The variation in cloud amount over polar ice sheets, sea ice, and ocean surfaces can have important effects on planetary albedo gradients and on surface energy exchanges, so that monitoring of polar cloud cover is crucial to studies of climate change. The spectral andd textural characteristics of polar clouds and surfaces for a 7-day summer series of advanced very high resoluton radiometer (AVHRR) data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and exture sensiivity tests indicate that a joint spectral-textural analysis based on the same cell size s inapopropriate, cloud detection with AVHRR data and surface identification with pasive microwave data are first done on the pixel level as detailed in part 1 (Key and Barry, 1989). Next, cloud patterns within 250 km)2 regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes. This methodology provides a basis for future 'objective automated mapping of cloud types and amount over snow and ice covered surfaces. ¿ American Geophysical Union 1990