Effects of tropical sea surface temperature variability on Northern Hemisphere tropical cyclone genesis

This study quantifies the contributions of tropical sea surface temperature (SST) variations during the boreal warm season to the interannual-to-decadal variability in tropical cyclone genesis frequency (TCGF) over the Northern Hemisphere ocean basins. The first seven leading modes of tropical SST variability are found to affect basin-wide TCGF in one or more basins, and are related to canonical El Niño–Southern Oscillation (ENSO), global warming (GW), the Pacific Meridional Mode (PMM), Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Mode (AMM). These modes account for approximately 58%, 50% and 56% of the variance in basin-wide TCGF during 1969–2018 over the North Atlantic (NA), Northeast Pacific (NEP) and Northwest Pacific (NWP), respectively. The SST effect is weak on TCGF variability in the North Indian Ocean. The dominant SST modes differ among the basins: ENSO, the AMO, AMM and GW for the NA; ENSO and the AMO for the NEP; and the PMM, interannual AMO and GW for the NWP. A specific mode may have opposite effects on TCGF in different basins, particularly between the NA and NEP. Sliding-window multiple linear regression analyses show that the SST effects on basin-wide TCGF are stable in time in the NA and NWP, but strengthen after the mid-1970s in the NEP. The SST effects on local TC genesis and occurrence frequency are also explored, and the underlying physical mechanisms are examined by diagnosing a genesis potential index and its components.

Explicit versus Parameterized Convection in Response to the Atlantic Meridional Mode

This study investigates whether the representation of explicit and parameterized convection influences the response to the Atlantic meridional mode (AMM). The main focus is on the precipitation response to the AMM-SST pattern, but possible implications for the atmospheric feedback on SST are also examined by considering differences in the circulation response between explicit and parameterized convection. On the basis of analysis from observations, SST composites are built to represent the positive and negative AMM. These SST patterns, in addition to the March–May climatology, are prescribed to the atmospheric ICON model. High-resolution simulations with explicit convection (E-CON) and coarse-resolution simulations with parameterized convection (P-CON) are used over a nested tropical Atlantic Ocean domain and a global domain, respectively. Our results show that a meridional shift of about 1° in the precipitation climatology explains most of the response to the AMM-SST pattern in simulations both with explicit convection and with parameterized convection. Our results also indicate a linearity in the precipitation response to the positive and negative AMM in E-CON, in contrast to P-CON. Further analysis of the atmospheric response to the AMM reveals that anomalies in the wind-driven enthalpy fluxes are generally stronger in E-CON than in P-CON. This result suggests that SST anomalies would be amplified more strongly in coupled simulations using an explicit representation of convection.

Influence of Pacific Meridional Mode on ENSO evolution and predictability: Asymmetric modulation and ocean preconditioning

This study investigates the mechanisms behind the Pacific Meridional Mode (PMM) in influencing the development of El Niño-Southern Oscillation (ENSO) event and its seasonal predictability. To examine the relative importance of various factors that may modulate the efficiency of the PMM influence, a series of experiments are conducted for selected ENSO events with different intensity using the Community Earth System Model, in which ensemble predictions are made from slightly different ocean initial states but under a common prescribed PMM surface heat flux forcing. Overall, the matched PMM forcing to ENSO, i.e., a positive (negative) PMM prior to an El Niño (a La Niña), plays an enhancing role, while a mismatched PMM forcing plays a damping role. For the matched cases, a positive PMM event enhances an El Niño more strongly than a negative PMM event enhances a La Niña. This asymmetry in influencing ENSO largely originates from the asymmetry in intensity between the positive and negative PMM events in the tropics, which can be explained by the nonlinearity in the growth and equatorward propagation of the PMM-related anomalies of sea surface temperature (SST) and surface zonal wind through both wind-evaporation-SST feedback and summer deep convection response. Our model results also indicate that the PMM acts as a modulator rather than a trigger for the occurrence of ENSO event. Furthermore, the response of ENSO to an imposed PMM forcing is modulated by the preconditioning of the upper-ocean heat content, which provides the memory for the coupled low-frequency evolution in the tropical Pacific.

Atmospheric Subseasonal Variability and Circulation Regimes: Spectra, Trends, and Uncertainties

The globally integrated subseasonal variability associated with the two main atmospheric circulation regimes, the balanced (or Rossby) and unbalanced (or inertia–gravity) regimes, is evaluated for the four reanalysis datasets: ERA-Interim, JRA-55, MERRA, and ERA5. The results quantify amplitudes and trends in midlatitude traveling and quasi-stationary Rossby wave patterns as well as in the equatorial wave activity across scales. A statistically significant reduction of subseasonal variability is found in Rossby waves with zonal wavenumber k = 6 along with an increase in variability in wavenumbers k = 3–5 in the summer seasons of both hemispheres. The four reanalyses also agree regarding increased variability in the large-scale Kelvin waves, mixed Rossby–gravity waves, and westward-propagating inertio-gravity waves with the lowest meridional mode. The amplitude and sign of trends in inertia–gravity modes with smaller zonal scales and greater meridional modes differ between the ERA-Interim and JRA-55 datasets on the one hand and the ERA5 and MERRA data on the other. An increased variability in the ERA-Interim and JRA-55 accounts for positive trends in their total subseasonal variability.