 28482868 https://doi.org/10.1002/qj.4738.

    • Search Google Scholar
    • Export Citation
  • Caron, L.-P., and C. G. Jones, 2012: Understanding and simulating the link between African easterly waves and Atlantic tropical cyclones using a regional climate model: The role of domain size and lateral boundary conditions. Climate Dyn., 39, 113135, https://doi.org/10.1007/s00382-011-1160-8.

    • Search Google Scholar
    • Export Citation
  • Cerveny, R. S., and Coauthors, 2017: WMO assessment of weather and climate mortality extremes: Lightning, tropical cyclones, tornadoes, and hail. Wea. Climate Soc., 9, 487497, https://doi.org/10.1175/WCAS-D-16-0120.1.

    • Search Google Scholar
    • Export Citation
  • Chand, S. S., and K. J. Walsh, 2010: The influence of the Madden–Julian oscillation on tropical cyclone activity in the Fiji region. J. Climate, 23, 868886, https://doi.org/10.1175/2009JCLI3316.1.

    • Search Google Scholar
    • Export Citation
  • Chang, C.-C., S. W. Lubis, K. Balaguru, L. R. Leung, S. M. Hagos, and P. J. Klotzbach, 2023: An extratropical pathway for the Madden–Julian oscillation’s influence on North Atlantic tropical cyclones. J. Climate, 36, 85398559, https://doi.org/10.1175/JCLI-D-23-0251.1.

    • Search Google Scholar
    • Export Citation
  • Chang, C.-W. J., M.-H. Lo, W.-L. Tseng, Y.-C. Tsai, and J.-Y. Yu, 2024: Impact of deforestation in the Maritime Continent on the Madden–Julian oscillation. J. Climate, 37, 22472261, https://doi.org/10.1175/JCLI-D-22-0746.1.

    • Search Google Scholar
    • Export Citation
  • Cheedela, S. K., and B. E. Mapes, 2019: Cumulus friction in the Asian monsoon of a global model with 7 km mesh. Current Trends in the Representation of Physical Processes in Weather and Climate Models, D. Randall et al., Eds., Springer Atmospheric Sciences, 197205, Springer, https://doi.org/10.1007/978-981-13-3396-5_10.

    • Search Google Scholar
    • Export Citation
  • Chen, G., and C. Chou, 2014: Joint contribution of multiple equatorial waves to tropical cyclogenesis over the western North Pacific. Mon. Wea. Rev., 142, 7993, https://doi.org/10.1175/MWR-D-13-00207.1.

    • Search Google Scholar
    • Export Citation
  • Chen, J.-M., C.-H. Wu, P.-H. Chung, and C.-H. Sui, 2018: Influence of intraseasonal–interannual oscillations on tropical cyclone genesis in the western North Pacific. J. Climate, 31, 49494961, https://doi.org/10.1175/JCLI-D-17-0601.1.

    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., 2006: Characteristics of African easterly waves depicted by ECMWF reanalyses for 1991–2000. Mon. Wea. Rev., 134, 35393566, https://doi.org/10.1175/MWR3259.1.

    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., S.-Y. Wang, and A. J. Clark, 2008: North Atlantic hurricanes contributed by African easterly waves North and South of the African easterly jet. J. Climate, 21, 67676776, https://doi.org/10.1175/2008JCLI2523.1.

    • Search Google Scholar
    • Export Citation
  • Daloz, A. S., F. Chauvin, K. Walsh, S. Lavender, D. Abbs, and F. Roux, 2012: The ability of general circulation models to simulate tropical cyclones and their precursors over the North Atlantic main development region. Climate Dyn., 39, 15591576, https://doi.org/10.1007/s00382-012-1290-7.

    • Search Google Scholar
    • Export Citation
  • DeMott, C. A., N. P. Klingaman, and S. J. Woolnough, 2015: Atmosphere-ocean coupled processes in the Madden-Julian oscillation. Rev. Geophys., 53, 10991154, https://doi.org/10.1002/2014RG000478.

    • Search Google Scholar
    • Export Citation
  • DeMott, C. A., J. J. Benedict, N. P. Klingaman, S. J. Woolnough, and D. A. Randall, 2016: Diagnosing ocean feedbacks to the MJO: SST-modulated surface fluxes and the moist static energy budget. J. Geophys. Res. Atmos., 121, 83508373, https://doi.org/10.1002/2016JD025098.

    • Search Google Scholar
    • Export Citation
  • DeMott, C. A., N. P. Klingaman, W.-L. Tseng, M. A. Burt, Y. Gao, and D. A. Randall, 2019: The convection connection: How ocean feedbacks affect tropical mean moisture and MJO propagation. J. Geophys. Res. Atmos., 124, 11 91011 931, https://doi.org/10.1029/2019JD031015.

    • Search Google Scholar
    • Export Citation
  • Deser, C., and Coauthors, 2020: Insights from Earth system model initial-condition large ensembles and future prospects. Nat. Climate Change, 10, 277286, https://doi.org/10.1038/s41558-020-0731-2.

    • Search Google Scholar
    • Export Citation
  • de Szoeke, S. P., E. D. Skyllingstad, P. Zuidema, and A. S. Chandra, 2017: Cold pools and their influence on the tropical marine boundary layer. J. Atmos. Sci., 74, 11491168, https://doi.org/10.1175/JAS-D-16-0264.1.

    • Search Google Scholar
    • Export Citation
  • Efron, B., 1992: Bootstrap methods: Another look at the Jackknife. Breakthroughs in Statistics, S. Kotz and N. L. Johnson, Eds., Springer Series in Statistics, Springer, 569593, https://doi.org/10.1007/978-1-4612-4380-9_41.

    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Search Google Scholar
    • Export Citation
  • Feng, X., G.-Y. Yang, K. I. Hodges, and J. Methven, 2023: Equatorial waves as useful precursors to tropical cyclone occurrence and intensification. Nat. Commun., 14, 511, https://doi.org/10.1038/s41467-023-36055-5.

    • Search Google Scholar
    • Export Citation
  • Feng, Z., S. Hagos, A. K. Rowe, C. D. Burleyson, M. N. Martini, and S. P. de Szoeke, 2015: Mechanisms of convective cloud organization by cold pools over tropical warm ocean during the AMIE/DYNAMO field campaign. J. Adv. Model. Earth Syst., 7, 357381, https://doi.org/10.1002/2014MS000384.

    • Search Google Scholar
    • Export Citation
  • Feng, Z., and Coauthors, 2021: A global high-resolution mesoscale convective system database using satellite-derived cloud tops, surface precipitation, and tracking. J. Geophys. Res. Atmos., 126, e2020JD034202, https://doi.org/10.1029/2020JD034202.

    • Search Google Scholar
    • Export Citation
  • Flatau, M., P. J. Flatau, P. Phoebus, and P. P. Niiler, 1997: The feedback between equatorial convection and local radiative and evaporative processes: The implications for intraseasonal oscillations. J. Atmos. Sci., 54, 23732386, https://doi.org/10.1175/1520-0469(1997)054<2373:TFBECA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 741866, https://doi.org/10.1017/CBO9781107415324.020.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and P. E. Roundy, 2006: The role of tropical waves in tropical cyclogenesis. Mon. Wea. Rev., 134, 23972417, https://doi.org/10.1175/MWR3204.1.

