A Statistical Assessment of Southern Hemisphere Tropical Cyclone Tracks in Climate Models

Abstract

Reliable projections of future changes in tropical cyclone (TC) characteristics are highly dependent on the ability of global climate models (GCMs) to simulate the observed characteristics of TCs (i.e., their frequency, genesis locations, movement, and intensity). Here, we investigate the performance of a suite of GCMs from the U.S. CLIVAR Working Group on Hurricanes in simulating observed climatological features of TCs in the Southern Hemisphere. A subset of these GCMs is also explored under three idealized warming scenarios. Two types of simulated TC tracks are evaluated on the basis of a commonly applied cluster analysis: 1) explicitly simulated tracks, and 2) downscaled tracks, derived from a statistical–dynamical technique that depends on the models’ large-scale environmental fields. Climatological TC properties such as genesis locations, annual frequency, lifetime maximum intensity (LMI), and seasonality are evaluated for both track types. Future changes to annual frequency, LMI, and the latitude of LMI are evaluated using the downscaled tracks where large sample sizes allow for statistically robust results. An ensemble approach is used to assess future changes of explicit tracks owing to their small number of realizations. We show that the downscaled tracks generally outperform the explicit tracks in relation to many of the climatological features of Southern Hemisphere TCs, despite a few notable biases. Future changes to the frequency and intensity of TCs in the downscaled simulations are found to be highly dependent on the warming scenario and model, with the most robust result being an increase in the LMI under a uniform 2°C surface warming.

Global warming changes tropical cyclone translation speed

“…In the North Atlantic, Daloz et al 23 did not find any significant TC track changes in the future. Ramsay et al 24 did not find a consistent poleward shift in the Southern Hemisphere TC tracks across multiple models, either. These previous studies could potentially lead to a different conclusion on the future change in the TC translation speed from this study.…”

Projected changes in ENSO-driven regional tropical cyclone tracks

“…However, analysing TC tracks in climate models requires a slightly different approach because models often detect TCs in regions where they do not occur in reality. This leads to the use of additional clusters in some regions (e.g., Ramsay et al 2018). Furthermore, fundamental differences between the observed and model-detected tracks (such as different track shapes and lifetimes) make it better practice to cluster all tracks together in one large set.…”

“…In this section, we first examine the ability of CMIP5 models to realistically simulate the ENSO-TC relationship for the entire Southern Hemisphere basin and then evaluate likely changes in TC track distributions under the RCP 8.5 projection for El Niño and La Niña events. Following Ramsay et al (2018), TC tracks in the Southern Hemisphere are represented here by eight clusters labelled S1 to S8: the first three clusters (i.e., clusters S1-S3) are in the South Indian Ocean, clusters S4-S6 are in the Australian region and clusters S7 and S8 are in the South Pacific Ocean (Fig. 4i).…”

Detecting Interdecadal Change in Western North Pacific Tropical Cyclone Genesis Based on Cluster Analysis Using pHash + Kmeans

“…Some recent studies have attempted to understand TC activity in detail with the help of cluster analysis (e.g., Choi an Kim, 2009;Kim et al, 2011;Daloz et al, 2015;Kim and Seo, 2016;Boudreault et al, 2017;Ramsay et al, 2012Ramsay et al, , 2018. Clustering algorithms were applied to group TC cases into several classes based on their tracks.…”