Weak lensing peak abundance analyses have been applied in different surveys and demonstrated to be a powerful statistics in extracting cosmological information complementary to cosmic shear two-point correlation studies. Future large surveys with high number densities of galaxies enable tomographic peak analyses. Focusing on high peaks, we investigate quantitatively how the tomographic redshift binning can enhance the cosmological gains. We also perform detailed studies about the degradation of cosmological information due to photometric redshift (photo-z) errors. We show that for surveys with the number density of galaxies $sim40,{rm arcmin^{-2}}$, the median redshift $sim1$, and the survey area of $sim15000,{rm deg^{2}}$, the 4-bin tomographic peak analyses can reduce the error contours of $(Omega_{{rm m}},sigma_{8})$ by a factor of $5$ comparing to 2-D peak analyses in the ideal case of photo-z error being absent. More redshift bins can hardly lead to significantly better constraints. The photo-z error model here is parametrized by $z_{{rm bias}}$ and $sigma_{{rm ph}}$ and the fiducial values of $z_{{rm bias}}=0.003$ and $sigma_{{rm ph}}=0.02$ is taken. We find that using tomographic peak analyses can constrain the photo-z errors simultaneously with cosmological parameters. For 4-bin analyses, we can obtain $sigma(z_{{rm bias}})/z_{{rm bias}}sim10%$ and $sigma(sigma_{{rm ph}})/sigma_{{rm ph}}sim5%$ without assuming priors on them. Accordingly, the cosmological constraints on $Omega_{{rm m}}$ and $sigma_{8}$ degrade by a factor of $sim2.2$ and $sim1.8$, respectively, with respect to zero uncertainties on photo-z parameters. We find that the uncertainty of $z_{{rm bias}}$ plays more significant roles in degrading the cosmological constraints than that of $sigma_{{rm ph}}$.
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