    • Search Google Scholar
    • Export Citation
  • Fu, J.-X., W. Wang, H.-L. Ren, X. Jia, and T. Shinoda, 2018: Three different downstream fates of the boreal-summer MJOs on their passages over the Maritime Continent. Climate Dyn., 51, 18411862, https://doi.org/10.1007/s00382-017-3985-2.

    • Search Google Scholar
    • Export Citation
  • Fu, X., and P.-c. Hsu, 2011: Extended-range ensemble forecasting of tropical cyclogenesis in the northern Indian Ocean: Modulation of Madden-Julian Oscillation. Geophys. Res. Lett., 38, L15803, https://doi.org/10.1029/2011GL048249.

    • Search Google Scholar
    • Export Citation
  • Fu, X., W. Wang, J.-Y. Lee, B. Wang, K. Kikuchi, J. Xu, J. Li, and S. Weaver, 2015: Distinctive roles of air–sea coupling on different MJO events: A new perspective revealed from the DYNAMO/CINDY field campaign. Mon. Wea. Rev., 143, 794812, https://doi.org/10.1175/MWR-D-14-00221.1.

    • Search Google Scholar
    • Export Citation
  • Fujita, T., 1959: Precipitation and cold air production in mesoscale thunderstorm systems. J. Meteor., 16, 454466, https://doi.org/10.1175/1520-0469(1959)016<0454:PACAPI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gao, K., J.-H. Chen, L. M. Harris, S.-J. Lin, B. Xiang, and M. Zhao, 2017: Impact of intraseasonal oscillations on the tropical cyclone activity over the Gulf of Mexico and western Caribbean Sea in GFDL HiRAM. J. Geophys. Res. Atmos., 122, 13 12513 137, https://doi.org/10.1002/2017JD027756.

    • Search Google Scholar
    • Export Citation
  • Gelaro, R., and Coauthors, 2017: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). J. Climate, 30, 54195454, https://doi.org/10.1175/JCLI-D-16-0758.1.

    • Search Google Scholar
    • Export Citation
  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447462, https://doi.org/10.1002/qj.49710644905.

    • Search Google Scholar
    • Export Citation
  • Goldenberg, S. B., and L. J. Shapiro, 1996: Physical mechanisms for the association of El Niño and West African rainfall with Atlantic major hurricane activity. J. Climate9, 1169–1187, https://doi.org/10.1175/1520-0442(1996)009<1169:PMFTAO>2.0.CO;2.

  • Gonzalez, A. O., and X. Jiang, 2017: Winter mean lower tropospheric moisture over the Maritime Continent as a climate model diagnostic metric for the propagation of the Madden-Julian oscillation. Geophys. Res. Lett., 44, 25882596, https://doi.org/10.1002/2016GL072430.

    • Search Google Scholar
    • Export Citation
  • Gregory, P., F. Vitart, R. Rivett, A. Brown, and Y. Kuleshov, 2020: Subseasonal forecasts of tropical cyclones in the Southern Hemisphere using a dynamical multimodel ensemble. Wea. Forecasting, 35, 18171829, https://doi.org/10.1175/WAF-D-20-0050.1.

    • Search Google Scholar
    • Export Citation
  • Gutjahr, O., D. Putrasahan, K. Lohmann, J. H. Jungclaus, J.-S. von Storch, N. Brüggemann, H. Haak, and A. Stössel, 2019: Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP). Geosci. Model Dev., 12, 32413281, https://doi.org/10.5194/gmd-12-3241-2019.

    • Search Google Scholar
    • Export Citation
  • Haarsma, R., and Coauthors, 2020: HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR—Description, model performance, data handling and validation. Geosci. Model Dev., 13, 35073527, https://doi.org/10.5194/gmd-13-3507-2020.

    • Search Google Scholar
    • Export Citation
  • Haarsma, R. J., and Coauthors, 2016: High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6. Geosci. Model Dev., 9, 41854208, https://doi.org/10.5194/gmd-9-4185-2016.

    • Search Google Scholar
    • Export Citation
  • Hagos, S., and Coauthors, 2010: Estimates of tropical diabatic heating profiles: Commonalities and uncertainties. J. Climate, 23, 542558, https://doi.org/10.1175/2009JCLI3025.1.

    • Search Google Scholar
    • Export Citation
  • Hagos, S. M., C. Zhang, Z. Feng, C. D. Burleyson, C. De Mott, B. Kerns, J. J. Benedict, and M. N. Martini, 2016: The impact of the diurnal cycle on the propagation of Madden-Julian Oscillation convection across the Maritime Continent. J. Adv. Model. Earth Syst., 8, 15521564, https://doi.org/10.1002/2016MS000725.

    • Search Google Scholar
    • Export Citation
  • Hall, J. D., A. J. Matthews, and D. J. Karoly, 2001: The modulation of tropical cyclone activity in the Australian region by the Madden–Julian oscillation. Mon. Wea. Rev., 129, 29702982, https://doi.org/10.1175/1520-0493(2001)129<2970:TMOTCA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Han, Y., M.-Z. Zhang, Z. Xu, and W. Guo, 2022: Assessing the performance of 33 CMIP6 models in simulating the large-scale environmental fields of tropical cyclones. Climate Dyn., 58, 16831698, https://doi.org/10.1007/s00382-021-05986-4.

    • Search Google Scholar
    • Export Citation
  • Hansen, K. A., S. J. Majumdar, and B. P. Kirtman, 2020: Identifying subseasonal variability relevant to Atlantic tropical cyclone activity. Wea. Forecasting, 35, 20012024, https://doi.org/10.1175/WAF-D-19-0260.1.

    • Search Google Scholar
    • Export Citation
  • Held, I. M., and P. J. Phillips, 1990: A barotropic model of the interaction between the Hadley cell and a Rossby wave. J. Atmos. Sci., 47, 856869, https://doi.org/10.1175/1520-0469(1990)047<0856:ABMOTI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Henderson, S. A., and E. D. Maloney, 2013: An intraseasonal prediction model of Atlantic and east Pacific tropical cyclone genesis. Mon. Wea. Rev., 141, 19251942, https://doi.org/10.1175/MWR-D-12-00268.1.

    • Search Google Scholar
    • Export Citation
  • Henderson, S. A., E. D. Maloney, and S.-W. Son, 2017: Madden–Julian oscillation Pacific teleconnections: The impact of the basic state and MJO representation in general circulation models. J. Climate, 30, 45674587, https://doi.org/10.1175/JCLI-D-16-0789.1.

    • Search Google Scholar
    • Export Citation
  • Hendon, H. H., and J. Glick, 1997: Intraseasonal air–sea interaction in the tropical Indian and Pacific Oceans. J. Climate, 10, 647661, https://doi.org/10.1175/1520-0442(1997)010<0647:IASIIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 19992049, https://doi.org/10.1002/qj.3803.

    • Search Google Scholar
    • Export Citation
  • Hopsch, S. B., C. D. Thorncroft, K. Hodges, and A. Aiyyer, 2007: West African storm tracks and their relationship to Atlantic tropical cyclones. J. Climate, 20, 24682483, https://doi.org/10.1175/JCLI4139.1.

    • Search Google Scholar
    • Export Citation
  • Hopsch, S. B., C. D. Thorncroft, and K. R. Tyle, 2010: Analysis of African easterly wave structures and their role in influencing tropical cyclogenesis. Mon. Wea. Rev., 138, 13991419, https://doi.org/10.1175/2009MWR2760.1.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., M. E. McIntyre, and A. W. Robertson, 1985: On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc., 111, 877946, https://doi.org/10.1002/qj.49711147002.

