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

Abstract

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.

Authors:
 [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:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1261343
Alternate Identifier(s):
OSTI ID: 1321744; OSTI ID: 1353127
Report Number(s):
LA-UR-14-25386
Journal ID: ISSN 1364-8152; KP1702030; ERKJ292
Grant/Contract Number:  
AC05-00OR22725; AC52-06NA25396; 20110068DR; LA-UR-14-25386
Resource Type:
Accepted Manuscript
Journal Name:
Environmental Modelling and Software
Additional Journal Information:
Journal Volume: 78; Journal ID: ISSN 1364-8152
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; multiphysics; frameworks; directed acyclic graph; land surface modeling; thermal hydrology; 97 MATHEMATICS AND COMPUTING; framework

Citation Formats

Coon, Ethan T., Moulton, J. David, and Painter, Scott L. Managing complexity in simulations of land surface and near-surface processes. United States: N. p., 2016. Web. doi:10.1016/j.envsoft.2015.12.017.
Coon, Ethan T., Moulton, J. David, & Painter, Scott L. Managing complexity in simulations of land surface and near-surface processes. United States. https://doi.org/10.1016/j.envsoft.2015.12.017
Coon, Ethan T., Moulton, J. David, and Painter, Scott L. Tue . "Managing complexity in simulations of land surface and near-surface processes". United States. https://doi.org/10.1016/j.envsoft.2015.12.017. https://www.osti.gov/servlets/purl/1261343.
@article{osti_1261343,
title = {Managing complexity in simulations of land surface and near-surface processes},
author = {Coon, Ethan T. and Moulton, J. David and Painter, Scott L.},
abstractNote = {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.},
doi = {10.1016/j.envsoft.2015.12.017},
journal = {Environmental Modelling and Software},
number = ,
volume = 78,
place = {United States},
year = {Tue Jan 12 00:00:00 EST 2016},
month = {Tue Jan 12 00:00:00 EST 2016}
}

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Cited by: 43 works
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