Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5365-2024
https://doi.org/10.5194/tc-18-5365-2024
Research article
 | 
21 Nov 2024
Research article |  | 21 Nov 2024

Bounded and categorized: targeting data assimilation for sea ice fractional coverage and nonnegative quantities in a single-column multi-category sea ice model

Molly M. Wieringa, Christopher Riedel, Jeffrey L. Anderson, and Cecilia M. Bitz

Viewed

Total article views: 4,341 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,332 843 166 4,341 190 261
  • HTML: 3,332
  • PDF: 843
  • XML: 166
  • Total: 4,341
  • BibTeX: 190
  • EndNote: 261
Views and downloads (calculated since 15 Sep 2023)
Cumulative views and downloads (calculated since 15 Sep 2023)

Viewed (geographical distribution)

Total article views: 4,341 (including HTML, PDF, and XML) Thereof 4,235 with geography defined and 106 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 20 Sep 2026
Download
Short summary
Statistically combining models and observations with data assimilation (DA) can improve sea ice forecasts but must address several challenges, including irregularity in ice thickness and coverage over the ocean. Using a sea ice column model, we show that novel, bounds-aware DA methods outperform traditional methods for sea ice. Additionally, thickness observations at sub-grid scales improve modeled ice estimates of both thick and thin ice, a finding relevant for forecasting applications.
Share