A Bayesian-inferred simple climate model.
Download a release. Read The Fine Manual.
Pathfinder has been developed in Python 3.7 and run preferentially through IPython. Currently, packages required to run it are numpy
(v1.19.2), scipy
(v1.5.2) and xarray
(v0.16.0), and it has hard-coded dependencies on pymc3
(v3.8) and theano
(v1.0.4) that are in fact used only for calibration. Newer versions of Python or these packages are likely to work, although they were not tested.
-
The model requires a high number of substeps to remain stable under high CO2 (because of the ocean carbon cycle). This can be set using the
nt
argument when callingrun_xarray
. -
The temperature-driven mode (
Tdriven
) is extremely sensitive to its forcings: it can be very difficult to make it transition smoothly from historical to projections. This is unavoidable because mathematically it requires the second derivative ofT
and the first derivative ofERFx
as input. -
Unclear whether the
my_AR1
class fromcls_calib
is actually needed.
Exact same physical equations and numerical values as v1.0.
- Added: best-guess parameters and outputs (in
internal_data/pyMC_calib/
) for single-configuration runs. - Improved: README and MANUAL files.
Exact model described by Bossy et al. (subm).
First release!
v1.0 (full) | Bossy, T., T. Gasser & P. Ciais. "Pathfinder v1.0: a Bayesian-inferred simple carbon-climate model to explore climate change scenarios." Geoscientific Model Development (submitted). doi:10.5194/egusphere-2022-802.