This study finds a significant positive correlation between the Pacific meridional mode (PMM) index and the frequency of intense tropical cyclones (TCs) over the western North Pacific (WNP) during the peak TC season (June–November). The PMM influences the occurrence of intense TCs mainly by modulating large-scale dynamical conditions over the main development region. During the positive PMM phase, anomalous off-equatorial heating in the eastern Pacific induces anomalous low-level westerlies (and cyclonic flow) and upper-level easterlies (and anticyclonic flow) over a large portion of the main development region through a Matsuno–Gill-type Rossby wave response. The resulting weaker vertical wind shear and larger low-level relative vorticity favor the genesis of intense TCs over the southeastern part of the WNP and their subsequent intensification over the main development region. The PMM index would therefore be a valuable predictor for the frequency of intense TCs over the WNP.

The 2018 tropical cyclone (TC) season over the western North Pacific (WNP) underwent two extreme situations: 18 TCs observed during June-August (JJA) and ranked the second most active summer in the satellite era; only 5 TCs that occurred during September-October (SO), making it the most inactive period since the late 1970s. Here we attribute the two extreme situations based on observational analyses and numerical experiments. The extremely active TC activity and northward shift of TC genesis during JJA of 2018 can be attributed to the WNP anomalous low-level cyclone, which is due primarily to El Niño Modoki and secondarily to the positive phase of the Pacific Meridional Mode (PMM). Overall, the extremely inactive TC activity during SO of 2018 is due to the absence of TC formation over the South China Sea and Philippine Sea, which can be attributed to the in-situ anomalous low-level anticyclone associated with the positive phase of the Indian Ocean Dipole, although the positive PMM phase and El Niño Modoki still hold. Scientific RepoRtS | (2020) 10:5610 | https://doi.Model version 5.3 (CAM-5.3) 29 was used to perform numerical experiments. The model has T31 horizontal resolution (approximately 3.75° × 3.75°) and 26 vertical levels. Parameterization schemes adopted by the model include the deep convection scheme from Zhang and McFarlane 30 , the moist turbulence scheme from Bretherton and Park 31 , the shallow convection scheme from Park and Bretherton 32 , the stratiform cloud microphysics scheme by Morrison and Gettelman 33 , the Rapid Radiative Transfer Method for GCMs (RRTMG) radiation scheme 34 , etc. Details of the experiment design can be found in section 4.2. All the experiments were integrated for 100 years, simulations during the last 80 years were analyzed. Scientific RepoRtS | (2020) 10:5610 | https://doi.

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.