U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Modeling with Multiple Models Made Easy
Published: August 10, 2018
Posted: April 23, 2019

New code allows scientists to generate and analyze multiple models that vary in how processes are represented.

The Science 
Researchers developed a new modeling software package that allows many alternative models to be posed, run, and analyzed as an ensemble, saving scientists time and providing a path to decrease uncertainty in modeling analyses.

The Impact
There are many ways to represent real-world processes in computer models. But it is common that only a single representation is used in any given model, leading to results that are model specific. This new code now allows the modeling community to move away from the single-representation method to using many alternative models in a single study for a richer analysis that more broadly encompasses our current state of knowledge about ecosystem processes.

Summary
Alternative ways that real-world processes can be represented in computer models is a huge source of uncertainty in model output. Yet tools and modelling systems to examine these alternatives are not available. Researchers at Oak Ridge National Laboratory and a team of national and international collaborators have developed software that can combine alternative ways to represent many real-world processes into a complete set of all possible combinations of the alternatives. This will give a full range of possible model results and goes beyond the single-instance approach to running models. The software also includes novel tools for analysis of model sensitivity to alternative process models.

Contacts (BER PM)
Daniel Stover
Terrestrial Ecosystem Science
SC-23.1
Daniel.Stover@science.doe.gov

Dorothy Koch
Earth and Environmental System Modeling
SC-23.1
Dorothy.Koch@science.doe.gov

(PI Contact)
Anthony P. Walker
Oak Ridge National Laboratory
walkerap@ornl.gov

Funding
DOE Office of Science, Office of Biological and Environmental Research funded Oak Ridge National Laboratory Terrestrial Ecosystem Science SFA and Next Generation Ecosystem Experiments (NGEE) — Tropics.

Publications
Walker, A. P. et al. “The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources.” Geoscientific Model Development 11, 3159-3185 (2018). [DOI:10.5194/gmd-11-3159-2018]

Related Links
Paper
GITHUB MAAT

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Terrestrial Ecosystem Science
  • Research Area: Next-Generation Ecosystem Experiments (NGEE)

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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