Articles | Volume 14, issue 8
Geosci. Model Dev., 14, 5107–5124, 2021
https://doi.org/10.5194/gmd-14-5107-2021
Geosci. Model Dev., 14, 5107–5124, 2021
https://doi.org/10.5194/gmd-14-5107-2021

Development and technical paper 17 Aug 2021

Development and technical paper | 17 Aug 2021

An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3

Steven J. Phipps et al.

Related authors

Extending and understanding the South West Western Australian rainfall record using a snowfall reconstruction from Law Dome, East Antarctica
Yaowen Zheng, Lenneke M. Jong, Steven J. Phipps, Jason L. Roberts, Andrew D. Moy, Mark A. J. Curran, and Tas D. van Ommen
Clim. Past, 17, 1973–1987, https://doi.org/10.5194/cp-17-1973-2021,https://doi.org/10.5194/cp-17-1973-2021, 2021
Short summary
Ocean carbon and nitrogen isotopes in CSIRO Mk3L-COAL version 1.0: a tool for palaeoceanographic research
Pearse J. Buchanan, Richard J. Matear, Zanna Chase, Steven J. Phipps, and Nathan L. Bindoff
Geosci. Model Dev., 12, 1491–1523, https://doi.org/10.5194/gmd-12-1491-2019,https://doi.org/10.5194/gmd-12-1491-2019, 2019
Short summary
The PMIP4 contribution to CMIP6 – Part 1: Overview and over-arching analysis plan
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018,https://doi.org/10.5194/gmd-11-1033-2018, 2018
Short summary
Response to marine cloud brightening in a multi-model ensemble
Camilla W. Stjern, Helene Muri, Lars Ahlm, Olivier Boucher, Jason N. S. Cole, Duoying Ji, Andy Jones, Jim Haywood, Ben Kravitz, Andrew Lenton, John C. Moore, Ulrike Niemeier, Steven J. Phipps, Hauke Schmidt, Shingo Watanabe, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 18, 621–634, https://doi.org/10.5194/acp-18-621-2018,https://doi.org/10.5194/acp-18-621-2018, 2018
Short summary
Comparing proxy and model estimates of hydroclimate variability and change over the Common Era
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017,https://doi.org/10.5194/cp-13-1851-2017, 2017
Short summary

Related subject area

Numerical methods
A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021,https://doi.org/10.5194/gmd-14-6241-2021, 2021
Short summary
SymPKF (v1.0): a symbolic and computational toolbox for the design of parametric Kalman filter dynamics
Olivier Pannekoucke and Philippe Arbogast
Geosci. Model Dev., 14, 5957–5976, https://doi.org/10.5194/gmd-14-5957-2021,https://doi.org/10.5194/gmd-14-5957-2021, 2021
Short summary
NDCmitiQ v1.0.0: a tool to quantify and analyse greenhouse gas mitigation targets
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730, https://doi.org/10.5194/gmd-14-5695-2021,https://doi.org/10.5194/gmd-14-5695-2021, 2021
Short summary
Combining ensemble Kalman filter and reservoir computing to predict spatiotemporal chaotic systems from imperfect observations and models
Futo Tomizawa and Yohei Sawada
Geosci. Model Dev., 14, 5623–5635, https://doi.org/10.5194/gmd-14-5623-2021,https://doi.org/10.5194/gmd-14-5623-2021, 2021
Short summary
The Coastline Evolution Model 2D (CEM2D) V1.1
Chloe Leach, Tom Coulthard, Andrew Barkwith, Daniel R. Parsons, and Susan Manson
Geosci. Model Dev., 14, 5507–5523, https://doi.org/10.5194/gmd-14-5507-2021,https://doi.org/10.5194/gmd-14-5507-2021, 2021
Short summary

Cited articles

Albrecht, T., Martin, M., Haseloff, M., Winkelmann, R., and Levermann, A.: Parameterization for subgrid-scale motion of ice-shelf calving fronts, The Cryosphere, 5, 35–44, https://doi.org/10.5194/tc-5-35-2011, 2011. a
Albrecht, T., Aschwanden, A., Brown, J., Bueler, E., DellaGiustina, D., Feldman, J., Fischer, B., Habermann, M., Haseloff, M., Hock, R., Khroulev, C., Levermann, A., Lingle, C., Martin, M., Mengel, M., Maxwell, D., van Pelt, W., Seguinot, J., Winkelmann, R., and Ziemen, F.: PISM User's Manual, manual date 30 June 2015, based on PISM revision stable v0.7.1-2-g79b8840, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
An, M., Wiens, D. A., Zhao, Y., Feng, M., Nyblade, A., Kanao, M., Li, Y., Maggi, A., and Lévêque, J.: Temperature, lithosphere-asthenosphere boundary, and heat flux beneath the Antarctic Plate inferred from seismic velocities, J. Geophys. Res.-Sol. Ea., 120, 8720–8742, https://doi.org/10.1002/2015JB011917, 2015. a
Aschwanden, A. and Blatter, H.: Mathematical modeling and numerical simulation of polythermal glaciers, J. Geophys. Res., 114, F01027, https://doi.org/10.1029/2008JF001028, 2009. a
Aschwanden, A., Bueler, E., Khroulev, C., and Blatter, H.: An enthalpy formulation for glaciers and ice sheets, J. Glaciol., 58, 441–457, https://doi.org/10.3189/2012JoG11J088, 2012. a, b
Download
Short summary
Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.