Regional climate simulations over Europe were initialized with soil moisture derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) in order to assess the model accuracy in predicting soil moisture and other components of the hydrological cycle. The AMSR-E soil moisture initially showed systematic differences with model-predicted soil moisture. For proper initialization the AMSR-E product had to be rescaled and after that vertically profiled. To retrieve a root zone soil moisture profile, we tested the application of an exponential filter. The smoothing through the layers of the ERA-Interim soil moisture profile was applied to the rescaled AMSR-E surface soil moisture. The filter performed very well for that part of the data set where the top layer is positively correlated with the deeper layers. After the preparation of the soil moisture fields, several sensitivity simulations were performed. The model's soil moisture was replaced with the vertically profiled AMSR-E soil moisture at different initial times for a dry summer (2003) and a wet summer (2005). In general, the surplus of soil moisture in the AMSR-E data resulted in a better performance in predicting temperature when compared with observations. This finding was more pronounced in the dry summer of 2003 when the model results appeared very sensitive to land-atmosphere feedbacks. Our results suggest that in dry years, the use of appropriate observed soil moisture may help more to reduce modeled surface temperatures than inducing additional rainfall in the model. Using the AMSR-E product led to a decrease in areal extent sensitive to land-atmosphere interactions. Copyright 2011 by the American Geophysical Union.