Seasonal variability of vegetation, determined by plant phenology, impacts the seasonality of surface and atmospheric water cycles as well as the seasonality of surface energy budget. At the same time, leaf seasonal variations respond to both cumulative and concurrent hydrometeorological conditions. In order to account for this vegetation feedback at the seasonal timescale, a predictive phenology scheme for various plant functional types is developed on the basis of previous studies, and a methodology for crop simulations is proposed and implanted to supplement this phenology scheme. The phenology scheme is then incorporated into the Community Land Model (CLM). The geographic focus of this study is on the United States where the need for seasonal prediction is urgent and vegetation seasonal characteristics have been shown to significantly influence summer precipitation and temperature. Comparison of the model simulation with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index data indicates that our model reproduces the observed vegetation seasonality reasonably well. Subsequent experiments demonstrate the interannual variability of vegetation phenology and its impact on surface water and energy budgets using the 1988 drought and 1993 flood in the U.S. Midwest as examples.