A Climatology of Multiple Tropical Cyclone Events

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Abstract The present study provides a climatology of multiple tropical cyclone (TC) events (MTCEs) and the potential environmental factors responsible for triggering MTCEs in the North Atlantic (NATL), eastern North Pacific (EPAC), and western North Pacific (WPAC). While single TC events (STCEs) occur more frequently than MTCEs in each basin, a substantial fraction (34%–57%) of all TCs within each basin occur during MTCEs. Comparison of the total monthly number of MTCEs and STCEs reveals significant correlations (0.79 ≤ R ≤ 0.90), while nonsignificant correlations exist between the annual number of MTCEs and STCEs. New TCs that form during MTCEs occur in the eastern main development region east of the STCE formation location in the NATL and EPAC, while new TC formation locations are spread evenly throughout the WPAC during both MTCEs and STCEs. The spatiotemporal separation between TCs during MTCEs is consistent among basins with median zonal distances between TCs of ~(1640–2010) km and median temporal separation between TC formation of 3.00–3.25 days. Composites of EPAC MTCEs suggest the existence of significantly stronger large-scale intraseasonal anomalies compared to STCEs, which may favor EPAC MTCE occurrence. Eastward zonal group velocities and the agreement of the zonal wavelength of TC-induced Rossby waves with the observed zonal distance between TCs suggests that Rossby wave radiation may contribute to a substantial fraction of MTCEs in all basins. These results suggest remarkable similarity in MTCE characteristics among basins, while potentially indicating that the large-scale environment is preconditioned for EPAC MTCE occurrence.

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The present study intercompares multiple tropical cyclone event (MTCE) characteristics among each global tropical cyclone (TC) basin using best-track data. Specific focus is placed on examining the number of MTCEs and TCs during MTCEs, the zonal distance between TCs during MTCEs, and the spatiotemporal separation between genesis events during MTCEs. The results suggest that the ratio of MTCEs relative to single TCs is substantially higher in the eastern North Pacific (ENP), western North Pacific (WNP), and south Indian Ocean (SI) basins compared to the North Atlantic (NA) and South Pacific (SP). The prolific nature of ENP, WNP, and SI MTCE activity results in approximately half of TCs occurring during MTCEs. During new TC genesis, the majority of preexisting TCs are generally located westward at a consistent zonal distance from new TC genesis for MTCEs within each basin with median values between −1620 and −1961 km. TC-induced Rossby wave dispersion may set this zonal length scale as implied by its moderate-to-strong correlations (R = 0.38–0.85; p < 0.05) with the shallow-water zonal wavelength of TC-induced stationary Rossby waves. A substantial majority of TC genesis events occur progressively eastward during ENP, WNP, and SP MTCEs, whereas NA and SI MTCEs exhibit no such tendency. Last, the temporal separation between the genesis of preexisting and new TCs is generally similar among basins with median values between 3 and 4 days. Together, these results are indicative of unusual similarity in MTCE characteristics among basins despite differences in environmental and TC characteristics in each basin.

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This study identifies a significant positive correlation between the Pacific Meridional Mode (PMM) index and frequency of tropical cyclones (TCs) landfalling in China during peak TC season (June–November) of the period 1977–2018. This interannual association is independent of two types of El Niño–Southern Oscillation. Large‐scale circulation over the western North Pacific (WNP) modulated by PMM can affect TC genesis location/frequency and steering flow that directly determine TC landfalls in China. During the positive PMM phase, anomalous off‐equatorial heating over the eastern North Pacific can induce anomalous low‐level cyclonic circulation and upper‐level anticyclonic circulation over most of the main development region in the WNP, as a Gill‐type Rossby wave response. The resultant larger low‐level relative vorticity and weaker vertical wind shear are conducive to the formation of more TCs over the main development region. The anomalous easterly steering flow in the north flank of the anomalous low‐level cyclonic circulation is favourable for more TCs moving westward/northwestward and making landfall in China. The physical mechanism for the impact of PMM on large‐scale circulation over the WNP is verified by numerical experiments using the Community Atmospheric Model. The PMM index is demonstrated to be a crucial predictor for landfalling TC frequency in China in statistical seasonal prediction models.

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We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC‐rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events, and 21% of rain amount in WNP. The fractional contribution of accumulated TC‐rain to total rain, Ω, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979–2005, and for the post‐SSM/I period (1988–2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979–2005 period, but not for the post‐SSM/I period. Trend analyses of Ω for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slightly more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Ω are mixed, and the long‐term relationship between TC rain and warm pool area is strongly influenced by interannual and interdecadal variability.

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