Development of an automated Arctic cloud mask using clear-sky satellite observations taken over the SHEBA and the ARM NSA Sites

Multispectral thresholds for discriminating clouds from clear areas were determined subjectively for each of the 500 NOAA-12 and 14 Advanced Very High Resolution Radiometer (AVHRR) images taken during the May-July First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Arctic Cloud Experiment (FIRE-ACE) and Surface Heat Budget of the Arctic Ocean (SHEBA). These AVHRR-derived cloud amounts were verified using values estimated by surface observers at the SHEBA ship, Des Groseilliers, and from the Atmospheric Radiation Measurement (ARM) project North Slope of Alaska (NSA) automated weather station. To eliminate this labor intensive process, an operational automated, theoretically based cloud mask developed for AVHRR wavelengths is applied over 8° latitude by 30° longitude grids centered on the Des Groseilliers and on the NSA site during 1998. Theoretical models of the bidirectional reflectance and emissivity of snow for the 3.7-µm channel are incorporated in the mask. Filtering algorithms are used to reduce the noise in the 3.7-µm channel at night. Results from the automated cloud mask will be compared to the subjective mask and to surface observations. Techniques for reducing the cloud mask errors are suggested. This validated scene classification technique should be extremely valuable for detecting clouds in snow-covered areas around the globe form operational meteorological satellite data.