Code supporting: "Bayesian diagnosis of climate feedback evolution and forced temperature response"

This code supports the paper:
Calafat, F. M., & Cael, B. B. (2023). Bayesian diagnosis of climate feedback evolution and forced temperature response, Geophysical Research Letters, submitted.

Please cite this paper when using this code.

Overview:

The code implements a Bayesian energy balance model that extracts the forced temperature response and climate feedback evolution from historical time-series of radiative forcing, ocean heat content, and global mean surface temperature. Inference in the model is performed using Hamiltonian Monte Carlo as implemented by the Stan probabilistic programming language.