Applying Computationally Efficient Schemes for BioGeochemical Cycles
Collaborative Institutional Lead
SciDAC Institute Investigator
The ACES4BGC Project seeks to advance the predictive capabilities of Earth System Models (ESMs) by reducing two of the largest sources of uncertainty, aerosols and biospheric feedbacks, with a highly efficient computational approach. In particular, this project will implement and optimize new computationally efficient tracer advection algorithms for large numbers of tracer species; add important biogeochemical interactions between the atmosphere, land, and ocean models; and apply uncertainty quantification (UQ) techniques to constrain process parameters and evaluate uncertainties in feedbacks between biogeochemical cycles and the climate system. The resulting improvements to the Community Earth System Model (CESM) will deliver new scientific capabilities and significantly improve the representation of biogeochemical interactions at the canopy-to-atmosphere, rivers-to-coastal oceans, and open oceans-to-atmosphere interfaces. ACES4BGC partners modelers with decades of cumulative research experience and a team of computer and computational scientist building scalable solvers and tools, developing advanced UQ methods, and applying technologies for performance optimization through U.S. DOE SciDAC Institutes. The five year project began April 15, 2012.