Global Vegetation Dynamics

Principal Investigator:  Dr. Prince 

 

A key uncertainty in the Earth System is the response of the vegetation-climate system to seasonal and interannual climate variability.  In this project models have been developed and tested that are capable of reasonable predictions of actual, as opposed to equilibrial, land surface and atmospheric conditions.  In particular, major changes have been accomplished in the accuracy of the measurement of land surface biophysical variables.  Three models have been adapted, modified or created to make use of the new data sources, including two biogeochemical models of different types and a SVAT model.  Numerical experiments have been conducted to test the effects of seasonal and interannual variability in the land surface boundary conditions on the climate and its variability, also the feedback effects of climate variability on vegetation.  This research has prepared the way to study the nature, causes and implications of regional-to-global scale vegetation changes, emphasizing the responses to transient climate anomalies, in an integrated, observational and process-modeling program.

Further, the project is exploring the implications of the observed and modeled vegetation dynamics on climate using a spatial run of the SVAT model for Africa and, if time permits, a coupled general circulation model (GCM) run.  The existing results will be prepared for publication.  Special attention is being paid to several regions where the climate is most sensitive to the land surface forcing, including the impact of atmospheric circulation changes on southern central Africa (current focus of the SAFARI 2000 program).  The use of the observational satellite data record ensures that plausible scenarios for regional vegetation-climate changes are addressed and that they are geographically realistic.  We will continue to explore the dynamics of regional-global vegetation changes in response to climate changes using the 20-year archive of NOAA Advanced Very High Resolution Radiometer data and other archival data.