Effects of warming and stratospheric aerosol injection on tropical cyclone distribution and frequency in a high-resolution global circulation model

Abstract

Tropical cyclones (TCs) occur stochastically in any given TC season, with varying numbers and intensities within basins over time. Nevertheless, they arise out of fundamental laws of thermodynamics and fluid physics, and in recent years, as global circulation models (GCMs) have increased in spatial resolution, increasingly realistic TCs and TC distributions have emerged from them. Where prior research on TC climatologies has relied on proxies like Potential Intensity (PI) and synthetic storm models, the cyclones emerging from the dynamics of newer GCMs can now be analyzed directly, using native model variables. Such direct analysis may be particularly useful in studying possible global storm distributions under radically altered future climates, including high-emissions warming scenarios, and even those shaped by climate interventions. These interventions include various directed changes in global albedo, such as Stratospheric Aerosol Injection (SAI), with only limited precedent in the historical period. GCMs simulating realistic climate intervention scenarios, have not as of yet paired storm-resolving resolution with realistic intervention scenario construction. This has left gaps in our understanding as to how interventions might affect global storm/TC distributions, and whether ameliorating warming in this way could also substantially lessen related natural disaster risk profiles. In this paper, we utilize a new high-resolution model configuration to conduct experiments examining the effects of SAI, on tropical cyclones and global storm physics more broadly. These experiments are constructed based on prior work on SAI using the GLENS GCM ensemble (Tilmes et al. 2020; Danabasoglu 2019a,b). Our analysis centers on 3 10-year experiments conducted using 30-km grid spacing. These include a recent-past calibration run; the Intergovernmental Panel on Climate Change climate pathway SSP 8.5 (IPCC 2021), for the years 2090-2099, with no SAI; and SSP 8.5, with SAI having begun in 2020 to maintain a global temperature rise of no more than 1.5° C, also simulated for the years 2090-2099. With the resulting data sets, we deploy a novel TC-tracking algorithm to analyze resulting changes in storm tracks and properties. Based on our results for these different scenarios, we find that SAI, while in some ways restoring global storm patterns to a pre-warming state, may also create unique basin-scale TC distribution features and pose novel related hazards.