    • Search Google Scholar
    • Export Citation
  • Hsieh, J.-S., and K. H. Cook, 2005: Generation of African easterly wave disturbances: Relationship to the African easterly jet. Mon. Wea. Rev., 133, 13111327, https://doi.org/10.1175/MWR2916.1.

    • Search Google Scholar
    • Export Citation
  • Hsieh, J.-S., and K. H. Cook, 2007: A study of the energetics of African easterly waves using a regional climate model. J. Atmos. Sci., 64, 421440, https://doi.org/10.1175/JAS3851.1.

    • Search Google Scholar
    • Export Citation
  • Hsu, H.-H., and M.-Y. Lee, 2005: Topographic effects on the eastward propagation and initiation of the Madden–Julian oscillation. J. Climate, 18, 795809, https://doi.org/10.1175/JCLI-3292.1.

    • Search Google Scholar
    • Export Citation
  • Hsu, P.-c., and T. Li, 2012: Role of the boundary layer moisture asymmetry in causing the eastward propagation of the Madden–Julian oscillation. J. Climate, 25, 49144931, https://doi.org/10.1175/JCLI-D-11-00310.1.

    • Search Google Scholar
    • Export Citation
  • Hsu, W.-C., C. M. Patricola, and P. Chang, 2019: The impact of climate model sea surface temperature biases on tropical cyclone simulations. Climate Dyn., 53, 173192, https://doi.org/10.1007/s00382-018-4577-5.

    • Search Google Scholar
    • Export Citation
  • Huang, R., S. Chen, W. Chen, and P. Hu, 2018: Interannual variability of regional Hadley circulation intensity over western Pacific during boreal winter and its climatic impact over Asia-Australia region. J. Geophys. Res. Atmos., 123, 344366, https://doi.org/10.1002/2017JD027919.

    • Search Google Scholar
    • Export Citation
  • Huang, X., C. Hu, X. Huang, Y. Chu, Y.-h. Tseng, G. J. Zhang, and Y. Lin, 2018: A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm. Climate Dyn., 51, 31453159, https://doi.org/10.1007/s00382-018-4071-0.

    • Search Google Scholar
    • Export Citation
  • Janiga, M. A., and C. D. Thorncroft, 2013: Regional differences in the kinematic and thermodynamic structure of African easterly waves. Quart. J. Roy. Meteor. Soc., 139, 15981614, https://doi.org/10.1002/qj.2047.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., 2017: Key processes for the eastward propagation of the Madden-Julian Oscillation based on multimodel simulations. J. Geophys. Res. Atmos., 122, 755770, https://doi.org/10.1002/2016JD025955.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., and Coauthors, 2012: Simulation of the intraseasonal variability over the eastern Pacific ITCZ in climate models. Climate Dyn., 39, 617636, https://doi.org/10.1007/s00382-011-1098-x.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., E. D. Maloney, J. F. Li, and D. E. Waliser, 2013: Simulations of the eastern North Pacific intraseasonal variability in CMIP5 GCMs. J. Climate, 26, 34893510, https://doi.org/10.1175/JCLI-D-12-00526.1.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., H. Su, S. S. Chen, and P. A. Ullrich, 2023: Simulation of African easterly waves in a global climate model. J. Climate, 36, 14151433, https://doi.org/10.1175/JCLI-D-22-0090.1.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., and P. J. Hamilton, 1988: The relationship of surface pressure features to the precipitation and airflow structure of an intense midlatitude squall line. Mon. Wea. Rev., 116, 14441473, https://doi.org/10.1175/1520-0493(1988)116<1444:TROSPF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jones, J. J., M. M. Bell, and P. J. Klotzbach, 2020: Tropical and subtropical North Atlantic vertical wind shear and seasonal tropical cyclone activity. J. Climate, 33, 54135426, https://doi.org/10.1175/JCLI-D-19-0474.1.

    • Search Google Scholar
    • Export Citation
  • Jonkman, S. N., B. Maaskant, E. Boyd, and M. L. Levitan, 2009: Loss of life caused by the flooding of New Orleans after Hurricane Katrina: Analysis of the relationship between flood characteristics and mortality. Risk Anal., 29, 676698, https://doi.org/10.1111/j.1539-6924.2008.01190.x.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311644, https://doi.org/10.1175/BAMS-83-11-1631.

    • Search Google Scholar
    • Export Citation
  • Kennedy, J., H. Titchner, N. Rayner, and M. Roberts, 2017: input4MIPs.MOHC.SSTsAndSeaIce.HighResMIP.MOHC-HadISST-2-2-0-0-0, version 20170505. Earth System Grid Federation, accessed 5 May 2017, https://doi.org/10.22033/ESGF/input4MIPs.1221.

    • Search Google Scholar
    • Export Citation
  • Kim, D., A. H. Sobel, E. D. Maloney, D. M. W. Frierson, and I.-S. Kang, 2011: A systematic relationship between intraseasonal variability and mean state bias in AGCM simulations. J. Climate, 24, 55065520, https://doi.org/10.1175/2011JCLI4177.1.

    • Search Google Scholar
    • Export Citation
  • Kim, D., M.-I. Lee, H.-M. Kim, S. D. Schubert, and J. H. Yoo, 2014: The modulation of tropical storm activity in the western North Pacific by the Madden–Julian Oscillation in GEOS-5 AGCM experiments. Atmos. Sci. Lett., 15, 335341, https://doi.org/10.1002/asl2.509.

    • Search Google Scholar
    • Export Citation
  • Kim, H., M. A. Janiga, and K. Pegion, 2019: MJO propagation processes and mean biases in the SubX and S2S reforecasts. J. Geophys. Res. Atmos., 124, 93149331, https://doi.org/10.1029/2019JD031139.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., 2010: On the Madden–Julian oscillation–Atlantic hurricane relationship. J. Climate, 23, 282293, https://doi.org/10.1175/2009JCLI2978.1.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., 2012: El Niño-Southern Oscillation, the Madden-Julian Oscillation and Atlantic basin tropical cyclone rapid intensification. J. Geophys. Res., 117, D14104, https://doi.org/10.1029/2012JD017714.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., 2014: The Madden–Julian oscillation’s impacts on worldwide tropical cyclone activity. J. Climate, 27, 23172330, https://doi.org/10.1175/JCLI-D-13-00483.1.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., and W. M. Gray, 2003: Forecasting September Atlantic basin tropical cyclone activity. Wea. Forecasting, 18, 11091128, https://doi.org/10.1175/1520-0434(2003)018<1109:FSABTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., and E. S. Blake, 2013: North-Central Pacific tropical cyclones: Impacts of El Niño–Southern Oscillation and the Madden–Julian oscillation. J. Climate, 26, 77207733, https://doi.org/10.1175/JCLI-D-12-00809.1.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., and E. C. J. Oliver, 2015a: Variations in global tropical cyclone activity and the Madden-Julian oscillation since the midtwentieth century. Geophys. Res. Lett., 42, 41994207, https://doi.org/10.1002/2015GL063966.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., and E. C. J. Oliver, 2015b: Modulation of Atlantic basin tropical cyclone Activity by the Madden–Julian oscillation (MJO) from 1905 to 2011. J. Climate, 28, 204217, https://doi.org/10.1175/JCLI-D-14-00509.1.

