Total precipitable water is an important parameter in the understanding of the water cycle and for climate analysis. Therefore, reliable estimates of this parameter are of importance. This study aims to analyze and compare spatio-temporal patterns and signals of total precipitable water from various datasets. The datasets being used are the National Aeronautics and Space Administration Water Vapor Project (NVAP), the National Centers for Environmental Prediction (NCEP) Reanalysis, the NCEP/Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP) II Reanalysis (Reanalysis 2), and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis. These datasets are regridded into 2.5ox2.5o grids. Using the monthly anomalies, Empirical Orthogonal Functions (EOF) analysis of the datasets reveals almost similar spatio-temporal patterns and signals of the parameter of interest. In general, the cold- and warm-phase of the El Niņo Southern Osscilation (ENSO) stand out to be the dominant spatial patterns. However, there are spatial and temporal discrepancies in the details of the EOFs particularly in temporal signals of the principal components (PCs). Although the PCs captured the major ENSO events signals, the strengths of the events represented by the timeseries of the PCs are different. This finding signals that caution should be used in using precipitable water and its total from the datasets especially if one were to perform long-term water cycle and climate analysis. Further work will try to decompose and analyze temporal signals of total precipitable water over specified regions of interest from the datasets. In addition, a satellite-derived observational dataset may also be used.