Multi-year and first-year ice from RCM for assimilation in ECCC ice type analysis system

Arctic sea ice type information is essential for various operational and scientific applications including the support of marine users and guiding ice thickness retrieval algorithms operating with SMOS and CryoSat-2 data for improved sea ice prediction. A sea ice type analysis system developed at Environment and Climate Change Canada’s (ECCC) generates pan-Arctic ice type analyses at 5 km resolution every 6 hours. The ice type analysis system assimilates ice type information provided by passive microwave (AMSR2, SSMIS) and scatterometer (ASCAT) data, but assimilation of these observations is not reliable in the areas near land and in the narrow channels of the Canadian Arctic Archipelago due to their low spatial resolution of ~20-50 km. Therefore, assimilation of high-resolution ice type observations from synthetic aperture radar (SAR) is highly desired.

In this study, we extended our approach for automated detection of winter multi-year ice (MYI) and first-year ice (FYI) at 1.6 km scale from RADARSAT-2 to RCM data. To this end, we collected more than 2,000 RCM images and corresponding image analyses products that were manually generated by the Canadian Ice Service (CIS) ice experts for the period of time between July 1, 2020 and July 31, 2023. From these RCM images we extracted SAR information for more than 30,000 pure MYI and more than 619,000 pure FYI data samples under no melt conditions as identified by the CIS image analyses.

We demonstrated that separability measures for MYI and FYI classes in the spaces of the two predictor parameters (HV/HH polarization ratio and standard deviation of HV signal) are consistent with those we previously observed for RADARSAT-2. Furthermore, we found that our RCM-based MYI/FYI detection approach allows us to classify 60% of the winter CIS ice data samples with the accuracy of 99.6%. Preliminary results of assimilating RCM-based MYI/FYI high-resolution retrievals in combination with passive microwave and scatterometer data in the ECCC ice type analysis system will be also presented.