This paper describes the adaptation of the Bayesian sea ice detection algorithm for the rotating fan-beam scatterometer CSCAT onboard CFOSAT (China-France Oceanography SATellite). The algorithm was originally developed for fixed fan-beam and rotating pencil-beam scatterometers. It is based on the probability of the wind and ice backscatter distances to their corresponding Geophysical Model Functions (GMFs). The new rotating Ku-band fan-beam design introduces very diverse geometry distributions across the swath, which leads to three main adaptations of the algorithm: (1) a new probability distribution function fit for the backscatter over open sea; (2) a linear ice model for each incidence angle; (3) the separation of outer swath WVCs (Wind Vector Cells, number 1, 2, 41, 42) from the other WVCs to form two sets of probability distribution function fits for these two WVC groups. The results are validated against sea ice extents from the active microwave ASCAT and the passive microwave SSMI. The validation shows good agreement with both instruments despite the discrepancy with SSMI during the melting season, and the discrepancy is caused by the lower sensitivity of passive microwave to detect the ice at low concentration with mixed water/ice state while scatterometer is more tolerant regarding to this situation. We observe that the sea ice GMF regression between HH and VV sea ice backscatter at low and high incidence angles decorrelates around -12 dB (28) and -20 dB (50) and an experiment with truncated backscatter values at these incidence angles is executed, which significantly improves the year-long average sea ice extents. In conclusion, the adapted algorithm for CSCAT works effectively and yields consistent sea ice extents compared with active and passive microwaves, as such it can in principle contribute to the long-term global scatterometer sea ice record, and as the adapted algorithm for rotating fan-beam scatterometer, it also can be a guideline for recent launched dual frequency rotating fan-beam scatterometer WindRAD.