LIVVkit 2.1: automated and extensible ice sheet model validation

<p>A collection of scientific analyses, metrics, and visualizations for robust validation of ice sheet models is presented using the Land Ice Verification and Validation toolkit (LIVVkit), version 2.1, and the LIVVkit Extensions repository (LEX), version 0.1. This software collection targets s...

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Bibliographic Details
Main Authors: K. J. Evans, J. H. Kennedy, D. Lu, M. M. Forrester, S. Price, J. Fyke, A. R. Bennett, M. J. Hoffman, I. Tezaur, C. S. Zender, M. Vizcaíno
Format: Article
Language:English
Published: Copernicus Publications 2019-03-01
Series:Geoscientific Model Development
Online Access:https://www.geosci-model-dev.net/12/1067/2019/gmd-12-1067-2019.pdf
Description
Summary:<p>A collection of scientific analyses, metrics, and visualizations for robust validation of ice sheet models is presented using the Land Ice Verification and Validation toolkit (LIVVkit), version 2.1, and the LIVVkit Extensions repository (LEX), version 0.1. This software collection targets stand-alone ice sheet or coupled Earth system models, and handles datasets and analyses that require high-performance computing and storage. LIVVkit aims to enable efficient and fully reproducible workflows for postprocessing, analysis, and visualization of observational and model-derived datasets in a shareable format, whereby all data, methodologies, and output are distributed to users for evaluation. Extending from the initial LIVVkit software framework, we demonstrate Greenland ice sheet simulation validation metrics using the coupled Community Earth System Model (CESM) as well as an idealized stand-alone high-resolution Community Ice Sheet Model, version 2 (CISM2), coupled to the Albany/FELIX velocity solver (CISM-Albany or CISM-A). As one example of the capability, LIVVkit analyzes the degree to which models capture the surface mass balance (SMB) and identifies potential sources of bias, using recently available in situ and remotely sensed data as comparison. Related fields within atmosphere and land surface models, e.g., surface temperature, radiation, and cloud cover, are also diagnosed. Applied to the CESM1.0, LIVVkit identifies a positive SMB bias that is focused largely around Greenland's southwest region that is due to insufficient ablation.</p>
ISSN:1991-959X
1991-9603