    • Search Google Scholar
    • Export Citation
  • Klotzbach, P. J., S. G. Bowen, R. Pielke Jr., and M. Bell, 2018: Continental U.S. hurricane landfall frequency and associated damage: Observations and future risks. Bull. Amer. Meteor. Soc., 99, 13591376, https://doi.org/10.1175/BAMS-D-17-0184.1.

    • Search Google Scholar
    • Export Citation
  • Kobayashi, S., and Coauthors, 2015: The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 548, https://doi.org/10.2151/jmsj.2015-001.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., D. K. Oosterhof, and A. V. Mehta, 1988: Air–sea interaction on the time scale of 30 to 50 days. J. Atmos. Sci., 45, 13041322, https://doi.org/10.1175/1520-0469(1988)045<1304:AIOTTS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Krishnamurti, T. N., B. Jha, H. S. Bedi, and U. C. Mohanty, 2000: Diabatic effects on potential vorticity over the global tropics. J. Meteor. Soc. Japan, 78, 527542, https://doi.org/10.2151/jmsj1965.78.5_527.

    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., 1993: A Climatology of intense (or major) Atlantic hurricanes. Mon. Wea. Rev., 121, 17031713, https://doi.org/10.1175/1520-0493(1993)121<1703:ACOIMA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., and J. L. Franklin, 2013: Atlantic hurricane database uncertainty and presentation of a new database format. Mon. Wea. Rev., 141, 35763592, https://doi.org/10.1175/MWR-D-12-00254.1.

    • Search Google Scholar
    • Export Citation
  • Lau, K.-M., and C.-H. Sui, 1997: Mechanisms of short-term sea surface temperature regulation: Observations during TOGA COARE. J. Climate, 10, 465472, https://doi.org/10.1175/1520-0442(1997)010<0465:MOSTSS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lavaysse, C., A. Diedhiou, H. Laurent, and T. Lebel, 2006: African Easterly Waves and convective activity in wet and dry sequences of the West African monsoon. Climate Dyn., 27, 319332, https://doi.org/10.1007/s00382-006-0137-5.

    • Search Google Scholar
    • Export Citation
  • Le, P. V. V., C. Guilloteau, A. Mamalakis, and E. Foufoula-Georgiou, 2021: Underestimated MJO variability in CMIP6 models. Geophys. Res. Lett., 48, e2020GL092244, https://doi.org/10.1029/2020gl092244.

    • Search Google Scholar
    • Export Citation
  • Lee, C.-Y., S. J. Camargo, F. Vitart, A. H. Sobel, and M. K. Tippett, 2018: Subseasonal tropical cyclone genesis prediction and MJO in the S2S dataset. Wea. Forecasting, 33, 967988, https://doi.org/10.1175/WAF-D-17-0165.1.

    • Search Google Scholar
    • Export Citation
  • Lee, C.-Y., S. J. Camargo, F. Vitart, A. H. Sobel, J. Camp, S. Wang, M. K. Tippett, and Q. Yang, 2020: Subseasonal predictions of tropical cyclone occurrence and ACE in the S2S dataset. Wea. Forecasting, 35, 921938, https://doi.org/10.1175/WAF-D-19-0217.1.

    • Search Google Scholar
    • Export Citation
  • Lee, J.-E., and Coauthors, 2012: Reduction of tropical land region precipitation variability via transpiration. Geophys. Res. Lett., 39, L19704, https://doi.org/10.1029/2012GL053417.

    • Search Google Scholar
    • Export Citation
  • Leroux, S., and N. M. J. Hall, 2009: On the relationship between African easterly waves and the African easterly jet. J. Atmos. Sci., 66, 23032316, https://doi.org/10.1175/2009JAS2988.1.

    • Search Google Scholar
    • Export Citation
  • Leroy, A., and M. C. Wheeler, 2008: Statistical prediction of weekly tropical cyclone activity in the Southern Hemisphere. Mon. Wea. Rev., 136, 36373654, https://doi.org/10.1175/2008MWR2426.1.

    • Search Google Scholar
    • Export Citation
  • Lewis-Merritt, C., J. P. Stachnik, M. A. Hollis, E. R. Martin, and R. R. McCrary, 2024: A global climatology of diabatic heating in tropical easterly waves. J. Climate, 37, 20812101, https://doi.org/10.1175/JCLI-D-23-0196.1.

    • Search Google Scholar
    • Export Citation
  • Li, H., J. H. Richter, C.-Y. Lee, and H. Kim, 2022: Subseasonal tropical cyclone prediction and modulations by MJO and ENSO in CESM2. J. Geophys. Res. Atmos., 127, e2022JD036986, https://doi.org/10.1029/2022JD036986.

    • Search Google Scholar
    • Export Citation
  • Li, Y., J. Wu, J.-J. Luo, and Y. M. Yang, 2022a: Evaluating the eastward propagation of the MJO in CMIP5 and CMIP6 models based on a variety of diagnostics. J. Climate, 35, 17191743, https://doi.org/10.1175/JCLI-D-21-0378.1.

    • Search Google Scholar
    • Export Citation
  • Li, Y., X. Li, S.-P. Xie, G. Zhang, Z. Wang, W. Wang, and Y. Hou, 2022b: Regional perspective of Hadley circulation and its uncertainties among different datasets: Spread in reanalysis datasets. J. Geophys. Res. Atmos., 127, e2022JD036940, https://doi.org/10.1029/2022JD036940.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., and C. A. Smith, 1996: Description of complete (interpolated) outgoing longwave radiation data set. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., H. H. Hendon, and J. D. Glick, 1994: The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden-Julian Oscillation. J. Meteor. Soc. Japan, 72, 401412, https://doi.org/10.2151/jmsj1965.72.3_401.

    • Search Google Scholar
    • Export Citation
  • Lim, S. Y., C. Marzin, P. Xavier, C.-P. Chang, and B. Timbal, 2017: Impacts of boreal winter monsoon cold surges and the interaction with MJO on southeast Asia rainfall. J. Climate, 30, 42674281, https://doi.org/10.1175/JCLI-D-16-0546.1.

    • Search Google Scholar
    • Export Citation
  • Ling, J., and C. Zhang, 2011: Structural evolution in heating profiles of the MJO in global reanalyses and TRMM retrievals. J. Climate, 24, 825842, https://doi.org/10.1175/2010JCLI3826.1.

    • Search Google Scholar
    • Export Citation
  • Ling, J., and C. Zhang, 2013: Diabatic Heating Profiles in Recent Global Reanalyses. Journal of Climate, 26, 33073325, https://doi.org/10.1175/JCLI-D-12-00384.1.

    • Search Google Scholar
    • Export Citation
  • Liu, B., and Coauthors, 2022: Will increasing climate model resolution be beneficial for ENSO simulation? Geophys. Res. Lett., 49, e2021GL096932, https://doi.org/10.1029/2021GL096932.

    • Search Google Scholar
    • Export Citation
  • Liu, N., L. R. Leung, and Z. Feng, 2021: Global mesoscale convective system latent heating characteristics from GPM retrievals and an MCS tracking dataset. J. Climate, 34, 85998613, https://doi.org/10.1175/JCLI-D-20-0997.1.

    • Search Google Scholar
    • Export Citation
  • Lubis, S. W., S. Hagos, C.-C. Chang, K. Balaguru, and L. R. Leung, 2023: Cross-equatorial surges boost MJO’s southward detour over the Maritime Continent. Geophys. Res. Lett., 50, e2023GL104770, https://doi.org/10.1029/2023GL104770.

