GSPC-WD catalogue This catalogue contains objects described in detail in Gaia Collaboration, Montegriffo et al., 2022, A&A, in press. The description of the catalogue from the paper is given below. We have made the GSPC-WD synthetic photometry available as a stand-alone catalogue27, including SDSS, JKC and JPLUS XPSP and the DA classification probability. The photometry of the individual J-PAS bands, used in the random forest analysis, is not included due to their low signal-to-noise. For WDs classified in SDSS, a subset of which were used in the training/validation of the random forest algorithim, we also include the full SDSS classifications as a separate column in the GSPC-WD catalogue table. When the synthetic spectral bands are very narrow a significant number of sources will have low signal-to-noise. Furthermore, at the edges of the Gaia spectral range, away from the peak of the effective area, this is also true for some stars in the wider bands included in the catalogue. In some extreme cases, there is no significant detection of the object. The random forest algorithm is only able to classify a WD when valid flux measurements are available for every photometric band we include in the analysis. Therefore, no classification is recorded in the catalogue when data for one or more bands is "missing". In total 15,003 WDs from the total sample of 101,783 are not classified. For completeness, we have made all the flux measurements and corresponding magnitudes available for all objects in the GSPC-WD. Hence magnitude/fluxes with very large errors, up to several times the flux itself, are included. However, where fluxes are negative, the magnitudes are not defined. When using the catalogue, appropriate signal-to-noise cuts are advisable for the specific work in-hand, to ensure data quality. Total number of objects = 101,786; Format 1 object per row, 73 columns of data as listed below. Column Description of contents 1 Gaia source_id 2 ra 3 ra_error 4 dec 5 dec_error 6 JohnsonStd_mag_U 7 JohnsonStd_mag_B 8 JohnsonStd_mag_V 9 JohnsonStd_mag_R 10 JohnsonStd_mag_I 11 JohnsonStd_flux_U 12 JohnsonStd_flux_B 13 JohnsonStd_flux_V 14 JohnsonStd_flux_R 15 JohnsonStd_flux_I 16 JohnsonStd_flux_error_U 17 JohnsonStd_flux_error_B 18 JohnsonStd_flux_error_V 19 JohnsonStd_flux_error_R 20 JohnsonStd_flux_error_I 21 SdssStd_mag_u 22 SdssStd_mag_g 23 SdssStd_mag_r 24 SdssStd_mag_i 25 SdssStd_mag_z 26 SdssStd_flux_u 27 SdssStd_flux_g 28 SdssStd_flux_r 29 SdssStd_flux_i 30 SdssStd_flux_z 31 SdssStd_flux_error_u 32 SdssStd_flux_error_g 33 SdssStd_flux_error_r 34 SdssStd_flux_error_i 35 SdssStd_flux_error_z 36 Jplus_mag_uJAVA 37 Jplus_mag_J0378 38 Jplus_mag_J0395 39 Jplus_mag_J0410 40 Jplus_mag_J0430 41 Jplus_mag_gJPLUS 42 Jplus_mag_J0515 43 Jplus_mag_rJPLUS 44 Jplus_mag_J0660 45 Jplus_mag_iJPLUS 46 Jplus_mag_J0861 47 Jplus_mag_zJPLUS 48 Jplus_flux_uJAVA 49 Jplus_flux_J0378 50 Jplus_flux_J0395 51 Jplus_flux_J0410 52 Jplus_flux_J0430 53 Jplus_flux_gJPLUS 54 Jplus_flux_J0515 55 Jplus_flux_rJPLUS 56 Jplus_flux_J0660 57 Jplus_flux_iJPLUS 58 Jplus_flux_J0861 59 Jplus_flux_zJPLUS 60 Jplus_flux_error_uJAVA 61 Jplus_flux_error_J0378 62 Jplus_flux_error_J0395 63 Jplus_flux_error_J0410 64 Jplus_flux_error_J0430 65 Jplus_flux_error_gJPLUS 66 Jplus_flux_error_J0515 67 Jplus_flux_error_rJPLUS 68 Jplus_flux_error_J0660 69 Jplus_flux_error_iJPLUS 70 Jplus_flux_error_J0861 71 Jplus_flux_error_zJPLUS 72 probability DA 73 SDSS WD type