Climate Model Code Genealogy and its Relation to Climate Feedbacks and
Contemporary general circulation models (GCMs) and Earth system models
(ESMs) are developed by a large number of modeling groups globally. They
use a wide range of representations of physical processes, allowing for
structural (code) uncertainty to be partially quantified with
multi-model ensembles (MMEs). Many models in the MMEs of the Coupled
Model Intercomparison Project (CMIP) have a common development history
due to sharing of code and schemes. This makes their projections
statistically dependent and introduces biases in MME statistics.
Previous research has focused on model output and code dependence, and
model code genealogy of CMIP models has not been fully analyzed. We
present a full reconstruction of CMIP3, CMIP5 and CMIP6 code genealogy
of 167 atmospheric models, GCMs, and ESMs (of which 114 participated in
CMIP) based on the available literature, with a focus on the atmospheric
component and atmospheric physics. We identify 12 main model families.
We propose family and code weighting methods designed to reduce the
effect of model structural dependence in MMEs. We analyze weighted
effective climate sensitivity (ECS), climate feedbacks, forcing, and
global mean near-surface air temperature, and how they differ by model
family. Models in the same family often have similar climate properties.
We show that weighting can partially reconcile differences in ECS and
cloud feedbacks between CMIP5 and CMIP6. The results can help in
understanding structural dependence between CMIP models, and the
proposed code and family weighting methods can be used in MME
assessments to ameliorate model structural sampling biases.