Preprints
https://doi.org/10.5194/egusphere-2024-3526
https://doi.org/10.5194/egusphere-2024-3526
19 Nov 2024
 | 19 Nov 2024
Status: this preprint is open for discussion.

Effects of Warming and Stratospheric Aerosol Injection on Tropical Cyclone Distribution and Frequency in a High-Resolution Global Circulation Model

Andrew Feder, David Randall, and Donald Dazlich

Abstract. In recent years, as global circulation models (GCMs) have increased in spatial resolution, increasingly realistic tropical cyclones (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.

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. 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 (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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Andrew Feder, David Randall, and Donald Dazlich

Status: open (until 15 Jan 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Andrew Feder, David Randall, and Donald Dazlich

Interactive computing environment

Code and Sample Data for PHAST Algorithm Andrew Feder https://github.com/afeder17/PHAST

Andrew Feder, David Randall, and Donald Dazlich

Viewed

Total article views: 142 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
103 34 5 142 2 1
  • HTML: 103
  • PDF: 34
  • XML: 5
  • Total: 142
  • BibTeX: 2
  • EndNote: 1
Views and downloads (calculated since 19 Nov 2024)
Cumulative views and downloads (calculated since 19 Nov 2024)

Viewed (geographical distribution)

Total article views: 141 (including HTML, PDF, and XML) Thereof 141 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
Short summary
We studied the effect of solar geoengineering on the intensity and distribution of tropical cyclones in global climate models, as compared to a historical baseline and a comparable, non-engineered warming scenario. We find that, while the given geoengineering approach does not completely bring cyclones back to their typical historical behavior, it restores important elements of cyclone behavior to baseline with some important regional deviations.