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Title: Managing complexity in simulations of land surface and near-surface processes

Increasing computing power and the growing role of simulation in Earth systems science have led to an increase in the number and complexity of processes in modern simulators. We present a multiphysics framework that specifies interfaces for coupled processes and automates weak and strong coupling strategies to manage this complexity. Process management is enabled by viewing the system of equations as a tree, where individual equations are associated with leaf nodes and coupling strategies with internal nodes. A dynamically generated dependency graph connects a variable to its dependencies, streamlining and automating model evaluation, easing model development, and ensuring models are modular and flexible. Additionally, the dependency graph is used to ensure that data requirements are consistent between all processes in a given simulation. Here we discuss the design and implementation of these concepts within the Arcos framework, and demonstrate their use for verification testing and hypothesis evaluation in numerical experiments.
 [1] ;  [1] ;  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 1364-8152; KP1702030; ERKJ292
Grant/Contract Number:
AC05-00OR22725; AC52-06NA25396; 20110068DR; LA-UR-14-25386
Accepted Manuscript
Journal Name:
Environmental Modelling and Software
Additional Journal Information:
Journal Volume: 78; Journal ID: ISSN 1364-8152
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; multiphysics; frameworks; directed acyclic graph; land surface modeling; thermal hydrology; 97 MATHEMATICS AND COMPUTING; framework
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1321744; OSTI ID: 1353127