Considerable attention in the past decade has focused on the importance of land memory, its influence on climate predictability and prediction, and the ability of our prediction systems to faithfully reproduce these aspects of the climate system. For the first time, two complementary sets of multi-model, global-scale simulations have been executed that can provide simulated land states and fluxes for a contemporaneous comparison and evaluation of many land models under prescribed and interactive atmospheric forcing. Under the Global Soil Wetness Project Phase 2 (GSWP 2), global land model simulations, spanning the years 1986-1995, have been performed in “standalone mode” with prescribed atmospheric conditions. In addition, the Atmospheric Model Intercomparison Project Phase 2 (AMIP 2) has resulted in a suite of coupled land-atmosphere general circulation model simulations, spanning the years 1979-1995, using globally prescribed sea-surface temperatures. In this study, we use the simulated land-model outputs from GSWP 2 and AMIP 2 for the years 1986-1995 to: characterize the degree of simulated land memory in uncoupled and coupled frameworks; evaluate the consistency of simulated land memory among the models; and assess the veracity of the simulated land memories. The diagnosis will employ autocorrelation metrics to establish the degree of memory in continental water storage (i.e. soil moisture and snow) among the land models under the standalone (GSWP 2) and coupled (AMIP 2) frameworks. A linear memory analysis is then applied the model simulations to assess the sources of disparity (i.e. controls) of continental water-storage memory between the various land models and their simulation frameworks (i.e. standalone and uncoupled). In addition, complementary observations of continental water storages and fluxes will be utilized in order to evaluate the simulated land-memory and its controls.