Memory Block Relocation in Cache-Only Memory Multiprocessors.

Abstract

Global estimation and monitoring of plant photosynthesis (known as Gross Primary Production--GPP) is a critical component of climate change research. Modeling of carbon cycling requires parameterization of the land surface, which, in a spatially continuous mode, is only possible using remote sensing. The increasing availability of high spectral resolution satellite observations with global coverage and high temporal frequency has allowed the scientific community to revisit a number of existing approaches for modeling GPP, and reassess the potential for using remotely sensed inputs. In this paper we examine the current status and future requirements of modeling global GPP thereby focusing on the light use efficiency approach which expresses GPP as product of the photosynthetically active radiation (PAR), the fraction of PAR being absorbed by the plant canopy (f(PAR)) and the efficiency epsilon with which this absorbed PAR can be converted into biomass. The capacity of remote sensing to provide the critical input variables for this approach is reviewed and key issues are identified and discussed for future research.