We assess similarities and differences between model effects for the North American Regional
Climate Change Assessment Program (NARCCAP) climate models using
varying classes of linear regression models. Specifically, we
consider how the average temperature effect differs for the various
global and regional climate model combinations, including assessment
of possible interaction between the effects of global and regional
climate models. We use both pointwise and simultaneous inference
procedures to identify regions where global and regional climate model effects differ. We also show
conclusively that results from pointwise inference are misleading, and
that accounting for multiple comparisons is important for making
proper inference
