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Title: LIVVkit 2.1: automated and extensible ice sheet model validation

Journal Article · · Geoscientific Model Development (Online)
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [4];  [5]; ORCiD logo [3];  [6]; ORCiD logo [7]; ORCiD logo [8]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Colorado School of Mines, Golden, CO (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Associated Engineering, Vernon, BC (Canada)
  5. Univ. of Washington, Seattle, WA (United States)
  6. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  7. Univ. of California, Irvine, CA (United States)
  8. Delft Univ. of Technology, Delft (The Netherlands)

A collection of scientific analyses, metrics, and visualizations for robustvalidation of ice sheet models is presented using the Land Ice Verificationand Validation toolkit (LIVVkit), version 2.1, and the LIVVkit Extensionsrepository (LEX), version 0.1. This software collection targets stand-aloneice sheet or coupled Earth system models, and handles datasets and analysesthat require high-performance computing and storage. LIVVkit aims to enableefficient and fully reproducible workflows for postprocessing, analysis, andvisualization of observational and model-derived datasets in a shareableformat, whereby all data, methodologies, and output are distributed to usersfor evaluation. Extending from the initial LIVVkit software framework, wedemonstrate Greenland ice sheet simulation validation metrics using thecoupled Community Earth System Model (CESM) as well as an idealizedstand-alone high-resolution Community Ice Sheet Model, version 2 (CISM2),coupled to the Albany/FELIX velocity solver (CISM-Albany or CISM-A). As oneexample of the capability, LIVVkit analyzes the degree to which modelscapture the surface mass balance (SMB) and identifies potential sources ofbias, using recently available in situ and remotely sensed data ascomparison. Related fields within atmosphere and land surface models, e.g.,surface temperature, radiation, and cloud cover, are also diagnosed. Appliedto the CESM1.0, LIVVkit identifies a positive SMB bias that is focusedlargely around Greenland's southwest region that is due to insufficientablation.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1505335
Journal Information:
Geoscientific Model Development (Online), Vol. 12, Issue 3; ISSN 1991-9603
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

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Cited By (2)

A Study on the Performance Portability of the Finite Element Assembly Process Within the Albany Land Ice Solver book February 2020
Regional grid refinement in an Earth system model: impacts on the simulated Greenland surface mass balance journal January 2019

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