With　the　development　of　Global　Navigation　Satellite　System　(GNSS),　the　detection　of　precipitable　water　vapor　(PWV)　using　the　GNSS　atmospheric　sounding　technique　becomes　a　research　interest　in　GNSS　meteorology.　In　the　conversion　of　zenith　tropospheric　delay　(ZTD)　to　PWV,　the　weighted　mean　temperature　(Tm)　plays　a　crucial　role.　Generally,　the　Tm　estimated　by　the　linear　regression　models　based　on　surface　temperature　(Ts)　cannot　meet　the　requirement　for　global　use,　and　the　accuracy　of　Tm　derived　from　the　empirical　models　is　limited.　In　this　study,　a　new　Tm　model,　named　GGTm-Ts　model,　was　developed　using　the　global　geodetic　observing　system　(GGOS)　atmosphere　Tm　data　and　European　Centre　for　Medium-Range　Weather　Forecasts　(ECMWF)　data　from　2011　to　2015.　Resting　upon　a　global　2.5　degrees*2　degrees　grid　of　coefficients　of　Tm-Ts　linear　function,　the　new　model　can　provide　Tm　at　any　site　in　two　modes,　one　for　the　case　with　measured　Ts　provided,　i.e.,　the　accurate　mode,　the　other　for　the　case　that　Ts　provided　by　a　subroutine,　i.e.,　the　normal　mode.　The　per-formance　of　GGTm-Ts　model　was　assessed　against　the　Bevis　formula,　GPT2w　and　GPT2wh　model　using　different　data　sources　in　2016　-the　GGOS　atmosphere　and　radiosonde　data.　The　results　show　that　the　GGTm-Ts　model　in　accurate　mode　achieves　best　performance　with　an　improvement　of　46.9　%/15.3　%,　37.8　%/19.5　%　and　34.4　%/14.2　%　over　other　three　models　in　the　GGOS　atmosphere/radiosonde　comparison.　For　the　normal　mode,　the　GGTm-Ts　model　outperforms　the　GPT2w　model　and　achieves　equivalence　results　with　the　GPT2wh　model.　Moreover,　the　impact　of　Tm　on　GNSS-PWV　was　analyzed　to　validate　the　performance　of　the　GGTm-Ts　model.　(c)　2022　COSPAR.　Published　by　Elsevier　B.V.　All　rights　reserved.