    • Search Google Scholar
    • Export Citation
  • Macalalad, R. V., R. A. Badilla, O. C. Cabrera, and G. Bagtasa, 2021: Hydrological response of the Pampanga River basin in the Philippines to intense tropical cyclone rainfall. J. Hydrometeor., 22, 781794, https://doi.org/10.1175/JHM-D-20-0184.1.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702708, https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Madden, R. A., and P. R. Julian, 1972: Description of global-scale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 11091123, https://doi.org/10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Majda, A. J., and Q. Yang, 2016: A multiscale model for the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden–Julian oscillation. J. Atmos. Sci., 73, 579604, https://doi.org/10.1175/JAS-D-15-0158.1.

    • Search Google Scholar
    • Export Citation
  • Maloney, E. D., and D. L. Hartmann, 2000a: Modulation of hurricane activity in the Gulf of Mexico by the Madden–Julian oscillation. Science, 287, 20022004, https://doi.org/10.1126/science.287.5460.2002.

    • Search Google Scholar
    • Export Citation
  • Maloney, E. D., and D. L. Hartmann, 2000b: Modulation of eastern North Pacific hurricanes by the Madden–Julian oscillation. J. Climate, 13, 14511460, https://doi.org/10.1175/1520-0442(2000)013<1451:MOENPH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Maloney, E. D., and J. Shaman, 2008: Intraseasonal variability of the West African Monsoon and Atlantic ITCZ. J. Climate, 21, 28982918, https://doi.org/10.1175/2007JCLI1999.1.

    • Search Google Scholar
    • Export Citation
  • Martin, E. R., and C. Schumacher, 2011: Modulation of Caribbean precipitation by the Madden–Julian oscillation. J. Climate, 24, 813824, https://doi.org/10.1175/2010JCLI3773.1.

    • Search Google Scholar
    • Export Citation
  • Martin, E. R., and C. Thorncroft, 2015: Representation of African easterly waves in CMIP5 models. J. Climate, 28, 77027715, https://doi.org/10.1175/JCLI-D-15-0145.1.

    • Search Google Scholar
    • Export Citation
  • Martin, J. E., 2006: Mid-Latitude Atmospheric Dynamics: A First Course. Wiley Press, 324 pp.

  • Matthews, A. J., 2000: Propagation mechanisms for the Madden-Julian Oscillation. Quart. J. Roy. Meteor. Soc., 126, 26372651, https://doi.org/10.1002/qj.49712656902.

    • Search Google Scholar
    • Export Citation
  • Matthews, A. J., 2004: Intraseasonal variability over tropical Africa during northern summer. J. Climate, 17, 24272440, https://doi.org/10.1175/1520-0442(2004)017<2427:IVOTAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Miller, D. E., V. A. Gensini, and B. S. Barrett, 2022: Madden-Julian Oscillation influences United States springtime tornado and hail frequency. npj Climate Atmos. Sci., 5, 37, https://doi.org/10.1038/s41612-022-00263-5.

    • Search Google Scholar
    • Export Citation
  • Mizuta, R., and Coauthors, 2012: Climate simulations using MRI-AGCM3.2 with 20-km grid. J. Meteor. Soc. Japan, 90A, 233258, https://doi.org/10.2151/jmsj.2012-A12.

    • Search Google Scholar
    • Export Citation
  • Mo, K. C., 2000: The association between intraseasonal oscillations and tropical storms in the Atlantic basin. Mon. Wea. Rev., 128, 40974107, https://doi.org/10.1175/1520-0493(2000)129<4097:TABIOA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Molinari, J., D. Knight, M. Dickinson, D. Vollaro, and S. Skubis, 1997: Potential vorticity, easterly waves, and eastern Pacific tropical cyclogenesis. Mon. Wea. Rev., 125, 26992708, https://doi.org/10.1175/1520-0493(1997)125<2699:PVEWAE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Molod, A., and Coauthors, 2020: GEOS-S2S version 2: The GMAO high resolution coupled model and assimilation system for seasonal prediction. J. Geophys. Res. Atmos., 125, e2019JD031767, https://doi.org/10.1029/2019jd031767.

    • Search Google Scholar
    • Export Citation
  • Moncrieff, M. W., 1992: Organized convective systems: Archetypal dynamical models, mass and momentum flux theory, and parametrization. Quart. J. Roy. Meteor. Soc., 118, 819850, https://doi.org/10.1002/qj.49711850703.

    • Search Google Scholar
    • Export Citation
  • Murakami, H., and B. Wang, 2010: Future change of North Atlantic tropical cyclone tracks: Projection by a 20-km-mesh global atmospheric model. J. Climate, 23, 26992721, https://doi.org/10.1175/2010JCLI3338.1.

    • Search Google Scholar
    • Export Citation
  • Nigam, S., C. Chung, and E. DeWeaver, 2000: ENSO diabatic heating in ECMWF and NCEP–NCAR reanalyses, and NCAR CCM3 simulation. J. Climate, 13, 31523171, https://doi.org/10.1175/1520-0442(2000)013<3152:EDHIEA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Oh, J.-H., B.-M. Kim, K.-Y. Kim, H.-J. Song, and G.-H. Lim, 2013: The impact of the diurnal cycle on the MJO over the Maritime Continent: A modeling study assimilating TRMM rain rate into global analysis. Climate Dyn., 40, 893911, https://doi.org/10.1007/s00382-012-1419-8.

    • Search Google Scholar
    • Export Citation
  • Papin, P. P., L. F. Bosart, and R. D. Torn, 2020: A feature-based approach to classifying summertime potential vorticity streamers linked to Rossby wave breaking in the North Atlantic basin. J. Climate, 33, 59535969, https://doi.org/10.1175/JCLI-D-19-0812.1.

    • Search Google Scholar
    • Export Citation
  • Pasch, R. J., L. A. Avila, and J.-G. Jiing, 1998: Atlantic tropical systems of 1994 and 1995: A comparison of a quiet season to a near-record-breaking one. Mon. Wea. Rev., 126, 11061123, https://doi.org/10.1175/1520-0493(1998)126<1106:ATSOAA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., Jr., J. Gratz, C. W. Landsea, D. Collins, M. A. Saunders, and R. Musulin, 2008: Normalized hurricane damage in the United States: 1900–2005. Nat. Hazards Rev., 9, 2942, https://doi.org/10.1061/(ASCE)1527-6988(2008)9:1(29).

    • Search Google Scholar
    • Export Citation
  • Pytharoulis, I., and C. Thorncroft, 1999: The low-level structure of African easterly waves in 1995. Mon. Wea. Rev., 127, 22662280, https://doi.org/10.1175/1520-0493(1999)127<2266:TLLSOA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Randel, W. J., and I. M. Held, 1991: Phase speed spectra of transient eddy fluxes and critical layer absorption. J. Atmos. Sci., 48, 688697, https://doi.org/10.1175/1520-0469(1991)048<0688:PSSOTE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rappin, E. D., and D. S. Nolan, 2012: The effect of vertical shear orientation on tropical cyclogenesis. Quart. J. Roy. Meteor. Soc., 138, 10351054, https://doi.org/10.1002/qj.977.

