Multisensor data fusion of operational sea ice observations - Wang, Keguang; Wang, Caixin; Dinessen, Frode; Spreen, Gunnar; Ricker, Robert; Tian-Kunze, Xiangshan (Frontiers in Marine Science, 2024)
Multisensor data fusion (MDF) is a process/technique of combining observations from multiple sensors to provide a more robust, accurate and complete description of the concerned object, environment or process. In this paper we introduce multisensor optimal data fusion (MODF) and apply it to fuse different operational sea ice observations around Svalbard. The overall MODF includes regridding, univariate multisensor optimal data merging (MODM), multivariate check of consistency, and generation of new variables. For MODF of operational sea ice observations around Svalbard, the AMSR2 sea ice concentration (SIC) is firstly merged with the Norwegian Meteorological Institute ice chart. Then the daily SMOS sea ice thickness (SIT) is merged with the weekly-mean CS2SMOS SIT to form a daily CS2SMOS SIT, which is further refined to be consistent with the SIC through consistency check. Finally sea ice volume (SIV) and its uncertainty are calculated based on the merged SIC and fused SIT. We note that uncertainties may vary during the regridding process, and correct determination of the observation uncertainties is critically important for MDF. The results show that the fused products provide an improved, united, consistent and multifaceted description for the operational sea ice observations, which overcomes the shortcomings in the original products. This fused products also provide consistent descriptions of sea ice edge and marginal ice zone, which may be challenging when using any individual products.Keywords: multisensor optimal data fusion (MODF), regridding, multisensor optimal data merging (MODM), sea ice concentration (SIC), sea ice thickness (SIT), sea ice volume (SIV), sea ice edge (SIE), marginal ice zone (MIZ)