1.In assessing sensitivity of D&A
results to Òmodel qualityÓ
2.By contributing state-of-the-art space-time modeling approaches to
Òfill in the gapsÓ in observational datasets with sparse, space- and
time-varying coverage
3.By helping to provide a better assessment of the Òtrade-offsÓ between
ensemble size (for any individual model) and the number of models contributing
to a multi-model average
4.By contributing improved methods for assessing whether human influences
have modulated the statistical behavior of existing modes of natural
variability
5.By bringing statistical rigor to regression-based predictions of
hurricane activity
6.Better constraining the Transient Climate Response obtained from
D&A methods