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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 1
Geosci. Model Dev., 10, 255-270, 2017
https://doi.org/10.5194/gmd-10-255-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 255-270, 2017
https://doi.org/10.5194/gmd-10-255-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 17 Jan 2017

Methods for assessment of models | 17 Jan 2017

An ice sheet model validation framework for the Greenland ice sheet

Stephen F. Price1, Matthew J. Hoffman1, Jennifer A. Bonin2, Ian M. Howat3, Thomas Neumann4, Jack Saba4,6, Irina Tezaur5, Jeffrey Guerber4,7, Don P. Chambers2, Katherine J. Evans8, Joseph H. Kennedy8, Jan Lenaerts9, William H. Lipscomb1, Mauro Perego10, Andrew G. Salinger10, Raymond S. Tuminaro10, Michiel R. van den Broeke9, and Sophie M. J. Nowicki4 Stephen F. Price et al.
  • 1Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, MS B216, Los Alamos, NM 87545, USA
  • 2College of Marine Science, University of South Florida, St. Petersburg, FL 33701, USA
  • 3School of Earth Sciences and Byrd Polar Research Center, The Ohio State University, Columbus, OH 43210, USA
  • 4Cryospheric Sciences, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
  • 5Extreme Scale Data Science and Analytics Department, Sandia National Laboratories, P.O. Box 969, MS 9159, Livermore, CA 94551, USA
  • 6Science, Systems, and Applications, Inc., Lanham, MD 20706, USA
  • 7Sigma Space Corp., Lanham, MD 20706, USA
  • 8Computational Earth Sciences Group, Oak Ridge National Laboratory, MS 6301, Oak Ridge, TN 37831, USA
  • 9Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, the Netherlands
  • 10Computational Mathematics Department, Sandia National Laboratories, P.O. Box 5800, MS 1320, Albuquerque, NM 87185, USA

Abstract. We propose a new ice sheet model validation framework – the Cryospheric Model Comparison Tool (CmCt) – that takes advantage of ice sheet altimetry and gravimetry observations collected over the past several decades and is applied here to modeling of the Greenland ice sheet. We use realistic simulations performed with the Community Ice Sheet Model (CISM) along with two idealized, non-dynamic models to demonstrate the framework and its use. Dynamic simulations with CISM are forced from 1991 to 2013, using combinations of reanalysis-based surface mass balance and observations of outlet glacier flux change. We propose and demonstrate qualitative and quantitative metrics for use in evaluating the different model simulations against the observations. We find that the altimetry observations used here are largely ambiguous in terms of their ability to distinguish one simulation from another. Based on basin-scale and whole-ice-sheet-scale metrics, we find that simulations using both idealized conceptual models and dynamic, numerical models provide an equally reasonable representation of the ice sheet surface (mean elevation differences of  < 1m). This is likely due to their short period of record, biases inherent to digital elevation models used for model initial conditions, and biases resulting from firn dynamics, which are not explicitly accounted for in the models or observations. On the other hand, we find that the gravimetry observations used here are able to unambiguously distinguish between simulations of varying complexity, and along with the CmCt, can provide a quantitative score for assessing a particular model and/or simulation. The new framework demonstrates that our proposed metrics can distinguish relatively better from relatively worse simulations and that dynamic ice sheet models, when appropriately initialized and forced with the right boundary conditions, demonstrate a predictive skill with respect to observed dynamic changes that have occurred on Greenland over the past few decades. An extensible design will allow for continued use of the CmCt as future altimetry, gravimetry, and other remotely sensed data become available for use in ice sheet model validation.

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We introduce the Cryospheric Model Comparison Tool (CmCt) and propose qualitative and quantitative metrics for evaluating ice sheet model simulations against observations. Greenland simulations using the Community Ice Sheet Model are compared to gravimetry and altimetry observations from 2003 to 2013. We show that the CmCt can be used to score simulations of increasing complexity relative to observations of dynamic change in Greenland over the past decade.
We introduce the Cryospheric Model Comparison Tool (CmCt) and propose qualitative and...
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