  Weak gravitational lensing surveys using photometric redshifts can have their
cosmological constraints severely degraded by errors in the photo-z scale. We
explore the cosmological degradation vs the size of the spectroscopic survey
required to calibrate the photo-z probability distribution. Previous work has
assumed a simple Gaussian distribution of photo-z errors; here we describe a
method for constraining an arbitrary parametric photo-z error model. As an
example we allow the photo-z probability distribution to be the sum of $N_g$
Gaussians. To limit cosmological degradation to a fixed level, photo-z models
with multiple Gaussians require up to 5 times larger calibration sample than
one would estimate from assuming a single-Gaussian model. This degradation
saturates at $N_g\approx 4$. Assuming a single Gaussian when the photo-z
distribution has multiple parameters underestimates cosmological parameter
uncertainties by up to 35%. The size of required calibration sample also
depends upon the shape of the fiducial distribution, even when the RMS photo-z
error is held fixed. The required calibration sample size varies up to a factor
of 40 among the fiducial models studied, but this is reduced to a factor of a
few if the photo-z parameters are forced to be slowly varying with redshift.
Finally we show that the size of the required calibration sample can be
substantially reduced by optimizing its redshift distribution. We hope this
study will help stimulate work on better understanding of photo-z errors.
