  We present an analysis of six independent on-sky datasets taken with the
Keck-II/NIRC2 instrument. Using the off-axis point spread function (PSF)
reconstruction software AIROPA, we extract stellar astrometry, photometry, and
other fitting metrics in order to characterize the performance of this package.
We test the effectiveness of AIROPA to reconstruct the PSF across the field of
view in varying atmospheric conditions, number and location of PSF reference
stars, stellar crowding and telescope position angle (PA). We compare the
astrometric precision and fitting residuals between a static PSF model and a
spatially varying PSF model that incorporates instrumental aberrations and
atmospheric turbulence during exposures. Most of the fitting residuals we
measure show little to no improvement in the variable-PSF mode over the
single-PSF mode. For one of the data sets, we find photometric performance is
significantly improved (by ${\sim}10\times$) by measuring the trend seen in
photometry as a function of off-axis location. For nearly all other metrics we
find comparable astrometric and photometric precision across both PSF modes,
with a ${\sim}13$% smaller astrometric uncertainty in variable-PSF mode in the
best case. We largely confirm that the spatially variable PSF does not
significantly improve the astrometric and other PSF fitting residuals over the
static PSF for on-sky observations. We attribute this to unaccounted
instrumental aberrations that are not characterized through afternoon adaptive
optics (AO) bench calibrations.
