Preprints
https://doi.org/10.5194/egusphere-2026-3101
https://doi.org/10.5194/egusphere-2026-3101
25 Aug 2026
 | 25 Aug 2026
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

A prior-regularised heteroscedastic ResUNet for fusing passive-microwave sea-ice concentration products

Fengxin Chen, Yu-Xuan Fu, Ruibin Xia, and Xiaochun Wang

Abstract. Passive microwave (PMW) sea-ice concentration (SIC) products provide pan-Arctic coverage, but their retrieval errors are often elevated near coastlines and within the marginal ice zone (MIZ), where land spillover, mixed pixels, melt ponds, and atmospheric effects complicate retrieval. We present a prior-regularised two-level residual U-Net (ResUNet) that generates a 12.5 km Arctic SIC field by fusing six PMW SIC products: Bremen-ASI, NSIDC-BT, NSIDC-NT, NSIDC-CDR, SICCI-25km, and OSI-450. The model combines a compact encoder-decoder backbone with auxiliary spatial and seasonal encodings and a heteroscedastic Gaussian negative log-likelihood loss. Empirical relationships between PMW SIC error and distance to land or to the ice edge (defined here as the 0.15 SIC contour), together with product-provided uncertainty estimates, are incorporated into the loss function as pixel-wise reliability information. On the held-out test set, the fused product outperforms all six individual PMW SIC products, reducing MAE by about 55 % and RMSE by about 30 % relative to the best-performing PMW product while maintaining near-zero bias. In the most error-prone regions, RMSE is reduced by about 34 % within 20 km of the coast and by about 25 % within 50 km of the ice edge. Independent validation against Landsat-derived SIC gives the lowest MAE and RMSE for the fused product (0.035 and 0.062), corresponding to improvements of about 13 % and 40 % over the best-performing PMW product, respectively. The fused product also has the lowest errors in the most error-prone regions and smaller interannual RMSE variability. The estimated heteroscedastic uncertainty is informative: on the held-out test set it increases consistently with error and reaches its maximum in coastal and ice-edge regions, while the Landsat validation also shows a consistent ordering of errors with uncertainty. Overall, the proposed framework combines complementary PMW SIC products into a single fused product with improved accuracy and reduced errors near coastlines and the ice edge, providing a useful basis for climate applications and near-real-time sea-ice mapping.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Fengxin Chen, Yu-Xuan Fu, Ruibin Xia, and Xiaochun Wang

Status: open (until 06 Oct 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Fengxin Chen, Yu-Xuan Fu, Ruibin Xia, and Xiaochun Wang
Fengxin Chen, Yu-Xuan Fu, Ruibin Xia, and Xiaochun Wang
Metrics will be available soon.
Latest update: 25 Aug 2026
Download
Short summary
Accurate maps of Arctic sea ice are important for climate research and safer operations in polar waters, but satellite estimates are often less reliable near coasts and the ice edge. We combined six existing satellite sea-ice maps with a computer model that learns where each map is most trustworthy. The resulting experimental map was more accurate than each input map, especially in difficult coastal and ice-edge areas, and it also shows where its estimates are more uncertain.
Share