Articles | Volume 9, issue 11
Geosci. Model Dev., 9, 3907–3918, 2016
https://doi.org/10.5194/gmd-9-3907-2016
Geosci. Model Dev., 9, 3907–3918, 2016
https://doi.org/10.5194/gmd-9-3907-2016

Development and technical paper 01 Nov 2016

Development and technical paper | 01 Nov 2016

An approach to computing discrete adjoints for MPI-parallelized models applied to Ice Sheet System Model 4.11

Eric Larour et al.

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Cited articles

AdjoinableMPI: AdjoinableMPI wiki, https://trac.mcs.anl.gov/projects/AdjoinableMPI/wiki, last access: 19 October 2016.
ADOL-C: ADOL-C, http://www.coin-or.org/projects/ADOL-C.xml (last access: 19 October 2016), 2007.
Amestoy, P. R., Duff, I. S., Koster, J., and L'Excellent, J.-Y.: A Fully Asynchronous Multifrontal Solver Using Distributed Dynamic Scheduling, SIAM J. Matrix Anal. Appl., 23, 15–41, 2001.
Applegate, P. J., Kirchner, N., Stone, E. J., Keller, K., and Greve, R.: An assessment of key model parametric uncertainties in projections of Greenland Ice Sheet behavior, The Cryosphere, 6, 589–606, https://doi.org/10.5194/tc-6-589-2012, 2012.
Arthern, R. J. and Gudmundsson, G. H.: Initialization of ice-sheet forecasts viewed as an inverse Robin problem, J. Glaciol., 56, 527–533, 2010.
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Short summary
We present an approach to derive the adjoint state of the C++ coded Ice Sheet System Model. The approach enables data assimilation of observations to improve projections of polar ice sheet mass balance and contribution to sea-level rise. It is applicable to other Earth science frameworks relying on C++ and parallel computing, is non-intrusive, and enables computation of transient adjoints for any type of physics, hence providing insights into the sensitivities of any model to its inputs.