What aspect of model performance is the most relevant to skillful future
projection on regional scale?
Abstract
Weighting models according to their performance has been used in
constructing multi-model regional climate change scenarios. But the
added value of model weighting is not always examined. Here we apply an
imperfect model framework to examine the added value of model weighting
in projecting summer temperature changes over China. Members of large
ensemble initial condition simulations by three climate models of
different climate sensitivities under the historical forcing and future
scenarios are used as pseudo-observations. Performance of the models
participating in the 6th phase of the coupled model
intercomparison project (CMIP6) in simulating past climate are evaluated
against the pseudo-observations based on climatology, trends in global,
regional and local temperatures. The performance along with model’s
independence are used to determine the model weights for future
projection. The weighted projections are then compared with the
pseudo-observations for the future. We find that regional trend as a
metric of model performance yields the best skill for future projection
while past climatology as performance metric does not improve future
projection. Trend at the grid-box scale is also not a good performance
indicator as small scale trend is highly uncertain. Projected summer
warming based on model weighting is similar to that of unweighted
projection, at 2.3°C increase relative to 1995-2014 by the middle of the
21st century under SSP8.5 scenario, but the
5th-95th uncertainty range of the
weighted projection is 18% smaller with the reduction mainly in the
upper bound, with the largest reduction in the northern Tibetan Plateau.