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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-213
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-213
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 08 Aug 2019

Submitted as: development and technical paper | 08 Aug 2019

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This discussion paper is a preprint. A revision of the manuscript for further review has not been submitted.

SICOPOLIS-AD v1: an open-source adjoint modeling framework for ice sheet simulation enabled by the algorithmic differentiation tool OpenAD

Liz C. Logan1, Sri Hari Krishna Narayanan2, Ralf Greve3, and Patrick Heimbach1,4,5 Liz C. Logan et al.
  • 1Oden Institute for Computational Science and Engineering, University of Texas at Austin, 201 East 24th Street, Austin, Texas, 78712, USA
  • 2Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
  • 3Institute of Low Temperature Science, Hokkaido University, Kita-19, Nishi-8, Kita-ku, Sapporo 060-0819, Japan
  • 4Jackson School of Geosciences, University of Texas at Austin, 201 East 24th Street, Austin, Texas, 78712, USA
  • 5Institute for Geophysics, University of Texas at Austin, J.J. Pickle Research Campus, Bldg. 196, 10100 Burnet Road (R2200), Room 2.236, Austin, TX 78758, USA

Abstract. We present a new capability of the ice sheet model SICOPOLIS that enables flexible adjoint code generation via source transformation using the open-source algorithmic differentiation (AD) tool OpenAD. The adjoint code enables efficient calculation of sensitivities of a scalar-valued objective function or quantity of interest (QoI) to a range of important, often spatially varying model input variables, including initial and boundary conditions, as well as model parameters. Compared to earlier work on adjoint code generation of SICOPOLIS, our work is based on several important advances: (i) it is embedded within the up-to-date trunk of the SICOPOLIS repository – accounting for one and a half decades of code development and improvements – and is readily available to the wider community; (ii) the AD tool used, OpenAD, is an open-source tool; (iii) the adjoint code developed is applicable to both Greenland and Antarctica, including grounded ice as well as floating ice shelves, and with an extended choice of thermodynamical representations. A number of code refactorization steps were required. They are discussed in detail in an Appendix as they hold lessons for application of AD to legacy codes at large. As an example application, we examine the sensitivity of the total Antarctic Ice Sheet volume to changes in initial ice thickness, summer precipitation, and basal and surface temperatures across the ice sheet. Simulations of Antarctica with floating ice shelves show that over 100 years of simulation the sensitivity of total ice sheet volume to the initial ice thickness and precipitation is almost uniformly positive, while the sensitivities to surface and basal temperature are almost uniformly negative. Sensitivity to summer precipitation is largest on floating ice shelves from Queen Maud to Queen Mary Land. The largest sensitivity to initial ice thickness is at outlet glaciers around Antarctica. Comparison between total ice sheet volume sensitivities to surface and basal temperature shows that surface temperature sensitivities are higher broadly across the floating ice shelves, while basal temperature sensitivities are highest at the grounding lines of floating ice shelves and outlet glaciers. A uniformly perturbed region of East Antarctica reveals that, among the four control variables tested here, total ice sheet volume is most sensitive to variations in summer precipitation as formulated in SICOPOLIS. Comparison between adjoint- and finite-difference-derived sensitivities shows good agreement, lending confidence that the AD tool is producing correct adjoint code. The new modeling infrastructure is freely available at www.sicopolis.net under the development trunk.

Liz C. Logan et al.
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Status: closed (peer review stopped)
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Interactive discussion
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Liz C. Logan et al.
Liz C. Logan et al.
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Short summary
A new capability has been developed for the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets) that enables the generation of derivative code, such as tangent linear or adjoint models, by means of algorithmic differentiation. It relies on the source-transformation algorithmic (AD) differentiation tool OpenAD. The reverse-mode of AD provides the adjoint model, SICOPOLIS-AD, which may be applied for comprehensive sensitivity analyses as well as gradient-based optimization.
A new capability has been developed for the ice sheet model SICOPOLIS (SImulation COde for...
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