TAM storm data

Compiled storm and storm cluster data from output of Titan Atmospheric Model simulation, as used/described in Olim et al. (https://doi.org/10.1016/j.icarus.2024.116290).

This record contains data in csv format in two files, one corresponding to individual storms and the other to storm clusters. In addition, a Python notebook is provided to read the csv files and generate the plots in the above paper.

Associated publication abstract:

Methane precipitation is a key component of the climate on Titan, and has been shown to impact surface features. Recent general circulation models (GCMs) have reproduced Titan’s hydroclimate, including precipitation, with increasing accuracy, yet characterization of their simulated precipitation events is lacking. We investigate the characteristics and evolution of methane storms simulated over 40 Titan years using the Titan Atmospheric Model, a validated GCM. Storms are identified and tracked using the density-based spatial clustering of applications with noise (DBSCAN) algorithm, allowing them to be followed through time and space. We find that storms follow seasonality expected from observations and prior modeling, occurring preferentially in the summer hemisphere, and tend to start over high topography. The population of storms is bimodal in traits corresponding to intensity, area, and duration, with a large population of small, short-lived, and weakly precipitating storms and a smaller population of exceptionally large, long-lasting, and intense storms. These largest storms tend to evolve similarly over their lifetimes, peaking early in intensity and in the middle of their lives in area. We also find temporal clustering of storms, in alignment with observations and the proposed relaxation-oscillation model of Titan’s methane precipitation. These storm clusters emerge quasi-periodically following long dry spells during which evaporation of surface methane recharges atmospheric methane. Approximately five clusters occur per Titan year, and their locations are strongly seasonal. Overall, our quantitative descriptions of storms and storm clusters over a long timescale provide additional insight into Titan’s methane cycle and surface features, and may assist in the planning of future missions such as Dragonfly.