Tuesday, 15 January 2002
Assessment of implementing satellite-derived land cover data in the Eta model
One of the challenges in land surface modeling involves specifying accurately the initial state of the land surface. 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 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.
These data are valid on the 15th of every month and are interpolated temporally for daily runs. Yet vegetation characteristics change from year-to-year and are influenced by short-lived events such as fires, crop harvesting, and hailstorms that will be missed using a climatological data
To explore the importance of the initial state vegetation characteristics to numerical weather forecasts, we examine how the Eta model responds to a different method of initializing fractional vegetation coverage. Studies have shown that several vegetation metrics can be estimated from bi-weekly, 1-km resolution NDVI maximum-value composites derived from NOAA's Advanced Very High Resolution Radiometer (AVHRR). This approach may allow for near real-time estimations of fractional vegetation coverage to be used. Several numerical forecasts of the Eta model, using both climatological and near real-time values of fractional vegetation coverage, are compared to examine the potential importance of variations in vegetation to forecasts of 2 m temperatures and surface fluxes.