Postdoc: Parallel Implementation of Modeling & Analyis of the Terrestrial Ecosystems' Response to the Changing Global Climate

本项目涉及三个方面。一是在全球尺度上研究全球气候变化对陆地生态系统的影响；其次，它将采用连接SP2平台的新型IBM高性能存储系统（HPCC），利用并行机制处理来自植被遥感的海量数据集；和第三;它将为生态系统建模设计并行算法。这三个方面将综合起来解决以下科学问题。至少自20世纪70年代中期以来，CO2浓度的季节性振幅一直在增加，这表明通过光合作用吸收CO2和通过呼吸作用释放CO2增加。此外，季节曲线的低谷在季节中出现得更早，二氧化碳的减少发生得更快。假设这些现象是由温度变暖和降水模式变化引起的，特别是自20世纪70年代中期以来，pi建议利用通过遥感技术和地面记录获得的大量数据集研究气候变量、陆地生态系统和大气CO2浓度之间的相互作用。

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.