MCMC parameter chains for FaIR v2 climate-model calibration (1850–2005) — data for "Do all Roads lead to Paris? Auditing Company-Level Paris-Alignment Assessments"

Monte Carlo (MCMC) parameter chains used to calibrate the parameter ensemble of the FaIR v2 simple climate model over the historical window 1850–2005. The file is a Python pickle holding the results dictionary of a DRAM (Delayed Rejection Adaptive Metropolis) run in the pymcmcstat format: 300,000 posterior samples of 20 parameters (r0, rc, rt, TCR, ECS, d1, d2, and forcing scaling factors F0–F12), together with prior bounds, proposal covariances and sampler settings. See the included README.md for the full key-by-key description and loading instructions. These chains are consumed by the replication code of the article "Do all Roads lead to Paris? Auditing Company-Level Paris-Alignment Assessments" (Pepe, Smith, Simon, 2026), available at https://github.com/emanuelePepeUAS/paris-alignment-audit-steel, to propagate parametric climate uncertainty. Chains generated by Hendrik Weichel and deposited with permission.