Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4845-2020
https://doi.org/10.5194/gmd-13-4845-2020
Methods for assessment of models
 | 
09 Oct 2020
Methods for assessment of models |  | 09 Oct 2020

Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes

Alex West, Mat Collins, and Ed Blockley

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Cited articles

Alexandrov, V., Sandven, S., Wahlin, J., and Johannessen, O. M.: The relation between sea ice thickness and freeboard in the Arctic, The Cryosphere, 4, 373–380, https://doi.org/10.5194/tc-4-373-2010, 2010. 
Bitz, C. M.: Some Aspects of Uncertainty in Predicting Sea Ice Thinning, in: Arctic Sea Ice Decline: Observations, Projections, Mechanisms, and Implications, edited by: DeWeaver, E. T., Bitz, C. M., and Tremblay, L.-B., American Geophysical Union, Washington, D.C., https://doi.org/10.1029/180GM06, 2008. 
Bitz, C. M. and Lipscomb, W. H.: An energy-conserving thermodynamic model of sea ice, J. Geophys. Res., 104, 15669–15677, https://doi.org/10.1029/1999JC900100, 1999. 
Bliss, A. C., Steele, M., Peng, G., Meier, W. N., and Dickinson, S.: Regional variability of Arctic sea ice seasonal change climate indicators from a passive microwave climate data record, Environ. Res. Lett., 14, 045003, https://doi.org/10.1088/1748-9326/aafb84, 2019. 
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Short summary
This study calculates sea ice energy fluxes from data produced by ice mass balance buoys (devices measuring ice elevation and temperature). It is shown how the resulting dataset can be used to evaluate a coupled climate model (HadGEM2-ES), with biases in the energy fluxes seen to be consistent with biases in the sea ice state and surface radiation. This method has potential to improve sea ice model evaluation, so as to better understand spread in model simulations of sea ice state.
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