    • Search Google Scholar
    • Export Citation
  • Reed, R. J., A. Hollingsworth, W. A. Heckley, and F. Delsol, 1988: An evaluation of the performance of the ECMWF operational system in analyzing and forecasting easterly wave disturbances over Africa and the tropical Atlantic. Mon. Wea. Rev., 116, 824865, https://doi.org/10.1175/1520-0493(1988)116<0824:AEOTPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Richardson, Y. P., K. K. Droegemeier, and R. P. Davies-Jones, 2007: The influence of horizontal environmental variability on numerically simulated convective storms. Part I: Variations in vertical shear. Mon. Wea. Rev., 135, 34293455, https://doi.org/10.1175/MWR3463.1.

    • Search Google Scholar
    • Export Citation
  • Richter, J. H., and Coauthors, 2022: Subseasonal earth system prediction with CESM2. Wea. Forecasting, 37, 797815, https://doi.org/10.1175/WAF-D-21-0163.1.

    • Search Google Scholar
    • Export Citation
  • Roberts, C. D., R. Senan, F. Molteni, S. Boussetta, M. Mayer, and S. P. E. Keeley, 2018: Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP. Geosci. Model Dev., 11, 36813712, https://doi.org/10.5194/gmd-11-3681-2018.

    • Search Google Scholar
    • Export Citation
  • Roberts, M. J., and Coauthors, 2019: Description of the resolution hierarchy of the global coupled HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments. Geosci. Model Dev., 12, 49995028, https://doi.org/10.5194/gmd-12-4999-2019.

    • Search Google Scholar
    • Export Citation
  • Roberts, M. J., and Coauthors, 2020: Impact of model resolution on tropical cyclone simulation using the HighResMIP–PRIMAVERA multimodel ensemble. J. Climate, 33, 25572583, https://doi.org/10.1175/JCLI-D-19-0639.1.

    • Search Google Scholar
    • Export Citation
  • Robertson, A. W., F. Vitart, and S. J. Camargo, 2020: Subseasonal to seasonal prediction of weather to climate with application to tropical cyclones. J. Geophys. Res. Atmos., 125, e2018JD029375, https://doi.org/10.1029/2018JD029375.

    • Search Google Scholar
    • Export Citation
  • Ross, A. N., A. M. Tompkins, and D. J. Parker, 2004: Simple models of the role of surface fluxes in convective cold pool evolution. J. Atmos. Sci., 61, 15821595, https://doi.org/10.1175/1520-0469(2004)061<1582:SMOTRO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Russell, J. O., A. Aiyyer, J. D. White, and W. Hannah, 2017: Revisiting the connection between African Easterly Waves and Atlantic tropical cyclogenesis. Geophys. Res. Lett., 44, 587595, https://doi.org/10.1002/2016GL071236.

    • Search Google Scholar
    • Export Citation
  • Russell, J. O. H., and A. Aiyyer, 2020: The potential vorticity structure and dynamics of African easterly waves. J. Atmos. Sci., 77, 871890, https://doi.org/10.1175/JAS-D-19-0019.1.

    • Search Google Scholar
    • Export Citation
  • Russell, J. O. H., A. Aiyyer, and J. D. White, 2020: African easterly wave dynamics in convection-permitting simulations: Rotational stratiform instability as a conceptual model. J. Adv. Model. Earth Syst., 12, e2019MS001706, https://doi.org/10.1029/2019MS001706.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 10151058, https://doi.org/10.1175/2010BAMS3001.1.

    • Search Google Scholar
    • Export Citation
  • Satoh, M., and Coauthors, 2012: The intra-seasonal oscillation and its control of tropical cyclones simulated by high-resolution global atmospheric models. Climate Dyn., 39, 21852206, https://doi.org/10.1007/s00382-011-1235-6.

    • Search Google Scholar
    • Export Citation
  • Schlemmer, L., and C. Hohenegger, 2014: The formation of wider and deeper clouds as a result of cold-pool dynamics. J. Atmos. Sci., 71, 28422858, https://doi.org/10.1175/JAS-D-13-0170.1.

    • Search Google Scholar
    • Export Citation
  • Schneider, E. K., and R. S. Lindzen, 1976: A discussion of the parameterization of momentum exchange by cumulus convection. J. Geophys. Res., 81, 31583160, https://doi.org/10.1029/JC081i018p03158.

    • Search Google Scholar
    • Export Citation
  • Schreck, C. J., III, 2015: Kelvin waves and tropical cyclogenesis: A global survey. Mon. Wea. Rev., 143, 39964011, https://doi.org/10.1175/MWR-D-15-0111.1.

    • Search Google Scholar
    • Export Citation
  • Schreck, C. J., III, and Coauthors, 2023: Advances in tropical cyclone prediction on subseasonal time scales during 2019–2022. Trop. Cyclone Res. Rev., 12, 136150, https://doi.org/10.1016/j.tcrr.2023.06.004.

    • Search Google Scholar
    • Export Citation
  • Shin, J., and S. Park, 2020: Impacts of ENSO and Madden–Julian oscillation on the genesis of tropical cyclones simulated by general circulation models and compared to observations. Environ. Res. Lett., 15, 034046, https://doi.org/10.1088/1748-9326/ab7466.

    • Search Google Scholar
    • Export Citation
  • Shultz, J. M., J. Russell, and Z. Espinel, 2005: Epidemiology of tropical cyclones: The dynamics of disaster, disease, and development. Epidemiol. Rev., 27, 2135, https://doi.org/10.1093/epirev/mxi011.

    • Search Google Scholar
    • Export Citation
  • Skinner, C. B., and N. S. Diffenbaugh, 2013: The contribution of African easterly waves to monsoon precipitation in the CMIP3 ensemble. J. Geophys. Res. Atmos., 118, 35903609, https://doi.org/10.1002/jgrd.50363.

    • Search Google Scholar
    • Export Citation
  • Smith, A. B., and R. W. Katz, 2013: US billion-dollar weather and climate disasters: Data sources, trends, accuracy and biases. Nat. Hazards, 67, 387410, https://doi.org/10.1007/s11069-013-0566-5.

    • Search Google Scholar
    • Export Citation
  • Stachnik, J. P., and C. Schumacher, 2011: A comparison of the Hadley circulation in modern reanalyses. J. Geophys. Res., 116, D22102, https://doi.org/10.1029/2011JD016677.

    • Search Google Scholar
    • Export Citation
  • Stan, C., 2018: The role of SST variability in the simulation of the MJO. Climate Dyn., 51, 29432964, https://doi.org/10.1007/s00382-017-4058-2.

    • 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
  • Thorncroft, C., and K. Hodges, 2001: African easterly wave variability and its relationship to Atlantic tropical cyclone activity. J. Climate, 14, 11661179, https://doi.org/10.1175/1520-0442(2001)014<1166:AEWVAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thorncroft, C. D., and B. J. Hoskins, 1994a: An idealized study of African easterly waves. I: A linear view. Quart. J. Roy. Meteor. Soc., 120, 953982, https://doi.org/10.1002/qj.49712051809.

    • Search Google Scholar
    • Export Citation
  • Thorncroft, C. D., and B. J. Hoskins, 1994b: An idealized study of African easterly waves. II: A nonlinear view. Quart. J. Roy. Meteor. Soc., 120, 9831015, https://doi.org/10.1002/qj.49712051810.

    • Search Google Scholar
    • Export Citation
  • Thorpe, A. J., M. J. Miller, and M. W. Moncrieff, 1982: Two-dimensional convection in non-constant shear: A model of mid-latitude squall lines. Quart. J. Roy. Meteor. Soc., 108, 739762, https://doi.org/10.1002/qj.49710845802.

