In the Global Soil Wetness Project Phase 2 (GSWP 2), global land model simulations spanning the years 1986-1995 have been performed in “standalone mode” (i.e. prescribed atmospheric conditions) with an array of land models from the participating international community. The resulting collection of land model simulations represents, to date, one of the most extensive sets of continental storage and flux estimates provided by an international modeling consortium. In this study, the multi-model estimates of the vertical water and energy fluxes and continental storages from GSWP 2 are utilized for a global water and energy cycle synthesis and analysis. In addition to the GSWP 2 data, monthly estimates from the Global Precipitation Climatology Project (GPCP), retrieval estimates of ocean evaporation from Special Scanning Microwave Imager (SSM/I) data, global total precipitable water from the NASA Water Vapor Project (NVAP), model estimates of continental storage and fluxes from the Global Land Data Assimilation (GLDAS) framework, as well as global energy/radiation data sets from the Surface Radiation Budget (SRB) and the International Satellite Cloud Climatology Project (constructed at the Goddard Institute for Space Studies) are also used. The analysis will assess the extent to which the assembly of these disparate observations/estimates of fluxes and storages according to the global water and energy conceptualizations depict consistent and balanced budgets. The diagnosis will place particular emphasis on the “consensus” of the GSWP 2 outputs in their ability to provide a confident and consistent assessment of the role of continental processes in the global water and energy cycles. Based on this assessment, the diagnosis will further characterize the relative contributions of the ocean and land on the global water and energy cycle rates, quantify the mean and interannual variability of the global-scale fluxes (i.e. the “rate” of the global water/energy cycles), and where possible, highlight the requirements as to the accuracy, sampling and resolution features for future in-situ and/or satellite observations.