Output climate model parameters reported in Izquierdo et al., (2022)

Data set containing an ensemble of model parameters for each of the candidate climate models in Table 1 of Izquierdo et al., (2022). These ensembles are stored as Python objects using the Pickle module, identified by the accumulation and lag sub models they contain 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, ensembles of best fit models (files that are not within a folder) and ensembles of best fit models with the addition of an age prior of 2 My.