    • Search Google Scholar
    • Export Citation
  • Tobin, G. A., 1997: Natural Hazards: Explanation and Integration. Guilford Press, 388 pp.

  • Tomassini, L., and G.-Y. Yang, 2022: Tropical moist convection as an important driver of Atlantic Hadley circulation variability. Quart. J. Roy. Meteor. Soc., 148, 32873302, https://doi.org/10.1002/qj.4359.

    • Search Google Scholar
    • Export Citation
  • Tsai, W.-M., and C.-M. Wu, 2017: The environment of aggregated deep convection. J. Adv. Model. Earth Syst., 9, 20612078, https://doi.org/10.1002/2017MS000967.

    • Search Google Scholar
    • Export Citation
  • Tseng, W.-L., H.-H. Hsu, N. Keenlyside, C.-W. June Chang, B.-J. Tsuang, C.-Y. Tu, and L.-C. Jiang, 2017: Effects of surface orography and land–sea contrast on the Madden–Julian oscillation in the Maritime Continent: A numerical study using ECHAM5-SIT. J. Climate, 30, 97259741, https://doi.org/10.1175/JCLI-D-17-0051.1.

    • Search Google Scholar
    • Export Citation
  • Tseng, W.-L., H.-H. Hsu, Y.-Y. Lan, W.-L. Lee, C.-Y. Tu, P.-H. Kuo, B.-J. Tsuang, and H.-C. Liang, 2022: Improving Madden–Julian oscillation simulation in atmospheric general circulation models by coupling with a one-dimensional snow–ice–thermocline ocean model. Geosci. Model Dev., 15, 55295546, https://doi.org/10.5194/gmd-15-5529-2022.

    • Search Google Scholar
    • Export Citation
  • Ullrich, P. A., and C. M. Zarzycki, 2017: TempestExtremes: A framework for scale-insensitive pointwise feature tracking on unstructured grids. Geosci. Model Dev., 10, 10691090, https://doi.org/10.5194/gmd-10-1069-2017.

    • Search Google Scholar
    • Export Citation
  • Ventrice, M. J., C. D. Thorncroft, and P. E. Roundy, 2011: The Madden–Julian oscillation’s influence on African easterly waves and downstream tropical cyclogenesis. Mon. Wea. Rev., 139, 27042722, https://doi.org/10.1175/MWR-D-10-05028.1.

    • Search Google Scholar
    • Export Citation
  • Ventrice, M. J., C. D. Thorncroft, and M. A. Janiga, 2012: Atlantic tropical cyclogenesis: A three-way interaction between an African easterly wave, diurnally varying convection, and a convectively coupled atmospheric Kelvin wave. Mon. Wea. Rev., 140, 11081124, https://doi.org/10.1175/MWR-D-11-00122.1.

    • Search Google Scholar
    • Export Citation
  • Vitart, F., 2009: Impact of the Madden Julian Oscillation on tropical storms and risk of landfall in the ECMWF forecast system. Geophys. Res. Lett., 36, L15802, https://doi.org/10.1029/2009GL039089.

    • Search Google Scholar
    • Export Citation
  • Vitart, F., 2017: Madden—Julian Oscillation prediction and teleconnections in the S2S database. Quart. J. Roy. Meteor. Soc., 143, 22102220, https://doi.org/10.1002/qj.3079.

    • Search Google Scholar
    • Export Citation
  • Vizy, E. K., and K. H. Cook, 2009: Tropical storm development from African easterly waves in the eastern Atlantic: A comparison of two successive waves using a regional model as part of NASA AMMA 2006. J. Atmos. Sci., 66, 33133334, https://doi.org/10.1175/2009JAS3064.1.

    • Search Google Scholar
    • Export Citation
  • Voldoire, A., and Coauthors, 2019: Evaluation of CMIP6 DECK experiments with CNRM-CM6-1. J. Adv. Model. Earth Syst., 11, 21772213, https://doi.org/10.1029/2019MS001683.

    • Search Google Scholar
    • Export Citation
  • Waliser, D., and Coauthors, 2009: MJO simulation diagnostics. J. Climate, 22, 30063030, https://doi.org/10.1175/2008JCLI2731.1.

  • Wang, B., and S.-S. Lee, 2017: MJO propagation shaped by zonal asymmetric structures: Results from 24 GCM simulations. J. Climate, 30, 79337952, https://doi.org/10.1175/JCLI-D-16-0873.1.

    • Search Google Scholar
    • Export Citation
  • Wang, B., and G. Chen, 2017: A general theoretical framework for understanding essential dynamics of Madden–Julian oscillation. Climate Dyn., 49, 23092328 https://doi.org/10.1007/s00382-016-3448-1.

    • Search Google Scholar
    • Export Citation
  • Wang, B., and Coauthors, 2018: Dynamics-oriented diagnostics for the Madden–Julian oscillation. J. Climate, 31, 31173135, https://doi.org/10.1175/JCLI-D-17-0332.1.

    • Search Google Scholar
    • Export Citation
  • Wang, J., H. Kim, D. Kim, S. A. Henderson, C. Stan, and E. D. Maloney, 2020a: MJO teleconnections over the PNA region in climate models. Part I: Performance- and process-based skill metrics. J. Climate, 33, 10511067, https://doi.org/10.1175/JCLI-D-19-0253.1.

    • Search Google Scholar
    • Export Citation
  • Wang, J., H. Kim, D. Kim, S. A. Henderson, C. Stan, and E. D. Maloney, 2020b: MJO teleconnections over the PNA region in climate models. Part II: Impacts of the MJO and basic state. J. Climate, 33, 50815101, https://doi.org/10.1175/JCLI-D-19-0865.1.

    • Search Google Scholar
    • Export Citation
  • Wang, J., H. Kim, and M. J. DeFlorio, 2022: Future changes of PNA-like MJO teleconnections in CMIP6 models: Underlying mechanisms and uncertainty. J. Climate, 35, 34593478, https://doi.org/10.1175/JCLI-D-21-0445.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., M. T. Montgomery, and C. Fritz, 2012: A first look at the structure of the wave pouch during the 2009 PREDICT–GRIP dry runs over the Atlantic. Mon. Wea. Rev., 140, 11441163, https://doi.org/10.1175/MWR-D-10-05063.1.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and M. Kimoto, 2000: Atmosphere-ocean thermal coupling in the North Atlantic: A positive feedback. Quart. J. Roy. Meteor. Soc., 126, 33433369, https://doi.org/10.1002/qj.49712657017.

    • Search Google Scholar
    • Export Citation
  • Wedd, R., and Coauthors, 2022: ACCESS-S2: The upgraded Bureau of Meteorology multi-week to seasonal prediction system. J. South. Hemisphere Earth Syst. Sci., 72, 218242, https://doi.org/10.1071/ES22026.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M., and G. N. Kiladis, 1999: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain. J. Atmos. Sci., 56, 374399, https://doi.org/10.1175/1520-0469(1999)056<0374:CCEWAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 19171932, https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xavier, P., and Coauthors, 2020: Seasonal dependence of cold surges and their interaction with the Madden–Julian oscillation over southeast Asia. J. Climate, 33, 24672482, https://doi.org/10.1175/JCLI-D-19-0048.1.

