Upper tropospheric water vapor plays a key role in regulating the flow of radiation through clear skies and the formation and dissipation of clouds. Unfortunately, due to the difficulty of accurately measuring this quantity, it remains a key uncertainty in model predictions of climate change. Much of the uncertainty surrounding upper tropospheric water vapor reflects an incomplete understanding of the processes which regulate its distribution and variations. This, in turn, reflects the lack of suitable observations to adequately quantify the relevant physical processes. The U.S. Dept. of Energy / Atmospheric Radiation Measurement (ARM) program recently conducted several state-of-the-art field campaigns for measuring water vapor profiles using a variety of surface and airborne instruments including: Vaisala and VIZ radiosondes, chilled-mirror sondes, Raman and DIAL lidars, microwave radiometers, and airborne interferometers. This presentation will use co-located satellite measurements of upper tropospheric water vapor at 6.7 micron from GOES as a common benchmark to intercompare these measurements. From these intercomparisons we will assess our current ability to monitor variations in upper tropospheric moisture. One difficulty in conducting this comparing is that the satellite and field instruments measure fundamentally different quantities. The satellites measures the radiance near 6.7 micron which is sensitive to moisture integrated over a broad layer of the upper troposphere (roughly 200-500 hPa), whereas the field instruments provide moisture profiles with much higher vertical resolution. Therefore, to compare the water vapor profiles with the satellite observed radiances we follow a "forward modeling" approach in which moisture (and coincident temperature) profiles are inserted into a radiative transfer model to calculate the radiance observed by the satellite under those conditions. The profile-computed radiances can then be directly compared with that observed from the satellite. To facilitate the interpretation of this comparison, both the observed and profile-simulated radiance are then consistently transformed into a layer-mean Upper Tropospheric relative Humidity (UTH) following Soden and Bretherton (1993). This methodology has the advantage of providing both an accurate comparison (via the forward modeling) as well as a easily interpreted measure of upper tropospheric water vapor (i.e, UTH) for interpreting the results. The results demonstrate how the satellite data are effective in linking together disparate field measurements to provide a common and unified benchmark for intercomparing and evaluating water vapor measurements taken at various times and locations. This intercomparison method, combined with the wide array of instruments supported by ARM, provides the most comprehensive assessment to date of our ability to monitor variations in upper tropospheric water vapor.