Ensembles of climate model parameters of Mars and significance values

Data set containing an ensemble of model parameters for each of the candidate climate models in Table 1 of Izquierdo et al., (2023). These ensembles are stored as Python objects using the Pickle module. Files for each candidate model are named based on the accumulation and lag sub models and the number of steps used in the Markov chain Monte Carlo algorithm. From each Python object, it can be extracted the distribution of accumulation and retreat rates with time following the scripts and notebooks of the repository referenced in the open research section of the paper. The folders in this repository refer to the ensembles of all candidate models dependent of insolation values (insolation), ensembles of all candidate models dependent on obliquity values (obliquity), and the mean likelihood and Bayes factor of each candidate model (bayesFactor).