  Through likelihood analyses of both current and future data that constrain
both the expansion history of the universe and the clustering of matter
fluctuations, we provide falsifiable predictions for three broad classes of
models that explain the accelerated expansions of the universe: $\Lambda$CDM,
the quintessence scenario and a more general class of smooth dark energy models
that can cross the phantom barrier $w(z)=-1$. Our predictions are model
independent in the sense that we do not rely on a specific parametrization, but
we instead use a principal component (PC) basis function constructed a priori
from a noise model of supernovae and Cosmic Microwave Background observations.
For the supernovae measurements, we consider two type of surveys: the current
JLA and the upcoming WFIRST surveys. We show that WFIRST will be able to
improve growth predictions in curved models significantly. The remaining
degeneracy between spatial curvature and $w(z)$ could be overcome with improved
measurements of $\sigma_8 \Omega_m^{1/2}$, a combination that controls the
amplitude of the growth of structure. We also point out that a PC-based Figure
of Merit reveals that the usual two-parameter description of $w(z)$ does not
exhaust the information that can be extracted from current data (JLA) or future
data (WFIRST).
