Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM

Abstract

With general circulation models (GCMs) being increasingly used to explore extreme events over short temporal and small spatial scales, understanding how design choices in model configuration impact simulation results is critical. This research shows that the number of spontaneously generated tropical cyclones (TCs) in a version of the Community Atmosphere Model can be controlled by changing the coupling frequency between the dynamical core and physical parameterizations. More frequent coupling (i.e., shorter physics timesteps), even in the presence of an otherwise identical model, leads to large increases in TC activity. It is suggested that this arises due to competition within moist physics subroutines. Simulations with reduced physics timesteps preferentially eliminate instantaneous atmospheric instability via grid‐scale motions, even while producing mean climates similar to those with longer timesteps. These small‐scale variability increases lead to more tropical “seeds,” which are converted to full‐fledged TCs. This behavior is confirmed through a set of sensitivity experiments and highlights the caution needed in studying and generalizing phenomena that depend on both resolved and sub‐grid scales in GCMs and the need for targeting physics‐dynamics coupling as a model improvement strategy.

Global tropical cyclone precipitation scaling with sea surface temperature

“…The AMIP Historical inner-core precipitation magnitudes are larger than the observed values for the same SSTs. This has been demonstrated for TCs in CAM5 in at least one previous study 29 and could be related to the relationship between the model’s physics timestep and the partitioning between large-scale and parameterized precipitation in CAM5 51 , 52 . Moon et al 53 also found higher peak inner-core 6-hourly precipitation rates compared to observations in HighResMIP model simulations 54 with similar grid spacings as the AMIP simulations in this study.…”

Addressing Complexity in Global Aerosol Climate Model Cloud Microphysics

“…Another difference to the 2M CMP schemes is that the P3 scheme introduces sub‐time stepping to resolve the vertical advection of cloud ice and parallel splitting of the whole CMP scheme (Dietlicher et al., 2018). This means that the CMP processes act on the same state of variables, whereas the 2M scheme employs sequential splitting, where processes are ordered and use the state updated from the preceding processes (Williamson, 2002; Zarzycki, 2022).…”

“…It is important to note that we investigate the model as it is used. Many factors in the model setup probably influence this analysis, for example, the tuning state (see Table A1), the model time step (Barrett et al., 2019; Gettelman et al., 2013; Zarzycki, 2022; Zhu et al., 2021), the ordering of processes (Donahue & Caldwell, 2018), the resolution, of course the CMP scheme choice but also the other schemes in the model that interact with the CMP (Yang et al., 2022). Thus, the sensitivity analysis results are not transferable to another model (version).…”

Effects of the Horizontal Scales of the Cloud-Resolving Model on Tropical Cyclones in the Superparameterized Community Atmosphere Model

“…Villafuerte et al (2021) showed that different convective parameterizations could cause significant differences in TC numbers from 1.2 to 22.5 TCs per year. In addition to directly changing convective schemes, reducing physics timestep can cause more TC numbers through decreased CAPE removal by convective parameterization and compensated grid-scale vertical mass flux (Zarzycki 2022). Zhao et al (2012) show that the TC frequency is sensitive to model parameters such as cumulus lateral mixing rate and divergence damping.…”