CommunicationEfficient Property Preservation in Tracer Transport
Abstract
Atmospheric tracer transport is a computationally demanding component of the atmospheric dynamical core of weather and climate simulations. Simulations typically have tens to hundreds of tracers. A tracer field is needed to preserve several properties, including mass, shape, and tracer consistency. To improve computational efficiency, it is common to apply different spatial and temporal discretizations to the tracer transport equations than to the dynamical equations. Using different discretizations increases the difficulty of preserving properties. This paper provides a unified framework to analyze the property preservation problem and classes of algorithms to solve it. We observe the primary problem and a safety problem; describe three classes of algorithms to solve these; introduce new algorithms in two of these classes; make connections among the algorithms; analyze each algorithm in terms of correctness, bound on its solution magnitude, and its communication efficiency; and study numerical results. A new algorithm, QLT, has the smallest communication volume, and in an important case it redistributes mass approximately locally. These algorithms are only very loosely coupled to the underlying discretizations of the dynamical and tracer transport equations and thus are broadly and efficiently applicable. In addition, they may be applied to remap problems in applications other thanmore »
 Authors:

 Sandia National Lab. (SNLNM), Albuquerque, NM (United States)
 Univ. of New Mexico, Albuquerque, NM (United States)
 Publication Date:
 Research Org.:
 Sandia National Lab. (SNLNM), Albuquerque, NM (United States)
 Sponsoring Org.:
 USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC23); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC21); USDOE National Nuclear Security Administration (NNSA)
 OSTI Identifier:
 1529149
 Report Number(s):
 SAND20192617J
Journal ID: ISSN 10648275; 673285
 Grant/Contract Number:
 AC0494AL85000; NA0003525
 Resource Type:
 Accepted Manuscript
 Journal Name:
 SIAM Journal on Scientific Computing
 Additional Journal Information:
 Journal Volume: 41; Journal Issue: 3; Journal ID: ISSN 10648275
 Publisher:
 SIAM
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; shape preservation; tracer consistency; semiLagrangian; remap; tracer transport
Citation Formats
Bradley, Andrew M., Bosler, Peter A., Guba, Oksana, Taylor, Mark A., and Barnett, Gregory A. CommunicationEfficient Property Preservation in Tracer Transport. United States: N. p., 2019.
Web. doi:10.1137/18M1165414.
Bradley, Andrew M., Bosler, Peter A., Guba, Oksana, Taylor, Mark A., & Barnett, Gregory A. CommunicationEfficient Property Preservation in Tracer Transport. United States. doi:10.1137/18M1165414.
Bradley, Andrew M., Bosler, Peter A., Guba, Oksana, Taylor, Mark A., and Barnett, Gregory A. Thu .
"CommunicationEfficient Property Preservation in Tracer Transport". United States. doi:10.1137/18M1165414. https://www.osti.gov/servlets/purl/1529149.
@article{osti_1529149,
title = {CommunicationEfficient Property Preservation in Tracer Transport},
author = {Bradley, Andrew M. and Bosler, Peter A. and Guba, Oksana and Taylor, Mark A. and Barnett, Gregory A.},
abstractNote = {Atmospheric tracer transport is a computationally demanding component of the atmospheric dynamical core of weather and climate simulations. Simulations typically have tens to hundreds of tracers. A tracer field is needed to preserve several properties, including mass, shape, and tracer consistency. To improve computational efficiency, it is common to apply different spatial and temporal discretizations to the tracer transport equations than to the dynamical equations. Using different discretizations increases the difficulty of preserving properties. This paper provides a unified framework to analyze the property preservation problem and classes of algorithms to solve it. We observe the primary problem and a safety problem; describe three classes of algorithms to solve these; introduce new algorithms in two of these classes; make connections among the algorithms; analyze each algorithm in terms of correctness, bound on its solution magnitude, and its communication efficiency; and study numerical results. A new algorithm, QLT, has the smallest communication volume, and in an important case it redistributes mass approximately locally. These algorithms are only very loosely coupled to the underlying discretizations of the dynamical and tracer transport equations and thus are broadly and efficiently applicable. In addition, they may be applied to remap problems in applications other than tracer transport.},
doi = {10.1137/18M1165414},
journal = {SIAM Journal on Scientific Computing},
number = 3,
volume = 41,
place = {United States},
year = {2019},
month = {5}
}
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