Ng, Chin Ho J., and Gabriel A Vecchi, May 2020: Large-scale environmental controls on the seasonal statistics of rapidly intensifying North Atlantic tropical cyclones. Climate Dynamics, 54(9-10), DOI:10.1007/s00382-020-05207-4. Abstract
This study is concerned with the connections between the large-scale environment and the seasonal occurrence of rapid intensification (RI) of North Atlantic tropical cyclones. Physically-motivated statistical analysis using observations and reanalysis products suggests that for tropical cyclones over the open tropical North Atlantic, the interannual variability of the probability of storms undergoing RI is influenced by seasonal large-scale atmospheric and oceanic variables, but not so for storms over the Gulf of Mexico and western Caribbean Sea. We suggest that this differentiated response is due to the former region exhibiting a strong negative correlation between the seasonal anomalies of vertical wind shear and potential intensity. Differences in the mean climatology and subseasonal variations of the large-scale environment in these regions appear to play an insignificant role in the distinctive seasonal environmental controls on RI. We suggest that the interannual correlation of vertical wind shear and potential intensity is an indicator of seasonal predictability of tropical cyclone activity (including RI) across the tropics .
This study explores the impact of El Niño and La Niña events on precipitation and circulation in East Asia. The results are based on statistical analysis of various observational datasets and Geophysical Fluid Dynamics Laboratory’s (GFDL’s) global climate model experiments. Multiple observational datasets and certain models show that in the southeastern coast of China, precipitation exhibits a nonlinear response to Central Pacific sea surface temperature anomalies during boreal deep fall/early winter. Higher mean rainfall is observed during both El Niño and La Niña events compared to the ENSO-Neutral phase, by an amount of approximately 0.4–0.5 mm/day on average per oC change. We argue that, in October to December, while the precipitation increases during El Niño are the result of anomalous onshore moisture fluxes, those during La Niña are driven by the persistence of terrestrial moisture anomalies resulting from earlier excess rainfall in this region. This is consistent with the nonlinear extreme rainfall behavior in coastal southeastern China, which increases during both ENSO phases and becomes more severe during El Niño than La Niña events.
Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
