One of the challenges in land surface modeling involves specifying accurately the initial state of the vegetation. Most efforts have focused upon using multi-year climatologies to specify the fractional coverage of vegetation. For example, the National Center for Environmental Prediction (NCEP) Eta model uses a five-year satellite climatology of monthly Normalized Difference Vegetation Index (NDVI) values to define the fractional vegetation coverage, or greenness, at 1/8 degree resolution. Yet vegetation characteristics change from year-to-year and are influenced by short-lived events such as fires, crop harvesting, droughts, floods, and hailstorms that are missed using a climatological database.

To explore the importance of the initial state vegetation characteristics to numerical weather forecasts, the response of the Eta model to satellite-derived fractional vegetation coverage information is examined. The vegetation fraction is derived from NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data composited during a two-week period surrounding the 12 cases of interest. These cases were chosen to span most of the 2001 growing season (April through August cases). This approach may allow for near real-time estimations of fractional vegetation coverage to be used routinely. Results indicate that the Eta model forecasts with the real-time vegetation fraction are significantly improved over those runs that use climatology.