    • Search Google Scholar
    • Export Citation
  • Xiang, B., and Coauthors, 2022: S2S prediction in GFDL SPEAR: MJO diversity and teleconnections. Bull. Amer. Meteor. Soc., 103, E463E484, https://doi.org/10.1175/BAMS-D-21-0124.1.

    • Search Google Scholar
    • Export Citation
  • Xiang, B., B. Wang, G. Chen, and T. L. Delworth, 2024: Prediction of diverse boreal summer intraseasonal oscillation in the GFDL SPEAR model. J. Climate, 37, 22172230, https://doi.org/10.1175/JCLI-D-23-0601.1.

    • 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, Y.-B., S.-J. Chen, I.-L. Zhang, and Y.-L. Hung, 1963: A preliminarily statistic and synoptic study about the basic currents over southeastern Asia and the initiation of typhoon (in Chinese). Acta Meteor. Sin., 33, 206217, https://doi.org/10.11676/qxxb1963.020.

    • Search Google Scholar
    • Export Citation
  • Xu, G., and Coauthors, 2022: Impacts of model horizontal resolution on mean sea surface temperature biases in the Community Earth System Model. J. Geophys. Res. Oceans, 127, e2022JC019065, https://doi.org/10.1029/2022JC019065.

    • Search Google Scholar
    • Export Citation
  • Yanai, M., J. Chu, T. E. Stark, and T. Nitta, 1976: Response of deep and shallow tropical maritime cumuli to large-scale processes. J. Atmos. Sci., 33, 976991, https://doi.org/10.1175/1520-0469(1976)033<0976:RODAST>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yu, W., W. Han, E. D. Maloney, D. Gochis, and S.-P. Xie, 2011: Observations of eastward propagation of atmospheric intraseasonal oscillations from the Pacific to the Atlantic. J. Geophys. Res., 116, D02101, https://doi.org/10.1029/2010JD014336.

    • Search Google Scholar
    • Export Citation
  • Yuan, J., and R. A. Houze Jr., 2010: Global variability of mesoscale convective system anvil structure from A-train satellite data. J. Climate, 23, 58645888, https://doi.org/10.1175/2010JCLI3671.1.

    • Search Google Scholar
    • Export Citation
  • Zarzycki, C. M., and P. A. Ullrich, 2017: Assessing sensitivities in algorithmic detection of tropical cyclones in climate data. Geophys. Res. Lett., 44, 11411149, https://doi.org/10.1002/2016GL071606.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 1996: Atmospheric intraseasonal variability at the surface in the tropical western Pacific Ocean. J. Atmos. Sci., 53, 739758, https://doi.org/10.1175/1520-0469(1996)053<0739:AIVATS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2005: Madden-Julian Oscillation. Rev. Geophys., 43, RG2003, https://doi.org/10.1029/2004RG000158.

  • Zhang, C., and J. Pennington, 2004: African dry air outbreaks. J. Geophys. Res., 109, D20108, https://doi.org/10.1029/2003JD003978.

  • Zhang, C., and M. Dong, 2004: Seasonality of the Madden-Julian oscillation. J. Climate., 17, 31693180, https://doi.org/10.1175/1520-0442(2004)017%3C3169:SITMO%3E2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., M. Dong, S. Gualdi, H. H. Hendon, E. D. Maloney, A. Marshall, K. R. Sperber, and W. Wang, 2006: Simulations of the Madden–Julian Oscillation in four pairs of coupled and uncoupled global models. Climate Dyn., 27, 573592, https://doi.org/10.1007/s00382-006-0148-2.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., and Z. Wang, 2013: Interannual variability of the Atlantic Hadley circulation in boreal summer and its impacts on tropical cyclone activity. J. Climate, 26, 85298544, https://doi.org/10.1175/JCLI-D-12-00802.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., and Z. Wang, 2018: North Atlantic extratropical Rossby wave breaking during the warm season: Wave life cycle and role of diabatic heating. Mon. Wea. Rev., 146, 695712, https://doi.org/10.1175/MWR-D-17-0204.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., Z. Wang, T. J. Dunkerton, M. S. Peng, and G. Magnusdottir, 2016: Extratropical impacts on Atlantic tropical cyclone activity. J. Atmos. Sci., 73, 14011418, https://doi.org/10.1175/JAS-D-15-0154.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G., Z. Wang, M. S. Peng, and G. Magnusdottir, 2017: Characteristics and impacts of extratropical Rossby wave breaking during the Atlantic hurricane season. J. Climate, 30, 23632379, https://doi.org/10.1175/JCLI-D-16-0425.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, G. J., and H.-R. Cho, 1991a: Parameterization of the vertical transport of momentum by cumulus clouds. Part I: Theory. J. Atmos. Sci., 48, 14831492, https://doi.org/10.1175/1520-0469(1991)048<1483:POTVTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, G. J., and H.-R. Cho, 1991b: Parameterization of the vertical transport of momentum by cumulus clouds. Part II: Application. J. Atmos. Sci., 48, 24482457, https://doi.org/10.1175/1520-0469(1991)048<2448:POTVTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, Q., X. Gu, J. Li, P. Shi, and V. P. Singh, 2018: The impact of tropical cyclones on extreme precipitation over coastal and inland areas of China and its association to ENSO. J. Climate, 31, 18651880, https://doi.org/10.1175/JCLI-D-17-0474.1.

    • Search Google Scholar
    • Export Citation
  • Zhao, C., H.-L. Ren, R. Eade, Y. Wu, J. Wu, and C. MacLachlan, 2019: MJO modulation and its ability to predict boreal summer tropical cyclone genesis over the northwest Pacific in Met Office Hadley Centre and Beijing Climate Center seasonal prediction systems. Quart. J. Roy. Meteor. Soc., 145, 10891101, https://doi.org/10.1002/qj.3478.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., 2020: Simulations of atmospheric rivers, their variability, and response to global warming using GFDL’s new high-resolution general circulation model. J. Climate, 33, 10 28710 303, https://doi.org/10.1175/JCLI-D-20-0241.1.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., I. M. Held, S.-J. Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM. J. Climate, 22, 66536678, https://doi.org/10.1175/2009JCLI3049.1.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., and Coauthors, 2018a: The GFDL global atmosphere and land model AM4.0/LM4.0: 1. Simulation characteristics with prescribed SSTs. J. Adv. Model. Earth Syst., 10, 691734, https://doi.org/10.1002/2017MS001208.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., and Coauthors, 2018b: The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies. J. Adv. Model. Earth Syst., 10, 735769, https://doi.org/10.1002/2017MS001209.

    • Search Google Scholar
    • Export Citation
  • Zhou, W., and J. C. L. Chan, 2005: Intraseasonal oscillations and the South China Sea summer monsoon onset. Int. J. Climatol., 25, 15851609, https://doi.org/10.1002/joc.1209.

    • Search Google Scholar
    • Export Citation
  • Zhou, W., D. Yang, S.-P. Xie, and J. Ma, 2020: Amplified Madden–Julian oscillation impacts in the Pacific–North America region. Nat. Climate Change, 10, 654660, https://doi.org/10.1038/s41558-020-0814-0.

    • Search Google Scholar
    • Export Citation
  • Zhu, J., W. Wang, and A. Kumar, 2017: Simulations of MJO propagation across the Maritime Continent: impacts of SST feedback. J. Climate, 30, 16891704, https://doi.org/10.1175/JCLI-D-16-0367.1.

    • Search Google Scholar
    • Export Citation
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