  Large sets of objects with spectroscopic redshift measurements will be needed
for imaging dark energy experiments to achieve their full potential, serving
two goals:_training_, i.e., the use of objects with known redshift to develop
and optimize photometric redshift algorithms; and_calibration_, i.e., the
characterization of moments of redshift (or photo-z error) distributions.
Better training makes cosmological constraints from a given experiment
stronger, while highly-accurate calibration is needed for photo-z systematics
not to dominate errors. In this white paper, we investigate the required scope
of spectroscopic datasets which can serve both these purposes for ongoing and
next-generation dark energy experiments, as well as the time required to obtain
such data with instruments available in the next decade. Large time allocations
on kilo-object spectrographs will be necessary, ideally augmented by infrared
spectroscopy from space. Alternatively, precision calibrations could be
obtained by measuring cross-correlation statistics using samples of bright
objects from a large baryon acoustic oscillation experiment such as DESI. We
also summarize the additional work on photometric redshift methods needed to
prepare for ongoing and future dark energy experiments.
