Comparing passive-microwave ice algorithms without a false winner

Passive-microwave sea-ice products can disagree because their retrievals, calibration, filtering, and surface assumptions differ. This methods note synthesises three published intercomparisons to show how a fair quantitative evaluation separates bias, scatter, spatial cancellation, and threshold effects. Invented matched-footprint examples demonstrate why zero average error can coexist with local errors, why clipping at full concentration can conceal retrieval bias, and why a small concentration difference can produce a large extent difference. The analysis distinguishes concentration from net ice surface fraction and treats summer melt as a separate evaluation problem. It does not rank current operational releases or rerun the cited studies. Its practical outcome is a conditional product comparison tied to a stated quantity, season, reference dataset, and downstream decision.