This project involves three aspects. First, it will attempt to investigate the impacts of the changing global climate on terrestrial ecosystems at global scale; second, it will tackle the handling of massive data sets from remote sensing of vegetation using parallel mechanisms employing the new IBM High Performance Storage System (HPCC) connecting the SP2 platform; and third; it will design parallel algorithms for ecosystems modeling. All three aspects will be integrated to address the following scientific questions. The seasonal amplitude of CO2 concentration has been increasing since at least the mid 1970's, suggesting an increase in CO2 absorption through photosynthesis and CO2 release through respiration. In addition, the trough of the seasonal curve has been occurring earlier in the season, with the CO2 draw down occurring faster. Assuming these phenomena are caused by the warming temperature and changing patterns in precipitation especially since mid-1970's, the PIs propose to study the interaction among climatic variables, terrestrial ecosystems, and atmospheric CO2 concentrations employing the massive datasets available through remote sensing technology and ground records.
