Preprints
https://doi.org/10.5194/tc-2021-127
https://doi.org/10.5194/tc-2021-127

  03 May 2021

03 May 2021

Review status: this preprint is currently under review for the journal TC.

Assimilation of sea ice thickness derived from CryoSat-2 along-track freeboard measurements into the Met Office’s Forecast Ocean Assimilation Model (FOAM)

Emma Kathleen Fiedler1, Matthew Martin1, Ed Blockley1, Davi Mignac1, Nicolas Fournier1, Andy Ridout2, Andrew Shepherd3, and Rachel Tilling4,5 Emma Kathleen Fiedler et al.
  • 1Met Office, Exeter, EX1 3PB, UK
  • 2Centre for Polar Observation and Modelling, University College London, London, WC1E 6BT, UK
  • 3Centre for Polar Observation and Modelling, University of Leeds, Leeds, LS2 9JT, UK
  • 4NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 5Earth System Interdisciplinary Center, University of Maryland, College Park, MD, USA

Abstract. The feasibility of assimilating SIT (sea ice thickness) observations derived from CryoSat-2 along-track measurements of sea ice freeboard is successfully demonstrated using a 3D-Var assimilation scheme, NEMOVAR, within the Met Office’s global, coupled ocean-sea ice model, FOAM (Forecast Ocean Assimilation Model). The Arctic freeboard measurements are produced by CPOM (Centre for Polar Observation and Modelling) and are converted to SIT within FOAM using modelled snow depth. This is the first time along-track observations of SIT have been used in this way, with other centres assimilating gridded and temporally-averaged observations. The assimilation greatly improves the SIT analysis and forecast fields generated by FOAM, particularly in the Canadian Arctic. Arctic-wide observation-minus-background assimilation statistics show improvements of 0.75 m mean difference and 0.41 m RMSD (root-mean-square difference) in the freeze-up period, and 0.46 m mean difference and 0.33 m RMSD in the ice break-up period, for 2015–2017. Validation of the SIT analysis against independent springtime in situ SIT observations from NASA Operation IceBridge shows improvement in the SIT analysis of 0.61 m mean difference (0.42 m RMSD) compared to a control without SIT assimilation. Similar improvements are seen in the FOAM 5-day SIT forecast. Validation of the SIT assimilation with independent BGEP (Beaufort Gyre Exploration Project) sea ice draft observations does not show an improvement, since the assimilated CryoSat-2 observations compare similarly to the model without assimilation in this region. Comparison with Air-EM (airborne electromagnetic induction) combined measurements of SIT and snow depth shows poorer results for the assimilation compared to the control, which may be evidence of noise in the SIT analysis, sampling error, or uncertainties in the modelled snow depth, the assimilated observations, or the validation observations themselves. The SIT analysis could be improved by upgrading the observation uncertainties used in the assimilation. Despite the lack of CryoSat-2 SIT observations over the summer due to the effect of meltponds on retrievals, it is shown that the model is able to retain improvements to the SIT field throughout the summer months, due to previous SIT assimilation. This also leads to regional improvements in the July SIC (sea ice concentration) of 5 % RMSD in the European sector, due to slower melt of the thicker modelled sea ice.

Emma Kathleen Fiedler et al.

Status: open (until 28 Jun 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Emma Kathleen Fiedler et al.

Emma Kathleen Fiedler et al.

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Short summary
Sea ice thickness (SIT) observations derived from CryoSat-2 satellite measurements have been successfully used to initialise an ocean and sea ice forecasting model (FOAM). Other centres have previously used gridded and averaged SIT observations for this purpose, but we demonstrate here for the first time that SIT measurements along the satellite orbit track can be used. Validation of the resulting modelled SIT demonstrates a substantial improvement in the model performance compared to a control.