NOAA/NESDIS is developing an algorithm for the remote sensing of global cloud cover using multi-spectral radiance measurements from the Advanced Very High Resolution Radiometer (AVHRR) on-board NOAA polar orbiting satellites. The current (Phase 1) algorithm uses a sequence of ``universal'' threshold tests to classify all 2×2 pixel arrays of GAC (4 km) observations into clear, mixed and cloudy categories. A subsequent version of the algorithm (Phase II) will analyze the previous 9-day series of mapped (1/2 degree) ``clear'' array data to replace the ``universal'' thresholds with space and time specific values. This will provide more accurate estimates of cloud amount for each pixel. The current algorithm is being implemented into the operational data processing stream for testing and evaluation of experimental products. Eventually, it is intended for use operationally to support weather and climate diagnosis and forecasting programs, as well as to provide clear sky radiance data sets for other remote sensing parameters, e.g., vegetation index, aerosol optical thickness, and sea surface temperature.