Articles | Volume 9, issue 3
Geosci. Model Dev., 9, 1125–1141, 2016
https://doi.org/10.5194/gmd-9-1125-2016
Geosci. Model Dev., 9, 1125–1141, 2016
https://doi.org/10.5194/gmd-9-1125-2016
Development and technical paper
24 Mar 2016
Development and technical paper | 24 Mar 2016

The location of the thermodynamic atmosphere–ice interface in fully coupled models – a case study using JULES and CICE

Alex E. West et al.

Related authors

Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt
Alex West, Ed Blockley, and Mat Collins
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-351,https://doi.org/10.5194/tc-2021-351, 2021
Preprint under review for TC
Short summary
Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes
Alex West, Mat Collins, and Ed Blockley
Geosci. Model Dev., 13, 4845–4868, https://doi.org/10.5194/gmd-13-4845-2020,https://doi.org/10.5194/gmd-13-4845-2020, 2020
Short summary
Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019,https://doi.org/10.5194/tc-13-2001-2019, 2019
Short summary
The sea ice model component of HadGEM3-GC3.1
Jeff K. Ridley, Edward W. Blockley, Ann B. Keen, Jamie G. L. Rae, Alex E. West, and David Schroeder
Geosci. Model Dev., 11, 713–723, https://doi.org/10.5194/gmd-11-713-2018,https://doi.org/10.5194/gmd-11-713-2018, 2018
Short summary
Development of the Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled model
J. G. L. Rae, H. T. Hewitt, A. B. Keen, J. K. Ridley, A. E. West, C. M. Harris, E. C. Hunke, and D. N. Walters
Geosci. Model Dev., 8, 2221–2230, https://doi.org/10.5194/gmd-8-2221-2015,https://doi.org/10.5194/gmd-8-2221-2015, 2015
Short summary

Related subject area

Cryosphere
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen​​​​​​​, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022,https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022,https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary
Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)
Adrian K. Turner, Kara J. Peterson, and Dan Bolintineanu
Geosci. Model Dev., 15, 1953–1970, https://doi.org/10.5194/gmd-15-1953-2022,https://doi.org/10.5194/gmd-15-1953-2022, 2022
Short summary
Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1)
Zhen Yin, Chen Zuo, Emma J. MacKie, and Jef Caers
Geosci. Model Dev., 15, 1477–1497, https://doi.org/10.5194/gmd-15-1477-2022,https://doi.org/10.5194/gmd-15-1477-2022, 2022
Short summary
NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022,https://doi.org/10.5194/gmd-15-1269-2022, 2022
Short summary

Cited articles

Best, M. J., Beljaars, A., Polcher, J., and Viterbo, P.: A Proposed Structure for Coupling Tiled Surfaces with the Planetary Boundary Layer, J. Hydrometerorol., 5, 1271–1278, https://doi.org/10.1175/JHM-382.1, 2004.
Best, M. J., Cox, P. M., and Warrilow, D. M.: Determining the optimal soil temperature scheme for atmospheric modelling applications, Bound. Lay. Meteorol., 114, 111–142, 2005.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R .L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bitz, C. M. and Lipscomb, W. H.: An energy-conserving thermodynamic model of sea ice, J. Geophys. Res., 104, 15669–15677, 1999.
Gordon, C., Cooper, C., Senior, C. A., Banks, H., Gregory, J. M., Johns, T. C., Mitchell, J. F. B., and Wood, R. A.: The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments, Clim. Dynam., 16, 147–168, https://doi.org/10.1007/s003820050010, 2000.
Download
Short summary
This study compares two methods of coupling a sea ice model to an atmospheric model in a series of idealized one-dimensional experiments. The JULES method calculates surface variables in the atmosphere; the CICE method calculates surface variables in the sea ice. It is found that simulations of all variables are more accurate in the JULES method, likely because of the shorter time step of the atmosphere.