Lagrangian Analysis of Tropical Cyclone Genesis Simulated by General Circulation Models Compared with Observations

Abstract

As a contribution to understanding the genesis of tropical cyclones (TCs), we compared TC genesis processes simulated by the Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0) and the Community Atmosphere Model version 5 (CAM5) with those from the ERA-Interim reanalysis (ERA-Interim, hereafter ERAI) and best track observations. In contrast to previous studies that estimated the TC genesis potential using the Eulerian mean environmental conditions, we calculated the probability of a pre-existing weak cyclonic embryo vortex (EV) developing into a TC by analyzing changes in the environmental conditions along the EV trajectories. Our analysis indicates that the spatial distribution and annual cycles of TCs obtained from the SAM0 and ERAI are similar to those obtained from the best track observation data. With the exception of the mesoscale convective organization and associated variables, most environmental variables along the trajectories of DEVs (EVs developing into TCs) showed monotonic variations. When EVs were born, environmental conditions of DEVs were significantly different from those of nondeveloping EVs, allowing for the prediction of TC genesis. In general, TC genesis probability increased as the environment became more cyclonic, moist, unstable, and with a weaker wind shear. Rapidly strengthening EVs were more likely to develop into TCs. SAM0 and ERAI have the same combination of environmental variables with the best prediction skill for TC genesis—absolute vorticity at 850 hPa, column saturation deficit, sea surface temperature, vertical shear of horizontal winds between 200 and 850 hPa, and latitude—with similar sensitivities to individual environmental variables, indicating that SAM0 well simulates the observed TC genesis processes.

Tropical Cyclone Activities in Warm Climate with Quadrupled CO2 Concentration Simulated by a New General Circulation Model

“…Several studies have noted that TC genesis is influenced by the saturation deficit in the mid‐troposphere (Camargo et al, 2014; Emanuel et al, 2008) and ω 500 (Sugi, Murakami, et al, 2012; Wang & Moon, 2017). Song et al (2020) showed that the above environmental variables analyzed in our study have significant impacts on TC genesis. Consistent with these studies, Δ GN appears to have spatial coherency with Δ ω 500 and Δ δ 600 .…”

“…The analysis with the environmental variable averaged over a larger 20.5 • lat × 20.5 • lon domain produced similar results (not shown). We note that the changes in the environmental conditions along individual TC tracks (i.e., our Lagrangian analysis shown in Figure 5 as Journal of Geophysical Research: Atmospheres 10.1029/2019JD032314 suggested by Song et al, 2020) could be caused by not only the changes in the environment variables at fixed locations but also the changes of the TC tracks. Both in cold and warm climates, individual TCs are strengthened as they pass through the regions of high SST, strong upward 500 , strong HMC 700 , more Q c , and high CAPE with weaker dependency on 600 , 850 , and V s .…”

“…As noted by Horn et al (2014), different detection methods can lead to different results in the analysis of GCM‐simulated TCs. The aforementioned TC detection method employed in our study is the one optimized for the SEM0‐UNICON simulations at the 0.5° horizontal resolution, such that the total number over the globe, spatial distribution, and annual cycle of TC genesis simulated by SEM0‐UNICON in the AMIP mode are similar to those from the observations (Song et al, 2020). The annual cycles of TC genesis in several regions where TCs are frequently generated are shown in Figure S1 of the supporting information.…”

“…Similar to other GCMs, our GCM has some limitations in simulating the observed TCs. For example, the horizontal grid resolution of SEM0 used in our study (0.475° latitude [lat] × 0.62° longitude [lon]) is not fine enough to simulate very strong TCs (Song et al, 2020). In addition, as noted by Park et al (2019), our model suffers from cold SST biases in the North Atlantic and portions of the western North Pacific and Indian Oceans, which may further weaken the strength of simulated TCs.…”

“…Park et al (2019) showed that the mean climate, El Niño‐Southern Oscillation (ENSO), and global warming simulated by SEM0 are similar to those obtained from CESM1. However, SEM0 substantially improves the simulations of the TCs (Song et al, 2020), Madden‐Julian oscillation (MJO) (Ahn et al, 2019; Yoo et al, 2015), diurnal cycle of precipitation (Park et al, 2019), and the impacts of ENSO and MJO on TC genesis (Shin et al, 2019; Shin & Park, 2020). Regarding the simulations of large‐scale environmental variables influencing TC activities (e.g., SST, vertical cross‐sections of grid‐mean vertical velocity, temperature, and moisture), SEM0‐UNICON has a similar or better performance than CESM1 in reproducing observations (Park et al, 2019).…”