Emerging networks of Global Positioning System (GPS) receivers can be
used in the remote sensing of atmospheric water vapor. The time-varyin
g zenith wet delay observed at each GPS receiver in a network can be t
ransformed into an estimate of the precipitable water overlying that r
eceiver. This transformation is achieved by multiplying the zenith wet
delay by a factor whose magnitude is a function of certain constants
related to the refractivity of moist air and of the weighted mean temp
erature of the atmosphere. The mean temperature varies in space and ti
me and must be estimated a priori in order to transform an observed ze
nith wet delay into an estimate of precipitable water. We show that th
e relative error introduced during this transformation closely approxi
mates the relative error in the predicted mean temperature. Numerical
weather models can be used to predict the mean temperature with an rms
relative error of less than 1%.