Water-vapor-weighted atmospheric mean temperature, Tm, is a key parameter in the retrieval of atmospheric precipitable water (PW) from ground-based Global Positioning System (GPS) measurements of zenith path delay (ZPD), as the accuracy of the GPS-derived PW is proportional to the accuracy of Tm. We compare and analyze global estimates of Tm from three different data sets from 1997 to 2002: the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year reanalysis (ERA-40), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, and the newly released Integrated Global Radiosonde Archive (IGRA) data set. Temperature and humidity profiles from both the ERA-40 and NCEP/NCAR reanalyses produce reasonable Tm estimates compared with those from the IGRA soundings. The ERA-40, however, is a better option for global Tm estimation because of its better performance and its higher spatial resolution. Tm is found to increase from below 255 K in polar regions to 295–300 K in the tropics, with small longitudinal variations. Tm has an annual range of ∼2–4 K in the tropics and 20–35 K over much of Eurasia and northern North America. The day-to-day Tm variations are 1–3 K over most low latitudes and 4–7 K (2–4 K) in winter (summer) Northern Hemispheric land areas. Diurnal variations of Tm are generally small, with mean-to-peak amplitudes less than 0.5 K over most oceans and 0.5–1.5 K over most land areas and a local time of maximum around 16–20 LST. The commonly used Tm-Ts relationship from Bevis et al. (1992) is evaluated using the ERA-40 data. Tm derived from this relationship (referred to as Tmb) has a cold bias in the tropics and subtropics (−1 ∼ −6 K, largest in marine stratiform cloud regions) and a warm bias in the middle and high latitudes (2–5 K, largest over mountain regions). The random error in Tmb is much smaller than the bias. A serious problem in Tmb is its erroneous large diurnal cycle owing to diurnally invariant Tm-Ts relationship and large Ts diurnal variations, which could result in a spurious diurnal cycle in GPS-derived PW and cause 1–2% day-night biases in GPS-based PW.