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 generate...
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| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2022-03-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2021MS002791 |
| _version_ | 1797838443740397568 |
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| author | Colin M. Zarzycki |
| author_facet | Colin M. Zarzycki |
| author_sort | Colin M. Zarzycki |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T15:42:03Z |
| format | Article |
| id | doaj.art-721aac538c384fb28b4f6d8903198f2b |
| institution | Directory Open Access Journal |
| issn | 1942-2466 |
| language | English |
| last_indexed | 2024-04-09T15:42:03Z |
| publishDate | 2022-03-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj.art-721aac538c384fb28b4f6d8903198f2b2023-04-27T07:53:09ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662022-03-01143n/an/a10.1029/2021MS002791Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCMColin M. Zarzycki0Pennsylvania State University University Park PA USAAbstract 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.https://doi.org/10.1029/2021MS002791climate modelnumerical methodstropical cyclonesparameterizationsconvectiontimestep |
| spellingShingle | Colin M. Zarzycki Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM Journal of Advances in Modeling Earth Systems climate model numerical methods tropical cyclones parameterizations convection timestep |
| title | Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM |
| title_full | Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM |
| title_fullStr | Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM |
| title_full_unstemmed | Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM |
| title_short | Sowing Storms: How Model Timestep Can Control Tropical Cyclone Frequency in a GCM |
| title_sort | sowing storms how model timestep can control tropical cyclone frequency in a gcm |
| topic | climate model numerical methods tropical cyclones parameterizations convection timestep |
| url | https://doi.org/10.1029/2021MS002791 |
| work_keys_str_mv | AT colinmzarzycki sowingstormshowmodeltimestepcancontroltropicalcyclonefrequencyinagcm |